Comparative Analysis of the SMART, TOPSIS, and MOORA Methods for Determining Village Fund Direct Cash Assistance Recipients

Ida Widaningrum; Ali Nur Wakhid; Jamilah Karaman

doi:10.34148/teknika.v15i2.1502

Authors

Ida Widaningrum Department of Informatics, Universitas Muhammadiyah Ponorogo, Ponorogo, East Java, Indonesia
Ali Nur Wakhid Department of Informatics, Universitas Muhammadiyah Ponorogo, Ponorogo, East Java, Indonesia
Jamilah Karaman Department of Informatics, Universitas Muhammadiyah Ponorogo, Ponorogo, East Java, Indonesia

DOI:

https://doi.org/10.34148/teknika.v15i2.1502

Keywords:

SMART, TOPSIS, MOORA, Direct Cash Assistance, Comparative Study

Abstract

Indonesia’s poverty is still a structural problem with a rate of around 9.36 percent as of March 2023. The government gave Village Fund Direct Cash Assistance (BLT-DD) based on PMK Number 190/PMK.07/2021 Article 33. Paragraph one. So far, different Multi-Criteria Decision Making (MCDM) techniques have been used for the selection of BLT-DD recipients, but none of them has been tested for their consistency using the same dataset. This study compared three MCDM approaches on 25 potential BLT-DD recipients in Plosokerep Hamlet, Dukuh Village, Magetan Regency, using six criteria of PMK 190/PMK.07/2021 with weights determined by the Village Head. The three approaches were Simple Multi-Attribute Rating Technique (SMART), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Multi-Objective Optimisation on the basis of Ratio Analysis (MOORA). We used Spearman Rank Correlation, Kendall Tau and Jaccard Similarity to compare the consistency of the top 16 processes. The Spearman SMART-TOPSIS 0.92, SMART-MOORA 0.95 and TOPSIS-MOORA 0.98 values were found to be highly consistent. Thirteen of the sixteen quotas were agreed upon by all three techniques, with the top three ranks consistent. TOPSIS and MOORA obtained almost the same rankings due to the same vector normalisation, whereas SMART with linear normalisation shows a more evident differentiation at the extreme profiles. This paper presents a multi-method consensus solution to improve the dependability of BLT-DD recipient selection.

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