Implementasi Algoritma K-Means untuk Mengelompokkan Data Tingkat Kemiskinan di Sulawesi Selatan Berdasarkan Kota/Kabupaten - Irfan; Faizal, Lut (Lembaga Penelitian dan Pengabdian Masyarakat Universitas Lamappapoleonro, 2024)
Poverty is a state in which individuals or groups lack sufficient access to the economic, social, and cultural resources required to attain a reasonable standard of living. The Central Bureau of Statistics (BPS) data offers an overview of the poverty rate in South Sulawesi province, although it only presents the poverty rate categorized by district or city. In order to prioritize their answers, the government must possess knowledge about the regions with the highest and lowest poverty rates to effectively address poverty. Hence, it is crucial to categorize districts or municipalities in South Sulawesi according to their poverty rate. This would enable the government to develop suitable policies or strategies to alleviate poverty while considering the poverty rate in each district or municipality. The data clustering in this study was performed using the K-Means algorithm and the RapidMiner program. The findings revealed the presence of four distinct clusters of districts or municipalities, which were categorized according to their poverty levels. The clusters are categorized as follows: Cluster 0 consists of Jeneponto, Gowa, Pangkep, Luwu, and North Luwu. Cluster 1 includes Bulukumba, Takalar, Maros, Wajo, Pinrang, Enrekang, Tana Toraja, and North Toraja. Cluster 2 comprises Bone and Makassar. Lastly, Cluster 3 consists of Selayar Islands, Bantaeng, Sinjai, Barru, Soppeng, Sidrap, East Luwu, Pare-Pare, and Palopo. Cluster 2 has the greatest poverty rate or number among all the clusters.