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All Journal Jurnal Komputer dan Teknologi (JUKOMTEK)
Dila Handayani
Universitas Islam Negeri Sumatera Utara
Computer Science & IT Library & Information Science

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ANALISIS TINGKAT PEMAHAMAN MAHASISWA ILMU KOMPUTER PADA JENIS PARAGRAF Tasya Aulia Fitri; Sazwani Ardhia Sahira; Nabil Nailul Abrar; Risya Sahdaini Br. Sembiring; Dila Handayani
Jurnal Komputer dan Teknologi Vol 5 No 2 (2026): JUKOMTEK JULI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i2.551

Abstract

This study aims to determine the level of understanding of students from the Computer Science Study Program at the State Islamic University of North Sumatra (UINSU) regarding types of paragraphs in the Indonesian language. The research employed a quantitative approach using questionnaires and descriptive analysis. The results show that persuasive (40.5%) and argumentative (35.1%) paragraphs are the most difficult for students to understand, while expository, descriptive, and narrative paragraphs are relatively easier. These findings indicate that non-language students experience difficulties with paragraph types that require reasoning and systematic argument construction, highlighting the need for more effective Indonesian language learning strategies
PERSEPSI PENGGUNA TERHADAP PENERAPAN AI UNTUK ANALISIS KOMENTAR MEDIA SOSIAL Amanda Putri Rizkita; Nadine Octavianta; Habibah Zahra Siregar; Salsabilla Khairus Syifa; Dila Handayani
Jurnal Komputer dan Teknologi Vol 5 No 1 (2026): JUKOMTEK JANUARI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i1.552

Abstract

This study examined user views on the use of artificial intelligence (AI) to analyze comments on Indonesian-language social media. Of the 50 respondents, 92% said AI was useful for understanding public opinion, while 8% still doubted the accuracy of the analysis results. While 88% felt AI could speed up the process of recognizing sentiment in comments, 74% felt the technology did not fully understand Indonesian casual language and social context. Furthermore, 81% agreed that the use of AI should be ethically supervised to prevent errors in data interpretation and use. The results showed that users generally held a positive and optimistic view of the future of AI, although adjustments were still needed regarding language and user ethics in Indonesia's digital world.
Co-Authors Amanda Putri Rizkita Habibah Zahra Siregar Nabil Nailul Abrar Nadine Octavianta Risya Sahdaini Br. Sembiring Salsabilla Khairus Syifa Sazwani Ardhia Sahira Tasya Aulia Fitri