Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Jurnal Komputer dan Teknologi (JUKOMTEK)
Muh Arfah Wahlil Pratama
universitas muhammadiyah kolaka utara
Computer Science & IT Library & Information Science

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
ANALISIS SENTIMEN ULASAN SHOPEE DI PLAY STORE DENGAN NAIVE BAYES: Sentiment Analysis of Shopee Reviews on the Play Store Using Naive Bayes Muh Arfah Wahlil Pratama; Suriyadi Suriyadi; Nurjaya Nurjaya; Haldi Alfaisal; Melni Melni; Andi Nurwafia; Nurkhafitri Sahra; Asya Syara Marzan; Arman Rusdin; Dirgasari Dirgasari
Jurnal Komputer dan Teknologi Vol 5 No 2 (2026): JUKOMTEK JULI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i2.710

Abstract

This study evaluates user sentiments towards the Shopee application on the Google Play Store using a dataset of 1,000 crawled reviews. Preprocessing methods including cleaning, normalization, stopword filtering, and stemming were conducted, followed by feature weighting using TF-IDF. The classification model based on the Naive Bayes Classifier yielded an overall accuracy of 84.5%, with a precision of 85.2%, recall of 83.8%, and F1-score of 84.5%. The analysis suggests that shipping promotions are the main drivers of positive sentiment, while post-update app performance drops and payment errors trigger negative reviews.
ANALISIS SENTIMEN ULASAN PENGGUNA APLIKASI PINTEREST PADA GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA NAIVE BAYES CLASSIFIER Muh Arfah Wahlil Pratama; Suryadi Suryadi; Haldi Alfaisal; Nurjaya Nurjaya; Nia rahmadani Nia; Ahmad Ashar; Elsa Elsa; Riksal Rivaldi; Sri Rejeki; Dimas Rezkianto; Iin Sugiarti; Zulfikar Isnansah
Jurnal Komputer dan Teknologi Vol 5 No 2 (2026): JUKOMTEK JULI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i2.728

Abstract

The rapid growth of user reviews on the Google Play Store offers valuable insights for app developers. This study conducts sentiment analysis on Pinterest user reviews using the Naive Bayes Classifier algorithm. Data was collected via web scraping using the `google-play-scraper` library within the Google Colaboratory environment. The dataset, consisting of Indonesian-language reviews, underwent preprocessing steps including case folding, tokenization, stopword removal, and stemming. Feature extraction was performed using TF-IDF, and the model was evaluated using a confusion matrix with an 80:20 train-test split. The results indicate that the Naive Bayes model achieved an accuracy of 84.00%, a precision of 84.00%, and a recall of 77.78%. The sentiment distribution reveals a predominance of positive reviews, reflecting overall user satisfaction with the Pinterest app. This research contributes to the understanding of public opinion regarding visual-based applications and validates the effectiveness of Google Colab as an integrated platform for Indonesian-language sentiment analysis.
Co-Authors Ahmad Ashar Andi Nurwafia Arman Rusdin Asya Syara Marzan Dimas Rezkianto Dirgasari Dirgasari Elsa Elsa Haldi Alfaisal Iin Sugiarti Melni Melni Nia rahmadani Nia Nurjaya Nurjaya Nurkhafitri Sahra Riksal Rivaldi Sri Rejeki Suriyadi Suriyadi Suryadi Suryadi Zulfikar Isnansah