Jurnal Teknologi Informasi dan Multimedia
Jurnal Teknologi Informasi dan Multimedia (JTIM) is a scientific journal in computers that contains research results and literature studies. It managed by Research and Development Center (PUSLITBANG) Sekawan Institute Nusa Tenggara, Mataram, NTB. This journal is managed by lecturers and practitioners from various University backgrounds in Indonesia, especially Mataram, NTB. JTIM is published 4 (four) times a year, namely every May, August, November and February.
Optimization of Support Vector Machine Using SMOTE and Grid Search for Kidney Health Data Classification
Kidney disease is a highly prevalent health problem that can seriously impact the quality of life of those affected. To improve diagnostic accuracy, machine learning methods are widely used to classify patient data. Class imbalance (imbalanced data) is one of the problems that often occurs in the classification process and can affect the performance of machine learning models, especially in detecting minority classes. This study aims to improve the performance of the Support Vector Machine (SVM) algorithm by applying the SMOTE (Synthetic Minority Over-sampling Tech-nique) and Grid Search methods in the data classification process. SMOTE is used to balance the class distribution by adding synthetic data to the minority class, while Grid Search is used to ob-tain optimal model parameters. The results show that the SVM model without handling data im-balance produces relatively low performance with an accuracy value of 51%, precision 17%, re-call 33%, and F1-score 23%. After applying the SMOTE method, the model performance increases significantly to 81% accuracy, 81% precision, 80% recall, and 81% F1-score. Furthermore, the ap-plication of Grid Search to the SVM + SMOTE model provides the best results with an accuracy of 84%, precision 82%, recall 81%, and F1-score 81% with an AUC value of 0,92. The findings of this study indicate that the combination of SMOTE and Grid Search is effective in improving the per-formance of the SVM algorithm in data classification. The novelty of this study demonstrates that data imbalance management and hyperparameter optimization play a crucial role in producing more accurate and optimal classification models.
Hak Cipta (c) 2026 Muhammad Maulana, Zulkipli Zulkipli, Tanwir Tanwir, Dading Oktaviadi Resmiranta, Naufal Hanif, Raisul Azhar https://creativecommons.org/licenses/by-sa/4.0
Hyperparameter Tuning Metode Long Short-Term Memory (LSTM) untuk Prediksi Harga Bawang Merah di Pasar Tradisional Jawa Timur
Shallots are one of the essential food commodities in East Java, the price of which frequently fluctuates due to seasonal influences and distribution factors. This price uncertainty often weakens the community's purchasing power and makes it difficult for farmers and sellers to make decisions. Therefore, this study proposes a daily shallot price prediction model for nine regions in East Java using the Long Short-Term Memory (LSTM) method with hyperparameter tuning to obtain the best-performing model. This study utilizes daily price data from PIHPS (Pusat Informasi Harga Pangan Strategis / Strategic Food Price Information Center) over four years, from January 1, 2021, to December 31, 2024. The research stages begin with data preprocessing, which includes imputing missing values to ensure continuity of the time sequence, data normalization, and arrangement of data based on temporal order (time series). To obtain the optimal model, the data was split into 80% for training and 20% for testing. Based on the experimental results, the optimal model configuration was found using a Window Size of 7 (the last seven days of data), 114 Epochs, and a Batch Size of 64. Furthermore, the reliability of the model was measured using MAPE, where the average across all regions fell below 10%, which is classified as "Very Good" based on MAPE interpretation standards. Additional testing using 2025 data as an independent dataset further confirmed that the model remains consistent and stable, as evidenced by an average MAPE of 3.10% across the nine regions.
Hak Cipta (c) 2026 M. Latifur Rahman, Mamluatul Hani'ah, Muhammad Afif Hendrawan https://creativecommons.org/licenses/by-sa/4.0
Game Edukasi Ilmu Pengetahuan Sosial (IPS) Berbasis Android menggunakan Metode R&D 4D di SMP Negeri 2 Rawalo
Technological advancements have had a significant impact on the world of education, particularly in accelerating and simplifying the learning process for Social Studies (IPS) courses. This study aims to design an Android-based educational game for 9th-grade students at SMP Negeri 2 Rawalo using the Research and Development (R&D) method and the 4D model (define, design, develop, disseminate). This game was designed using the Construct 3 application and named “Society in A Game: Game of Social Changes and Digital Economy Growth.” The study involved 20 students, and the research utilized pre-tests and post-tests to measure improvements in learning outcomes as well as an application evaluation test using the System Usability Scale (SUS) based on a 1–4 Likert scale. The average pre-test score of 57.8 increased to 77.6 on the post-test, representing a 34.2% increase. Additionally, the average SUS score of 74.5 falls into the “Acceptable” category. The research results indicate that Android-based educational games can serve as an interactive learning medium while introducing the use of technology in the field of education.
Hak Cipta (c) 2026 Annas Ridwan Pangestu, Sigit Sugiyanto, Tito Pinandita, Dimara Kusuma Hakim https://creativecommons.org/licenses/by-sa/4.0
Penerapan Teknik Steganografi dalam Gambar pada Aplikasi Telegram Menggunakan Metode Least Significant Bit (LSB)
In the digital era, the threat of data leakage demands secure information exchange mechanisms on instant messaging applications. This study aims to implement and test the robustness of the Least Significant Bit (LSB) steganography method on image media transmitted through the Telegram platform to ensure information confidentiality and create secure cyber communication against eavesdropping. The novelty of this research lies in the comparative analysis of the pure LSB method's robustness against Telegram's compression protocols, which frequently corrupt lower bits in digital media. This study employs an experimental quantitative approach by testing 15 digital image samples in PNG, BMP, and JPG formats sourced from the Google public repository. The experimental process involves embedding text messages using StegOnline tools, transmission via Telegram, extraction, and image quality analysis based on Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) metrics. The test results indicate that the LSB method achieves a 100% extraction success rate and a Bit Error Rate (BER) of 0 when utilizing the "send document" feature due to its lossless transmission nature, with optimal visual quality indicated by PSNR values above 58 dB. Conversely, transmission through the "send image" feature causes extraction failure due to the platform's compression that corrupts the secret bits. This study concludes that the accuracy stability of LSB steganography highly depends on selecting a lossless transmission for-mat to fully guarantee data integrity.
