Implementasi Algoritma Naive Bayes dan Algoritma C4.5 dalam Klasifikasi Kelayakan Bantuan UMKM
DOI:
https://doi.org/10.30865/klik.v4i1.1099Keywords:
UMKM; Website; Classification; Naïve Bayes; C4.5Abstract
Indonesia's economic development has slowed down due to rising inflation. Entrepreneurs often face several problems in starting an entrepreneurial activity, including: capital, licensing, accounting guidelines, promotion, goods, pricing, human resources, advertising and other activities that often hinder the business process. Financial Management for MSME Empowerment is one of the business processes run by the Ministry of Finance in improving the performance of MSMEs through the provision of business capital. But in practice, there are obstacles in the process of testing the feasibility classification of the assistance activities carried out, because it still uses inefficient manual methods. In order for the testing to be more effective and practical, integrated website-based software is needed. To achieve this, this research was conducted with the aim of producing information related to the eligibility status of MSMEs in all regions of Indonesia that are eligible or not eligible to receive financial assistance from the government. In order for the MSME eligibility status information obtained to be useful for regional offices throughout Indonesia, the algorithms used in this research are the Naive Bayes algorithm and the C4.5 algorithm. The results showed that both algorithms can be applied well in determining the eligibility of MSME assistance. The accuracy of the C4.5 algorithm is 90% while the accuracy of the Naive Bayes method is 70%. The C4.5 algorithm performs slightly better than Naive Bayes in this classification setting. The accuracy findings in this study can be compared to previous research already conducted using the same algorithm or with similar data sets. This helps determine if this research methodology results in a higher accuracy rate than previous studies
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