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MACHINE LEARNING FOR CLASSIFICATION OF IKM PROGRAMS AT THE DEPARTMENT OF INDUSTRY AND TRADE OF LANGKAT REGENCY

Mimi Chintya Adelina(1*), Wanayumini Wanayumini(2), Zakarias Situmorang(3)
(1) Universitas Potensi Utama, North Sumatra, Indonesia
(2) Universitas Potensi Utama, North Sumatra, Indonesia
(3) Universitas Potensi Utama, North Sumatra, Indonesia
(*) Corresponding Author

Abstract

This research attempts to address these challenges by constructing a classification model using the Naive Bayes algorithm. Naive Bayes is a statistical algorithm that can be employed to predict the probability of membership in a class based on the available data. This method can assist the Department of Industry and Trade of Langkat Regency in selecting targeted programs and identifying SMEs (Small and Medium Enterprises) with potential success. The research will involve the collection and analysis of data regarding SMEs in Langkat Regency, including information about the industry type, geographic location, and business formality status. This data will be utilized to train the Naive Bayes classification model to predict the potential success of programs offered by the Department of Trade and Industry. Consequently, it is anticipated that this model can aid in more effective and efficient decision-making in the management of SME programs

References


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