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All Journal Jurnal Pengabdian Kepada Masyarakat Advance Sustainable Science, Engineering and Technology (ASSET)
Rahmat Hidayat
Universitas Negeri Semarang
Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Nursing Public Health Social Sciences Veterinary Other

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Peningkatan Prediksi Kelainan Tekanan Darah dengan Logistic Regression dan Random Forest: Pendekatan Sequence Machine Learning Florentina Yuni Arini; Rahmat Hidayat; Arzaki Zunior Putra; Muhammad Nur Furqon; Muhammad Zuniar Hilmi
PaKMas: Jurnal Pengabdian Kepada Masyarakat Vol 6 No 1 (2026): Mei 2026
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/pakmas.v6i1.4497

Abstract

Early detection of blood pressure abnormalities plays a critical role in preventing and managing cardiovascular diseases, which remain the leading cause of death globally. This study proposes a sequence machine learning approach that combines Random Forest (RF) and Logistic Regression (LR) to enhance the accuracy of abnormal blood pressure prediction. The dataset, obtained from Kaggle, includes various clinical and lifestyle-related features. Data preprocessing involved handling missing values, label encoding, and normalization of numerical features. Evaluation of individual models showed that Random Forest achieved an accuracy of 0.83, while Logistic Regression reached 0.75. The sequence model, which incorporates Random Forest-generated prediction probabilities as an additional feature in Logistic Regression, improved the prediction performance with an accuracy of 0.84. Feature importance analysis identified hemoglobin level, chronic kidney disease, and genetic pedigree coefficient as the most influential predictors in classifying abnormal blood pressure. These findings highlight the effectiveness of the sequence approach in addressing the complexity of medical data and improving the precision of clinical decision support systems for hypertension diagnosis and management. Recommendations include developing advanced ensemble models, collecting longitudinal data, and conducting external validation to enhance model generalizability across diverse clinical populations.
Sustainable Utilization of Jute Sack Waste in Jute/Epoxy Laminate: Effect of Fiber Orientation for Bumper Applications Heri Yudiono; Hadromi; Deni Fajar Fitriyana; Januar Parlaungan Siregar; Tezara Cionita; Much Rizky Ubaidillah; Ayyub Ridananda; Rahmat Hidayat
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.3086

Abstract

Fiber orientation plays a major role in controlling the mechanical properties of natural fiber bio composites. An investigation into the impact of fiber direction variations on the toughness and tensile strength of burlap waste composites for automobile bumpers was carried out. This research was designed as a controlled experimental investigation. The factors evaluated were fiber orientation, while the tensile strength and impact toughness were. Bio composites were manufactured utilizing the hand lay-up procedure, and mechanical testing included tensile (ASTM D638) and impact (ASTM 4812). The number of test replications was fixed at three specimens for each variable. By improving interfacial adhesion, the 0°/+90°/0°/+90°/0° fiber orientation produces a tensile strength of 21.087 N/mm² and an impact toughness of 0.0482 J/mm², which is higher than a car bumper. These research show proof that burlap sack waste-based composites can be used as an alternative material for environmentally acceptable and sustainable bumpers. These findings complement SDG 12, which focuses on responsible production and consumption.
Co-Authors Arzaki Zunior Putra Ayyub Ridananda Fitriyana, Deni Fajar Florentina Yuni Arini Hadromi Heri Yudiono Januar Parlaungan Siregar Much Rizky Ubaidillah Muhammad Nur Furqon Muhammad Zuniar Hilmi Tezara Cionita