PROVINCIAL CLUSTERING IN INDONESIA BASED ON INFORMATION AND COMMUNICATION TECHNOLOGY (IP-TIK) DEVELOPMENT INDEX WITH SELF ORGANIZING MAPS (SOM) ALGORITHM - Husnayaini Nur'aini; Sri Andayani (Jurnal Kajian dan Terapan Matematika, 2025)
This study aims to: (1) Describe the results of province clustering in Indonesia using Self Organizing Maps (SOM) based on the ICT development index; and (2) Describe an overview of ICT development in Indonesia in 2021. This research uses Self Organizing Maps method with Davies Bouldin Index (DBI) as the best cluster validation index. The research data are 10 indicators: 1) fixed telephone subscribers, 2) cellular telephone subscribers, 3) households with computers, 4) households with internet, 5) individuals using internet, 6) average length of schooling, 7) secondary gross enrollment rate, 8) tertiary gross enrollment rate, 9) average household telecommunications consumption to total consumption, and 10) many villages have BTS. The data is taken from the official publication of BPS RI in 2022. The results of this study show: (1) The best model is 5 clusters with DBI value of 0.3171. Clusters 1, 2, 3, 4 and 5 consist of 3, 1, 22, 7 and 1 province respectively. (2) Cluster 1 is lower middle class, cluster 2 is very underdeveloped, cluster 3 is average because all its indicators have average values, clusters 4 and 5 excel in ICT development, resulting in gaps in ICT development in Indonesia in 2021.