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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Dedikasi: Jurnal Pengabdian Kepada Masyarakat
Heru Noviyanto Firmansyah
Universitas Muria Kudus
Religion Humanities Computer Science & IT Economics, Econometrics & Finance Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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PELATIHAN PENERAPAN SISTEM E-ARSIP SURAT UNTUK MENINGKATKAN EFISIENSI PENGELOLAAN SURAT DI DPMPTSP KUDUS Heru Noviyanto Firmansyah; Syafiul Muzid
Bestari: Jurnal Pengabdian Kepada Masyarakat Vol 5 No 2 (2025)
Publisher : Sekolah Tinggi Keguruan dan Ilmu Pendidikan (STKIP) Melawi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46368/dpkm.v5i2.3930

Abstract

The manual letter management in DPMPTSP Kudus makes the administrative process time-consuming, prone to errors, and archiving is not easy to search. There needs to be an improvement to increase efficiency in correspondence management. One of the solutions that can be applied is an e-archiving system that is able to reduce the use of paper, offer convenience in searching data, and speed up the archiving process. The method used in this service is training in the use of the e-archive system to DPMPTSP Kudus staff, including the use of the digital archiving system and procedures. The results of the service show that the utilization of this system can make the management of archives more efficient, reduce errors in archiving, and make mail data more retrievable. The utilization of the e-archive system is expected to be a gateway to digital transformation in government institutions.
Explainable XGBoost Early-Warning Framework for Academic Stress-Based Student Mental Health Risk Mapping Supriyono; Heru Noviyanto Firmansyah; Soni Adiyono
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 4 (2026): August 2026 (in progress)
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i4.7812

Abstract

Existing university mental health monitoring often depends on voluntary help-seeking or manual questionnaire interpretation, which may delay early support for students experiencing academic stress. This study proposes an explainable XGBoost-based early-warning framework for non-clinical mapping of student mental health risk from academic stress indicators. The single-site dataset comprised 1,002 anonymized student records from Universitas Muria Kudus. K-Means clustering was used to transform DASS-21 depression, anxiety, and stress scores into low, moderate-, and high-risk categories, while XGBoost predicted the cluster-derived labels using seven single-item academic stress indicators and engineered aggregate and interaction features. On a stratified hold-out testing set of 201 records, the model achieved weighted precision, recall, and F1-score values of 0.8907, 0.8905, and 0.8906, respectively, with class-level F1-scores of 0.9109 for low risk, 0.8900 for moderate risk, and 0.8713 for high risk. Additional ablation, clustering sensitivity, subgroup, threshold, and SHAP stability analyses were conducted to strengthen robustness and interpretability. The findings show that cumulative academic stress and interaction features involving parental expectations, exam anxiety, and learning-method adaptation were consistently influential predictors. The framework is intended to support early institutional prioritization and counseling referral, not clinical diagnosis. Generalization remains limited by the single-institution sample and the use of single-item academic stress indicators; therefore, local retraining and recalibration are required before institutional deployment, including implementation of the Streamlit prototype.
Co-Authors Soni Adiyono Supriyono Syafiul Muzid