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All Journal Jurnal Teknik Hidro Jurnal Teknologi Terpadu Building of Informatics, Technology and Science JIKA (Jurnal Informatika) Indonesian Journal of Engagement, Community Services, Empowerment and Development (IJECSED) Journal Peqguruang: Conference Series Ceddi Journal of Education Jurnal Pengabdian Masyarakat (JURDIMAS)
Nurdiansah, Nurdiansah
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Journal : Ceddi Journal of Education

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WEB Based Social Assistance Recipient Selection Application Based on Community Education Level With C4.5 Algorithm Nurdiansah, Nurdiansah; Usman; Harlina, Sitti; Irmawati
Ceddi Journal of Education Vol. 1 No. 1 (2022): June
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/cje.v1i1.12

Abstract

The Koramil 1408-02 Tallo office is responsible for distributing social assistance to recipients, including basic food assistance for the general community and support for micro, small, and medium enterprises (MSMEs). Each type of assistance has distinct criteria for determining eligibility, including educational level, which complicates the selection process for the staff. To address these challenges, this study leverages data mining techniques to develop a classification system using the C4.5 algorithm, aimed at determining social assistance recipients more effectively. The primary goal of this study is to create a system that simplifies the selection process for social assistance recipients by incorporating educational levels into the decision-making criteria. The outcome of the research is an application designed to assist Koramil 1408-02 Tallo in accurately identifying eligible recipients based on predefined criteria, thus resolving inefficiencies in the existing system. This study contributes to the advancement of knowledge by showcasing the practical application of the C4.5 algorithm in the context of social welfare distribution. It not only improves the accuracy and efficiency of recipient selection but also serves as a model that can be adapted and expanded to other domains of social assistance. The findings highlight the transformative potential of data-driven decision-making tools, offering valuable insights for future research and development in optimizing resource allocation and enhancing the effectiveness of social support systems.
Co-Authors Abdul Rauf Ahmad Ahmad Akhmad Qashlim, Akhmad Ardimansyah Ardimansyah, Ardimansyah Asran, Asran Bahtiar, Akbar Cucut Susanto, Cucut Dani Rachman, Suci Rahma Djamro, Risnayanti Andi Faizal Faizal, Faizal Fithriyah Arief Wangsa Hardi Hardi, Hardi Harlina, Sitti Hasriani Hasriani, Hasriani Herlinda Herlinda, Herlinda Husain Husain Irmawati Irmawati Irmawati Irwan, Muhammad Ahlil Khairi Kasmawaru, Kasmawaru Kunda, Asri Marsa, Marsa Michael Octavianus Mudarsep, Mudarsep Nenny, Nenny Nirwana, Nirwana Rahman, Baharuddin S. Kuba, Muhammad Syafa'at Sopyan, Edy Sri Wahyuni Suryani Suryani Syafruddin Syafruddin T, Husain Tamsir, Nurlindasari Thabrani R, Thabrani R Usman Usman Usman W Soetikno, Y Johny