JTIM : Jurnal Teknologi Informasi dan Multimedia

Aplikasi Augmented Reality sebagai Media Edukasi Monumen Bersejarah di Indonesia

2024-04-18T02:41:41+00:00

Indonesia has many monuments spread from Sabang to Merauke, because of the many historical events. So, to be able to explore the historical monuments spread across Indonesia, can only be done by visiting the region, so not all levels of people can easily visit all regions of Indonesia. Based on these problems, an application was created which aims to be an educational medium for introducing historical monuments in Indonesia using Augmented Reality technology. By utilizing Augmented Reality as an interactive educational medium, it is hoped that it can increase interest in learning from many groups by using smartphones to introduce historical monuments in Indonesia and obtain information and visualization with 3D objects. The research method that will be used in this research has four stages including data collection, application design and application creation, evaluation and conclusions. Application design uses Augmented Reality technology with the MDLC (Multi-media Development Life Cycle) approach method. Based on the results of Black Box testing, all functional systems in the application can function properly. The final results of the evaluation using the System Usability Scale (SUS) testing method with 30 respondents received a score of 77.166. So, it can be concluded from this assessment that the Augmented Reality application as an educational medium for historical monuments in Indonesia in the adjective rating category is GOOD with a grade scale of C, which means usability based on the data obtained has received an acceptable level of acceptance. So this application can be said to be suitable for use.

Sistem Monitoring Capaian Pembelajaran di SMKN 1 Kota Bima Berbasis Web dan Android

2024-04-18T02:41:42+00:00

In the process of teaching and learning, there is always a specific goal to be achieved, aiming to fulfill and produce a set of achievements targeted by a subject teacher. Each subject has different learning outcomes. Supervision of learning outcomes is necessary to ensure that both students and teachers can achieve the agreed-upon or school-established learning outcomes. Throughout this process, schools face difficulties in carrying out supervision to ensure that learning outcomes are met. This challenge underscores the need for an application that can assist in the supervision of learning outcomes, aiding schools in ensuring that both teachers and students can successfully achieve the set learning outcomes. The application development process utilizes the waterfall method, with data collection using documentation techniques. The programming languages used are Dart and PHP. The developed application includes the ability to monitor quiz scores, assignment grades, student attendance levels, as well as creating an interactive and engaging discussion forum. After implementation and testing, the application proves to be highly effective in fulfilling its function of supervising learning outcomes. In summary, during the teaching and learning process, the primary objective is to achieve the set learning outcomes. The challenges faced by schools in supervising these outcomes emphasize the necessity for an application that can facilitate this process, ensuring the successful attainment of learning goals by both teachers and students. The development process, using the waterfall method, along with Dart and PHP programming languages, results in an application with features such as quiz and assignment monitoring, attendance tracking, and an interactive discussion forum. The successful implementation and testing demonstrate the application's effectiveness in supervising learning outcomes, providing a practical and efficient solution for schools to monitor and enhance the quality of education.

Optimalisasi Model Ensemble Learning dengan Augmentasi dan SMOTE pada Sistem Pendeteksi Kualitas Buah

2024-04-18T02:41:42+00:00

Fruit quality is an important factor in selecting fruit for consumption because it affects consumer health and satisfaction. Identification of fruit quality has become the focus of research, and one of the approaches used is a non-destructive approach through measuring the gases produced by the fruit. Machine learning can be used to process this gas data and build system models that can classify fruit quality. This research discusses the application of the DCS-OLA and Stacking dynamic ensemble learning algorithms to build a fruit quality detection system model. The basic methods used to build models are Logistic Regression, Decision Tree, Gaussian Naïve Bayes, and Mul-ti-Layer Perceptron. The fruit used is mango with a shelf life of 7 days and Srikaya (sugar apple) with a shelf life of 4 days. The condition of the initial dataset is unbalanced. The research results show that trimming the mango dataset to only 4 days according to the shelf life of sugar apple helps reduce the difference in shelf life between the two. Then jittering and balancing techniques are used to increase and balance the number of datasets between the two types of fruit. High accuracy is achieved by the DCS-OLA ensemble and stacking ensemble by combining the basic methods of Logistic Regression and Decision Tree, especially in balanced dataset conditions. In conclusion, the use of ensemble learning in detecting fruit quality has great potential for real-world applications. However, further validation is needed with larger datasets and a wider variety of conditions.