Meidika Arni Saraswati

A Decision Support System for the Selection of Social Assistance Recipients: Comparison of SAW and TOPSIS Methods in Ponggol Village

Introduction

A decision support system for the selection of social assistance recipients: comparison of saw and topsis methods in ponggol village. Web-based DSS for objective, transparent selection of social assistance (PKH) recipients in Ponggol Village. Compares SAW and TOPSIS methods for efficient decision-making.

Abstract

The selection process for prospective recipients of the Program Keluarga Harapan (PKH) social assistance in RW. 03, Ponggol Village, is currently conducted manually, which is time-consuming and prone to subjectivity. To address these issues, this research aims to develop a web-based decision support system (DSS). The system was designed using PHP and MySQL for the backend, along with HTML, CSS, and JavaScript for the frontend. Two DSS methods, namely Simple Additive Weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), were implemented to perform calculations and rank alternatives based on five criteria determined through an interview. System testing results show that both the SAW and TOPSIS methods successfully provided consistent ranking results for ranks 1 to 5. Therefore, the developed system can serve as an objective, transparent, and efficient tool for decision-makers in determining the most deserving recipients of social assistance.

Review

This paper presents a pertinent and valuable contribution to the field of decision support systems, addressing a critical need for objectivity and efficiency in the allocation of social assistance. The authors effectively highlight the existing problems of subjectivity and time consumption inherent in the manual selection process for the Program Keluarga Harapan (PKH) in Ponggol Village. The primary objective of developing a web-based decision support system to overcome these limitations is well-articulated and directly targets a real-world problem with significant social implications. Methodologically, the research describes the development of a web-based DSS utilizing a standard and practical technology stack, including PHP and MySQL for backend development, complemented by HTML, CSS, and JavaScript for the frontend. The core of the system lies in its implementation of two widely recognized Multi-Criteria Decision Making (MCDM) methods: Simple Additive Weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). These methods are employed to rank alternatives based on five distinct criteria, which were reportedly identified through an interview process, adding a layer of empirical grounding to the criteria selection. A notable finding from the system testing is the consistent ranking results for the top five alternatives across both SAW and TOPSIS methods, suggesting a degree of robustness and reliability in the system's core computational logic. In conclusion, the developed DSS offers a highly promising solution to a persistent challenge in social welfare administration. By providing an objective, transparent, and efficient tool, it directly supports decision-makers in accurately identifying and prioritizing the most deserving recipients of social assistance. This research not only demonstrates the practical application of MCDM techniques in a real-world scenario but also underscores the potential for technology to enhance fairness and accountability in public service delivery. The successful development and testing of this system lay a strong foundation for its potential implementation and broader adoption in similar contexts, contributing positively to community welfare management.

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