Implementasi Metode K-Medoids Untuk Clustring Penerima Bantuan Berdasarkan Normalisasi Data Masyarakat Miskin Dengan Metode Desimal Scaling

Abstract

The Social Welfare Office is the distributor of aid for the economically disadvantaged population in accordance with the regulations set by the Minister of Social Affairs of the Republic of Indonesia Number 20 of 2019. This aid is provided to the economically disadvantaged population selectively, not continuously, in the form of goods or cash, aiming to improve the welfare of the economically disadvantaged and socially vulnerable. The data of aid recipients from the economically disadvantaged population needs to be processed and normalized to obtain the desired information, facilitating the grouping of aid recipients at the Southeast Aceh Social Welfare Office. The aid recipients' data is processed and normalized to ease the grouping process using Decimal Scaling method, enabling the extraction of desired information. Subsequently, the data is clustered using the K-Medoids method to group aid recipients based on the normalized data, thus simplifying the identification of the most suitable aid recipients. This research employs a system capable of providing a solution for clustering aid recipient data using the K-Medoids method and the RapidMiner application