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All Journal Teknika ITEj (Information Technology Engineering Journals) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Inotera Jurnal Vokasi JINAV: Journal of Information and Visualization Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology Jurnal Tika jeti Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Brilliance: Research of Artificial Intelligence TECHSI - Jurnal Teknik Informatika DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Dharmawangsa: International Journal of the Social Sciences, Education and Humanitis Jurnal Malikussaleh Mengabdi Gameology and Multimedia Expert Nawadeepa: Jurnal Pengabdian Masyarakat Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Nunsina, Nunsina
Universitas Malikussaleh
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Improving Vegetable Production in North Aceh Regency: An Implementation of a Smart Farming Monitoring System Fitri, Zahratul; Meiyanti, Rini; Nunsina, Nunsina; Fitria, Rahma; Munauwar, Muhammad Muaz
JINAV: Journal of Information and Visualization Vol. 6 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav4322

Abstract

This research aims to design and implement a smart farming monitoring system that is appropriate for the local conditions of North Aceh to optimize the production of leading vegetables and facilitate sustainable agricultural transformation. In line with the national agenda toward the digitalization of the agricultural sector, this research is part of a concrete effort to encourage the adoption of smart farming technology at the local level. North Aceh Regency has great horticultural potential, but it is not yet optimal due to the minimal application of technology. This research supports the development of agriculture based on local potential. The study also promotes a participatory and educative approach to increase farmers' digital literacy and reduce the technology gap between conventional and modern technology-adopting farmers. The Smart Farming monitoring system was successfully implemented using soil moisture, air temperature, soil pH, and light intensity sensors integrated into a web-based dashboard and mobile application. The implementation of this system was able to increase vegetable productivity by 18–22%, especially for mustard greens, chili, and tomatoes, compared to conventional methods. The system also contributed to the efficient use of resources, shown by a 25% savings in irrigation water and a 15% reduction in the use of chemical fertilizers. The farmer response was quite positive, although there are still challenges related to digital literacy among some older farmers. Overall, the implementation of Smart Farming in North Aceh Regency had a real impact on increasing productivity and cost efficiency while supporting sustainable agriculture in line with the SDGs.
Food Security Optimization Forecasting Fertilizer Production With Method Weighted Moving Average (WMA) Rifkial Iqwal; Dahlan Abdullah; Nunsina
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

This research focuses on optimizing food security through the application of fertilizer production forecasting method at PT Pupuk Iskandar Muda (PIM) using Weighted Moving Average (WMA). Effective food security relies heavily on stable and adequate fertilizer availability, which in turn requires accurate production predictions to ensure efficiency. In this study, historical data of urea and ammonia fertilizer production from January 2019 to December 2023 is used to build a forecasting model that can provide an overview of future production trends. The WMA method was chosen due to its adaptive nature, where greater weight is given to the most recent data, allowing the model to be more responsive to changes and emerging trends. The results showed that for urea production, WMA produced a MAPE value of 1773.8% and MAD of 13,223.2, while for ammonia production, the MAPE was recorded at 3085.5% with MAD of 7,538.5. Total production showed a MAPE of 69.7% with a MAD of 20,568.9, indicating significant fluctuations in production during the period under study. Nevertheless, the WMA method still provides a fairly good prediction and can be used as a reference in future production planning. In addition, the results of this study also provide valuable insights into the production dynamics at PIM, which is critical in supporting the national food security strategy. This research recommends further exploration of other more advanced forecasting methods, such as ARIMA or machine learning techniques, to improve prediction accuracy and better anticipate changes in production patterns. Keywords: Food security, Weighted Moving Average, Fertilizer Production Forecasting, MAPE, MAD.
Co-Authors Ade Nahya Zahara Akbar, Andry Maulana Ananda Faridhatul Ulva Annisa Fitria Ariyandi, Zulham Cut Fadhilah Cut Fadhilah Dahlan Abdullah Eva Darnila Eva Darnila Fadhilah, Cut Fadhlilah, Cut Fatimah Zuhra Fatimah Zuhra Fuadi, Wahyu Hasibuan, Fadilah Suryani Ichsan Kulbahri, Kulbahri Mahara, Sabda Maysura Muhammad Muaz Munauwar Munawwar Khalil, Munawwar Mustaqim Mutasar Nazimah Nazimah Nilahayati Nurdin Nurdin Putri Raihatul Jannah Rahma Fitria, Rahma Rahmad Rahmad Razi, Ar Rifkial Iqwal Rini Meiyanti Rosma Siregar Safrizal Safrizal Taufiq Taufiq Viki, Zakial Wahyu Fuadi Yanti, Epa Zahidi Pratama Zahratul Fitri Zahratul Fitri, Zahratul Zakial Viki Zara Yunizar Zuliani Zuliani