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All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Ininnawa: Jurnal Pengabdian Masyarakat
Himawan, Kevin
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Energy Engineering Public Health Social Sciences

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Pembelajaran Berbasis Teknologi dalam Meningkatkan Kemampuan dan Minat Belajar Anak Desa Sei Wain Prihasto, Bima; Winarni; Kamil, Muhammad Insan; Febriandini, Nanda Clariza; Pratama, Abdul Rizal; Himawan, Kevin; Akbar, Muhammad; Syakbani, Ahmad Rusdianto Andarina; Edia, Naflah Shafa
Ininnawa : Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2024): Volume 02 Nomor 02 (Oktober 2024)
Publisher : Program Studi Manajemen FEB UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/ininnawa.v2i2.4448

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan pemahaman dan minat belajar anak-anak di RT 36 Kelurahan Karang Joang, Kecamatan Balikpapan Utara, terhadap bahasa Inggris, matematika, dan pemrograman. Dengan pendekatan interaktif dan berbasis gamifikasi, melalui penggunaan aplikasi Duolingo, CodeCombat, dan Kahoot, anak-anak diajak untuk belajar dengan cara yang menyenangkan dan menantang. Evaluasi program menunjukkan peningkatan yang signifikan dalam pemahaman matematika dan bahasa Inggris, serta dalam membangun rasa percaya diri dalam menggunakan bahasa Inggris. Untuk penyempurnaan program di masa mendatang, disarankan untuk melakukan evaluasi yang lebih terperinci, melibatkan lebih banyak pihak, dan memperluas jangkauan program.
Analisis Sentimen dan Pemodelan Topik Terhadap Ulasan Aplikasi Mobile JKN Menggunakan SVM dan LDA Arisa, Nursanti Novi; Himawan, Kevin
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.8029

Abstract

In 2024, the number of internet users in Indonesia reached 221.56 million, accounting for 79.5% of the population an increase of 1.4% from the previous year (APJII). This growth has driven digital transformation in various sectors, including healthcare. To support this, the government launched the Mobile JKN app as part of the digitalization of the National Health Insurance (JKN) program, aimed at expanding access to services, especially in remote areas. Despite over 50 million downloads, the app still faces technical issues such as difficulties with registration, verification, and frequent updates that disrupt user experience. This study analyzes user complaints using sentiment analysis with the Support Vector Machine (SVM) algorithm and topic modeling via Latent Dirichlet Allocation (LDA). A total of 285,661 reviews from the Google Play Store (June 2016–December 2024) were collected and pre-processed. Of these, 181,657 reviews were analyzed—80% used for training (145,615) and 20% for testing (36,042). The SVM model showed strong performance, achieving 90% accuracy, 90% precision, 89% recall, and an F1-score of 89%. It classified 12,965 reviews as positive and 23,077 as negative. Topic modeling of negative reviews revealed five key themes with a coherence score of 0.5064: app usage, login and registration, data verification, online services and data changes, and app updates. Further analysis of version 4.12.0 informed improvement recommendations, particularly regarding phone number verification, login, and facial recognition issues.
Co-Authors Arisa, Nursanti Novi Edia, Naflah Shafa Febriandini, Nanda Clariza Muhammad Akbar Muhammad Insan Kamil, Muhammad Insan Pratama, Abdul Rizal Prihasto, Bima Syakbani, Ahmad Rusdianto Andarina Winarni