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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar Language and Education Journal Jurnal Ekonomi Syariah Pelita Bangsa Indonesian Journal of Electrical Engineering and Renewable Energy (IJEERE) TRIMAS: Jurnal Inovasi dan Pengabdian Kepada Masyarakat Information Technology Education Journal Abdi Kimia : Jurnal Pengabdian Masyarakat Qomaruna Journal of Excellence Humanities and Religiosity
Alimin
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Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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The Effect of Generative AI as a Coding Assistant in Deep Learning Practicum on Code Quality and Conceptual Understanding Nurhidayah; Alimin; Ohfit Rijei; Owentianus Nouvic; Putra Langlang Buana; Putra Rajawijaya
Information Technology Education Journal Vol. 4, No. 1, February (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v4i1.2502

Abstract

The rapid adoption of Generative AI as a coding assistant in programming education raises critical pedagogical questions regarding its impact on learning quality. This study investigates whether the use of Generative AI in a deep learning practicum enhances students’ code quality and conceptual understanding or merely improves productivity without meaningful comprehension. A quasi-experimental pretest–posttest control group design was employed involving 60 undergraduate students enrolled in a Deep Learning course. The experimental group (n = 30) used Generative AI tools (ChatGPT/GitHub Copilot) during practicum sessions, while the control group (n = 30) relied on conventional resources. Instruments included a validated conceptual understanding test (α = 0.87) and an analytic code quality rubric based on ISO/IEC 25010 standards (κ = 0.82). Data were analyzed using independent samples t-tests and MANOVA at α = 0.05. Results show that the experimental group achieved significantly higher posttest conceptual scores (M = 78.63) than the control group (M = 72.10), t(58) = 3.34, p = 0.001, d = 0.86. Code quality scores were also significantly higher (20.77 vs. 18.12 out of 25), t(58) = 4.57, p < 0.001, d = 1.18. MANOVA confirmed a significant combined effect (Wilks’ Λ = 0.71, p < 0.001). The study was limited to a single institution and a six-week intervention period, which may restrict generalizability and long-term interpretation. This research provides controlled experimental evidence demonstrating that Generative AI can enhance both technical code quality and conceptual mastery in deep learning education, contributing empirical guidance for responsible AI integration in computing curricula
Analisis Konsumsi dan Produksi Energi Kebun Hidroponik Tenaga Surya di Desa Lenek Lombok Timur : Analisis Konsumsi dan Produksi Energi Kebun Hidroponik Tenaga Surya di Desa Lenek Lombok Timur Alimin; Muhammad Nurswal Isnani; Yuliani Hasni; Rizkia Rahmawati; Muji Juherwin
Indonesian Journal of Electrical Engineering and Renewable Energy (IJEERE) Vol 6 No 1 (2026): IJEERE Juni 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/ijeere.v6i1.2456

Abstract

The utilization of solar energy in hydroponic systems offers a potential solution to reduce dependence on conventional electricity and lower operational costs. This study aims to analyze the balance between energy consumption and production in a solar-powered hydroponic farm located in Lenek Daya Village, East Lombok Regency. The system consists of two 80 Wp solar panels, a 4 × 4.2 W water pump, a light sensor, and a 12 V 100 Ah battery for energy storage. The research method includes daily measurement of energy production and consumption over one month, as well as 10-minute interval monitoring for three consecutive days to capture short-term energy dynamics. The results show that daily energy production ranges from 200 to 350 Wh, while energy consumption remains relatively stable between 100 and 200 Wh. The production profile follows a diurnal pattern, with peak power occurring between 11:30 and 14:00. Overall, the solar panels sufficiently meet the system’s energy requirements, even generating a surplus under clear weather conditions. However, weather fluctuations significantly affect daily production, highlighting the important role of energy storage in ensuring continuous operation. This study concludes that the implementation of solar-powered hydroponic systems is feasible and efficient, supporting sustainable agricultural operations in rural areas.
Co-Authors Ainiyah, Maslakhatul Andriadin Auliah, Dwi Rezeki Auliah Auliah, Indah Annisa Bilqis Shofiyah HAPPY KUSUMA WARDANI Hasri Hidayah, Bariqotul Himyar Pasrizal Jefri Mahendra Jusniar Khabibullah, Muttaqin Magfirah Ilyas, Nita Maryono Melinda Puspita Sari Jaya Muammar Iksan Muhamad Idris Muhammad Nurswal Isnani Muji Juherwin Nurhidayah Ohfit Rijei Owentianus Nouvic Putra Langlang Buana Putra Rajawijaya Rizkia Rahmawati Sholahuddin, Gus Malik Imam Suriati Eka Putri Syamsidah Wahyuningsi, Neneng Wahyuningsi Wardani, Happy Kusuma Yuliani Hasni Zubair, Sakinah