Application Of The C4.5 Algorithm To Determine The Eligibility Of Recipients Of The Hope Family Program Aid In The Cawang Baru District
Keywords:
Family Hope Program, Data Mining, C4.5 AlgorithmAbstract
The problem of poverty is a central issue that must be addressed immediately. Talking about poverty, in Indonesia itself poverty is a social welfare problem that is always relevant. The government has made many efforts to overcome poverty with various programs, one of which is the Family Hope Program. Pekan Baru City also implements the Family Hope Program. However, the Family Hope Program data verification officer or team does this manually, namely by visiting each head of family participating in the Family Hope Program. So a simulation system is needed to quickly classify participants in the Family Hope Program, with the help of artificial neural networks, making it easier for agencies and providing an overview to determine the compon ents of prospective PKH participants. PNN is one of the Artificial Neural Network classification methods which has the advantage of being easy to modify the network when adding or subtracting the training data used. The calculation of the Probabilistic Neural Network algorithm used in the PKH data classification produced an accuracy value of 99.07%. In testing the algorithm using the confusion matrix method, the recall value was 99.30% and the precision value was 97.81%.
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