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All Journal Building of Informatics, Technology and Science J-Intech (Journal of Information and Technology)
Prakoso, Muhammad Sidiq Bagus
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering Library & Information Science

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Analisis Sentimen Terhadap Kualitas Pelayanan Aplikasi In-Drive Menggunakan Metode Naive Bayes Classifier Prakoso, Muhammad Sidiq Bagus; Hanif, Isa Faqihuddin
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6682

Abstract

This research analyzes user sentiment towards the service quality of the In-Drive application using the Naive Bayes Classifier method. A total of 15,000 reviews from the Google Play Store were collected using web scraping techniques from the results of sentiment analysis of the data, 9,665 negative sentiments and 5,335 positive sentiments were found. The data went through a pre-processing stage including cleaning, case folding, stopword removal, tokenizing, and stemming. Naive Bayes algorithm was used to classify the reviews into positive and negative sentiments. Evaluation using the confusion matrix resulted in 76.56% accuracy, 78.26% precision, 87.69% recall, and 82.71% F1 score. These results indicate that most reviews are negative. This research is expected to help In-Drive app developers understand user experience and improve service quality based on automatically available reviews.
Penerapan Bussiness Intelligence Terhadap Penjualan Vending Machine di Central New Jersey USA Menggunakan Tableau hilmi, nizar fawwazun; Abdillah, Allif Rizki; Maulana, Putra Syahri; Prakoso, Muhammad Sidiq Bagus
J-INTECH (Journal of Information and Technology) Vol 12 No 1 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i1.1275

Abstract

This research aims to analyze the application of Business Intelligence (BI) to vending machine sales in Central New Jersey, USA, using the Tableau data visualization tool. In the current digital era, BI is the key for companies to make faster and more precise decisions based on existing data. Vending machines as an automated sales channel produce large and varied sales data, requiring in-depth analysis to improve sales performance. This research uses a case study approach by collecting sales data from a number of vending machines spread across various locations in Central New Jersey. Data is analyzed using Tableau to identify sales patterns, seasonal trends, and factors that influence sales performance. The resulting data visualization helps in revealing important insights such as products with the highest sales, the most effective sales times, and strategic locations for vending machine placement. The research results show that using Tableau in BI is very effective in identifying and analyzing vending machine sales data. These findings provide concrete recommendations for vending machine managers to improve sales strategies, including stock management, pricing, and machine placement. Overall, implementing BI with Tableau provides significant added value in data-based decision making and can be adapted for various other types of business.
Co-Authors Abdillah, Allif Rizki Hanif, Isa Faqihuddin hilmi, nizar fawwazun Maulana, Putra Syahri