Hak Cipta (c) 2026 Lu’lu’ Atik Fitriyani, Fahmi Fachri https://creativecommons.org/licenses/by-sa/4.0
Game Edukatif pada Materi Teks Wawancara untuk Mendukung Literasi Membaca Siswa Sekolah Dasar
This study aims to develop an educational game-based learning media using Smart Apps Creator 3, named “SIMAKA,” to support elementary school students’ reading literacy in interview text materials. The method used is Research and Development (R&D) with the ADDIE model, which includes the stages of analysis, design, development, implementation, and evaluation. Data collection techniques involve validation questionnaires and user responses, which are analyzed quantitatively in descriptive form using percentages. The results show that the media achieved a feasibility level of 92.8% from experts, 95% from teachers, and 93% from students, all categorized as very good. These findings indicate that the developed media is feasible to be used as an alternative learning tool to support students’ reading literacy.
Hak Cipta (c) 2026 Ragil Dian Purnama Putri, Wiwik Kusuma, Tri Lestari https://creativecommons.org/licenses/by-sa/4.0
Optimizing Green-Synthesized Chitosan Nanoparticles for Anticancer Drug Delivery Using Artificial Intelligence: A Systematic Literature Review
Chitosan nanoparticles (CNPs) are promising anticancer drug-delivery carriers because of their biodegradability, mucoadhesive behavior, drug-loading capacity, and surface modifiability. However, previous studies have often examined green synthesis, CNP formulation, artificial intel-ligence (AI), and anticancer delivery as separate research domains, leaving limited synthesis of how AI-assisted optimization can improve environmentally sustainable CNP systems for cancer therapy. This systematic literature review evaluated studies published from 2016 to 2025 on green-synthesized CNPs optimized through AI, machine learning, or statistical optimization approaches for anticancer applications. A Scopus search using the Boolean string "chitosan AND anticancer AND optimization" identified 95 records. After eligibility screening, 42 records were excluded because they were older than 2016, non-article publications, non-English records, or out-side the oncology/green-CNP scope, leaving 53 studies for review. The evidence was synthesized into four domains: optimization and predictive modeling, green synthesis and material innova-tion, targeted and multifunctional nanocarriers, and preclinical efficacy and translational readiness. Across the included studies, optimized CNPs showed particle sizes ranging from approxi-mately 5 to 473 nm, encapsulation efficiency up to 98%, and zeta potentials from -31 to +98 mV. Reported therapeutic improvements included enhanced cytotoxicity, reduced IC50 values, sus-tained release up to 72 h, and inhibition rates up to 82% in selected cancer models. Nevertheless, cross-study comparison was limited by inconsistent model-validation metrics, incomplete toxicity reporting, limited in vivo validation, and insufficient scalability assessment. Integrating AI-guided optimization with green CNP synthesis can accelerate sustainable nanomedicine design, but future studies should prioritize standardized reporting, risk-of-bias control, life-cycle assess-ment, and regulatory translation.
Hak Cipta (c) 2026 Halil Akhyar, Ahmad Taufik S, Susi Rahayu https://creativecommons.org/licenses/by-sa/4.0
Implementasi Multi-Authentication pada Smart Door Lock Berbasis ESP8266
Home security has become a primary concern, where conventional lock systems have significant weaknesses such as risk of loss, ease of duplication, and inability for remote monitoring. This re-search develops a Smart Door Lock system based on ESP8266 and Blynk with a multi-sensor and multi-authentication approach to overcome these problems. The system integrates RFID RC522 and 4x4 keypad as two-factor authentication (2FA) that can be toggled as needed, equipped with IR MH-B sensor for forced entry detection, ESP32-CAM for visual documentation, and Blynk platform for remote management. The research uses the ADDIE method which includes analysis, design, development, implementation, and evaluation stages with Black Box Testing approach. Imple-mentation results show the system successfully functions with a success rate of 98.29% from 1,405 tests. Average RFID reading time 447.5ms, total access time 1.27 seconds, and Blynk notification delay 2.38 seconds, meeting the response target of < 3 seconds. The 2FA mechanism proved effec-tive with 100% validation accuracy, toggle mode functions perfectly with EEPROM persistence. Remote management features via Blynk achieved 100% reliability for adding and removing RFID cards, changing passwords, and remote control. The IR sensor successfully distinguished legal and forced openings with 97.5% accuracy. ESP32-CAM integrated perfectly with automatic trigger via REST API for visual documentation to Telegram. The system is considered feasible as a modern, secure, and easy-to-operate home security solution.
