Analisis Sentimen Ulasan Pengguna Aplikasi Alfagift Menggunakan Random Forest

Alfagift is a mobile application developed by Alfamart to support online ordering, with features such as promos, transactions, ordering, and delivery from the nearest point according to the consumer's address. User feedback on the Google Play Store shows mixed sentiments, including both positive and negative responses, which can be utilized by developers as material to improve the quality of the application. This study focuses on assessing the sentiment of Alfagift app user reviews through the application of the Random Forest algorithm. A total of 4,379 review data was collected from the Google Play Store and grouped into two categories, namely positive and negative sentiment. The research steps include data collection, data labeling, data preprocessing, word weighting, data division into training and testing sets, Random Forest algorithm implementation, and model evaluation. The test results show that the Random Forest algorithm achieves an accuracy of 97.6% and an AUC of 0.98, which falls into the category of excellent classification. This research is expected to contribute to application developers in understanding user perceptions, so as to improve application quality and increase overall user convenience.

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Publication Details

Journal
JISKA (Jurnal Informatika Sunan Kalijaga)
Published
2025-05-31
DOI
https://doi.org/10.14421/jiska.2025.10.2.158-170
Citations
1
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
3.25
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article

Analisis Sentimen Ulasan Pengguna Aplikasi Alfagift Menggunakan Random Forest

M. Bagus Prayogi, Gustina Masitoh
1 citations
JISKA (Jurnal Informatika Sunan Kalijaga)
Data Mining and Machine Learning Applications
3.25
article

Analisis Sentimen Ulasan Pengguna Aplikasi Alfagift Menggunakan Random Forest

M. Bagus Prayogi, Gustina Masitoh
article en
1 citations

Abstract

Alfagift is a mobile application developed by Alfamart to support online ordering, with features such as promos, transactions, ordering, and delivery from the nearest point according to the consumer's address. User feedback on the Google Play Store shows mixed sentiments, including both positive and negative responses, which can be utilized by developers as material to improve the quality of the application. This study focuses on assessing the sentiment of Alfagift app user reviews through the application of the Random Forest algorithm. A total of 4,379 review data was collected from the Google Play Store and grouped into two categories, namely positive and negative sentiment. The research steps include data collection, data labeling, data preprocessing, word weighting, data division into training and testing sets, Random Forest algorithm implementation, and model evaluation. The test results show that the Random Forest algorithm achieves an accuracy of 97.6% and an AUC of 0.98, which falls into the category of excellent classification. This research is expected to contribute to application developers in understanding user perceptions, so as to improve application quality and increase overall user convenience.

JISKA (Jurnal Informatika Sunan Kalijaga)Vol. 10(2)
Universitas Nurtanio (ID)
Openalex Percentile: Top 9%
Data Mining and Machine Learning Applications
3.25
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Analisis Sentimen Ulasan Pengguna Aplikasi Alfagift Menggunakan Random Forest — M. Bagus Prayogi, Gustina Masitoh · JISKA (Jurnal Informatika Sunan Kalijaga) (2025) | TGRS Research Map | TGRS