KLASIFIKASI OPINI GREEN AND CLEAN KABUPATEN LAMONGAN MENGGUNAKAN ALGORITMA MULTINOMIAL NAIVE BAYES

Authors

  • Agus Setia Budi Universitas Islam Lamongan

DOI:

https://doi.org/10.30736/jti.v3i1.198

Keywords:

Opinion, Opinion Mining, Multinomial Naive Bayes

Abstract

This study aims to process and classify an opinion (Opinion mining), opinion is a subjective statement that reflects public sentiment or perception of the entity or activity. Most opinions has not been managed well, if The Opinions properly managed will provide important information can be used to make improvements toward better at an activity or program. This study focuses on the processing of opinions that come from public opinion In Lamongan against LGC program which includes cleanliness, green and financial. The study was divided into two phases, namely the training process to produce data (dataset) to perform the classification process and the subjective (datates). Both processes are aimed to extract attributes and object components that have been commented upon in any document and to determine whether positive or negative comments. The results of the subjective test classification using Multinomial Naive Bayes algorithm has a success rate above 80% classification accuracy when it is matched with the manual classification

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Author Biography

Agus Setia Budi, Universitas Islam Lamongan

Dosen Fakultas Teknik Prodi Teknik Informatika Universitas Islam Lamongan

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Published

2018-04-23

How to Cite

Budi, A. S. (2018). KLASIFIKASI OPINI GREEN AND CLEAN KABUPATEN LAMONGAN MENGGUNAKAN ALGORITMA MULTINOMIAL NAIVE BAYES. Joutica : Journal of Informatic Unisla, 3(1), 125–128. https://doi.org/10.30736/jti.v3i1.198

Issue

Section

Jouticla Jurnal Teknik Informatika