Hak Cipta (c) 2026 Lilik Widyawati, Husain Husain, Kurniadin Abdul Latif, L. Irvan Sastrawan https://creativecommons.org/licenses/by-sa/4.0
Evaluasi Sistem Retrieval-Augmented Generation Berbasis Low-Code dalam Meningkatkan Akurasi Konseptual Pembelajaran Sosiologi
The utilization of Large Language Models (LLMs) in higher education offers significant efficiency, yet it introduces critical risks of information hallucination and conceptual bias, particularly in the discipline of Sociology. This study aims to evaluate the performance of a Retrieval-Augmented Generation (RAG) system based on the low-code platform n8n as a robust solution for hallucina-tion mitigation. The system integrates semantic search using Supabase as a vector database and the Gemini 2.5 Flash model to restrict response generation exclusively to verified academic litera-ture. The research employed an Experimental Single-System Evaluation method with a du-al-evaluation approach (quantitative and qualitative) across 50 test instruments. Quantitative testing using the ROUGE-L metric recorded a mean score of 0.354, indicating adequate structural similarity despite variations inherent to the paraphrasing nature of LLMs in analytical tasks. Thematic qualitative analysis of evaluator comments revealed 98.2% positive sentiment, with the dominant theme being “Conceptually Accurate”. Ultimately, 100% of the expert panel declared the system suitable for implementation as a reliable supplementary learning medium.
Hak Cipta (c) 2026 Rusmanto, Jasrino Maulana Putra https://creativecommons.org/licenses/by-sa/4.0
Sistem Rekomendasi Pekerjaan Berbasis Kompetensi Mahasiswa Menggunakan Pendekatan Content-Based Filtering
Students often experience difficulties in obtaining job recommendations that match their academic competencies and personal interests. This problem is caused by the suboptimal utilization of stu-dents' academic data in the job matching process, resulting in recommendations that are often less relevant to students' profiles and abilities. Therefore, a job recommendation system is needed that can process academic data and user preferences to produce more appropriate job recommenda-tions that meet students' needs. This study aims to develop a web-based job recommendation sys-tem that utilizes Grade Point Average (GPA) with a Content-Based Filtering approach. The devel-oped system matches student profiles—including GPA, major, skills, and interests—with job characteristics in the information technology field. The level of match between student profiles and job profiles is calculated using the Cosine Similarity algorithm. Evaluation of system performance is carried out by implementing a 5-fold cross-validation scheme and using Top-3 Accuracy and Exact Accuracy metrics. The test results show that the system obtained an average Top-3 Accuracy score of 85.0% and Exact Accuracy of 54.7%. These results demonstrate that the developed system is capable of generating relevant job recommendations with a high level of consistency. Therefore, this system is expected to contribute to supporting students' decision-making process in planning career paths that align with their academic achievements and individual preferences.
Hak Cipta (c) 2026 Intan Sulistyaningrum Sakkinah, Muhammad Ainul Fikri, Rosyida Arian Rahma https://creativecommons.org/licenses/by-sa/4.0
Pemanfaatan IoT dalam Sistem Kontrol Lingkungan Tanaman Drosera sessilifolia Menggunakan Fuzzy Type-2
Drosera sessilifolia is a carnivorous plant that requires optimal environmental conditions, par-ticularly in terms of light intensity, temperature, and water level. This study aims to utilize the In-ternet of Things (IoT) to implement an environmental control system using Type-2 Fuzzy Logic for monitoring and controlling the environmental parameters of Drosera sessilifolia. The system uses an ESP32 microcontroller supported by several sensors, including a DS18B20 temperature sensor, an LDR light intensity sensor, and a water level sensor, to monitor environmental parameters ac-curately. The acquired data are processed using the Type-2 Fuzzy method to generate control deci-sions for actuators such as a heater, peltier, lamp, peristaltic pump, and fan. The Blynk platform is used to display environmental conditions, including temperature, light intensity, water level, and actuator decision status in real time. Based on the results of a 7-day indoor test conducted in the morning and at night, the average morning temperature was 30.04°C and the average nighttime temperature was 27.91°C, while the average light intensity was 1278 ADC in the morning and 2525.43 ADC at night, and the average water level was 1.16 cm in the morning and 0.99 cm at night. Based on 14 observations over 7 days, the system showed appropriate control responses in all observed scenarios, resulting in a 100% response success rate for the detected conditions. The novelty of this study lies in the implementation of an IoT-based Type-2 Fuzzy system specifically designed for the indoor cultivation of Drosera sessilifolia by simultaneously controlling temper-ature, light intensity, and water level. In addition, this study highlights the novelty of integrating Type-2 Fuzzy Logic and IoT for carnivorous plants, which remains very limited, especially for the cultivation of Drosera sessilifolia in a controlled indoor environment. The test results show that the system is capable of controlling temperature, light intensity, and water level effectively and responsively to environmental changes. The Type-2 Fuzzy method also produces stable and adap-tive control decisions. This system offers a solution for real-time indoor monitoring and environ-mental control of Drosera sessilifolia.
Hak Cipta (c) 2026 Rhimba Aulia, Chrystia Aji Putra, Henni Endah Wahanani https://creativecommons.org/licenses/by-sa/4.0
Pemetaan Spasial Jemaat GPPS Betlehem Lombok Menggunakan Algortima K-Means Clustering dan Leaflet.js
The church as a place for people to gather requires accurate information to store congregational data. With the Geographic Information System (GIS) it will be easier for church officials to map congregations that number more than hundreds of people and share locations of scheduled activities. The purpose of this study is to implement the K-Means algorithm to map the distribution of the GPPS Bethlehem congregation so that it can provide informative and easy-to-understand spatial visualization. The clustering algorithm method groups multiple data sets by explaining how data within a group has similar characteristics and how they differ from other groups. The data in the form of geographic coordinates (latitude and longitude) of the congregation's location was then processed using the K-Means algorithm with a predetermined number of clusters. The processing results showed that the data was successfully grouped into several clusters based on location proximity, each cluster having a centroid as the center point of the group, the centroid value changing at each iteration until it reached a convergent condition. Based on the research results, it can be concluded that: The clustering process produces several groups (clusters) that represent the distribution pattern of congregations in a particular area with a clear cluster center (centroid) and visualization using Leaflet.js is able to display the clustering results in the form of an interactive map that is informative and easy for users to understand.
