SISTEM PENDUKUNG KEPUTUSAN PENYELEKSIAN PENERIMA BANTUAN RUMAH LAYAK HUNI MENGGUNAKAN METODE TECHNIQUE FOR OTHERS PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) DAN SIMPLE ADDITIVE WEIGHTING (SAW)

  • Ferry Susanto
  • Riski Putri Ameliya
  • Novelia Hasmarani
Keywords: Decision Support System, Technique For Others Preference by Similarity to Ideal Solution (TOPSIS), Simple Additive Weighting (SAW)

Abstract

               In Kalibalangan Village, South Abung District, North Lampung Regency, in determining who deserves to receive housing assistance, proper data processing is needed so that it is hoped that residents who really need housing assistance can be achieved. Determining the population, which was previously done using this traditional method, needs to be made a Decision Support System (DSS) that is able to process data from criteria effectively so that it can produce accurate data. The purpose of this decision support system is to be able to determine which residents are truly considered eligible to receive housing assistance. The method used for this research is the Technique For Others Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW) methods. This method is used for the selection of livable housing beneficiaries.

              The results of the calculation using the sample method used were 15 people with a population of 55. From the sample for ranking results for the Technique For Others Preference by Similarity to Ideal Solution (TOPSIS) method, the highest score was Taridi with a value of 1 and the lowest value was Supardi with a score of 1 0.2159, and the results of the Simple Additive Weighting (SAW) ranking, the highest ranking value is Taridi with a value of 1.45 and the lowest value is Supardi with a value of 0.95. From the results of calculations using the Maen Square Error (MSE) method for the Technique For Others Reference by Similarity to Ideal Solution method with 31835.3 results and for the Simple Additive Weighting method with 31608.3 results. So that the result closest to 0 is the most optimal Simple Additive Weighting method to use.

Published
2021-12-24