Atikah, Nur (2026) Analisis Sentimen Ulasan Aplikasi OSS (Online Single Submission) Pada Google Play Store Menggunakan Metode Naive Bayes Classifier. Undergraduate thesis, Politeknik Negeri Jember.
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Abstract
The Online Single Submission (OSS) application is an electronic business licensing service designed to assist the public in managing business permits. Various user responses toward the OSS application are expressed through reviews on the Google Play Store, making sentiment analysis necessary to identify overall user opinion. This study aims to determine users' views toward the OSS application, classify review sentiments using the Naive Bayes Classifier method, and measure the performance of the model. The research data were collected through web scraping of OSS application reviews from the Google Play Store and classified into three sentiment classes: positive, neutral, and negative. The analysis process involved text preprocessing, TF-IDF weighting, and classification using the Naive Bayes Classifier. The analysis of 2,598 reviews showed that negative sentiment was the most dominant category compared with positive and neutral sentiments, indicating that users' responses tend to reflect unfavorable experiences with the OSS application. The model evaluation achieved an accuracy of 88.06%, indicating that the Naive Bayes Classifier provides good classification accuracy in identifying the sentiment of OSS application user reviews.
| Item Type: | Thesis (Undergraduate) | ||||||
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| Uncontrolled Keywords: | Analisis Sentimen, Google Play Store, Naive Bayes Classifier, Online Single Submission, TF-IDF. | ||||||
| Subjects: | 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 458 - Teknik Informatika 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 459 - Ilmu Komputer 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 461 - Sistem Informasi 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 463 - Teknik Perangkat Lunak 550 - Rumpun Ilmu Ekonomi > 570 - Ilmu Manajemen > 577 - Manajemen Informatika |
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| Divisions: | Jurusan Teknologi Informasi > Prodi D4 Teknik Informatika > Tugas Akhir | ||||||
| Depositing User: | Nur Atikah | ||||||
| Date Deposited: | 19 Aug 2026 05:50 | ||||||
| Last Modified: | 19 Aug 2026 05:50 | ||||||
| URI: | https://sipora.polije.ac.id/id/eprint/59839 |
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