Hak Cipta (c) 2026 Ahmat Adil, Bambang Krimono Triwijoyo, Heroe Santoso, Muhammad Azwar, Raymond Putra Suntana https://creativecommons.org/licenses/by-sa/4.0
Efektivitas IndoBERT pada Klasifikasi Sentimen Evaluasi Dosen: Studi Komparatif Support Vector Machine dan Naive Bayes
Sentiment analysis of student feedback plays an important role in evaluating the quality of teach-ing and learning processes in higher education. Qualitative comments in Student Evaluation of Teaching (SET) provide deeper insights than numerical ratings. However, they are expressed in unstructured textual form, making large-scale analysis difficult to conduct consistently and sys-tematically. Therefore, Natural Language Processing (NLP) approaches are required to automati-cally identify sentiment tendencies within student comments. This study aims to compare the per-formance of Gaussian Naive Bayes and Support Vector Machine (SVM) algorithms for classifying sentiment in SET comments using IndoBERT-based text embeddings. The research follows the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, including stages of data understanding, data preparation, modeling, evaluation, and deployment. Text comments were preprocessed and transformed into numerical vectors using IndoBERT Sentence-BERT em-beddings to capture contextual semantic relationships between words. These embeddings were then used as input features for both classification algorithms. Evaluation results show that the In-doBERT + SVM model achieved an accuracy of 93.88%, outperforming IndoBERT + Naive Bayes which obtained 92.40%. The SVM model also demonstrated more balanced precision, recall, and F1-score values across sentiment classes. These findings indicate that SVM is more effective in uti-lizing high-dimensional contextual embeddings for sentiment classification of student feedback.
Hak Cipta (c) 2026 Tifanny Nabarian, Maryam Hasnaa' Syamila, Salman El Farisi, Ananto Dwi Saputro https://creativecommons.org/licenses/by-sa/4.0
Rancang Bangun Manajemen Aset Laboratorium Sistem Informasi FMIPA Untan Berbasis Website
This study aims to design and build a website-based laboratory asset management information system at the Information Systems Department, Faculty of Mathematics and Natural Sciences, Tanjungpura University. The main problem with the current system is that the asset management process is still carried out manually, resulting in delays in recording, potential data errors, and limited access to information. In addition, the lack of an integrated system capable of supporting real-time asset management indicates a gap between the need for effective asset management and current system capabilities. The system development method used is the Fountain Model, which is iterative and flexible in supporting the software design and development process. System evalua-tion was conducted using the Black-Box Testing method to assess the suitability of system func-tions, and the System Usability Scale (SUS) to measure system usability from the user perspective. The test results showed that all system features run according to the functional requirements, with no critical errors found during Black Box testing. In addition, the evaluation results using the SUS method yielded a score of 82.5, which falls within the excellent category and indicates that the sys-tem is easy to use and acceptable to users. The implementation of this system also improved the ef-ficiency of the asset management process, sped up data retrieval, and reduced the risk of recording errors compared to the previous manual system. Thus, the developed information system not only addresses asset management problems but also improves service quality and data-driven deci-sion-making in the laboratory environment.
Hak Cipta (c) 2026 Ferdy Febriyanto, Renny Puspita Sari https://creativecommons.org/licenses/by-sa/4.0
Perancangan Aplikasi FinTech Locavest sebagai Sistem Pendukung Keputusan Analisis Kelayakan Lokasi Usaha Menggunakan Metode Design Thinking
The development of financial technology (fintech) and artificial intelligence (AI) opens up oppor-tunities to increase efficiency and objectivity in business decision-making, including business loca-tion selection. However, the integration of fintech, property, and AI-based location analysis in a single mobile platform has rarely been comprehensively studied. This study designed a prototype of the Locavest application as an AI-based fintech solution for business location feasibility analy-sis using a Design Thinking approach. The development method included the stages of empathize, define, ideate, prototype, and test to ensure the suitability of the features to the needs of MSMEs and novice investors. Prototype validation was conducted using the System Usability Scale (SUS) with 10 user respondents, resulting in an average score of 85, indicating a very good level of usability (category "excellent"). This application is expected to become an integrated decision support sys-tem that can help users analyze business locations and property investments more quickly, meas-urably, and easily. The contribution of this research lies in the integration of fintech, property, and AI features in a single mobile application and the use of Design Thinking methods to produce in-novative and user-friendly digital solutions.
Hak Cipta (c) 2026 Muhamad Ikhsan Tazudin, Randhu Fulki Ramadhan, Hyuga Ramdhan Noer, Genta Nazwar Tarempa https://creativecommons.org/licenses/by-sa/4.0
Penerapan E-CRM Berbasis Web Menggunakan Metode RAD pada Showroom Wali Sanga Motor
Customer service at Wali Sanga Motor Showroom is still conducted manually, causing delays in information delivery, unstructured customer data management, and less optimal handling of or-ders and customer complaints. This study aims to develop a web-based Electronic Customer Rela-tionship Management (E-CRM) system using the Rapid Application Development (RAD) method to improve service effectiveness and customer relationship management. The RAD method was applied through stages of requirements planning, prototyping design, system construction, and implementation. The system was developed using the Laravel framework and MySQL database with main features including product information management, online motorcycle ordering, cus-tomer complaint services, and administrative data management. System testing was carried out using User Acceptance Test (UAT) and White Box Testing on all functional requirements that had been designed. The test results show that the system runs 100% in accordance with the UAT sce-narios and all main modules function according to user needs without any significant logical er-rors. The implementation of this E-CRM system is expected to improve service efficiency, acceler-ate responses to customers, and support integrated and sustainable management of customer ser-vice data at Wali Sanga Motor Showroom.
