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All Journal JURIKOM (Jurnal Riset Komputer) TIN: TERAPAN INFORMATIKA NUSANTARA
Marta Ardiyanto
Universitas Duta Bangsa Surakarta, Surakarta
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Pengembangan Sistem Informasi Penanganan Feedback Client Berbasis Web Menggunakan Metode Waterfall Caesar Yoga Pratama; Marta Ardiyanto; Mira Erlinawati
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10104

Abstract

Client feedback management at BIIS Corp still relies on WhatsApp group communication and manual spreadsheet recording, resulting in difficulties in monitoring work progress, inadequate documentation of handling history, and poor coordination between staff and programmers. This study aims to design and develop a web-based client feedback information system to support centralized and structured feedback management. Problem identification was conducted using the PIECES framework, which revealed weaknesses across all six aspects. The system was developed using the Waterfall model within the SDLC framework, with UML-based modeling and functional testing through the Blackbox Testing method. Built using PHP, MySQL, HTML, CSS, and JavaScript, the system accommodates three user roles, namely administrator, staff, and programmer, and is equipped with features including feedback recording, programmer assignment, status updates, completion confirmation, reopen feedback mechanism, real-time notifications, activity log, and performance reporting. Testing across 15 scenarios achieved a 100% success rate. The contribution of this research is the development of a system specifically designed for a software house environment, integrating three user roles into a centralized workflow equipped with a reopen feedback mechanism, real-time notifications, and an activity log to support more effective feedback monitoring and documentation.
Perbandingan Kinerja Model Forecasting Nilai Perdagangan Komoditas HS pada Evaluasi Time-Based Ridwan Dwi Irawan; Marta Ardiyanto; Ringgo Ismoyo Buwono; Faulinda Ely Nastiti
JURIKOM (Jurnal Riset Komputer) Vol. 13 No. 3 (2026): Juni 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i3.9843

Abstract

Global economic uncertainty, trade-regime shifts, and supply-chain disruptions have made export-import trade-value forecasting increasingly complex. This study compares the performance of Random Forest, Extra Trees Regression, and SARIMA in predicting monthly trade values of HS commodities in the apparel and footwear sector, covering HS 61, HS 62, HS 63, and HS 64. The dataset was obtained from Indonesia?s Central Bureau of Statistics (BPS) and organized as a monthly time series using a leakage-safe workflow through a time-based train-validation-test split. The modeling stage employed 19 predictive features consisting of historical, local statistical, calendar-seasonal, and exogenous variables, and each model was tuned on the validation set before being evaluated on the holdout test. Performance was assessed using MAE, RMSE, MAPE, sMAPE, and wMAPE, with MAPE as the primary ranking metric. The main contribution of this study lies in providing a fair and replicable comparison of three forecasting models under a time-based evaluation protocol for HS commodity trade data, making the model selection results more representative of real implementation settings. The results show that Random Forest achieved the best MAPE at 22.7746%, slightly outperforming Extra Trees Regression at 22.9469%, while SARIMA recorded 28.9794%. These findings indicate that tree-based ensemble models are more adaptive to volatile trade data, whereas SARIMA remains relevant as a statistical baseline for structured seasonal patterns.
Co-Authors Caesar Yoga Pratama Faulinda Ely Nastiti Mira Erlinawati Ridwan Dwi Irawan Ringgo Ismoyo Buwono