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ANALISIS PERSEPSI MAHASISWA PASCASARJANA TERHADAP PENGGUNAAN CHATGPT DALAM PENULISAN KARYA ILMIAH DITINJAU DARI ETIKA AKADEMIK Muhammad Rasyid Ridha; Irwansyah Putera Sitorus; Katharina Tyas Aprilia; Muhammad Amin
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5824

Abstract

Abstract: The development of artificial intelligence, particularly generative Artificial Intelligence (AI) such as ChatGPT, has brought significant changes to the world of higher education. ChatGPT, as a form of intelligent system, is utilized by postgraduate students to support scientific writing. This study aims to analyze postgraduate students' perceptions of the use of ChatGPT in scientific writing and to review them from an academic ethics perspective. The research method used was a quantitative descriptive survey approach. Data were collected through a Likert-scale-based questionnaire distributed to postgraduate students who had used ChatGPT in academic activities. Data analysis was conducted using descriptive statistics to illustrate the trends in respondents' perceptions. The results show that ChatGPT is perceived to provide convenience and benefits in assisting the process of scientific writing, but also raises concerns regarding potential violations of academic ethics if used without clear boundaries. Therefore, an understanding and ethical guidelines are needed for the use of ChatGPT in higher education environments. Keyword: ChatGPT; Intelligent Systems; Academic Ethics; Graduate Students; Generative AI Abstrak: Perkembangan kecerdasan buatan, khususnya Artificial Intelligence (AI) generatif seperti ChatGPT, telah membawa perubahan signifikan dalam dunia pendidikan tinggi. ChatGPT sebagai salah satu bentuk sistem cerdas dimanfaatkan oleh mahasiswa pascasarjana dalam mendukung penulisan karya ilmiah. Penelitian ini bertujuan untuk menganalisis persepsi mahasiswa pascasarjana terhadap penggunaan ChatGPT dalam penulisan karya ilmiah serta meninjaunya dari perspektif etika akademik. Metode penelitian yang digunakan adalah kuantitatif deskriptif dengan pendekatan survei. Data dikumpulkan melalui kuesioner berbasis skala Likert yang disebarkan kepada mahasiswa pascasarjana yang pernah menggunakan ChatGPT dalam kegiatan akademik. Analisis data dilakukan menggunakan statistik deskriptif untuk menggambarkan kecenderungan persepsi responden. Hasil penelitian menunjukkan bahwa ChatGPT dipersepsikan memberikan kemudahan dan manfaat dalam membantu proses penulisan karya ilmiah, namun juga menimbulkan kekhawatiran terkait potensi pelanggaran etika akademik apabila digunakan tanpa batasan yang jelas. Oleh karena itu, diperlukan pemahaman dan pedoman etis dalam pemanfaatan ChatGPT di lingkungan pendidikan tinggi. Kata kunci: ChatGPT, Sistem Cerdas, Etika Akademik, Kata kunci: ChatGPT, Sistem Cerdas, Etika Akademik, Mahasiswa Pascasarjana, AI Generatif
ANALISIS SENTIMEN MASYARAKAT TERHADAP KEBIJAKAN PEMBERANTASAN JUDI ONLINE DI INDONESIA MENGGUNAKAN NATURAL LANGUAGE PROCESSING PADA MEDIA SOSIAL Irwansyah Putera Sitorus; Muhammad Irfan Sarif; Nurlina Sari Harahap
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 2 (2026): April 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i2.6175

Abstract

The rapid growth of online gambling in Indonesia has become a serious social problem, prompting the government to implement various eradication policies. This study aims to analyze public sentiment toward Indonesia's online gambling eradication policy using Natural Language Processing (NLP) techniques on social media data collected from YouTube. A total of 237 comments were gathered and processed through preprocessing stages including cleaning, normalization, stopword removal, and stemming using the Sastrawi library. Sentiment labeling was performed using a weighted lexicon-based approach with 600+ sentiment words. Classification was conducted using three models—Random Forest, Linear SVM, and Logistic Regression—with SMOTE applied for class balancing and 5-fold cross-validation for robustness evaluation. The best model, Linear SVM, achieved an accuracy of 97.92% and a CV score of 97.56%. Results showed that 57.4% of public sentiment was neutral, 28.3% positive, and 14.3% negative, indicating that the majority of the public responds to this issue informationally. This study demonstrates that NLP-based sentiment analysis is an effective tool for evaluating public perception of digital policy in Indonesia.