Hak Cipta (c) 2026 Jihan Salsabila Arifin, Bayu Priyatna, Fitria Nurapriani, April Lia Hananto https://creativecommons.org/licenses/by-sa/4.0
Utilizing Natural Language Processing for the Analysis of BMKG Decadal Atmospheric Dynamics Reports in 2025
The Meteorology, Climatology, and Geophysics Agency (BMKG) publish decennial reports that provide valuable insights into Indonesia's meteorological conditions and their temporal fluctuations. However, due to their narrative structure, conducting direct quantitative analysis is problematic. This study seeks to address this issue by using a transparent, repeatable natural language processing (NLP) method to identify temporal trends in climatic conditions favourable to the formation of acid rain. The collection contains 36 BMKG decadal atmospheric dynamics studies for 2025. The proposed approach entails gathering textual input, performing basic preprocessing (case normalization, character sanitization, space-based tokenization, and stop-word removal), and subsequently employing predefined keyword dictionaries for analysis. These dictionaries delineate weather conditions that either facilitate or inhibit the formation of acid rain. The scores for acid rain conditions are determined by the frequency of specific keywords, adjusted for the document's length. Subsequently, they are categorized into groups utilizing statistical thresholds derived from the mean and standard deviation of the adjusted scores. Non-parametric statistical tests are employed to examine temporal patterns with greater specificity. The findings indicate that normalized acid rain scores are elevated in the initial years of the decade, specifically 2025, before gradually declining until year-end. The Spearman rank correlation test reveals a statistically significant negative correlation between normalized scores and time (\rho = -0.494, p = 0.0022). The Mann–Kendall test indicates a significant downward trend (Z = -2.902). These results demonstrate that the climatic conditions responsible for acid rain occurred only temporarily, rather than year-round. The core element of this work is a straightforward, lexicon-based NLP approach that is easily understood, replicable, and applicable, and can transform narrative atmospheric reports into structured quantitative metrics. This is beneficial for research on atmospheric dynamics and environmental analysis with official written data.
Hak Cipta (c) 2026 Ardiansyah Ramadhan, Aaz Muhmmad Hafidz Azis https://creativecommons.org/licenses/by-sa/4.0
Game Edukasi dengan Narasi Bercabang tentang Sejarah Puputan Margarana
History education in Indonesia still tends to be one-sided and lacks interactivity, which can di-minish interest in studying history. In this game, players will take on the role of a fictional young Balinese character who fought to defend Indonesia’s independence in Bali. This study aims to cre-ate an educational game with a branching narrative about the history of the Puputan Margarana. The contribution of this research lies in the application of branching narratives to explore the his-torical story of the Puputan Margarana interactively. This game was developed using a branching narrative with a Branch and Bottleneck narrative pattern for the Windows and WebGL platforms. An evaluation was conducted on 21 junior high school student respondents using the GUESS-18 instrument. The game evaluation results showed an average total score of 4.10 on a 5-point scale, with the Stealth dimension receiving the highest score of 4.24 and the Enjoyment dimension re-ceiving the lowest score of 3.90. Validity test results for the additional dimensions showed that all items were valid (r > 0.443; p < 0.05), and reliability tests confirmed that the additional dimen-sions were reliable (alpha > 0.7). The research results indicate that the developed educational game received a positive response from players.
Hak Cipta (c) 2026 Raditya Lungguk Satya Putra, Chrystia Aji Putra, Andreas Nugroho Sihananto https://creativecommons.org/licenses/by-sa/4.0
Game Virtual Tour Pengenalan Sistem Tata Surya Berbasis VR Google Cardboard dan Voice Command
The solar system is an essential topic in elementary school science education, playing a role in developing students' critical thinking skills and scientific understanding. However, conventional teaching methods often make students passive recipients of information, discouraging interaction and independent exploration. This can decrease interest and engagement in learning. Therefore, a more interactive and engaging approach is necessary to teach students about the solar system ef-fectively. This game uses VR technology and voice commands to provide an immersive experience exploring the solar system. Players can interact with objects in the solar system. It also features voice control, which allows students to interact with objects in the solar system and access addi-tional information. The average score on the questionnaire survey of the application was 86.30%. Integrating VR and voice commands has proven effective in increasing students' interest in learn-ing and facilitating navigation in immersive learning environments.
Hak Cipta (c) 2026 Muh Ulil Alkhaq, Siti Asmiatun https://creativecommons.org/licenses/by-sa/4.0
Rancang Bangun Aplikasi Laporan Keuangan Berbasis Web Dengan Metode Prototype (Studi Kasus: Praktik Mandiri Bidan Nining)
Technological advances in the digital era have had a significant impact on various aspects of life, including the financial reporting system. One form of this transformation is the use of web-based applications to facilitate the process of managing and presenting financial data. PMB Nining, an Independent Midwife Practice in Sukatenang Village, Bekasi Regency, still carries out manual financial reporting using books, which risks causing recording errors, physical data damage, and delays in reporting. This study aims to design and build a web-based financial reporting system using the prototype method with the Laravel framework. This approach involves users in every stage of the design so that the system developed is in accordance with their needs. In addition, system testing is carried out using the black box testing method to ensure that each function runs according to specifications. The test results show that all main features, such as user authentication, transaction recording, data validation, printing reports in PDF and Excel formats, and staff data management, function properly and achieve a 100% success rate. The system is also able to handle various types of input, both valid and invalid. The presence of dashboard and report filter features also supports a more efficient financial monitoring process. Thus, this system can be a solution to improve the accuracy and effectiveness of financial reporting at PMB Nining, while also contributing to the development of information technology in the health services sector.
