cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota bandung,
Jawa barat
INDONESIA
Jurnal Rekayasa Hijau
Published by Institut Teknologi Nasional Bandung
ISSN : 25794264     EISSN : 25501070     DOI : -
Core Subject : Science, Agriculture,
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences
Jurnal Rekayasa Hijau diterbitkan 3 kali dalam satu tahun. Berisi tulisan yang diangkat dari hasil penelitian dan kajian analisis di bidang ilmu pengetahuan, teknologi, desain dan kebijakan ramah lingkungan.
Arjuna Subject : -
Articles 306 Documents
 27   28   29   30   31 
Evaluation of Pseudo-First-Order Kinetics of Starch Acid Hydrolysis in Red Rice and White Rice Teodora Maria Fernandes Brito Da Silva; Kholifatul Nisa; Puspita Anggraeni; Nurur Rifky Wibowo; Diyah Puspita Sari
Rekayasa Hijau : Jurnal Teknologi Ramah Lingkungan Vol 10, No 2 (2026)
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/jrh.v10i2.143-153

Abstract

AbstrakPenelitian ini bertujuan untuk mengevaluasi kesesuaian model kinetika pseudo-ordo satu pada proses hidrolisis asam pati beras merah dan beras putih serta menentukan konstanta laju reaksi berdasarkan data konversi yang diperoleh. Proses hidrolisis dilakukan secara batch menggunakan 10 gram substrat basis kering dengan penambahan HCl 37% pada kondisi isotermal selama 50 menit. Kadar gula reduksi hasil hidrolisis dianalisis menggunakan metode Fehling dan digunakan untuk menghitung konversi reaksi. Parameter kinetika ditentukan melalui hubungan ln(1−X) terhadap waktu reaksi. Hasil penelitian menunjukkan bahwa konversi pati beras merah meningkat dari 12,85% menjadi 16,85%, sedangkan beras putih meningkat dari 31,05% menjadi 93,17% selama 50 menit. Analisis regresi menunjukkan hubungan linier yang kuat dengan nilai R² masing-masing sebesar 0,9682 dan 0,9926. Konstanta laju reaksi diperoleh sebesar 0,00093 menit⁻¹ dan 0,0445 menit⁻¹. Secara umum, perbedaan laju reaksi dipengaruhi struktur pati. Kajian kinetika ini dapat menjadi dasar optimasi proses hidrolisis biomassa menuju teknologi yang lebih berkelanjutan dan efisien energi.Kata kunci: Hidrolisis Asam, Kinetika Pseudo-Ordo Satu, Pati beras, Biomassa Terbarukan, Rekayasa Hijau  AbstractThis study aims to evaluate the suitability of the pseudo-first-order kinetic model in the acid hydrolysis process of brown rice and white rice starch and determine the reaction rate constant based on the conversion data obtained. The hydrolysis process was carried out in batches using 10 grams of dry base substrate with the addition of 37% HCl under isothermal conditions for 50 minutes. The reducing sugar content of the hydrolysis results was analyzed using the Fehling method and used to calculate the reaction conversion. Kinetic parameters were determined through the relationship of ln(1−X) to reaction time. The results showed that the conversion of brown rice starch increased from 12.85% to 16.85%, while that of white rice increased from 31.05% to 93.17% over 50 minutes. Regression analysis showed a strong linear relationship with R² values of 0.9682 and 0.9926, respectively. The reaction rate constants were obtained at 0.00093 min⁻¹ and 0.0445 min⁻¹. In general, differences in reaction rates are influenced by starch structure. This kinetic study can provide a basis for optimizing biomass hydrolysis processes toward more sustainable and energy-efficient technologies.Keywords: Acid Hydrolysis, Pseudo-First-Order Kinetics, Rice Starch, Renewable Biomass, Green Engineering
Comparison of RStudio and Python Performance on Green Computing-Based Big Data Analytics Salman Salman; Heni Sulastri; Muhammad Al Husaini
Rekayasa Hijau : Jurnal Teknologi Ramah Lingkungan Vol 10, No 2 (2026)
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/jrh.v10i2.118-127

