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All Journal Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Jurnal Ilmu Komputer dan Sistem Informasi
Muhammad Wahyu Hidayat
Universitas Harapan Medan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Library & Information Science

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Sistem Pendukung Keputusan Penerimaan Mahasiswa Baru Universitas Harapan Dengan Menggunakan Metode PSI Rafi Jariansyah; Muhammad Wahyu Hidayat; Wahyu Cavin Gunawan; Yessi Fitri Annisah Lubis; David David
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 4 No. 1 (2025): Januari 2025
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v4i1.169

Abstract

The new student selection process is very important to ensure the quality of prospective students accepted into universities. Harapan University considers various factors, such as high school majors (science, social sciences, or TKJ), academic test results, interviews, diplomas, and academic and extracurricular achievements. The manual approach that is still often used tends to be time-consuming, inefficient, and prone to errors. This study aims to develop a decision support system based on the Preference Selection Index (PSI) method to improve the effectiveness and efficiency of the selection process. The PSI method was chosen because of its ability to evaluate criteria directly without requiring weighting. The results of the study show that the PSI approach is able to produce the best candidate rankings based on predetermined criteria. This system offers a more organized, transparent, and accurate solution in the new student selection process.
PERANCANGAN SISTEM PREDIKSI VOLUME EKSPOR PISANG , KOPI DAN KELAPA SUMATERA UTARA KE MALAYSIA MENGGUNAKAN METODE ARIMA BERBASIS WEB Muhammad Wahyu Hidayat; Siti Sundari
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.870

Abstract

The adoption of information technology in predictive systems is increasingly popular in the agricultural export sector, leveraging historical data analysis to forecast global market fluctuations and optimize supply chains for commodities such as bananas, coffee, and coconuts. Exporters in North Sumatra face challenges related to fluctuating export volumes to Malaysia, influenced by seasonal factors, international price changes, weather dependency, and a lack of accurate data. This results in supply imbalances, economic losses, and difficulties in strategic planning. This research offers a solution by employing the Autoregressive Integrated Moving Average (ARIMA) method in the development of a web-based system to address these issues. ARIMA is a statistical time series model that combines autoregressive (AR) components for dependencies on previous values, integrated (I) components to handle non-stationarity through differencing, and moving average (MA) components to predict the influence of past errors; its seasonal variant (SARIMA) is applied to capture monthly harvest cycle patterns. The developed solution involves processing historical export data from 2019–2024 sourced from the Central Bureau of Statistics (BPS) via a Python Flask API with an automated ARIMA approach, integrated into a PHP CodeIgniter 4 web platform, providing interactive visualizations, real-time data updates, and easy user access. The expected outcomes from this system are more accurate export volume predictions, with a MAPE of approximately 19.02% and MAE of 180,755.28 tons on 2024 test data for bananas as a representative sample, which can support strategic decision-making, production efficiency, and enhanced competitiveness for banana, coffee, and coconut exports from North Sumatra to Malaysia.
Co-Authors David David Rafi Jariansyah Siti Sundari Wahyu Cavin Gunawan Yessi Fitri Annisah Lubis