CLUSTERING PENINDAKAN KASUS KORUPSI DI INDONESIA MENGGUNAKAN K-MEANS: ANALISIS DATA KPK TAHUN 2004-2024 - Anjarwati, Dwi (Universitas Multi Data Palembang, 2025)
Abstract The enforcement of corruption cases by the Corruption Eradication Commission (CEC) from 2004 to 2024 shows variation in both the number of cases and the completion of legal processes. This study employs a quantitative approach using the K-Means Clustering method to group annual data based on five legal stages: investigation, inquiry, prosecution, final verdict (inkracht), and execution. Clustering was conducted based on the similarity of centroid values across years, with the optimal number of clusters determined using the Davies-Bouldin Index (DBI). The analysis divides the period into four main phases: initiation, expansion, transition, and intensification, illustrating shifts in enforcement patterns over time. The findings indicate that the success of corruption enforcement is determined not only by the number of cases handled but also by the ability to complete the legal process through to the final stage. This method provides an objective overview that can be used to evaluate KPK’s enforcement performance and to formulate more effective anti-corruption strategies. Keywords: Corruption, CEC, Enforcement, Clustering, K-Means, Centroid, Davies-Bouldin Index