Hak Cipta (c) 2026 Dewi Sonia Putrie, Aditya Dwi Putro, Gunawan Wibisono https://creativecommons.org/licenses/by-sa/4.0
Rancang Bangun Sistem Informasi Pendaftaran Siswa Baru Berbasis Web dengan Metode Waterfall pada TK Pertiwi 14
The transformation of information technology in the modern era provides significant opportunities to improve the effectiveness of educational administration, particularly in the new student admission process. One form of implementation is a web-based registration system that can automate the online registration flow and minimize data recording errors. Pertiwi 14 Kindergarten currently still uses the conventional registration method through paper forms that require parents to be present in person at the school, potentially causing verification delays, information duplication, and data input errors. This study aims to design and build a web-based new student registration system using the Laravel framework with Laravel Filament support to display a dynamic interface and structured data management. The system development uses the Waterfall model through the stages of needs analysis, design, implementation, testing, and maintenance. Testing results using Black Box Testing show that all system functions run according to specifications without any errors and are able to reduce input errors by up to 100% compared to manual methods. In addition, the registration data verification process is faster with an increase in time efficiency of 70%. The implementation of this system makes a real contribution to improving ease of access, data accuracy, management transparency, and administrative efficiency in the new student admission process at Pertiwi 14 Kindergarten.
Hak Cipta (c) 2026 Gilang Akbar Romadhoni, Susanto Susanto, Titis Handayani https://creativecommons.org/licenses/by-sa/4.0
Perancangan Sistem Rekapitulasi Data Order Menggunakan Bot Otomatis pada Layanan Indihome
This study discusses the design of a data order recap system using an automated bot for Indi-Home services from PT Telekomunikasi Indonesia (Telkom). IndiHome is a fiber optic-based communication service that provides home telephone, cable television, and internet facilities. With the growth of customers, the need for an efficient order management system becomes important because manual processes often lead to delays, recording errors, and difficulty in monitoring or-der status in real-time. A Telegram-based automated bot is proposed as a solution to automate the process of recording, reporting, and monitoring order data, thereby improving the speed, ac-curacy, and transparency of order management. The research method used is Research and De-velopment (R&D) with the stages of observation, design, creation, testing, and product validation. The evaluation results from 30 respondents, consisting of 1 team leader, 3 admins, and 26 salespeople, showed that this bot system is very effective and efficient, with a 100% success rate for the 1 team leader and 3 admins, while the trial conducted with the 26 salespeople achieved a 97.71% success rate. This system provides convenience, reduces manual errors, speeds up the follow-up process, and improves team coordination in managing IndiHome orders. Therefore, this recap bot has the potential to become the new standard in order data management.
Hak Cipta (c) 2026 Syifa Aqilah, Khairan AR https://creativecommons.org/licenses/by-sa/4.0
Evaluasi Teknik Prompting pada Large Language Model untuk Otomatisasi Penyusunan Skenario Unit Testing Smart Contract
Automated unit testing is essential for ensuring the security and reliability of smart contracts, particularly because their immutable nature prevents post-deployment modifications. However, manually creating test scenarios remains time-consuming, costly, and highly dependent on expert knowledge. A potential solution is to utilize AI technology, particularly Large Language Models (LLMs), to automatically generate test scenarios. This study fills the research gap in leveraging LLM technology in the software testing space by proposing a workflow for automatically gener-ating unit test scenarios for blockchain smart contract code using Large Language Models (LLMs). The proposed workflow consists of two stages: converting Solidity smart contracts into structured Gherkin scenarios and translating those scenarios into executable Hardhat unit test scripts. This study proposes an automated workflow using Large Language Models (LLMs) to address these challenges. The workflow consists of two stages: con-verting Solidity smart con-tracts into structured Gherkin scenarios and trans-lating those scenarios into executable Hardhat unit test scripts. Using the Gemini 2.5 Pro model, the research evaluates three prompting tech-niques such as Chain-of-Thought, Few-Shot, and Role-Based through quantitative analysis based on code coverage metrics, including Statements, Branches, Functions, and Lines. The experimental results show that Role-Based Prompting achieves the highest average coverage (92.02%), fol-lowed by Few-Shot Prompting (89.52%), while Chain-of-Thought produces the lowest coverage (78.79%). Role-Based Prompting also attains the highest Branch coverage, demonstrating superi-or capability in capturing conditional logic within smart contracts.
Hak Cipta (c) 2026 Salman El Farisi, Fahlia Athiyya Marva https://creativecommons.org/licenses/by-sa/4.0
Perancangan Dan Implementasi Game Interaktif untuk Pembelajaran Digital pada Pelajaran TIK di MTsN 2 Banda Aceh Menggunakan Scracth
ICT learning currently demands the use of innovative learning media, to increase students' moti-vation and understanding of the material being studied, but at MTsN 2 Banda Aceh, convention-al methods such as lectures still dominate, which reduce students' motivation towards storage device and output device materials. This study aims to design, develop, and implement learning media in the form of scratch-based interactive games as a means of ICT (information and com-munication technology) learning to increase interactivity, learning motivation, and understand-ing of grade VIII students towards storage device and output device materials. Development re-search with a 4D model (Define, Design, Develop, Disseminate) and a mixed methods approach integrates quantitative data from questionnaires and qualitative data from observations and in-terviews. The results of media expert validation reached an average of 91% (strongly agree), while the assessment of 36 students showed an average score of 91% (very good) in the aspects of design, navigation, material understanding, and learning motivation. The Maze Tech game has been proven to be feasible, effective, and fun as an ICT digital learning media that supports inde-pendent and active learning. Furthermore, the Maze Tech game was developed with attention to the characteristics of junior high school students who tend to prefer visual and challenge-based learning. The integration of game elements, such as maze navigation, audio-visual feedback, and evaluative quizzes, provides a contextual and meaningful learning experience. This media also encourages active student involvement in the learning process, so it serves not only as a means of entertainment but also as an effective pedagogical tool. Therefore, the results of this study are ex-pected to contribute to the development of game-based digital learning media and serve as a ref-erence for educators in implementing ICT learning innovations in the madrasah environment.
