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Agung Teguh Setyadi
Universitas Anwar Medika
Computer Science & IT

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Combination of SAW Method and Linear Interpolation in Selection of Raskin Recipients Agung Teguh Setyadi; Pandu Adi Cakranegara; Arianto Muditomo; Iwan Henri Kusnadi; Efendi
INFOKUM Vol. 10 No. 03 (2022): August, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

The government assistance program is one of the efforts to promote community welfare, as is the case with the Raskin assistance program. In the contribution of aid from the center to the regions, of course, many things are of concern, namely the equitable distribution and correct targeting of the rightful recipients. In reality, there are problems in determining the recipients of Raskin assistance due to the indication of an element of subjectivity in making decisions and the mismatch between candidate data and recipients due to not taking into account the assessment criteria in determining the selected candidates for assistance. This study proposes an evaluation of the selection process for Raskin beneficiaries with four criteria, namely Income (C1), Marital Status (C2), Dependent of Children (C3), and Age (C4). The method combines the Simple Additive Weighting (SAW) method in determining the nature of the criteria to calculate the final score and the Linear Interpolation technique for the scoring process to determine the difference in numerical values. The study results are seven alternative recipients of assistance selected into three selected alternatives. The analysis of the influential criteria shows that the Dependent of Children (C3) and Age (C4) criteria affect the final ranking of the alternative recipients of Raskin assistance.
Co-Authors Arianto Muditomo Cakranegara, Pandu Adi Efendi Efendi Iwan Henri Kusnadi