Article Per Year (5 Year)
p-Index From 2020 - 2025
3.496
P-Index
This Author published in this journals
All Journal Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komtika (Komputasi dan Informatika) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) IJIIS: International Journal of Informatics and Information Systems Journal of Computer System and Informatics (JoSYC) KLIK: Kajian Ilmiah Informatika dan Komputer Prosiding Seminar Nasional Program Pengabdian Masyarakat Techno Prosiding University Research Colloquium Borobudur Informatics Review IJESPG (International Journal of Engineering, Economic, Social Politic and Government) journal
Mukhtar Hanafi
Universitas Muhammadiyah Magelang, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Social Sciences

Published : 32 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 32 Documents
Search

 1   2   3   4 
Penerapan Metode SAW untuk Mengurangi Subjektivitas dalam Menentukan Kelayakan Penerima PKH Rochanah, Rochanah; Nuryanto, Nuryanto; hanafi, Mukhtar
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): Januari 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6556

Abstract

This study aims to determine the priority scale for families eligible to receive benefits from the Family Hope Program (PKH) using the Simple Additive Weighting (SAW) method. The primary issue addressed is the limited allocation of assistance, which necessitates an objective and transparent selection process to ensure that aid reaches the families most in need. This research aims to provide a decision support system-based solution to assist in the selection process.The research employs the SAW approach, which involves several key steps: collecting data on prospective beneficiary families, normalizing the data to standardize the criteria scale, assigning weights to each criterion according to its importance, and calculating the final scores to rank each family. The criteria used include the number of family members, the presence of young children, the educational level of family members, disability status, elderly status, and pregnancy, with weights determined based on policy. The results indicate that the SAW method effectively identifies the families most in need based on objectively calculated total scores. From the total data tested, 75% of families were categorized as "Eligible" to receive assistance based on total scores exceeding the threshold, while 25% were categorized as "Not Eligible."This study contributes to improving the accuracy and transparency of the PKH beneficiary selection process. The generated data can be adopted by local governments to optimize the distribution of social assistance, minimize potential errors, and enhance fairness in aid distribution to the community.
Analisis Kepuasan Masyarakat terhadap Pelayanan Publik menggunakan K-Means Clustering Hariyanto, Yenik; Primadewi, Ardhin; Hanafi, Mukhtar
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): Januari 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6577

Abstract

This study aims to analyze data clustering using the K-Means Clustering method in order to understand certain patterns contained in public satisfaction data on public services. The problem of this study focuses on how to optimally group data to evaluate the quality of service indicators based on 9 indicators in the Public Satisfaction Survey (SKM). The purpose of this study is to divide data into several clusters so that it can provide a clear picture of the differences in quality between service groups. The method used in this study is the K-Means Clustering method, which consists of several stages, namely determining the number of clusters, determining the initial center point, calculating the distance of data to the center point, grouping data, updating the center point, and providing cluster labels. Evaluation of the quality of clustering results is carried out using two evaluation metrics, namely the Silhouette Score and the Davies-Bouldin Index. The results showed that the data was divided into two clusters with a Silhouette Score value of 0.515 which indicated a fairly good clustering quality. In addition, the Davies-Bouldin Index value of 0.784 indicates that the clusters formed have a fairly good distance between each other. The results of this analysis provide an overview that the first cluster has a higher quality of service compared to the second cluster based on the average value of the service indicators measured. This study is useful in providing more structured and accurate information regarding service quality, so that it can be a basis for policy makers to improve service performance in the future. In addition, this study can also be a reference for further research in the application of the K-Means method for similar cases with a focus on evaluation and development of public services.
Co-Authors Achmat Mujafar Ajeng Tri Rahayu Alfathin, Abdullah Husain Alif Kemal Verdito Andi Widiyanto Andi Widiyanto Ardhin Primadewi Arief Setyawan Asroni Asroni Asti Nur Imani Auliya Burhanuddin Bambang Pujiarto Bambang Pujiarto Bambang Pujiarto Cahya Damarjati Choirul Anam AM Diponegoro Dewantara, Helmy Dimas Sasongko Eky Rizky Prasetya Emilya Ully Artha Endah Ratna Arumi Hafidz Fahrizal Rahman Hariyanto, Yenik Heri Purwanto Humaid Husain As’ad Layli Nur'Aini Maimunah Meidar Hadi Avizenna Mohammad Rahardian Adhitama Mubarak, Rosyid Muhammad Alfadha Termahadi Muhammad Hafizh Hamdanuddinsyah Nugraha, Setiya Nugroho Agung Prabowo Nugroho Agung, Nugroho Nurhidayat, Linggarjati Rudyan Nuryanto Nuryanto Nuryanto Prasetyo, Ahmad Zudha Purwono Hendradi Qosim Nurdin Haka R Arri Widyanto Ramadhan, Radzi Diva Rochanah, Rochanah Rusdjijati, Retno Sidik Priyo Utomo Sukmasetya, Pristi Sunarni Sunarni Suta, Saka Nano Vyan Martha, Aldo Wildan Fatkhul Barry