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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic
Abror , Muhamad
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Computer Science & IT Decision Sciences, Operations Research & Management

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TOPSIS and WP for BLT Decision Support in Srimulyo Abror , Muhamad; Hasibuan, Muhammad Said
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10606

Abstract

Srimulyo Village, situated in Anak Ratu Aji District, Central Lampung Regency, faces difficulties in ensuring an accurate and efficient process for determining recipients of Direct Cash Assistance (BLT). The current manual system often results in errors and perceived inequities. This research explores the application of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method alongside the Weighted Product (WP) method to enhance decision-making in selecting BLT recipients. TOPSIS is employed to identify optimal alternatives based on their closeness to a positive ideal solution, while WP emphasizes the importance of criteria through assigned weights. The findings indicate that integrating these two methods yields recommendations that are more objective, transparent, and efficient. The TOPSIS approach enables the system to rank alternatives by assessing their proximity to the ideal solution, facilitating data-driven decision-making. Meanwhile, the WP method ensures that each criterion's importance is appropriately weighted, thereby increasing the reliability of the results. This dual-method approach not only minimizes human error but also promotes fairness in the selection process. The proposed integrated system offers a practical solution to improve the accuracy of social assistance distribution in Srimulyo Village. By adopting these decision-support methods, local authorities can establish a more equitable, reliable, and efficient mechanism for BLT allocation, ensuring that aid reaches the individuals who need it most.
Co-Authors M Said Hasibuan