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Aplikasi Prediksi Produksi Cabai dengan Algoritma C.45 untuk Dinas Pertanian Provinsi Aceh Berbasis Web Afkar, M Kadafi; Wali, Muhammad; Imilda
Jurnal Ilmu Komputer dan Teknologi Informasi Vol. 1 No. 1 (2024): Maret
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jikti.v1i1.732

Abstract

This research develops a chili production prediction application using the C.45 algorithm for the Aceh Province Agriculture Service. Weather data and chili prices from 2022-2023 are used to build a prediction model. After going through the data selection, preprocessing, and transformation stages, the C.45 algorithm model was successfully built and tested with new data. The results show a prediction accuracy of 84.03%. Furthermore, this model is implemented in the form of a web application which includes various features such as public pages, calculation of prediction results, graphs, and admin pages. Research shows that the use of the C.45 algorithm and this application has the potential to support agricultural decision making and planning in Aceh. Suggestions for further research include adding additional variables such as soil quality and socio-economic factors, as well as exploring remote sensing technology and other machine learning methods to increase prediction accuracy. Evaluation of the impact of using the application is also recommended to measure its effectiveness in supporting sustainable agriculture in Aceh
Designing a Solar-Powered IoT-Based Flood Early Warning System Prototype with Audio-Visual Alarm for Aceh Region Wali, Muhammad; Iqbal, Taufiq; Salam, Abdus; Syafrinal, Syafrinal
Design Journal Vol. 4 No. 1 (2026): January
Publisher : Yayasan Pendidikan Mitra Mandiri Aceh (YPMMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58477/dj.v4i1.386

Abstract

Floods have repeatedly threatened the people of Aceh Province. Thousands of families lost their property and lives because the early warning information was delayed. This research designs a flood early warning system prototype based on IoT using renewable energy, which can operate on its own without PLN electricity. The system uses three IP68 float switch sensors to detect water levels at thresholds of 0.5m (normal), 1.0m (alert), and 1.5m (danger) combined with a 2-in-1 audio-visual alarm (strobe and siren) with a coverage distance of 100-150 meters. The energy design uses a solar panel of 50-100W with 12V DC voltage and has a minimum backup for 48 hours without sunlight. Hardware design, sensor accuracy testing, validation of the energy system, and testing the effectiveness of alarms are the research methods in this study which is conducted in Banda Aceh City. The results indicate that this system can run independently at low power consumption because float switch sensors are more effective than ultrasonic sensors under conditions where the water is turbid and full of debris as found in rivers in Aceh Province. This prototype is low-cost (less than Rp 2 million), requires minimal maintenance, and has high reliability; therefore, it can be adopted by communities that do not have many resources. This research provides a technical blueprint for developing an early warning system that fits geographically and climatically with Aceh Province which may be replicated in other flood-prone districts for disaster risk reduction programs.