Jurnal Pseudocode
Vol 13 No 1 (2026): Volume 13 Nomor 1 Februari 2026

Analisis Sentimen Ulasan Aplikasi Access by KAI Menggunakan Algoritma Naïve Bayes

Ariansyah, Beni (Unknown)
Negara, Edi Surya (Unknown)



Article Info

Publish Date
28 Feb 2026

Abstract

The Access By KAI application, developed by PT Kereta Api Indonesia (Persero), allows users to purchase train tickets via mobile devices. This study aims to perform sentiment analysis on user reviews of the Access By KAI application using the naive Bayes algorithm. Data processing was carried out through stages such as case folding, cleaning, tokenizing, stopword removal, and stemming, and evaluation using metrics of accuracy, precision, recall, and F1-score showed that the naive Bayes algorithm provides satisfactory results. The study results indicate that the naive Bayes algorithm is able to classify reviews with an accuracy rate of up to 68% with a precision of 83% for the positive class, 59% for the negative class, and 79% for the neutral class; recall of 67% for the positive class, 93% for the negative class, and 42% for the neutral class. From these results, it is expected to help developers identify the aspects most complained about by users and improve service quality.

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Journal Info

Abbrev

pseudocode

Publisher

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

Description

Pseudocodeis a scientific journal in the information science family that contains the results of informatics research, scientific literature on informatics, and reviews of the development of theories, methods, and application of informatics engineering science. Pseudocode is published by the ...