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All Journal Jurnal Kependidikan: Penelitian Inovasi Pembelajaran Jurnal Sains Dasar Techno.Com: Jurnal Teknologi Informasi Jurnal Pendidikan Fisika Indonesia Jurnal Pendidikan IPA Indonesia Indonesian Journal of Mathematics and Natural Sciences JURNAL FISIKA Sainteknol : Jurnal Sains dan Teknologi Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Informatika dan Teknik Elektro Terapan Historika Jukung (Jurnal Teknik Lingkungan) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Pendidikan Matematika (JUDIKA EDUCATION) KOMPUTIKA - Jurnal Sistem Komputer ASEAN Journal on Science and Technology for Development Indonesian Physical Review Integrated Lab Journal Jurnal INFOTEL JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Varia Humanika
Sunarno
Universitas Negeri Semarang, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Mathematics Physics Social Sciences

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An IoT-based wireless monitoring system for the measurement of SO2 and NO2 concentrations emitted from a point source Sunarno - Sunarno; Purwanto - Purwanto; Edy - Wibowo
JURNAL INFOTEL Vol 17 No 4 (2025): November
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i4.1340

Abstract

Air pollution monitoring and assessment is a challenging problem from local to global scales with consequences on human health and other resources. Furthermore, monitoring of air pollution is often difficult to attain due to the high cost of research especially using the conventional bulky monitoring samplers. Therefore, the purpose of this study is to develop a cheap, portable, and efficient NO2 and SO2 pollution monitoring system using IoT technology. The experimentation consists of two major stages vis-a-vis system design and field implementation. The system design is mainly the use of SO2, NO2, and meteorology sensors attached to a microprocessor which transfers processed data to the cloud repository. The monitoring system developed in this study showed good stability, but the quality of the communication network was in the unsatisfactory category hence its baud rate could be improved in the future. This system was successfully deployed to measure the concentration of SO2 and NO2 emitted from combustions of sawdust, coal powder in an incinerator. In addition, NO2 from the exhaust of a 96 kWh-1 diesel-powered electric generator engine was also monitored. The results showed high variations in SO2 concentrations were obtained during combustion of sawdust and coal powder, though with only 25 % violation of the national reference-quality standard even with different weights. For the exhaust gas of the generator set engine, the average concentration of NO2 detected was 6.68 ppm which was lower than the QSA (Quality Standard of Ambient air) value of 79.9 ppm. Further works are needed to demonstrate the use of this technology in monitoring SO2 and NO2 emitted from other sources such as industrial, vehicular, solid waste combustions, and biogenic emissions
Prediksi Suhu Udara dengan Algoritma Artificial Neural Network di Jawa Timur Karnisih, Karnisih; Sunarno, Sunarno; Iqbal
Jurnal Pendidikan Matematika : Judika Education Vol. 9 No. 1 (2026): Jurnal Pendidikan Matematika: Judika Education
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/s5kx4a49

Abstract

This study aims to systematically optimize the hyperparameters of an Artificial Neural Network (ANN) using an algorithm-based approach to obtain the best configuration, as well as to compare the air temperature prediction accuracy of ANN with other machine learning algorithms. Feature selection was performed using a physical approach to identify variables that significantly influence air temperature, while ANN hyperparameter optimization was conducted using the Random Search method. The ANN model was compared with Linear Regression (LR), Random Forest (RF), and Support Vector Regression (SVR) in predicting air temperature. Model performance was evaluated using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R²). The results indicate that the ANN model generally achieved lower MSE, RMSE, MAE, and MAPE values and higher R² values compared to the other methods across four study locations: Banyuwangi, Juanda, Sangkapura, and Pasuruan. These findings demonstrate that ANN with properly optimized hyperparameters can provide more accurate air temperature predictions..   Keywords: Artificial Neural Network, East Java, Machine Learning, Air Temperature
EVALUASI PAPARAN KEBISINGAN LALU LINTAS TERHADAP KUALITAS LINGKUNGAN AKUSTIK RUANG AKADEMIK (STUDI KASUS: KEBISINGAN RUANG KULIAH FMIPA UNIVERSITAS NEGERI SEMARANG) Sunarno Sunarno; Masturi Masturi; Suharto Linuwih; Dicko Alyandri Samudra; Musa Abdul Halim
Jukung (Jurnal Teknik Lingkungan) Vol 12, No 1 (2026)
Publisher : Program Studi Teknik Lingkungan Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jukung.v12i1.25790

