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Penguatan kompetensi mahasiswa melalui integrasi scite.AI dalam analisis literatur karya ilmiah Santi Yunus; Rita Yunus; Muhammad Akbar; Albetris Albetris; Nurfadilah Sindika Sari
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v10i2.38569

Abstract

Abstrak Perkembangan Artificial Intelligence (AI) di pendidikan tinggi menghadirkan peluang dalam penguatan literasi akademik, khususnya pada kemampuan analisis literatur mahasiswa. Kegiatan pengabdian ini bertujuan meningkatkan kompetensi mahasiswa melalui integrasi Scite.AI sebagai pendukung analisis literatur dalam karya ilmiah. Program dilaksanakan pada 16 Agustus 2025 di Ruang BTE 21 dengan melibatkan 33 mahasiswa yang sedang atau akan menyusun tugas akhir. Metode yang digunakan adalah pelatihan berbasis pendampingan dengan desain workshop praktik dan pendekatan experiential learning. Kegiatan meliputi pemaparan konsep citation context, demonstrasi fitur Scite.AI, praktik analisis fungsi sitasi (mentioning, supporting, contrasting), serta diskusi dan refleksi. Hasil menunjukkan bahwa penggunaan Scite.AI membantu mahasiswa memahami konteks sitasi secara lebih kritis dan tidak lagi bergantung pada jumlah sitasi semata. Integrasi AI yang dipadukan dengan pendampingan terstruktur terbukti mendukung peningkatan ketelitian analisis literatur dan kualitas argumentasi ilmiah. Dengan demikian, pemanfaatan Scite.AI berbasis pendampingan dapat menjadi strategi efektif dalam memperkuat kompetensi literasi akademik mahasiswa di era digital. Kata kunci: artificial intelligence; scite.AI; analisis literatur; citation context; pendampingan. Abstract The development of Artificial Intelligence (AI) in higher education offers opportunities to strengthen students’ academic literacy, particularly in literature analysis skills. This community service program aimed to enhance students’ competencies by integrating Scite.AI as a tool to support literature analysis in academic writing. The program was conducted on August 16, 2025, in Room BTE 21 and involved 33 students preparing their undergraduate theses or scientific articles. The method employed was mentoring-based training combined with a practice-oriented workshop and an experiential learning approach. Activities included introducing citation context concepts, demonstrating Scite.AI features, practicing citation function analysis (mentioning, supporting, contrasting), and conducting guided discussions and reflections. The results indicate that Scite.AI helped students interpret citation contexts more critically and move beyond relying solely on citation counts. The integration of AI with structured mentoring contributed to improved rigor in literature analysis and stronger scientific argumentation. Therefore, mentoring-based integration of Scite.AI represents an effective strategy for strengthening academic literacy competencies in the digital era. Keywords: artificial intelligence; scite.AI; literature analysis; citation context; mentoring.
Identifying Proprietary Channel Impact as A Digital Financial Services Indicator on Inflation in Indonesia Rahayu Rahayu; Musthafa Luthfi; Albetris Albetris; Failur Rahman; Nurhayani Nurhayani
Journal of Economic Education and Entrepreneurship Studies Vol. 7 No. 3 (2026)
Publisher : Department of Economics Education, Faculty of Economics, Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62794/je3s.v7i3.207

Abstract

Availability of financial services by Banks in Indonesia can make transactions in some sectors of economy more flexible and easier. This inclusiveness creates a new habit in society for payments, money transfer, and other transaction, furthermore, the use of digital financial services can boost the selling performance of MSME’s, especially in e-commerce. Nowadays, the increasing of digital financial services using, affecting money in circulation to prevent inflation. This research aims to measure the extent of the digital financial services can impact inflation by measuring of money supply that use a digital financial service making an econometrics model of Error Correction Model. This model construct of digital financial services that be indicated by proprietary channel. Some variable of proprietary channel includes the use of mobile-internet banking as first variable and the use of phone banking as second variable. This research will find which variable can affect the money supply as an inflation indicator. The finding of this research can be concluded that mobile-internet banking has a significant impact on inflation and phone banking has a significant impact on inflation too. These variables also have simultaneously significant impact on inflation in short run and in long run. So, maintaining inflation have to be considered by the relevant authority.