Perbandingan Metode Biclustering untuk Pengelompokan Wilayah Berdasarkan Faktor Penyebab Kusta di Sulawesi
DOI:
https://doi.org/10.35746/jtim.v8i3.1028Keywords:
Biclustering, Cheng & Church, Iterative Signature Algorithm, Leprosy, SulawesiAbstract
Leprosy is one of the health issues that spread due to various social and environmental factors. It is a public health issue whose spread is influenced by various social and environmental factors. The aim of this study is to group districts/cities on the island of Sulawesi based on the factors that influence the spread of leprosy using a biclustering approach. The methods used were Cheng & Church (CC) and Iterative Signature Algorithm (ISA), which can cluster data simultaneously on the dimensions of area and variables. The data used are secondary data from 2024 covering eight variables and a number of districts/cities as the units of observation. The analysis stages included pre-processing, missing value handling using mean imputation, data standardisation, and application of the two biclustering methods. The performance was evaluated using Mean Squared Residue (MSR), the Liu & Wang index, and variance. The results of the study show that the CC method produces an average MSR value of 0.006015, which is lower than the ISA method's value of 0.015006. The average Liu & Wang index value for the CC method was 0.2905, lower than the ISA method's value of 0.7356. Furthermore, the average variance in the CC method was 0.07737, which was lower than the ISA method at 2.7859. Based on these three evaluation criteria, the Cheng & Church method is more effective in grouping regions based on factors influencing the spread of leprosy in Sulawesi.
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