Recommendation for Self-Help Housing Stimulus Assistance (BSPS) Recipient Using Multi-Criteria Decision Making Methods

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

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Publication Details

Journal
PIKSEL Penelitian Ilmu Komputer Sistem Embedded and Logic
Published
2024-09-30
DOI
https://doi.org/10.33558/piksel.v12i2.9584
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Recommendation for Self-Help Housing Stimulus Assistance (BSPS) Recipient Using Multi-Criteria Decision Making Methods

Sri Lestari, Deka Mario
PIKSEL Penelitian Ilmu Komputer Sistem Embedded and Logic
Data Mining and Machine Learning Applications
article

Recommendation for Self-Help Housing Stimulus Assistance (BSPS) Recipient Using Multi-Criteria Decision Making Methods

Sri Lestari, Deka Mario
article en

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

PIKSEL Penelitian Ilmu Komputer Sistem Embedded and LogicVol. 12(2)
Informatics and Business Institute Darmajaya (ID), Institut Teknologi dan Bisnis Kalbe (ID)
Sustainable cities and communities
Openalex Percentile: Top 71%
Data Mining and Machine Learning Applications
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