KLASIFIKASI KELAYAKAN MASYARAKAT PENERIMA BANTUAN SOSIAL (BANSOS) MENGGUNAKAN METODE NAÃVE BAYES
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
ISWAHYUDIN, ISWAHYUDIN
Aziza, Rosida Nur
Kuswardani, Dwina
Aziza, Rosida Nur
Kuswardani, Dwina
Subject
Teknik Informatika
Datestamp
2022-09-20 03:48:52
Abstract :
Social Assistance is assistance in the form of money, goods, or services to a person, family, group or community who are poor, underprivileged, and/or vulnerable to social risks. This study uses data on social assistance recipients in Ngali Village, Belo District, Bima Regency, West Nusa Tenggara. Sometimes in the implementation of the provision of social assistance, there are still many that are still not optimal because many are not on target. Classification can use data mining techniques using the Naïve Bayes algorithm. The Naïve Bayes algorithm is a classification method that is able to predict future opportunities based on previous experience. The parameters used are dependents, occupation, age, income, home ownership and vehicle ownership. Based on the test results using the Confusion Matrix, obtained an accuracy rate of 99.64%, a precision value of 87.31% and a recall of 100%.
Social Assistance is assistance in the form of money, goods, or services to a person, family, group or community who are poor, underprivileged, and/or vulnerable to social risks. This study uses data on social assistance recipients in Ngali Village, Belo District, Bima Regency, West Nusa Tenggara. Sometimes in the implementation of the provision of social assistance, there are still many that are still not optimal because many are not on target. Classification can use data mining techniques using the Naïve Bayes algorithm. The Naïve Bayes algorithm is a classification method that is able to predict future opportunities based on previous experience. The parameters used are dependents, occupation, age, income, home ownership and vehicle ownership. Based on the test results using the Confusion Matrix, obtained an accuracy rate of 99.64%, a precision value of 87.31% and a recall of 100%.
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