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All Journal JSiI (Jurnal Sistem Informasi) Physics Education Research Journal
Wenty Dwi Yuniarti
UIN Walisongo Semarang
Computer Science & IT Decision Sciences, Operations Research & Management Education Physics

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Pengembangan Modul Fisika Berbantuan Teknologi Augmented Reality pada Materi Gelombang Bunyi untuk SMA/MA Kelas XI Lilin Nazwa Khunaeni; Wenty Dwi Yuniarti; Muhammad Ardhi Khalif
Physics Education Research Journal Vol 2, No 2 (2020)
Publisher : Faculty of Science and Education, UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/perj.2020.2.2.6144

Abstract

This research aims to determine the appropriateness of a physics module with Augmented Reality (AR) technology. This research is an RD research consisting of the initial study stages, planning, development, product assessment, product revision and field trials. Data collection techniques used were observation and interviews during the preliminary study, and questionnaires for validation of material experts and media experts, validation of physics teachers, and student responses. Based on the data analysis, it was concluded that the quality of the physics module was very good with a percentage value of 95% from material experts, 86.67% from media experts and 90% from physics teachers. Student responses to the physics module obtained a percentage of 89% in the very good category. Based on the research results, the physics module with Augmented Reality (AR) technology developed is appropriate and can be used in physics learning.
Analisis Sentimen Ulasan Mobile Legends di Google Play Store dan YouTube Menggunakan Pelabelan Otomatis Roberta dan Klasifikasi Random Forest Muhammad Rafid Pratama; Maya Rini Handayani; Wenty Dwi Yuniarti; Khothibul Umam
Jurnal Sistem Informasi Vol. 12 No. 2 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i2.10459

Abstract

Perkembangan industri game mobile telah mendorong meningkatnya jumlah pengguna dan ulasan terhadap berbagai judul populer, salah satunya Mobile Legends: Bang Bang. Penelitian ini bertujuan untuk menganalisis persepsi pengguna terhadap aplikasi Mobile Legends melalui ulasan yang diperoleh dari Google Play Store dan YouTube. Metode yang digunakan meliputi pengambilan data secara crawling, pelabelan otomatis menggunakan model RoBERTa untuk klasifikasi sentimen (positif, negatif, dan netral), serta pemodelan menggunakan algoritma Random Forest. Dataset terdiri dari 1.400 data dari Google Play Store dan ratusan data dari YouTube yang telah melalui proses pra-pemrosesan. Evaluasi model menggunakan metrik precision, recall, dan f1-score. Hasil pengujian menunjukkan bahwa model mampu mengklasifikasikan ulasan dengan cukup baik, dengan akurasi sebesar 80% pada data Google Play Store dan 82% pada data YouTube. Model menunjukkan performa tinggi dalam mendeteksi ulasan negatif dan positif, meskipun akurasi untuk kelas netral masih rendah. Secara keseluruhan, model berbasis Random Forest cukup andal dalam mengolah data ulasan pengguna, dan memberikan wawasan mengenai persepsi masyarakat terhadap Mobile Legends di berbagai platform.
Co-Authors Khothibul Umam Lilin Nazwa Khunaeni Maya Rini Handayani Muhammad Ardhi Khalif, Muhammad Ardhi Muhammad Rafid Pratama