Abstract

AbstrakPerkembangan data berskala menengah mendorong kebutuhan platform analitik yang tidak hanya cepat, tetapi hemat sumber daya. Penelitian ini bertujuan membandingkan performa R (melalui RStudio) dan Python terhadap Big Data Analytics berbasis Green Computing pada data skala menengah. Melalui metode komparatif pada dataset ‘‘AI4I 2020 Predictive Maintenance’’, penelitian ini mengukur waktu eksekusi, utilisasi CPU, penggunaan memori, dan konsumsi energi. Hasil pengujian menunjukkan RStudio mencatat waktu eksekusi 19.916,67 ms, utilisasi CPU 0,08%, penggunaan memori 75,43 MB, dan konsumsi energi 440,95 J, sedangkan Python mencatat 270.447,73 ms, utilisasi CPU 1,14%, penggunaan memori 689,67 MB, dan konsumsi energi 7.178,24 J. Temuan menunjukkan bahwa perbedaan performa bersifat kontekstual terhadap karakteristik workload dan desain pipeline analitik, serta menegaskan adanya trade-off antara efisiensi komputasi dan fleksibilitas ekosistem dalam kerangka Green Computing. Kata kunci: green computing, big data analytics, benchmarking, rstudio, python AbstractThe growth of medium scale data is driving the need for analytics platforms that are not only fast, but also resource-efficient. This research aims to compare the performance of R (via RStudio) and Python on Green Computing based Big Data Analytics on medium scale data. Through comparative methods on the ‘‘AI4I 2020 Predictive Maintenance’’ dataset, this research measures execution time, CPU utilization, memory usage and energy consumption. Test results show that RStudio recorded an execution time of 19,916.67 ms, CPU utilization 0.08%, memory usage 75.43 MB, and energy consumption 440.95 J, while Python recorded 270,447.73 ms, CPU utilization 1.14%, memory usage 689.67 MB, and energy consumption 7,178.24 J. The findings show that the performance differences are contextual to the characteristics. workload and analytical pipeline design, and emphasizes the existence of a trade-off between computing efficiency and ecosystem flexibility in the Green Computing framework. Keywords: green computing, big data analytics, benchmarking, rstudio, python
Accuracy Analysis of Mining Material Volume Estimation Using Terrestrial Laser Scanning and UAV Photogrammetry Dedi Wijaya; Gusti Ayu Jessy Kartini
Rekayasa Hijau : Jurnal Teknologi Ramah Lingkungan Vol 10, No 2 (2026)
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/jrh.v10i2.128-142

Abstract

AbstrakPengukuran volume stockpile batubara berperan penting dalam perencanaan produksi dan pengendalian logistik tambang. Penelitian ini mengevaluasi akurasi, efisiensi operasional, dan biaya survei menggunakan Terrestrial Laser Scanning (TLS) dan UAV fotogrametri pada stockpile batubara di Site Banko Barat, Sumatera Selatan. Akuisisi data dilakukan menggunakan TLS Riegl VZ-2000i dan UAV Wingtra Gen II. Hasil menunjukkan error registrasi TLS sebesar 0,0244 m dan UAV sebesar 0,0647 m. Volume yang dihasilkan masing-masing sebesar 170.625,147 m3 dan 168.580,104 m3, dengan selisih 1,199%, masih berada di bawah toleransi ASTM D6172-98 sebesar 2%. Perbedaan volume dipengaruhi mekanisme pembentukan point cloud, di mana TLS menghasilkan representasi elevasi yang lebih detail dibandingkan rekonstruksi Structure from Motion (SfM) pada UAV. UAV lebih efisien dari sisi waktu dan biaya, sedangkan TLS memberikan akurasi geometrik yang lebih tinggi sehingga keduanya dapat dipilih sesuai kebutuhan operasional.Kata kunci: batubara, stockpile, akurasi, volume, TLS, UAV fotogrametri, point cloud  AbstractCoal stockpile volume measurement is essential for production planning and mine logistics management. This study evaluates the accuracy, operational efficiency, and survey cost of Terrestrial Laser Scanning (TLS) and UAV photogrammetry for measuring a coal stockpile at Banko Barat Site, South Sumatra, Indonesia. Data were acquired using a Riegl VZ-2000i TLS and a Wingtra Gen II UAV. The registration errors were 0.0244 m for TLS and 0.0647 m for UAV. The calculated volumes were 170,625.147 m3 and 168,580.104 m3, respectively, with a difference of 1.199%, which is below the 2% tolerance specified by ASTM D6172-98. The volume discrepancy is attributed to differences in point cloud generation, where TLS provides more detailed elevation representation than Structure from Motion (SfM)-based UAV reconstruction. UAV offers greater time and cost efficiency, whereas TLS provides higher geometric accuracy, making both methods suitable depending on operational requirements.Keywords: coal, stockpile, accuracy, volume, TLS, UAV photogrammetry, point cloud
Assessment of Roadside Ambient Air Quality and Transportation Pollutant Dispersion Using CALINE-4 in South Cimahi Rahasta Kandiawan; Mila Dirgawati; Didin Agustian Permadi
Rekayasa Hijau : Jurnal Teknologi Ramah Lingkungan Vol 10, No 2 (2026)
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/jrh.v10i2.154-169

