Decision Support System for the Selection of Prospective Recipients of the Smart Indonesia Program (PIP) Assistance using the Topsis Method

Putri Amelia Lubis; Chairunisah; Mulyono; Insan Taufik

doi:10.59934/jaiea.v5i3.2494

Authors

Putri Amelia Lubis Ilmu Komputer, Universitas Negeri Medan
Chairunisah Universitas Negeri Medan
Mulyono Universitas Negeri Medan
Insan Taufik Universitas Negeri Medan

DOI:

https://doi.org/10.59934/jaiea.v5i3.2494

Keywords:

Decision Support System, Normalization, Python, Scholarship, TOPSIS

Abstract

This study aims to implement a Decision Support System (DSS) using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method to determine the recipients of the Indonesia Smart Program (PIP) at SMPNegeri 36 Medan. The TOPSIS method was chosen for its ability to produce objective and measurable results based on five main criteria: parents’ occupation (C1), number of dependents (C2), parents’ income (C3), student status (C4), and distance from home to school (C5). Data were collected from 306 students, with assigned weights of 25% for income, 25% for occupation, 20% for dependents, 20% for student status, and 10% for distance.The research stages included scoring, decision matrix formation, data normalization, weighted normalization, and determining positive and negative ideal solutions to obtain preference values (Vᵢ). The results show that students with V ≥ 0.5 are categorized as eligible, while those with V < 0.5 are not eligible. Out of 306 students, 103 were eligible and 203 were not. The implementation of the TOPSIS method in DSS effectively assists schools in selecting PIP recipients more quickly, objectively, and accurately, ensuring that aid is given to students who truly need it.

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