Mapping the Performance Improvement of MSMEs in Pesawaran Regency, Lampung Using the Naive Bayes Algorithm

EasyChair Preprint 6068

Abstract

Empowerment of Micro, Small and Medium Enterprises (MSMEs) is very important in anticipating the future economy, especially in strengthening the structure of the national economy. The current national economic crisis has greatly affected national, economic and political stability, the impact of which has affected the activities of large businesses which are getting worse. To realize strong and independent Micro, Small and Medium Enterprises (MSMEs) that have high competitiveness, guidance or training and assistance from the government is very important for MSMEs today so that MSMEs in Pesawaran Regency do not get worse. However, because there are many MSMEs in Pesawaran and have not been properly classified between micro, small and medium enterprises, there are still many assistance and guidance from the government that are not well targeted. Therefore, a data mining classification technique is needed using the Naive Bayes theorem to classify Micro, Small and Medium Enterprises which can help the Department of Cooperatives and SMEs in Pesawaran Regency to compile data in a systematic and structured manner. Based on the results of testing on sample data using the Naive Bayes algorithm, it produces an accuracy rate of 98.68%, which means that the Naive Bayes algorithm can be used as input for decision makers.

Keyphrases: Data Mining, Naive Bayes, UMKM, klasifikasi

@booklet{EasyChair:6068,
  author    = {Ari Rohmawati and Sri Lestari},
  title     = {Mapping the Performance Improvement of MSMEs in Pesawaran Regency, Lampung Using the Naive Bayes Algorithm},
  howpublished = {EasyChair Preprint 6068},
  year      = {EasyChair, 2021}}