Implementation of Data Mining for Social Assistance Funds Using the C4.5 Algorithm in the Empat Lawang Regency Government

Abstract

The Government of Empat Lawang Regency seeks to improve public welfare through social assistance programs, including the Home Renovation Assistance Program for residents living in uninhabitable houses. Many residents still live below the housing eligibility line, creating the need for a fair, data-driven selection mechanism. Traditionally, the selection process begins at the village level, where village heads identify residents with inadequate housing and low daily income levels. These data are then submitted to the Regency Government, where the Verification Team determines the final recipients. However, manual data processing makes it difficult to ensure transparency and efficiency. This study applies the C4.5 Decision Tree Algorithm to classify eligibility for social assistance using existing data from the Empat Lawang Regency Government. A web-based system was developed to support automated classification and decision-making in line with the criteria set by the Minister of Public Works and Housing Regulation No. 13/PRT/M/2016. The system enhances accuracy, transparency, and efficiency in determining eligible beneficiaries for social housing renovation programs.