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- Title
Penerapan Algoritma Naive Bayes Untuk Analisis Sentimen Penggunaan Aplikasi Jobstreet.
- Authors
Widodo, Bobby Kurniadi; Matondang, Nur Hafifah; Prasvita, Desta Sandya
- Abstract
The Jobstreet application is a job vacancy application that has been downloaded by more than 10 million people which provides several types of jobs such as accounting, human resources, marketing, communication, services, and others. With so many people downloading this application, people will definitely give their reviews of this application. In times of a pandemic like this, many people are looking for work using android applications where the information is faster and easier to find job vacancies, therefore the Jobstreet application helps people find job vacancies in the companies they want. This review of public opinion comments can be used as an opportunity to dig up information about the evaluation and assessment of jobstreet application services that have been running using sentiment analysis. The purpose of this study is to classify the sentiment of reviews on the Jobstreet application using the Naïve Bayes method. In this study, opinions will be divided into two groups as positive and negative, then classified using the Naïve Bayes algorithm. The test results obtained using test data have an accuracy value of 0.96; precision value is 0.98; recall value of 0.94.
- Subjects
JOB applications; JOB vacancies; MARKETING; HUMAN resources departments; SENTIMENT analysis; ACCOUNTING software
- Publication
Techno.com, 2022, Vol 21, Issue 3, p523
- ISSN
1412-2693
- Publication type
Article
- DOI
10.33633/tc.v21i3.6361