Analisis sentimen terhadap aplikasi Sistem Pengelolaan Pengaduan Pelayanan Publik Nasional (SP4N) Layanan Aspirasi dan Pengaduan Online Rakyat (LAPOR!) menggunakan Algoritma Naïve Bayes

Nugraha, Zamzam H. K. (2023) Analisis sentimen terhadap aplikasi Sistem Pengelolaan Pengaduan Pelayanan Publik Nasional (SP4N) Layanan Aspirasi dan Pengaduan Online Rakyat (LAPOR!) menggunakan Algoritma Naïve Bayes. Sarjana thesis, UIN Sunan Gunung Djati Bandung.

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Abstract

Public services in Indonesia tend not to experience development, and efforts to improve service quality are carried out by the government by creating the SP4N LAPOR! application. (National Public Service Complaint Management System for People's Online Aspirations and Complaint Services). One of the parameters of application effectiveness can be seen through user reviews, however, the large amount of review data needs to be processed using a special method to get maximum results with a more concise process. Sentiment analysis is one technique that can be used to achieve this goal. By implementing CRISP-DM as the method used in this study, as well as the Naïve Bayes Classifier algorithm for modeling and data processing. The results obtained were that there were 54.6% reviews with negative sentiment, and 45.4% reviews with positive sentiment from all the data analyzed. In addition, the comparison of tests on split data (70:30, 80:20, and 90:10) produces various levels of accuracy. The highest accuracy value for sentiment analysis using the Naïve Bayes algorithm in this study was obtained at 90:10 split data, which is 91%.

Item Type: Thesis (Sarjana)
Uncontrolled Keywords: Sentiment Analysis; Analisis Sentimen; Naïve Bayes; SP4N LAPOR!
Subjects: Data Processing, Computer Science
Special Computer Methods > Artificial Intelligence
Technology, Applied Sciences
Divisions: Fakultas Sains dan Teknologi > Program Studi Teknik Informatika
Depositing User: Zamzam H. K. Nugraha
Date Deposited: 12 Oct 2023 02:42
Last Modified: 12 Oct 2023 02:42
URI: https://digilib.uinsgd.ac.id/id/eprint/80075

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