Implementation of KNN and AHP-TOPSIS as Recommendation System for Mustahik Selection

Abstrak

The National Amil Zakat Agency (BAZNAS) has the task of managing zakat on a national scale, including zakat. The number of prospective zakat recipients is greater than the availability of zakat funds distributed, which has an impact on the need for a selection process for mustahik. In this research, to assist the mustahik selection process, KNN will be used to classify mustahik candidates who meet the requirements, AHP to obtain consistent weights, and TOPSIS to provide recommendations for the order of mustahik whose zakat will be distributed. The dataset used in the research consisted of 77 data consisting of the criteria for number of dependents, husband's job, wife's job, total income, total expenses, and acceptance status of mustahik candidates. The application of KNN produced 15 data that were declared worthy of being considered mustahik. In the next stage, using AHP, the weights for each criterion were obtained at 12.66%, 9.23%, 10.10%, 45.96% and 22.04%. These weights were used in the TOPSIS decision support system and the results obtained were that the 76th mustahik candidate was the first ranked candidate to be proposed as a mustahik. In this research, a system was also built using KNN and AHP-TOPSIS using the PHP programming language as a recommendation system tool.