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All Journal Jurnal Ilmu Teknologi Informasi Indonesia (JITIFNA)
Anuarman Hura
Universitas Nias
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering

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Penerapan Machine Learning Untuk Prediksi Produktivitas Pertanian Berbasis Data Cuaca Di Indonesia Anuarman Hura
Jurnal Ilmu Teknologi Informasi Indonesia Vol. 2 No. 1 (2026): JITIFNA - Januari
Publisher : CV. SINAR HOWUHOWU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70134/jitifna.v2i1.1018

Abstract

The agricultural sector plays a vital role in ensuring food security and economic sustainability in Indonesia. However, agricultural productivity is highly vulnerable to weather fluctuations and climate change, which significantly affect crop yields. This study aims to develop a machine learning-based predictive model for estimating agricultural productivity using meteorological data such as rainfall, temperature, humidity, and solar radiation. Historical data from 2013 to 2023 were collected from the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG) and the Central Bureau of Statistics (BPS). Three machine learning algorithms—Random Forest (RF), Artificial Neural Network (ANN), and Support Vector Regression (SVR)—were implemented and compared using Python. Model performance was evaluated through Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²). The results show that the Random Forest model achieved the best performance, with R² = 0.912, MAE = 0.318, and RMSE = 0.445, indicating a strong predictive capability. Rainfall and temperature were identified as the most influential variables, contributing over 60% of yield variation. The findings suggest that machine learning can effectively support data-driven decision-making in Indonesia’s agricultural sector, enabling more accurate crop planning and climate adaptation strategies to enhance national food resilience.
Perancangan Dan Implementasi Sistem Informasi Layanan Surat Keterangan Aktif Kuliah Berbasis Web Di Fakultas Sains Dan Teknologi Universitas Nias Anuarman Hura; Damanotona Harefa; Hadirat Syukur Ziliwu; Jurisman Waruwu
Jurnal Ilmu Teknologi Informasi Indonesia Vol. 2 No. 2 (2026): JITIFNA - Juli
Publisher : CV. SINAR HOWUHOWU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70134/jitifna.v2i2.1553

Abstract

The process of applying for a Certificate of Active Student Status at the Faculty of Science and Technology, Nias University, is still conducted manually, causing inefficiencies in academic services. This study aims to design and implement a Web-Based Information System for Active Student Status Certificate Services to facilitate online application and document management processes. This research employed the Research and Development (R&D) method with the Waterfall model. Data were collected through observation, interviews, documentation, and literature studies. The system was developed using PHP, MySQL, and Bootstrap, and tested using Black Box Testing and the System Usability Scale (SUS). The results show that the system can facilitate online applications, document uploads, verification, approval, status monitoring, and digital archiving. Functional testing indicated that all features operated properly, while usability testing showed good user acceptance. In conclusion, the developed system improves the effectiveness and efficiency of academic administrative services and supports the digitalization of academic services at the Faculty of Science and Technology, Nias University.
Co-Authors Damanotona Harefa Hadirat Syukur Ziliwu Jurisman Waruwu