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Cahyadi
Universitas Yayasan Pendidikan Imam Bonjol Majalengka
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences

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PEMODELAN TOPIK BERITA NASIONAL INDONESIA MENGGUNAKAN LATENT DIRICHLET ALLOCATION Fajar Maula Hidayat; Cahyadi; Hafidz Sanjaya; Dwi Purnomo; Heri Wiranto
INFOTECH journal Vol. 12 No. 1 (2026)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/infotech.v12i1.16926

Abstract

Penelitian ini membahas penerapan metode Latent Dirichlet Allocation (LDA) untuk pemodelan topik berita terkini di Indonesia. Data dikumpulkan melalui RSS feed dari beberapa portal berita nasional seperti Detik, Kompas, Tribunnews, Liputan6, Tempo, CNN Indonesia, dan Antara News. Proses penelitian meliputi tahapan pengambilan data, pembersihan dan preprocessing teks, eksplorasi awal frekuensi kata, penyusunan representasi korpus, pemodelan topik LDA, visualisasi interaktif dengan pyLDAvis, serta evaluasi model menggunakan metrik coherence score. Hasil analisis menunjukkan model LDA dengan lima topik memberikan distribusi kata kunci yang relevan dengan isu-isu utama seperti bencana, politik, demonstrasi, korupsi, dan kriminal. Nilai coherence score sebesar 0,3591 mengindikasikan tingkat koherensi cukup baik, meskipun terdapat ruang optimasi melalui penyesuaian parameter. Visualisasi interaktif menunjukkan keterpisahan topik yang memadai, dengan tumpang tindih yang relatif kecil. Temuan ini memperlihatkan bahwa LDA efektif untuk mengidentifikasi topik dominan dalam berita nasional, sehingga dapat dimanfaatkan untuk analisis tren isu publik, pengelompokan konten media, serta mendukung pengambilan keputusan berbasis data.
PELATIHAN ENGLISH SPEAKING BERBASIS ARTIFICIAL INTELLIGENCE UNTUK MENINGKATKAN SELF-CONFIDENCE MAHASISWA Cahyadi; Dwi Purnomo; Heri Wiranto; Fajar Maula Hidayat; Hafidz Sanjaya
Jurnal Pengabdian Kepada Masyarakat Vol 4 No 2 (2026): JURNAL PENGABDIAN KEPADA MASYARAKAT (PENGMAS)
Publisher : Pusat Penelitian dan Pengabdian pada Masyarakat (P3M)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/pengmas.v4i2.534

Abstract

The rapid development of Artificial Intelligence (AI) has significantly influenced various educational practices, including English language learning. Many students still experience difficulties in speaking English due to low self-confidence, fear of making mistakes, and limited opportunities for speaking practice. This community service activity aimed to enhance students’ self-confidence through AI-based English speaking training. The program involved 25 students who participated in interactive speaking practices using AI applications such as ChatGPT and AI voice assistants. The methods employed included training sessions, demonstrations, guided speaking practice, discussions, and evaluations through questionnaires and observations. The results indicated that participants experienced improvements in self-confidence, motivation, and speaking participation after attending the training. Students perceived AI-based learning as a flexible, interactive, and supportive medium for independent speaking practice. Furthermore, the implementation of AI in English language learning created a more comfortable learning environment, reducing speaking anxiety. Therefore, AI-based speaking training was found to be effective in enhancing students’ self-confidence and communication skills in English language learning.
Co-Authors Dwi Purnomo Fajar Maula Hidayat Hafidz Sanjaya Heri Wiranto