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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic
Deka Mario
Institut Teknologi Bisnis Dan Bahasa Dian Cipta Cendikia
Computer Science & IT Decision Sciences, Operations Research & Management

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Recommendation for Self-Help Housing Stimulus Assistance (BSPS) Recipient Using Multi-Criteria Decision Making Methods Deka Mario; Sri Lestari
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9584

Abstract

The Housing and Settlement Area Office aims to improve the accuracy and efficiency of selecting beneficiaries for the Self-Help Housing Assistance (BSPS) program by using the Weighted Product (WP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. This study was conducted in Sungkai Tengah Subdistrict, North Lampung, involving six criteria: land ownership, employment, house condition, income, independence, and household size.The WP method is used to determine the weight of each criterion by calculating the product of the criteria values raised to the power of their respective weights, which helps in ranking the alternatives. TOPSIS is applied to identify the best alternative by comparing the geometric distance of each option to the ideal solution, which is either the maximum or minimum value of each criterion The results indicate that the WP and TOPSIS methods can provide more objective and transparent rankings. The application of these methods resulted in the highest ranking for ID V3 with a vector V score of 0.1317. The decision support system developed from this research is expected to assist the Housing and Settlement Area Office in distributing aid more accurately, fairly, and efficiently, thereby supporting the government's goals in improving housing quality and spatial planning
Co-Authors Sri Lestari