ANALISIS SENTIMEN PADA ULASAN APLIKASI BUKUKAS DI GOOGLE PLAY STORE MENGGUNAKAN METODE NAÏVE BAYES DENGAN SELEKSI FITUR CHI-SQUARE

Hariyanto Prasetyo, . (2022) ANALISIS SENTIMEN PADA ULASAN APLIKASI BUKUKAS DI GOOGLE PLAY STORE MENGGUNAKAN METODE NAÏVE BAYES DENGAN SELEKSI FITUR CHI-SQUARE. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Bukukas is an application that serves to help make the activities of recording all transactions, making financial reports, and recording accounts payable can be done online. The Bukukas application is an application whose features are very dependent on the users who use it, because it makes most of the complaints from users on the Google Play Store against the Bukukas application are complaints in the form of features that are omitted being asked to be returned. To find out the problems experienced by users and make it easier to carry out an analysis to determine future application development, a sentiment analysis will be carried out with opinions obtained from the Google Play Store. The stages of this research begin with text processing data followed by term weighting using TF-IDF and feature selection process using chi square followed by classification and then evaluation results. The results obtained using the nave Bayes method and feature selection using chi square obtained an increase in accuracy of 6%, namely the best accuracy obtained is 81% when using feature selection, for the error rate, precision, and recall values obtained by 19% for the error rate, 69% for the precision value, and 72% for the recall value.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 1810511058] [Pembimbing 1: Iin Ernawati] [Pembimbing 2: Nurul Chamidah] [Penguji 1: Didit Widiyanto] [Penguji 2: Yuni Widiastiwi]
Uncontrolled Keywords: Bukukas, nave Bayes, sentiment analysis.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: Hariyanto Prasetyo
Date Deposited: 22 Aug 2022 07:31
Last Modified: 22 Aug 2022 07:31
URI: http://repository.upnvj.ac.id/id/eprint/19962

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