Abstract
Poverty is a condition that is below the line of minimum requirement standard values, both for food and non-food. The Government of Indonesia has various programs to overcome poverty-based assistance social, including the family hope program. This family hope program is the provision of conditional cash assistance to very poor households in which there are pregnant women, toddlers, elementary, junior high, high school, elderly, and severe disabilities. The amount of assistance obtained based on the level of family poverty with poverty level parameters is seen from the many categories of very poor households concerned along with the obligation of participants to carry out important commitments in the field of Health and Education. The purpose of this research is the development of a mobile-based poor family monitoring application using the k-means clustering method. Validity test results using sample data 21, it can be concluded that the system can group poor families into 7 clusters with a thoroughness rate of 90.4%. Based on these results, K-Means Clustering can be said to have a high accuracy value for clustering poor families.
Highlights
Pemerintah Indonesia sudah menyelenggarakan berbagai program bantuan sosial untuk menanggulangi kemiskinan, diantaranya adalah Program Keluarga Harapan (PKH)
PKH is a conditional cash assistance provided to very poor households where there are toddlers, elementary school, junior high, high school, pregnant women, elderly parents and family members with severe disabilities
The poverty level determines the amount of assistance received, where many categories of households are very poor and is the obligation for participants to continue to carry out their commitments in the health and education sectors is a parameter of the poverty level
Summary
Kondisi yang berada di bawah garis suatu nilai standar kebutuhan minimum baik itu untuk makanan ataupun non makanan merupakan suatu kemiskinan. PKH merupakan program bantuan sosial yang diberikan kepada keluarga miskin dan rentan. Penerapan Metode ini dapat menentukan keluarga mana yang dianggap kurang mampu (miskin), sederhana, dan kaya dalam membutuhkan bantuan dana dengan tingkat akurasi sebesar 69%. Data Mining untuk mengelompokkan penerima bantuan dengan menggunakan metode K-Means dalam pengklasteran penduduk miskin [7][8]. Clustering K- Means, didapatkan bahwa sistem mampu mengolah data warga miskin beserta atribut dan kriteria yang dikelompokkan kedalam 3 nilai kategori, yakni Mampu, Miskin, Cukup pada setiap daerah dari beberapa warga yang digunakan untuk proses perhitungan. Harapan (PKH) juga dapat digunakan untuk memantau penyebaran program bantuan dengan menggunakan smartphone. Perbedaan dengan penelitian sebelumnya adalah penentuan Clustering dalam 7 tingkatan kemiskinan yaitu Miskin 1 sampai 7 dan untuk monitoring bantuan PKH dapat dilakukan menggunakan Sistem Informasi Geografis berbasis mobile phone
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