Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Nabilah Iftah Nella
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Klasifikasi Penerima Bantuan Program Keluarga Harapan menggunakan Algoritme Decision Tree C4.5 (Studi Kasus: Desa Mlirip Kabupaten Mojokerto) Nabilah Iftah Nella; Nanang Yudi Setiawan; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 3 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Social assistance is the provision of assistance in the form of money or goods distributed to certain individuals or groups. As a form of responsibility in alleviating poverty, the government allocates costs to handle this, one of which is the Family Hope Program (PKH). PKH is a program to provide cash assistance to poor households. One of the villages that has received PKH assistance from the government is Mlirip village, Mojokerto Regency. With the help of PKH, people with low incomes feel very helpful. Unfortunately, until now PKH is still considered not optimal because many aids are not well targeted and the village head's office does not yet have a reference in choosing a truly worthy family. Classification is carried out to determine the eligibility of PKH beneficiaries so that they are not misdirected. The data used is data for 2020-2021 with a total of 357 data from 7 hamlets in Mlirip village. Based on the results of the confusion matrix, it produces 71.1% accuracy, 90.9% precision, 70.4% recall, and 79.3% f1-score. The results of the classification process are visualized using a dashboard which produces a SUS Score of 87.5 which indicates the dashboard is acceptable to stakeholders
Co-Authors Dian Eka Ratnawati Nanang Yudi Setiawan