PANGESTIKA, OLIFIA (2021) KLASIFIKASI KEMISKINAN DALAM MENENTUKAN PEMBERIAN BANTUAN COVID-19 MENGGUNAKAN METODE DECISSION TREE (Studi kasus: Kantor Desa Miyono). Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
OLIFIA PANGESTIKA Department of Informatics, Faculty of Science & Technology University of Technology Yogyakarta North Ringroad St., Jombor Sleman Yogyakarta E-mail: olifiapgstk@gmail.com ABSTRACT The Covid-19 pandemic has affected many world citizens. The people of Miyono village are one of the residents affected by the pandemic. One of the government's actions is to organize a Bantuan Langsung Tunai (BLT) program for affected communities. However, the quota was given by the government often creates new problems in society, namely not being well targeted. Therefore, it is necessary to have certain conditions or criteria that underlie the provision of BLT to the community. The approach taken is to make a classification using criteria to determine the eligibility of beneficiaries. The C4.5 algorithm is a classification algorithm that can be used to determine the eligibility of BLT recipients. The results obtained in the research based on system testing using the Confusion Matrix are 90% accuracy of the classification results using the C4.5 algorithm so that the system built can assist an officer in distributing BLT appropriately to eligible citizens. Keywords: BLT, C4.5, Classification
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 01 Sep 2021 09:02 |
| Last Modified: | 01 Sep 2021 09:02 |
| URI: | http://eprints.uty.ac.id/id/eprint/7819 |
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