Abdul Rahman, Rizqi (2022) Implementasi Data Mining Dalam Memprediksi Penerima Bantuan Masyarakat Miskin Di Kota Pekanbaru Menggunakan Algoritma C4.5 Berbasis Web. Other thesis, Fakultas Teknik Informatika.
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Abstract
The problem of poverty faced by the government is closely related to low income so that it cannot meet its basic needs. The low income earned has an impact on the lack of opportunity to access education and other government facilities. Likewise, low regional income causes less distribution of income distribution for the community. In response to this, in this study the authors tried to apply a classification technique using the C4.5 algorithm as a settlement method in predicting poor community aid recipients in Pekanbaru City. From the results obtained, this research is expected to be able to identify factors in the number of poverty and can provide information or input for the government in taking appropriate steps as an effort to reduce the number of poverty in the city of Pekanbaru. Before this poor community aid beneficiary prediction system was designed. The Ministry of Social Affairs of Pekanbaru keeps the data as documentation for the annual report. The data obtained is in the form of Name, Electric Power, Income, Source of Drinking Water, Status of Residence Ownership. From this research, a Prediction System for Poor Community Assistance Recipients Using the C4.5 Algorithm will be created to obtain handling strategies in order to suppress and reduce the level of poor people. The system can provide results from manual calculations with the C4.5 Algorithm using decision rules and this system can make it easier for users because it is equipped with reports in the form of beneficiary data.predictions Aid Recipients Poverty, C4.5 Algorithm
Item Type: | Thesis (Other) |
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Contributors: | Contribution Contributors NIDN/NIDK Sponsor Syafitri, Nesi 9088102 |
Uncontrolled Keywords: | predictions Aid Recipients Poverty, C4.5 Algorithm |
Subjects: | T Technology > T Technology (General) |
Divisions: | > Teknik Informatika |
Depositing User: | Fajro Gunairo S.Ip |
Date Deposited: | 09 Sep 2025 04:06 |
Last Modified: | 09 Sep 2025 04:06 |
URI: | https://repository.uir.ac.id/id/eprint/27971 |
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