Hak Cipta (c) 2026 Zahwanul Ramadhana, Sarini Vita Dewi https://creativecommons.org/licenses/by-sa/4.0
Pengembangan Platform Intervensi Status Gizi Ibu Hamil Berbasis Integrasi Case-Based Reasoning dan Teori Dempster–Shafer
Nutritional problems among toddlers and pregnant women remain a major public health issue in Indonesia, necessitating a decision-support system capable of providing rapid and accurate nu-tritional diagnosis and intervention. This study develops an expert system integrating Case-Based Reasoning (CBR) and the Dempster–Shafer theory to diagnose the nutritional status of toddlers and pregnant women. The CBR method is employed to identify solutions for new cases based on similarity to previous cases, while the Dempster–Shafer theory is utilized to handle un-certainty and combine multiple forms of evidence derived from anthropometric, clinical, and health history parameters. The system was tested using 20 cases involving variables such as body weight, height, mid-upper arm circumference (MUAC), hemoglobin level (Hb), gestational age, and dietary intake. The results indicate that the system achieved an accuracy of 90%, an average confidence level of 82.7%, and a diagnostic precision of 88% when compared to expert nutrition-ists’ assessments. Diagnostic discrepancies occurred in only two cases (10%), both of which ex-hibited parameter values near the classification thresholds. These findings demonstrate that the integration of CBR and the Dempster–Shafer theory enhances the reliability of expert systems in generating accurate and measurable nutritional diagnoses despite data uncertainty, and shows strong potential as a decision-support tool for nutritionists in providing faster, more objective, and evidence-based nutritional interventions.
Hak Cipta (c) 2026 Muhammad Haris Nasri, Rifqi Hammad, Gede Yogi Pratama https://creativecommons.org/licenses/by-sa/4.0
Pengembangan Katalog Interaktif Aksesoris Pernikahan Adat Sumatera Selatan Berbasis Augmented Reality
The preservation of local culture faces serious challenges, particularly among younger genera-tions who tend to view traditional clothing merely as ceremonial costumes without understand-ing the cultural values they embody. To address this issue, this study aims to develop a visuali-zation media based on Augmented Reality (AR) in the form of a catalog of South Sumatran wed-ding attire accessories, accompanied by cultural narratives as an educational effort and a means of digitally preserving traditional heritage. The research employs a Design-Based Research (DBR) approach, starting from the collection of cultural data, content development, and AR ap-plication prototyping, to user testing with target participants. Results indicate a 32% increase in cultural understanding, an average usability score of 82.5 (excellent), and positive user responses toward interactivity, 3D visualization, and contextual audio narration. Qualitative analysis re-veals increased interest in local culture and favorable perceptions of AR as an educational me-dium. These findings confirm that the use of a digital catalog and AR is effective as an interactive, informative, and engaging learning tool that supports the preservation of local cultural heritage.
Hak Cipta (c) 2026 Meiyi Darlies, RM Chairil Andri, Liza Utama, Dewi Indasari https://creativecommons.org/licenses/by-sa/4.0
Perancangan dan Implementasi Sistem Pengelolaan Order Barang Berbasis Web dengan Laravel
CV. Surya Sarana Dinamika currently faces significant operational inefficiencies due to its man-ual, paper-based order management process. These challenges lead to frequent data recording errors, substantial delays in information flow, and a critical lack of real-time visibility regarding order status, which ultimately hinders effective administrative decision-making. This study aims to address these systemic issues by designing and implementing a web-based order management system utilizing the Laravel Framework. The system was developed using the Agile Development methodology, employing iterative cycles to ensure that the final product remains aligned with dynamic business requirements. The architecture is built upon the Model-View-Controller (MVC) pattern to ensure code scalability and long-term maintenance ease. Functional validation via Black-Box testing confirms that all core features, including order submission and purchasing validation, operate according to specifications. Quantitatively, the implementation resulted in a drastic efficiency increase; the average time for order submission decreased from 20-25 minutes to just 3-5 minutes (an efficiency gain of over 75%), while purchasing validation time was re-duced from 30-60 minutes to 5-10 minutes. These findings demonstrate that digital automation effectively eliminates manual bottlenecks and reduces the risk of human error. By providing cen-tralized data and real-time tracking, the system significantly enhances accountability and trans-parency within the company’s supply chain, providing a replicable model for digital transfor-mation in similar organizational contexts..
