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Sentiment Analysis on Google Reviews Using Naïve Bayes, K-Nearest Neighbors, and Logistic Regression to Improve Novotel Services Dhamma, Yonathan Arya; Barus, Simon Prananta
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8923

Abstract

The application of artificial intelligence (AI) has been widely used in various industrial sectors, including the hospitality industry. One of the applications that is widely used in the hospitality industry is sentiment analysis. Sentiment analysis is carried out by analyzing feedback data from hotel guests or customers. The results of this sentiment analysis are important for decision makers to improve and improve their services. This study aims to obtain sentiment analysis results from Novotel hotel Google reviews based on machine learning by comparing three algorithms, namely Naïve Bayes, K-Nearest Neighbors (KNN), and Logistic Regression. The stages carried out in this study are data collection, data labeling, exploratory data analysis (EDA), data preprocessing, text representation, data sharing, modeling, model training, model evaluation, selection of the most accurate model, visualization of the most accurate model, interpretation of results and writing research reports. The dataset used was 1200 reviews, only 1190 reviews were used in the analysis. From the training results, the model produced by the Logistic Regression algorithm was the most accurate, namely 94.54% with unigrams (n = 1). Here are the results of each category, positive as many as 723 reviews (60.76%), negative as many as 218 reviews (18.32%), and neutral as many as 249 reviews (20.92%). Thus, most of the sentiment towards the service is positive, but some services need to be fixed and improved for customer satisfaction. The next research, the research area is expanded and the use of Deep Learning.
Development of Hydroponic Application based on Web and Internet of Things for The Community to Monitor pH and Total Dissolved Solids Barus, Simon Prananta; Dhamma, Yonathan Arya
International Journal of Research in Community Services Vol. 5 No. 3 (2024)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v5i3.708

Abstract

Construction of the Mortality Table with Gompertz's Law Using the 2019 TMI Reference
Pelatihan Pembuatan Website dengan Menggunakan HTML dan Javascript Untuk SMK Media Informatika di Tangerang Widjaja, Prya Artha; Warsito, Ary Budi; Laia, Nico Abel; Leonesta, Jose Ryu; Anthony, Eveline Valencia; Dhamma, Yonathan Arya
Abdimas Galuh Vol 6, No 1 (2024): Maret 2024
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v6i1.13270

Abstract

Dunia digital saat ini sudah menjadi bagian dalam kehidupan sehari-hari. Masyarakat semakin terbiasa dengan aplikasi teknologi informasi. Semasa pandemi peranan teknologi informasi sangat terasa dalam kehidupan di semua bidang. Untuk membuat perangkat lunak yang digunakan dibutuhkan para ahli pemrograman. Saat ini Indonesia dan juga di dunia masih mengalami kekurangan programmer. Masih banyak yang berpikir bahwa membuat program itu sulit. Pelatihan ini ditujukan untuk siswa/i SMA dan SMK untuk menarik minat mereka dalam belajar pemrograman. Siswa/i diperkenalkan dengan pemrograman web yang sederhana. Tujuannya supaya mereka dapat mencoba sendiri membuat web dengan HTML dan melihat hasilnya. Pemrograman web sendiri bersifat interaktif dan para siswa/i dapat melihat hasilnya secara langsung. Dari pelaksanaan pelatihan ini didapatkan hasil yang cukup memuaskan. Beberapa siswa/i tertarik untuk mempelajari pemrograman lebih lanjut. Diharapkan semakin banyak yang berminat sehingga dapat menghasilkan programmer yang baik.