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All Journal Mattawang: Jurnal Pengabdian Masyarakat Panrannuangku Jurnal Pengabdian Masyarakat Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Information Technology Education Journal Journal of Vocational, Informatics and Computer Education Journal of Deep Learning, Computer Vision and Digital Image Processing Indonesian Technology and Education Journal Jurnal Pengabdian Masyarakat dan Riset Pendidikan Jurnal MediaTIK Innovation and Applied Education Journal
Putri Nirmala
Unknown Affiliation
Humanities Computer Science & IT Education Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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Persepsi Mahasiswa terhadap Infrastruktur Pendidikan dan Integrasi Computational Thinking di Perguruan Tinggi: Student Perceptions of Educational Infrastructure and Integration of Computational Thinking in Higher Education M. Nurul Fajri; Ruslan Kadir; Putri Nirmala; Rachmawaty Kadir; Rahmawati
Journal of Vocational, Informatics and Computer Education Vol 3, No 1 (2025): Juni 2025
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/21tmsg76

Abstract

The disparity in educational infrastructure across universities in Indonesia presents a significant barrier to the integration of computational thinking (CT) in higher education. This study aims to explore students’ perceptions of educational infrastructure development and the integration of CT in university learning. A descriptive quantitative method was employed using a Likert-scale questionnaire distributed to 73 university students. The results show that students perceive CT as highly relevant for enhancing critical thinking and problem-solving skills, with strong support for its integration into curricula. However, perceptions regarding the adequacy of educational infrastructure in Indonesia remain neutral to negative. Students also highlighted the importance of teacher and parent roles, as well as equitable access to professional training for successful CT implementation. These findings suggest that while awareness of CT’s relevance is high, systemic improvements in infrastructure and educator capacity are essential to support effective implementation in higher education.
ChatGPT dalam Dunia Virtual: Eksplorasi Pemanfaatan AI dalam Lingkungan Pembelajaran Mahasiswa: ChatGPT in a Virtual World: An Exploration of AI Utilization in Student Learning Environments Mutmainnah; Nurul Azizah; Putri Nirmala; Hajar Dewantara; Andika Isma
Journal of Vocational, Informatics and Computer Education Vol 3, No 1 (2025): Juni 2025
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/ev7sxe85

Abstract

The rapid development of information and communication technology presents challenges in higher education, particularly regarding students’ limited understanding of how to effectively integrate emerging tools like ChatGPT and Metaverse into learning. This study aims to explore students’ perceptions of ChatGPT utilization within the Metaverse learning environment at Universitas Negeri Makassar. A mixed-method approach was applied by distributing online questionnaires to 60 students across various cohorts and conducting interviews with selected respondents. The findings reveal that most students perceive ChatGPT positively, with 56% rating it effective in supporting learning, 58% expressing comfort in using it for academic tasks, and over 70% acknowledging its role in enhancing learning efficiency, critical thinking, and confidence in discussions. Moreover, ChatGPT was reported to improve access to learning resources, problem-solving in academic tasks, and overall learning quality, despite some students facing minor challenges in adoption. These results suggest that ChatGPT, when integrated into Metaverse-based learning, has significant potential to enhance educational outcomes, provided institutions offer proper guidance and support to maximize its benefits.
Unraveling the Effects of AI Usage on Burnout among Programmers: An Apriori Algorithm Data Mining Approach Muhammad Fardan; Alwi, Ana Sulistiana; Darwing, Khalil Mubaraq; Surianto, Dewi Fatmarani; Putri Nirmala; Nurrahmah Agusnaya
Information Technology Education Journal Vol. 4, No. 3, August (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v4i3.9858

Abstract

Burnout is a growing problem across various industries, particularly among programmers who face high workloads and prolonged stress. In this digital era, the use of technologies such as AI can be a solution to reduce workloads and improve employee well-being. This study aims to identify how the use of AI can reduce burnout levels in programmers. The method used is a cross-sectional research design with data collection through a survey using the Google Form platform, and data analysis using descriptive techniques and the Apriori algorithm to find patterns in the relationship between the duration of AI use, workload, and burnout levels. The results show that the use of AI can help reduce burnout levels by lowering workloads, providing a basis for more effective interventions in the workplace.
Sistem Pakar Gangguan Menstruasi dengan Metode Teorema Bayes Ismail Ismail; Putri Nirmala; Rina Andriyani
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 5 No. 3 (2025): November: Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v5i3.1748