Hak Cipta (c) 2026 Nabela Yulian Anggraini, Susanto Susanto https://creativecommons.org/licenses/by-sa/4.0
Perancangan Enterprise Architecture Aplikasi Manage Personal Finance dengan Framework TOGAF dan PEAF
The development of information technology encourages the use of the Manage Personal Finance application as a more systematic and data-driven financial management tool. However, in prac-tice, the application still faces various problems, such as an unintegrated financial recording pro-cess, limited system architecture documentation, and the absence of an enterprise architecture framework that best suits business needs and long-term development. These problems have the potential to cause the system to be out of alignment with the organization's strategic objectives and difficult to develop sustainably. This study aims to: (1) design an enterprise architecture for the Manage Personal Finance application using the TOGAF ADM 9.2 framework; (2) produce an integrated business, data, application, and technology architecture blueprint; and (3) compare the effectiveness of the TOGAF and PEAF frameworks quantitatively based on five indicators, namely alignment with business needs, completeness of documentation, implementation speed, scalability, and resource requirements. The research method used is the design of an enterprise architecture based on TOGAF ADM, followed by a comparative analysis of the PEAF framework as an alternative, more pragmatic approach. The results of the study indicate that TOGAF excels in 3 out of 5 indicators (60%), namely business needs alignment, completeness of documentation, and system scalability, while PEAF excels in 2 indicators (40%), namely speed of implementation and resource efficiency. These findings indicate that TOGAF is more suitable for the development of Manage Personal Finance applications that have high complexity and long-term orientation. Thus, this study provides an empirical contribution in selecting the optimal enterprise architec-ture framework for the development of integrated and sustainable financial systems.
Hak Cipta (c) 2026 Mangapul Siahaan, Yulsen Yulsen, Muhammad Dody Firmansyah https://creativecommons.org/licenses/by-sa/4.0
Development of an AR-Based Solar System Flashcard Learning Media for Elementary Students Using the MDLC Method
Understanding the solar system remains challenging for elementary school students due to the abstract, spatial, and three-dimensional nature of astronomical concepts, which are often difficult to convey through conventional learning media. In response to this challenge, this study aims to develop and evaluate an Augmented Reality (AR)–based solar system flashcard learning media to support interactive and meaningful science learning at the elementary level. The learning media was developed using the Multimedia Development Life Cycle (MDLC) method, which consists of concept formulation, design, material collection, assembly, testing, and distribution stages. The AR application integrates three-dimensional planetary visualizations with flashcards to facili-tate concrete representation of abstract concepts and enhance student engagement. The evaluation focused on usability and learning support through User Acceptance Testing (UAT), involving 10 elementary school students and employing a 3-point Likert scale questionnaire. The results indi-cate that the AR-based flashcard media is easy to use, functions reliably, and effectively supports students’ understanding of solar system concepts. Students reported positive experiences in in-teracting with the learning media, suggesting its potential to improve motivation and conceptual comprehension in science learning. This study contributes to the development of innovative digi-tal learning media that promotes inclusive and quality education by integrating emerging tech-nologies into early science instruction. In alignment with Sustainable Development Goal (SDG) 4, the proposed AR-based learning media supports equitable access to engaging educational re-sources and enhances learning quality through interactive, technology-enabled instruction for elementary students.
Hak Cipta (c) 2026 Regania Pasca Rassy, Nurrahmadayeni Nurrahmadayeni, Muhammad Dzulhi Raihan, Latifa Zahra Agustini, Anandi Neina Aeyska Mahdi, Ghina Briliana Fatin Octariana, Luthfiyyah Az Zahro https://creativecommons.org/licenses/by-sa/4.0
Pengembangan Aplikasi Media Pembelajaran Matematika Berbasis Android untuk Siswa Kelas V di SD Negeri 3 Panggisari Menggunakan Metode MDLC
This study aims to develop Android-based mathematics learning media for 5th-grade students of SD 3 Panggisari as a solution to the low interest in learning and the limitations of conventional learning media. The development method used is the Multimedia Development Life Cycle (MDLC) which includes the stages of concept, design, material collection, assembly, testing, and distribution. The application is designed to contain mathematics materials according to the cur-riculum, equipped with visual illustrations, practice questions, and multiple-choice-based evalu-ations. Functional testing using the black box method shows that all application features run well. The implementation results show an increase in student learning interest, indicated by the results of the questionnaire testing using a Likert scale which obtained an average value of 4.39, thus in-cluded in the agree category. With these results, this Android-based mathematics learning media can be accepted in elementary school environments and is suitable for use as a learning support medium.
Multimedia Development Life Cycle (MDLC)
Hak Cipta (c) 2026 Sholakhudin Al Ayubi, Sigit Sugiyanto https://creativecommons.org/licenses/by-sa/4.0
Implementasi Algoritma FP-Growth untuk Sistem Rekomendasi Produk Kebutuhan Pokok pada E-Commerce
The rapid development of e-commerce in Indonesia necessitates recommendation systems that can capture user purchasing patterns accurately, adaptively, and in a data-driven manner. This study implements the FP-Growth algorithm to analyze transaction data from a self-developed essential-goods e-commerce platform. The research dataset consists of 60 user accounts with a total of 600 completed transactions, processed using a Python-based analytical module and au-tomatically integrated into a Laravel backend through a dedicated execution script. The FP-Growth algorithm is applied to generate frequent itemsets and association rules using a min-imum support of 0.01, a minimum confidence of 0.1, and a minimum lift of 1.0. The results indi-cate that the most dominant associative patterns occur among kitchen staple products such as in-stant noodles, chicken eggs, and wheat flour, as well as household cleaning products such as de-tergents and fabric softeners. Several rules exhibit confidence values as high as 0.9615 and lift values up to 4.451, indicating strong and statistically significant relationships between products. System performance evaluation using a Top-4 recommendation scheme shows a Hit Rate of 54.35% and a Recall of 54.35%, demonstrating that the system is able to provide relevant recom-mendations for the majority of transactions. This implementation is shown to improve recom-mendation accuracy while strengthening personalization and cross-selling strategies on essen-tial-goods e-commerce platforms. These findings confirm that FP-Growth is an effective and effi-cient method for identifying empirical purchasing patterns and supporting the development of recommendation systems in small- to medium-scale e-commerce environments.
Hak Cipta (c) 2026 Mahjid Herlambang, Susanto Susanto https://creativecommons.org/licenses/by-sa/4.0