Monitoring Quality of KAI Access Application Based on Customer Reviews on Google Play Store Using Laney p’ Control Chart Based on Convolutional Neural Network

DOI

10.2991/978-94-6463-332-0_20How to use a DOI?

Keywords

Convolutional Neural Network; KAI Access; Laney p’ Control Chart

Abstract

The variety of activities that Indonesian people have has made mobilization increase. One form of transportation that can support close and long distance mobilization is rail transport. Purchasing train tickets can be made directly at the station or online. Online purchases can be made through an official ap-plication issued by PT Kereta Api Indonesia (KAI Access) or other service provider applications. The KAI Access application has a feature that allows ticket buyers to use complementary services such as railfood, connecting transportation, cancellation or rescheduling without having to go to the station, and other services. Despite its advantageous features, the app’s Google Play Store rating remains relatively low at 2.5. Users also provide reviews, serving as valuable material for sentiment analysis and quality evaluation. Data spans from July 16, 2014, to February 15, 2023. Sentiment analysis, conducted through Convolutional Neural Network classification, revealed that 47.8% of reviews conveyed negative sentiment, while 52.12% were positive. Classification accuracy (AUC) for training data was 76.4%, falling under the fair category, while testing data achieved 97.3%, classified as excellent. The analysis identified common user issues, including challenges with account registration and login, application performance lag, and payment difficulties. The study ultimately demonstrates the potential for attribute control charts, specifically the Laney p’, in effectively monitoring sentiments within large and varied sample sizes.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Naila Adelia Pribadi
AU  - Muhammad Ahsan
PY  - 2023
DA  - 2023/12/18
TI  - Monitoring Quality of KAI Access Application Based on Customer Reviews on Google Play Store Using Laney p’ Control Chart Based on Convolutional Neural Network
BT  - Proceedings of the 5th International Conference on Statistics, Mathematics, Teaching, and Research 2023 (ICSMTR 2023)
PB  - Atlantis Press
SP  - 175
EP  - 184
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-332-0_20
DO  - 10.2991/978-94-6463-332-0_20
ID  - Pribadi2023
ER  -