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All Journal Jurnal Abdimas Ekonomi Dan Bisnis (JAMEB) International Journal of Information Technology and Computer Science Applications (IJITCSA)
Tyastuti Sri Lestari
Universitas Bhyangkara Jakarta Raya
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Social Sciences

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PELATIHAN MULTIMEDIA UNTUK KARYAWAN DAN ANGGOTA TNI DI PUSINFOLATHA wo2ntea Wowon Priatna; M. Fadhli Nursal; Tyastuti Sri Lestari; Joni Warta
Jurnal Abdimas Ekonomi dan Bisnis (JAmEB) Vol 1 No 2 (2021): JAMEB (Jurnal Abdimas Ekonomi dan Bisnis)
Publisher : Fakultas Ekonomi Dan Bisnis Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (358.564 KB) | DOI: 10.31599/jameb.v1i2.906

Abstract

The purpose of this multimedia is to improve the ability of training members and employees with abilities in the field of multimedia through. Multimedia uses several media to present information which is a combination of text, graphics, animation, images, video and sound such as making graphic designs, text, images, video, audio, animation. This implementation was carried out for 2 months starting from the training in July and August 2019 at the Pushinfolatha Computer Lab, TNI Headquarters, Cilangkap. The training participants are TNI members and PNS employees and 20 people. The training was carried out using practical methods in the Pusinfolatha computer lab with the material presented was making infographic-based presentations, making logos, posters, banners, banners and video editing. The implementation of this training was successful and all participants were able to follow the training material well, it can be seen from the work and evaluation results that the average score obtained by participants was above 90.
Public Sentiment Analysis on the Service Quality of PT PLN on X Using Naïve Bayes and K-Nearest Neighbor Algorithms. Nurul Zahra; Wowon Priatna; Tyastuti Sri Lestari
International Journal of Information Technology and Computer Science Applications Vol. 4 No. 1 (2026): January - April 2026
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

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Abstract

Quality services since electricity is a primary public need. However, numerous complaints still highlight PLN’s lack of responsiveness, especially on the X platform (formerly Twitter). This study aims to analyze public sentiment toward PLN’s service quality expressed on X and compare the performance of the Naïve Bayes and K-Nearest Neighbor (KNN) algorithms in classifying sentiments into positive, negative, and neutral categories. The research employs the Knowledge Discovery in Databases (KDD) approach, involving data collection through tweet scraping using Tweet-Harvest, preprocessing (case folding, tokenizing, filtering, stemming), transformation with TF-IDF weighting, and data mining using Naïve Bayes and KNN. Evaluation through a confusion matrix shows that Naïve Bayes achieved an accuracy of 87%, outperforming KNN with an accuracy of 86%. These findings provide insights for PLN to better understand public perception and serve as a reference for future sentiment analysis research using machine learning.
Co-Authors Joni Warta M. Fadhli Nursal Nurul Zahra Priatna , Wowon Wowon Priatna