Abstract

Advancements in information technology have brought significant impacts in the healthcare sector, particularly in the medical diagnosis process. Expert systems, as a technological innovation, mimic the capabilities of human experts in making decisions based on knowledge bases and inference rules. The development of expert systems aims to improve the efficiency and accuracy of diagnosis, especially when facing uncertainty and variations in clinical data. This system integrates symptom data, diseases, and prior probabilities derived from epidemiological studies and expert medical experience. In this study, the author designed and implemented an expert system for diagnosing menstrual disorders based on the Bayes’ Theorem method. The system utilizes main components such as a knowledge base, inference engine, and an intuitive user interface. The system workflow begins with the collection of symptom data, calculating probabilities using Bayes’ Theorem, and ultimately delivering probabilistic diagnoses presented informatively to the user. Testing the system demonstrated satisfactory accuracy in identifying menstrual disorders such as menorrhagia, dysmenorrhea, and premenstrual syndrome (PMS). The results show that applying Bayes’ Theorem enhances system reliability in managing data uncertainty and provides diagnosis recommendations based on probability. This system is expected to serve as an effective tool for healthcare professionals and patients for early diagnosis of menstrual disorders while expanding access to accurate and trustworthy health information. Future development will focus on improving the knowledge base and integrating advanced technologies to maximize its benefits in reproductive health.
Transformasi Pembelajaran Vokasi Pertanian melalui Integrasi IoT dan Computer Vision pada Smart Greenhouse di SMKN 4 Barru: Penelitian Marwan Ramdhany Edy; Muh. Ihsan Zulfikar; Nurfauziah; Putri Nirmala; Nurrahmah Agusnaya
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 2 (2025): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 2 (October 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i2.3765

Abstract

The digital agricultural transformation demands strengthening technological literacy and skills in vocational schools, particularly in the utilization of the Internet of Things (IoT) and Computer Vision to support precision farming practices. This community service program aims to improve the competency of teachers and students of SMKN 4 Barru in integrating IoT-based Smart Greenhouse technology and Computer Vision into agribusiness learning. The activity uses a Participatory Action Research (PAR) approach through the stages of preparation, training, technology implementation, mentoring-evaluation, and sustainability, involving teachers, education staff, and students. Evaluation was conducted through pre-post tests, observation, and participatory reflection. The results showed a significant increase in participants' conceptual understanding and practical skills, including the use of temperature, humidity, and soil pH sensors for IoT-based hydroponic systems, as well as the use of Computer Vision to visually detect plant conditions. Participants also reported increased confidence in operating modern agricultural technology devices and awareness of the importance of digital-based innovation in vocational learning. Key challenges identified include the integration of sensor data into monitoring systems and the development of Computer Vision algorithms, requiring further mentoring and infrastructure strengthening. Overall, this program contributes to increasing digital literacy, readiness for the implementation of precision agriculture, and the development of a creative agro-education ecosystem relevant to the demands of Industry 4.0 in Barru Regency.
Co-Authors Akmar Aqilah Kautsar Alwi, Ana Sulistiana Andi Dio Nurul Awalia Andi Fatir Islam Andika Isma Annajmi Rauf Daffa Fakhir Darwing, Khalil Mubaraq Della Fadhilatunisa Desi Arianti Dewi Fatmarani Surianto Dimas Prayoga Elma Nurjannah Fachry Abda El Rahman Fadhlirrahman Baso Hajar Dewantara Herawati Irwansyah Suwahyu Ismail Ismail M. Gilang Ramadhan M. Miftach Fakhri M. Nurul Fajri Marwan Ramdhany Edy Muh Akhlatul Ihsan Muh Dzaky Baridwan Muh. Ihsan Zulfikar Muhammad Arafah Alif Muhammad Fardan Muhammad Imran Hidajat H Muhammad Ma’ruf Musaytir Husain Nabila Al Buqari Jufri Nur Syafitra Ramadhani Nurfauziah Nurrahmah Agusnaya NURUL AZIZAH Rachmawaty Kadir Rahmawati Ricky Saputra Rina Andriyani Rosidah Ruslan Kadir Shalsa Nabila Syukur, Pramudya Asoka Ummul Khaeri Masna Wahyu Hidayat M Yohana Rara