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Syahroni Hidayat
Universitas Negeri Semarang
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Ensemble Learning Approaches for Air Pollution Classification and Environmental Health Risk Assessment Budi Sunarko; Syahroni Hidayat; Uswatun Hasanah
JURNAL KESEHATAN LINGKUNGAN Vol. 18 No. 2 (2026): JURNAL KESEHATAN LINGKUNGAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jkl.v18i2.2026.159-170

Abstract

Introduction: Conventional statistical models often struggle to represent complex interactions among multiple air pollutants and their non-linear associations with health outcomes. To address this limitation, this study evaluates the effectiveness of ensemble learning approaches for classifying air pollution exposure levels and predicting associated health risks across heterogeneous pollutant contexts. Methods: Two publicly accessible datasets were analyzed. The first dataset comprises toxic gas exposure measurements (CH₄, CO₂, and CO) annotated with short-term physiological health effect categories, reflecting acute exposure scenarios. The second dataset is the Jakarta Air Quality dataset (2021), which includes AQI-based criteria pollutants (PM10, PM2.5, SO₂, CO, O₃, and NO₂) representing urban ambient air quality conditions. Multiple base classifiers Decision Trees, Random Forests, Naïve Bayes, k-Nearest Neighbor, Logistic Regression, Support Vector Machines, AdaBoost, and Multi-Layer Perceptrons were implemented. Data preprocessing involved cleaning, normalization, and a 70:30 training-testing split. Ensemble strategies, particularly stacking, were developed to integrate complementary classifier strengths and improve predictive reliability. Results and Discussion: The stacking ensemble consistently outperformed individual base classifiers, achieving classification accuracies of 0.9993 for the toxic gas exposure dataset and 0.9816 for the Jakarta AQI dataset. These results indicate that ensemble learning enhances robustness, mitigates misclassification risks, and adapts effectively to variations in pollutant concentration patterns across different exposure contexts. Conclusion: Ensemble learning demonstrates strong potential as a reliable computational approach for environmental health risk assessment. Its high predictive performance supports its application in air quality management, early warning systems, and evidence-based policy development aimed at mitigating health risks associated with air pollution.
THE EFFECTIVENESS OF VIRTUAL REALITY IN VOCATIONAL EDUCATION FOR FASHION DESIGN AND PRODUCTION Irmayanti, Irmayanti; Hidayat, Syahroni; Budisantoso, Heri Tri Luqman; Khoiron, Ahmad Mustamil; Achmadi, Taofan Ali
JURNAL EDUSCIENCE Vol 13, No 2 (2026): Jurnal Eduscience (JES), (Authors from Malaysia and Indonesia)
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jes.v13i2.8267

Abstract

Purpose – The fashion industry must master the practical skills needed today to employ immersive technology like VR in Vocational Education and Training. Due to the cost and hazard of hands-on instruction, Indonesian vocational high schools have a skill gap. In order to deal with this problem, this study talks about the real-life outcomes of "Fashion Tech Edu-VR," an immersive learning tool that fits perfectly with the Indonesian national curriculum.Methodology – This study employs a quasi-experimental research approach with a pre-test and post-test Control Group Design. The research subjects consist of 90 grade XI (Phase F) students from the Fashion Design and Production expertise program at a Vocational High School (SMK) in Semarang City. The data collection techniques used were threefold: tests, observation, and questionnaires. To test the hypotheses in this study, a t-test (paired sample t-test) was utilized with the assistance of IBM SPSS Statistics 26, comparing the post-test scores between the control group and the experimental group.Findings – The findings show a statistically significant difference in learning outcomes between the control and experimental classes (t = -27.935). Student engagement in the control group was 3.31, compared to 4.62 in the experimental class after the Fashion Tech Edu-VR intervention. This study found that students who used 'Fashion Tech Edu-VR' achieved significantly higher learning gains compared to the control group. The platform also received excellent usability ratings and fostered much higher levels of student engagement, confirming its effectiveness as an educational tool.Contribution – The study concludes that "Fashion Tech Edu-VR" is a useful educational tool that solves real-world training problems and is a very effective teaching example
Co-Authors Abdulloh Abdulloh Abdurahim, Abdurahim Achmadi, Taofan Ali Adam Bachtiar Maulachela Agung Budiwirawan Agus Ardiyanto Ahmad Zuli Amrullah Ahmat Adil Akbar Juliansyah Amrullah Anan Nugroho Ananda, Briska Putra Andi Sofyan Anas Ansar Ansar Ardiansyah, Muhammad Irfan Astri Iga Siska Baroroh, Luluk Taufiqul Budi Sunarko Budiarto, Jian Budisantoso, Heri Tri Luqman Danang Tejo Kumoro Danang Tejo Kumoro Dian Syafitri Chani Saputri Diyanasari, Ledi Esa Apriaskar Feddy Setio Pribadi Fikri, Akmal Habib Ratu Perwira Negara Haikal Abror Hakiki, Muhammad Khikam Hanif Ardhiansyah Hanif Hidayat Hanifah Ayu Ida Ayu Widhiantari Ince Siti Wardatullatifah S Intan Ermawati Irmayanti Irmayanti, Irmayanti Ismarmiaty Ismarmiaty, Ismarmiaty Joko Sumarsono Khoiron, Ahmad Mustamil Khoirudin Fathoni, Khoirudin Kumoro, Danang Tejo Mirriyadhil Jannah Mona Subagja Muhammad Fathurrahman Muhammad Hilmy Herdiansyah Muhammad Muhammad MUHAMMAD TAJUDDIN Muhammad, Naufal Murad Murad Murad, Murad Ni Luh Putu Merawati Nugroho, Anan Nur Iksan Qudsi, Jihadil R Fanny Priniti Raden Fanny Printi Ardi Rahmat Sabani Rezky Ramdhaningsih Ria Rismayati Rian Febriyanto Rina Rachmawati Risanuri Hidayat Rismayati, Ria Rizal, Ahmad Ashril Salim, Nur Azis Sandi Justitia Putra Satria, Rifki Lukman Simanjuntak, Jhonatur Stheven Subagja, Mona Sukmawaty Sukmawaty Sukmawaty Sukmawaty Sulistyawan, Vera Noviana Tajuddin, Muhammad Taofan Ali Achmadi Teguh Bharata Adji Uswatun Hasanah Uswatun Hasanah USWATUN HASANAH Wafi, Ahmad Zein Al Wahyudi, Tri Agus Yusuf, Siti Agrippina Alodia Zaenal Abidin Zaurarista Dyarbirru Zidan Vieri Wijaya