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All Journal JURIKOM (Jurnal Riset Komputer) Innovative: Journal Of Social Science Research
Mahfudza, Nurbaiti
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Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Public Health Other

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Sistem Monitoring Karyawan PT Telkom Akses Medan Menggunakan Teknologi GPS Haliza, Dinda; Mahfudza, Nurbaiti
Innovative: Journal Of Social Science Research Vol. 3 No. 6 (2023): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

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Abstract

Teknologi berkembang semakin cepat, dan hampir semua layanan dirancang untuk memberi manfaat bagi kehidupan manusia. Seiring dengan kemajuan teknologi, semakin mudah untuk menemukan seseorang. Perkembangan ini memungkinkan untuk mengetahui keberadaan karyawan dengan tujuan untuk meningkatkan semangat kerja karyawan dan mencegah terjadinya ketidakjujuran di kalangan karyawan. Oleh karena itu, pada penelitian ini kami mengembangkan program yang memanfaatkan teknologi GPS untuk memantau langsung lokasi karyawan dan mendukung kinerja karyawan. Teknologi GPS memudahkan orang menemukan objek yang dicarinya dengan layanan Open StreetMaps yang dapat melihat lokasi tujuan dalam bentuk peta digital. Metode penelitian yang digunakan dalam penelitian ini adalah pengamatan, studi lieratur dan metode SDLC untuk mengembangkan sistem. Informasi yang ditampilkan dalam aplikasi ini diharapkan untuk membantu perusahaan memverifikasi lokasi karyawannya.
Sentiment Analysis of Youtube Comments on Indonesian Presidential Candidates in 2024 using Naïve Bayes Classifier Mahfudza, Nurbaiti; Ihksan, Muhammad
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 2 (2025): April 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i2.8538

Abstract

The 2024 Indonesian presidential election is one of the most talked about topics on various social media platforms, including YouTube. The comments that appear on political-themed videos can reflect public opinion towards presidential candidates. This research aims to conduct sentiment analysis of YouTube comments related to Indonesian presidential candidates in 2024 using the Naïve Bayes Classifier method. This method was chosen due to its ability to classify text data effectively and efficiently. Data was collected from a number of relevant Kompas tv videos on YouTube, then text preprocessing stages such as data cleaning, tokenization, and stemming were performed. Next, the data was classified into three sentiment categories, namely positive, negative, and neutral. The research shows that the Naïve Bayes model is able to classify sentiment with sufficient accuracy.  This finding can provide an overview of public perceptions of each presidential candidate as well as input for interested parties in the fields of politics and public communication. The results of this study show that the naïve bayes classifier algorithm can analyze with an accuracy of 61 % in the evaluation process using confusion matrix. The results of this study indicate that the naïve bayes classifier algorithm can be an effective alternative for analyzing the sentiment of YouTube comments on presidential candidates.
Co-Authors Haliza, Dinda Ihksan, Muhammad