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All Journal Jurnal Ilmu Ekonomi, Pendidikan dan Teknik (IDENTIK) Jurnal Komputer, Informasi dan Teknologi
Salvia Nabillah Syifa
Universitas Negeri Surabaya
Religion Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media

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Analisis Sentimen Komentar Youtube Rencana Pemerintah terhadap Pemblokiran Roblox Menggunakan Model Naïve Bayes Firdiawati Firdiawati; Salvia Nabillah Syifa; Harun Al Rosyid
Jurnal Komputer, Informasi dan Teknologi Vol. 6 No. 1 (2026): June
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v6i1.3454

Abstract

Perkembangan teknologi digital telah meningkatkan popularitas platform permainan daring seperti Roblox. Namun, rencana pemerintah untuk memblokir platform tersebut memunculkan beragam respons publik yang terlihat pada kolom komentar YouTube. Penelitian ini bertujuan untuk mengidentifikasi kecenderungan sentimen masyarakat terhadap isu pemblokiran Roblox. Data penelitian terdiri dari 2.500 komentar YouTube yang diperoleh melalui YouTube Data API, kemudian melalui tahapan preprocessing dan pelabelan sentimen berbasis lexicon hingga tersisa 2.427 komentar yang layak dianalisis. Data selanjutnya diubah menjadi fitur TF-IDF dan diklasifikasikan menggunakan metode Naïve Bayes algoritma Multinomial Naïve Bayes dengan skema pembagian data 90:10 dan 80:20. Hasil terbaik diperoleh pada skema 80:20 dengan akurasi 71,19%, precision 73,31%, recall 71,19%, dan f1-score 70,23%. Hasil yang didapat dari penelitian menunjukkan bahwa opini publik didominasi sentimen netral dengan kecenderungan negatif. Penelitian ini menyimpulkan bahwa Multinomial Naïve Bayes efektif dalam mengklasifikasikan sentimen komentar berbahasa Indonesia terkait isu pemblokiran Roblox.
Pengembangan Lms Moodle Berbasis Project Based Learning Untuk Meningkatkan Kompetensi Kognitif Pada Elemen Pemrograman Web Siswa Kelas Xi Rpl Smk Negeri 4 Bojonegoro Salvia Nabillah Syifa; Ersha Aisyah Elfaiz
Jurnal Ilmu Ekonomi, Pendidikan dan Teknik Vol. 3 No. 4 (2026): IDENTIK - Juli
Publisher : CV. SINAR HOWUHOWU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70134/identik.v3i4.1734

Abstract

The implementation of digital learning media for the Web Programming element at SMK Negeri 4 Bojonegoro remains significantly constrained, leading to a high reliance on conventional teaching methods and a lack of a specialized Learning Management System (LMS) that supports project-based learning. This research aims to develop a Project-Based Learning (PjBL)-based Moodle LMS called DigiLearn and analyze its effectiveness in improving the cognitive competence of students. Using a Research and Development (R&D) approach with the ADDIE model, this study employed a Nonequivalent Control Group Design. The study involved two classes of eleventh-grade Software Engineering (RPL) students, split into an experimental group (XI RPL 1) and a control group (XI RPL 2), each consisting of 34 students. The developed LMS was integrated with the Monitoring Kanban Board plugin to help students track their project milestones through To Do, Doing, and Done categories. Data collection was conducted via expert validation and pretest-posttest instruments, subsequently analyzed using feasibility percentages, N-Gain tests, and Independent Samples t-Tests. The validation results demonstrated that the LMS is highly feasible for implementation. The N-Gain analysis revealed that the experimental group achieved a score of 0.712 (high category), significantly outperforming the control group's score of 0.381 (moderate category). Furthermore, the Independent Samples t-Test confirmed a statistically significant difference in cognitive competence between the two groups. It is concluded that the PjBL-based Moodle LMS is highly effective in enhancing students' cognitive competence within the Web Programming element.
Co-Authors Ersha Aisyah Elfaiz Firdiawati Firdiawati Harun Al Rosyid