Integration of the Hybrid Decision Support System and Machine Learning Algorithm to Determine Government Assistance Recipients: A Case Study in the Indonesian Funding Program

Abstract

The Indonesian government provides incentives to facilitate community development through various funding programs to improve the economy and restore the national economy. However, there were many obstacles in determining the proper target beneficiaries. This study aims to assist decision-makers in determining targeted and accountable beneficiary candidates. In this study, a hybrid Analytical Hierarchy Process (AHP) method with Simple Additive Weighting (SAW) was used and integrated with machine learning modeling using Logistic Regression (LR). The AHP approach is used to determine the weight of each criterion, and the SAW method is used to sort out each available alternative with the help of an expert team's assessment. Instead, the LR method is used for the predictive analysis and classification of the resulting data.