Abstract

AbstrakUdara merupakan komponen vital bagi kehidupan, namun peningkatan jumlah kendaraan, pembangunan kawasan, dan pertumbuhan penduduk perkotaan menurunkan kualitas udara ambien. Penelitian ini bertujuan mengevaluasi kualitas udara ambien di tepi jalan serta memprediksi penyebaran polutan CO dan PM₁₀ di Kecamatan Cimahi Selatan menggunakan model CALINE 4. Metode penelitian meliputi pemantauan kualitas udara, survei kinerja lalu lintas, dan pemodelan dispersi polutan berdasarkan data meteorologi, volume kendaraan, dan faktor emisi. Hasil penelitian menunjukkan konsentrasi tertinggi SO₂ 40,36 µg/Nm³ atau 26,9%, CO 6.675 µg/Nm³ atau 66,8%, NO₂ 22,33 µg/Nm³ atau 11,2%, PM₁₀ 68,20 µg/Nm³ atau 90,9%, dan PM₂.₅ 32,20 µg/Nm³ atau 58,5%, seluruhnya masih memenuhi PP No. 22 Tahun 2021. Kinerja lalu lintas berada pada LOS C, dan prediksi dispersi menunjukkan konsentrasi tertinggi pada area downwind searah angin dominan. Pengendalian emisi dan sosialisasi masyarakat disarankan. Kata kunci: CALINE 4, kualitas udara ambien, pemodelan dispersi, polutan CO, PM₁₀  AbstractAir is a vital component for life; however, the increasing number of vehicles, urban development, and population growth in urban areas have contributed to the degradation of ambient air quality. This study aims to evaluate roadside ambient air quality and predict the dispersion of CO and PM₁₀ pollutants in Cimahi Selatan District using the CALINE-4 model. The research methods include air quality monitoring, traffic performance surveys, and pollutant dispersion modeling based on meteorological data, vehicle volume, and emission factors. The results show that the highest concentrations were SO₂ at 40.36 µg/Nm³ (26.9%), CO at 6,675 µg/Nm³ (66.8%), NO₂ at 22.33 µg/Nm³ (11.2%), PM₁₀ at 68.20 µg/Nm³ (90.9%), and PM₂.₅ at 32.20 µg/Nm³ (58.5%), all of which remain within the limits of Government Regulation No. 22 of 2021. Traffic performance was categorized as LOS C, and dispersion predictions indicate the highest concentrations occur in downwind areas aligned with the prevailing wind direction. Emission control measures and public awareness campaigns are recommended. Keywords: CALINE 4, dispersion modeling, roadside ambient air quality, CO pollutant, PM₁₀
Smart Green Environment: IoT Integration with Organic Fertilizer to Support Sustainable Environmental Management Mutia Perwita sari; Isnein Akbar
Rekayasa Hijau : Jurnal Teknologi Ramah Lingkungan Vol 10, No 2 (2026)
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/jrh.v10i2.170-181

