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All Journal Buletin Sistem Informasi dan Teknologi Islam Scientific Journal of Engineering Research
Alyandi, La Ode
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Computer Science & IT Engineering

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Menganalisis Ulasan Mobile Legends: Analisis Kinerja Berdasarkan Opini Pengguna dengan Naive Bayes Kariyamin, Kariyamin; Alyakin, Muh. Ikhsan; Alyandi, La Ode
Buletin Sistem Informasi dan Teknologi Islam (BUSITI) Vol 6, No 1 (2025)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v6i1.2475

Abstract

This research explores sentiment analysis on user reviews of the game Mobile Legends: Bang Bang using the Naïve Bayes method. With the rapid growth in user numbers, the reviews received reflect a diverse range of positive, negative, and neutral sentiments. One of the main challenges is the data imbalance among the three sentiments, which can affect the model's accuracy. Data was collected through scraping techniques from the Google Play Store, followed by preprocessing to enhance data quality. The analysis results show that the Naïve Bayes model achieved an accuracy of 75.28%, demonstrating good performance in identifying negative reviews, although there is still room for improvement in the positive and neutral categories. These findings are expected to provide valuable insights for game developers in understanding user experiences and improving application features based on sentiment analysis. 
Implementasi Naive Bayes dalam Analisis Sentimen Komentar Game Honor of Kings di Playstore Alyandi, La Ode; Hadiani, La; Irma, Irma
Buletin Sistem Informasi dan Teknologi Islam (BUSITI) Vol 6, No 1 (2025)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v6i1.2589

Abstract

Penelitian ini menganalisis sentimen ulasan pengguna game Honor of Kings di Playstore menggunakan algoritma Naive Bayes. Sebanyak 500 ulasan terbaru dikumpulkan melalui teknik scraping dan diproses melalui tahapan cleaning , casefolding , tokenizing , stopword removal , dan stemming . Data kemudian diklasifikasi sentimen menjadi positif atau negatif dengan algoritma Naive Bayes, menggunakan pembagian data 70% untuk pelatihan dan 30% untuk pengujian. Hasil menunjukkan akurasi model sebesar 71%, dengan distribusi sentimen yang hampir seimbang: 50,5% positif dan 49,5% negatif. Kata-kata dominan pada ulasan positif mencerminkan aspek positif seperti "bagus" dan "seru", sedangkan ulasan negatif berisi keluhan terkait fitur atau masalah teknis. Penelitian ini memberikan wawasan penting bagi pengembang game untuk meningkatkan kualitas produk dan menanggapi kebutuhan pengguna berdasarkan analisis sentimen.
Comparative Analysis of Hierarchical Token Bucket and Per Connection Queue Methods in Video Conferences Kariyamin; Alyandi, La Ode; A'an, Deyti Lusty; Suarti, Wa Ode Reni; Yapono, Putri; Tangaro, Diana May Glaiza G.; Talirongan, Florence Jean B.
Scientific Journal of Engineering Research Vol. 1 No. 2 (2025): April
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjer.v1i2.2025.13

Abstract

Video conferencing is a set of interactive telecommunication technologies that allow two or more parties in different locations to interact using audio and video simultaneously. In video conferencing tools, bandwidth management is needed to maintain the quality of data transmitted through bandwidth. The Hierarchical Token Bucket (HTB) method is a method that uses a hierarchical structure and priorities for the client so that the distribution of bandwidth can be adjusted. In contrast, the Per Connection Queue (PCQ) method is a method that applies bandwidth sharing so that the allocation of bandwidth can be done more evenly to all clients. The parameters used to determine the quality of service in both methods are throughput, packet loss, delay, and jitter. The test results showed that in the Zoom application, the HTB method had an average TIPHON Standard Index of 3.5, while the PCQ method was 3.75. However, in the TrueConf application, the HTB method has a TIPHON standard index of 3.75, while the PCQ method has a TIPHON standard index of 3.5. In the TrueConf application, the HTB method is superior, while in the Zoom application, the PCQ method is superior.
Co-Authors A'an, Deyti Lusty Alyakin, Muh. Ikhsan Hadiani, La Irma Irma Kariyamin Kariyamin, Kariyamin Suarti, Wa Ode Reni Talirongan, Florence Jean B. Tangaro, Diana May Glaiza G. Yapono, Putri