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All Journal Jurnal Informatika dan Teknik Elektro Terapan Journal of Applied Data Sciences
Alhamda, Denisa Septalian
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Optimizing The XGBoost Model with Grid Search Hyperparameter Tuning for Maximum Temperature Forecasting Sugiarto, Sugiarto; Mas Diyasa, I Gede Susrama; Alhamda, Denisa Septalian; Aryananda, Rangga Laksana; Fatmah Sari, Allan Ruhui; Sukri, Hanifudin; Dewi, Deshinta Arrowa
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.885

Abstract

This study presents a novel comparative approach to maximum temperature forecasting in Surabaya, Indonesia, by integrating Extreme Gradient Boosting (XGBoost) with Grid Search Hyperparameter Tuning and benchmarking it against Autoregressive Integrated Moving Average (ARIMA) and Neural Prophet models. The main idea is to evaluate the capability of XGBoost in capturing nonlinear patterns in environmental time series data, which traditional models often fail to address. Using 15,388 historical daily maximum temperature records from the BMKG Juanda weather station spanning 1981–2022, the objective is to identify the most accurate predictive model for short- and medium-term forecasts. The modeling process involved four stages: data acquisition, preprocessing, training, and evaluation, with performance assessed using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The findings show that, after hyperparameter tuning, XGBoost achieved the best performance with MAE = 0.32 and RMSE = 0.65, outperforming ARIMA (MAE = 0.85, RMSE = 1.20) and Neural Prophet (MAE = 0.70, RMSE = 0.98). Prediction results for 2025 indicate peak maximum temperatures in January, October, and November, aligning with recent climate patterns. The contribution of this research lies in demonstrating the superiority of a tuned XGBoost model for complex environmental datasets, offering a practical tool for urban climate planning, agricultural scheduling, and heatwave risk mitigation. The novelty of this work is the systematic integration of Grid Search-based optimization with XGBoost for meteorological forecasting in a tropical urban context, producing higher accuracy than both classical statistical and modern hybrid time series methods. These results highlight the model’s adaptability and potential for broader climate-related applications, with future research recommended to incorporate additional meteorological variables such as humidity and wind speed for even greater predictive capability.
ANALISIS MANAJEMEN RISIKO KEAMANAN INFORMASI SISTEM LAYANAN UPA-PKK UPN “VETERAN” JAWA TIMUR MENGGUNAKAN METODE NIST SP800-30 Suryantari, Putu Anggi; Aryananda, Rangga Laksana; Alhamda, Denisa Septalian; Sari, Anggraini Puspita; Prasetya, Dwi Arman
Jurnal Informatika dan Teknik Elektro Terapan Vol. 14 No. 1 (2026)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v14i1.8779

Abstract

Keamanan informasi merupakan aspek penting dalam penerapan sistem layanan berbasis teknologi informasi di lingkungan perguruan tinggi. Sistem layanan UPA PKK UPN Veteran Jawa Timur berperan dalam mendukung kegiatan pengembangan karier dan kewirausahaan mahasiswa serta alumni sehingga memerlukan pengelolaan risiko keamanan informasi yang terstruktur. Penelitian ini bertujuan untuk menganalisis risiko keamanan informasi menggunakan metode NIST SP 800-30. Tahapan penelitian meliputi identifikasi ancaman, identifikasi kerentanan, analisis pengendalian, penilaian tingkat kemungkinan dan dampak, serta penentuan tingkat risiko. Hasil penelitian menunjukkan bahwa risiko keamanan informasi pada sistem layanan UPA PKK berada pada kategori rendah, sedang, hingga tinggi, dengan risiko dominan berada pada tingkat sedang hingga tinggi, terutama pada aspek keamanan akses sistem dan pengelolaan data. Rekomendasi pengendalian difokuskan pada penguatan mekanisme autentikasi, pembaruan sistem secara berkala, serta peningkatan prosedur keamanan. Metode NIST SP 800-30 terbukti memberikan pendekatan yang sistematis dalam pengelolaan risiko keamanan informasi pada sistem layanan UPA PKK.
Co-Authors Anggraini Puspita Sari Aryananda, Rangga Laksana Dewi, Deshinta Arrowa Dwi Arman Prasetya Fatmah Sari, Allan Ruhui Mas Diyasa, I Gede Susrama Sugiarto S Sukri, Hanifudin Suryantari, Putu Anggi