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BAKTI SOSIAL KHITANAN MASSAL DAN SANTUNAN SEBAGAI PROGRAM KERJA KKN UPI DI DESA PAKUWON Nazlaliyah, Isnaisa Salma; Fauziah, Naila Raima; Syachfitri, Luthfiana; Fitri, Ade Lia Nur; Williyanto, Septian
Abdimas Galuh Vol 5, No 2 (2023): September 2023
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v5i2.12164

Abstract

Kuliah Kerja Nyata (KKN) telah menjadi salah satu bagian dari kurikulum pendidikan tinggi di Indonesia. Program ini dirancang untuk menghubungkan mahasiswa dengan masyarakat, memberikan pengalaman lapangan, dan mendorong mahasiswa untuk berpartisipasi aktif dalam pembangunan sosial. Kuliah Kerja Nyata (KKN) merupakan peluang berharga bagi mahasiswa untuk mengembangkan keterampilan sosial, kepemimpinan, dan empati sosial, sembari mengabdi kepada masyarakat. Pengabdian kepada masyarakat ini dilaksanakan di Desa Pakuwon Kecamatan Cisurupan Kabupaten Garut dengan berbasis tema Sustainable Development Goals (SDGs). Mengacu pada Sustainable Development Goals (SDGs), dilaksanakan kegiatan bakti sosial khitanan massal dan santunan.
Unpacking the negative effects of generative AI on student motivation and procrastination Widarsih, Wiwi; Syachfitri, Luthfiana; Maheshbabu, N.; Haziman, Muhammad Luthfan
Jurnal Psikologi Vol 25, No 1 (2026): April 2026
Publisher : Faculty of Psychology, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jp.25.1.35-51

Abstract

Background: The rapid integration of Generative Artificial Intelligence (GenAI) in higher education has reshaped how students engage with academic work. While GenAI improves efficiency and accessibility, concerns arise regarding its effects on cognitive engagement and self regulation.Purpose: This study examined how Ease of Internet Access (EIA) and Frequency of GenAI Use (FGAI) influence Learning Motivation (LM), with Academic Procrastination (AP) as a mediating variable.Method: A total of 205 undergraduate students from Politeknik AKA Bogor completed standardized questionnaires adapted to GenAI-related learning. Data were analyzed using multiple regression, mediation analysis based on Baron and Kenny’s framework, and multi-group confirmatory factor analysis (MGCFA).Findings: The results showed EIA and FGAI did not significantly predict LM (R² = .006; p > .05). EIA significantly predicted AP (β = .146, p = .039), and AP negatively predicted LM (β = −.603, p < .001). Mediation analysis confirmed a significant indirect effect of EIA on LM through AP (Sobel = −2.075, p = .038). MGCFA supported configural and metric invariance across GenAI-use groups (ΔCFI = .003), with partial scalar invariance achieved.Implication: These findings indicate that digital accessibility may indirectly reduce motivation by increasing procrastination, emphasizing the importance of self-regulation and guided AI integration in higher education.