Classification of Program Keluarga Harapan Assistance Recipients Using a Website-Based Support Vector Machine Algorithm (Case Study: Panyabungan Kota Subdistrict)

Khoirul Ahyar

doi:10.59934/jaiea.v5i2.1941

Authors

Khoirul Ahyar Universitas Negeri Medan

DOI:

https://doi.org/10.59934/jaiea.v5i2.1941

Keywords:

PKH, Support Vector Machine (SVM), classification, family income, eligibility, Panyabungan Kota Subsdistrict, Mandailing Natal District, web-based system, PHP, JavaScript.

Abstract

Program Keluarga Harapan (PKH) is a social assistance program aimed at reducing poverty by providing financial aid to eligible families. This research focuses on the development and implementation of the Support Vector Machine (SVM) algorithm to classify PKH recipients in Panyabungan Kota Subdistrict, Mandailing Natal Destrict. The classification process utilizes factors such as family income, number of family members, and the presence of elderly members. These three factors are chosen due to their availability from public records, ensuring the privacy of participants. The classification model developed in this study is implemented in a web-based system built with PHP and JavaScript, designed to facilitate the automatic classification of PKH recipients. This system helps streamline the registration to be more precise and effective, providing an efficient solution for local government officials to identify eligible families for the PKH program. The evaluation results show that this system can classify PKH recipients well with an accuracy of 93%, offering an automated approach that supports decision-making in the distribution of social assistance.

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