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All Journal Journal Software, Hardware and Information Technology
Yulia Ardana
Universitas Islam Negeri Alauddin Makassar
Computer Science & IT

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Analisis Sentimen Terhadap Jasa Ekspedisi Pos Indonesia Pada Sosial Media Twitter Menggunakan Naïve Bayes Classifier Muhammad Nur Akbar; Darmatasia Darmatasia; Yulia Ardana
Journal Software, Hardware and Information Technology Vol 2 No 2 (2022)
Publisher : Jurusan Sistem Informasi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/shift.v2i2.34

Abstract

Nowdays, the rapid growth of information technology positively impacts companies engaged in industry, sales, and services, especially e-commerce. The increase in the number of transactions in various e-commerce impacts the increase in the use of expedition services. Pos Indonesia is the oldest expedition service provider in Indonesia and is required to be able to innovate in providing the best service for its customers. The importance of customers for a company depends on how the company builds customer relationships. A strong company will have good customer relations. Many customers have expressed their opinions regarding Pos Indonesia through Twitter. In this study, text mining techniques are used, namely sentiment analysis which helps analyze opinions, sentiments, evaluations, assessments, attitudes, and public emotions towards Pos Indonesia services. Naïve Bayes Classifier was chosen because it is simple, fast, and has high accuracy. The Naïve Bayes Classifier has successfully classified positive and negative sentiments on 100 tweets from Pos Indonesia customers with an accuracy of 87%.
Co-Authors Darmatasia Darmatasia Muhammad Nur Akbar