Abstract

Suasana belajar di beberapa ruang perkuliahan FMIPA UNNES yang dekat dengan jalan raya terasa tidak nyaman dan bising karena kegiatan lalu lintas yang padat. Sementara itu, data tentang tingkat kebisingan yang terjadi di lingkungan ruang perkuliahan FMIPA tidak tersedia, sehingga perlu dilakukan pengukuran terhadap intensitas suara yang terjadi dan yang berpotensi menimbulkan kebisingan atau ketidaknyamanan. Tujuan penelitian ini adalah melakukan pengukuran dan analisis kebisingan di beberapa ruang kuliah di FMIPA UNNES sebagai antisipasi terhadap polusi suara yang terjadi. Penelitian dilakukan di 2 lokasi, yaitu jalan raya Sekaran, sekitar Kampus FMIPA dan Gedung D1 - D4 FMIPA UNNES. Pengukuran dilakukan selama 3 hari dengan rentang waktu 21 jam, sedangkan untuk gedung perkuliahan, yaitu di D1, D2, D3 dan D4, pengukuran dilakukan selama 3 hari dalam rantang waktu 10 jam. Hasil penelitian menunjukkan bahwa untuk jalan raya Sekaran tingkat kebisingannya rata – rata 71,38 dBA sedangkan untuk tingkat kebisingan Gedung D1 ruang D1-107 sebesar 51,08 dBA, dan ruang D1-207 sebesar 63,11 dBA, untuk Gedung D2, ruang D2-115 sebesar 73,75 dBA dan ruang D2-215 sebesar 60,21 dBA, untuk Gedung D3, ruang 119 sebesar 59,97 dBA dan ruang D3-219 sebesar 47,02 dBA, untuk Gedung D4, ruang D4-125 sebesar 37,17 dBA dan ruang D4-225 sebesar 47,80 dBA. Dari data tersebut, dapat disimpulkan bahwa tingkat kebisingan di gedung D1, D2 dan D3, melebihi ketentuan yang berlaku (baku mutu kebisingan) yang ditetapkan pemerintah sebesar 55 dBA.
Co-Authors - Sudartono A. Cristina Aditya Bagus Wicaksana Agung Wibowo Bambang Subali D Martina, D Dicko Alyandri Samudra Djuniadi , Djuniadi Djuniadi Djuniadi E Setiowati Edy - Wibowo Feddy Setio Pribadi Fianti Fianti, Fianti Hamidatul Faqqiyyah Haydnn Caesha Maulana Hidayah, Rizki Roqissatul Ian Yulianti, Ian Indrawan Nur Cahyono Iqbal Iqbal Iqbal Isa Akhlis Isa Akhlis Karnisih, Karnisih L Khakim L Lestari Langlang Handayani Leonardy, Joshu Masturi Masturi Masturi Masturi Muchamad Ngafifuddin Mufatihah, Nishfa Musa Abdul Halim N. Hindarto N. Istiana P Purwanto P. Dwijananti Prayogo, Defrian Purwanto - Purwanto R Indriyanto R. Setiawan Rohmad Rohmad Rudi Setiawan S. Rustad, S. S. Susanto, S. Santoso Santoso Slamet Haryono Sugianto Sugianto Sugiyanto - Suharto Linuwih Sulistyowati, Indah Dwi Supriyadi - Supriyadi Supriyadi Susilo - Susilo Susilo Susilo Susilo Sutaryani, Apit Sutikno - Sutikno Sutikno Syamsuri, KGS M Nurs Teguh Darsono Utomo, Galih R. W. P, Wasi Sakti Warsito, B. Wawan Kurniawan Wiujianna, Atri Yohannes Sardjono