IMPLEMENTASI METODE NAÏVE BAYES UNTUK PREDIKSI KELAYAKAN BANTUAN MODAL DAN KREDIT USAHA DI DESA SELAT ABIANSEMAL BADUNG
DOI:
https://doi.org/10.59819/jmti.v15i2.3985Keywords:
UMKM, Classification, Naïve Bayes, WebAbstract
Small, Micro, and Medium Enterprises (MSMEs) are small-scale businesses carried out by individuals or business entities with a certain amount of net worth and sales proceeds. MSMEs in Abiansemal Strait Village, Badung, still use manual methods in analyzing data. Conditions like this are the basis for this study to create a system that can help make it easier for the Abiansemal Badung Strait Village if there is an assistance program from the government, both business capital assistance, and business credit applications to be given to MSME actors. Naïve Bayes' method of classifying MSMEs is built on concepts explored from the interview process, literature studies and system implementation. The design of this system was made using the Python programming language. The CRISP-DM model is a system development method used in the classification of MSMEs. The Feasibility Prediction Model for Capital Assistance and Business Credit using the Naïve Bayes Method can make it easier for users to find out whether the existence of a web-based classification and recommendation system can make it easier for users to carry out the MSME classification process easily and users can see the solutions recommended by referral MSMEs that have better business conditions directly.
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