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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 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 Artificial Intelligence in Lifelong and Life-Course Education
Putri Nirmala
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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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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.
Artificial Intelligence Use and Emotional Well-Being in Higher Education: A Life-Course Perspective on Technology Acceptance and Trust Nailha Dinda Aprilia; Kartika Ratna Sari; Putri Nirmala; Rosidah; Shera Afidatunisa
Artificial Intelligence in Lifelong and Life-Course Education Vol 1 No 1 (2026): Artificial Intelligence in Lifelong and Life-Course Education
Publisher : PT. Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/aillce.v1i1.5

Abstract

Purpose – The growing integration of artificial intelligence (AI) in higher education has reshaped students’ cognitive and emotional learning experiences. From a life-course education perspective, higher education represents a critical phase of early adulthood in which interactions with AI may influence emotional regulation and readiness for lifelong learning. However, empirical studies examining the affective consequences of AI use through technology acceptance and trust mechanisms remain limited. This study investigates how AI usage frequency, perceived usefulness, perceived ease of use, and trust in AI influence university students’ emotional well-being.Design/methods/approach – A quantitative cross-sectional survey was administered to university students who actively used AI to support their learning activities. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the direct effects of technology acceptance factors and trust in AI on emotional well-being.Findings – The results indicate that AI usage frequency and trust in AI have significant positive effects on students’ emotional well-being. In contrast, perceived usefulness and perceived ease of use do not directly influence emotional well-being. These findings suggest that affective benefits of AI-supported learning are shaped more by familiarity and psychological trust than by technical efficiency alone.Research implications/limitations – The cross-sectional design, reliance on self-reported measures, and single-institution sample limit causal interpretation and generalizability. Future studies are encouraged to adopt longitudinal or mixed-method approaches to capture emotional dynamics across educational stages.Originality/value – This study extends the Technology Acceptance Model by positioning emotional well-being as a key outcome within a life-course framework, offering insights into how AI interaction during early adulthood may support psychological sustainability and lifelong learning readiness
Co-Authors Ahmad Syarif Hidayatullah Akhmad Affandi 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 Mustamin Nabila Al Buqari Jufri Nailha Dinda Aprilia Nur Syafitra Ramadhani Nurfauziah Nurrahmah Agusnaya NURUL AZIZAH Rachmawaty Kadir Rahmawati Ratna Kartika Sari Ricky Saputra Rina Andriyani Rosidah Ruslan Kadir Shalsa Nabila Shera Afidatunisa Syukur, Pramudya Asoka Ummul Khaeri Masna Wahyu Hidayat M Yohana Rara