INOVTEK Polbeng - Seri Informatika
Vol. 10 No. 1 (2025): Maret

Sentiment Analysis of Gojek, Grab, Maxim Applications Using Support Vector Machine Algorithm

Muhammad Iqrom (Universitas Islam Negeri Sultan Syarif Kasim Riau)
M. Afdal (Universitas Islam Negeri Sultan Syarif Kasim Riau)
Rice Novita (Universitas Islam Negeri Sultan Syarif Kasim Riau)
Medyantiwi Rahmawita (Universitas Islam Negeri Sultan Syarif Kasim Riau)
Tengku Khairil Ahsyar (Universitas Islam Negeri Sultan Syarif Kasim Riau)



Article Info

Publish Date
21 Mar 2025

Abstract

This research analyzes user sentiment towards three major online transportation applications in Indonesia—Gojek, Grab, and Maxim using the \SVM algorithm. The analysis results indicate that Maxim has the highest positive sentiment rate (42.45%) compared to Grab (32.83%) and Gojek (20.21%). Maxim's advantages lie in its competitive pricing and driver professionalism. However, Gojek recorded the best performance in sentiment classification with an accuracy of 94%, followed by Maxim (90%) and Grab (87%). The evaluation based on five main variables (general sentiment, drivers, services, applications, and pricing/costs) reveals the strengths of each application in different categories. Maxim excels in general sentiment and driver satisfaction, Grab dominates in pricing/cost, and Gojek stands out in the application category. Wordcloud visualization reveals frequently mentioned words such as "driver," "application," and "order," reflecting users' primary concerns and experiences. This research provides valuable insights for online transportation service providers to improve service quality, although it has limitations in exploring external factors such as user demographics and marketing strategies, as well as relying on a single algorithm without comparison. The choice of the SVM algorithm is based on its ability to handle well-structured data and provide high accuracy in classification. SVM is effective in finding the optimal hyperplane that clearly separates data classes, making it suitable for sentiment analysis involving multiple variables.

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Journal Info

Abbrev

ISI

Publisher

Subject

Computer Science & IT

Description

The Journal of Innovation and Technology (INOVTEK Polbeng—Seri Informatika) is a distinguished publication hosted by the State Polytechnic of Bengkalis. Dedicated to advancing the field of informatics, this scientific research journal serves as a vital platform for academics, researchers, and ...