Abstract

AbstrakPenataan lingkungan permukiman secara berkelanjutan saat ini menghadapi kendala akibat buruknya pengelolaan limbah organik rumah tangga dan tidak akuratnya metode perawatan tanaman konvensional yang memicu inefisiensi air. Penelitian ini bertujuan mengintegrasikan konsep rekayasa hijau melalui pemanfaatan pupuk organik dengan teknologi Internet of Things (IoT) untuk mengoptimalkan pemeliharaan tanaman. Metode penelitian diawali dengan survei lingkungan, pembuatan kompos dari limbah lokal menggunakan fermentasi EM4, serta perancangan alat kontrol otomatis berbasis mikrokontroler ESP32 yang terhubung dengan sensor DHT11 dan soil moisture. Hasil penelitian menunjukkan bahwa integrasi sistem cerdas berbasis IoT dan pemanfaatan pupuk organik dari limbah rumah tangga berhasil memantau parameter lingkungan secara real-time melalui aplikasi Virtuino, mengotomatisasi penyiraman tanaman, meningkatkan efisiensi penggunaan air sebesar 40%, serta mendukung pengurangan volume sampah organik dan penghijauan lingkungan secara berkelanjutanKata kunci: Internet of Things, Smart Farming, Pupuk Organik, Monitoring Tanaman, Smart Environment, ESP32  AbstractSustainable residential environmental management is currently facing challenges due to poor household organic waste management and the inaccuracy of conventional plant maintenance methods, which lead to inefficient water use. This study aims to integrate the concept of green engineering through the utilization of organic fertilizer and Internet of Things (IoT) technology to optimize plant maintenance. The research methodology began with an environmental survey, followed by the production of compost from local organic waste using EM4 fermentation and the design of an automatic control system based on the ESP32 microcontroller integrated with DHT11 and soil moisture sensors. The results demonstrate that the integration of an IoT-based intelligent system and organic fertilizer derived from household waste successfully monitored environmental parameters in real time through the Virtuino application, automated plant irrigation, improved water-use efficiency by 40%, and contributed to the reduction of organic waste volume and sustainable environmental greening Keywords: Internet of Things, Smart Farming, Organic Fertilizer, Plant Monitoring, Smart Environment, ESP32
Study of Green Hydrogen Production from Excess Electricity Off-Grid Rooftop PV, FT-02, Universitas Tidar Arbye S; Achmad Aziizudin; Angger Bagus Prasetiyo; Cahyo Wibi Yogiswara; Setya Drana Harry Putra; Herlambang Fawwaz Prabowo; Tiko Es Saputra Ceren
Rekayasa Hijau : Jurnal Teknologi Ramah Lingkungan Vol 10, No 2 (2026)
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/jrh.v10i2.182-198

Abstract

AbstrakPemanfaatan PLTS atap berpotensi menghasilkan excess electricity ketika produksi energi surya melebihi kebutuhan beban, yang berpeluang dimanfaatkan untuk produksi green hydrogen melalui elektrolisis. Penelitian ini mengkaji potensi produksi green hydrogen berbasis excess electricity dari sistem PLTS atap di wilayah Magelang menggunakan pendekatan analitis berbasis data simulasi sekunder. Data utama diperoleh dari simulasi HOMER Pro pada sistem PLTS off-grid berkapasitas 14,6 kWp di Gedung FT02 Universitas Tidar. Potensi produksi hidrogen dihitung menggunakan pendekatan specific energy consumption (SEC) untuk tiga skenario teknologi: PEM electrolyzer, Alkaline Water Electrolyzer (AWE), dan HHO generator. Hasil analisis menunjukkan sistem PLTS objek kajian menghasilkan excess electricity sebesar 13.841 kWh/tahun (67,1% dari total produksi energi), yang berpotensi menghasilkan 240,71–287,75 kg H₂/tahun (PEM), 259,19–276,82 kg H₂/tahun (AWE), dan 153,79–238,64 kg H₂/tahun (HHO). Proyeksi indikatif pada enam lokasi PLTS atap di wilayah Magelang menunjukkan potensi produksi green hydrogen total sebesar 3.099–3.707 kg H₂/tahun untuk skenario PEM. Kata kunci: green hydrogen, excess electricity, plts atap, elektrolisis, magelang. AbstractRooftop PV systems can generate excess electricity when solar production exceeds load demand, offering an opportunity for green hydrogen production through electrolysis. This study evaluates the potential green hydrogen production from excess electricity of a rooftop off-grid PV system in Magelang, using secondary simulation data. The main dataset was obtained from a HOMER Pro simulation of a 14.6 kWp off-grid rooftop PV system at the FT02 Building, Universitas Tidar. Hydrogen production potential was calculated using the specific energy consumption (SEC) approach for three technology scenarios: PEM electrolyzer, Alkaline Water Electrolyzer (AWE), and HHO generator. Results show the system produces 13,841 kWh/year of excess electricity (67.1% of total energy production), potentially yielding 240.71–287.75 kg H₂/year (PEM), 259.19–276.82 kg H₂/year (AWE), and 153.79–238.64 kg H₂/year (HHO). Indicative projections for six rooftop PV locations in Magelang show a total green hydrogen potential of 3,099–3,707 kg H₂/year under the PEM scenario. Keywords: green hydrogen, excess electricity, rooftop solar PV, water electrolysis, magelang

Page 31 of 31 | Total Record : 306

 27   28   29   30   31 

Filter by Year

2017 2026


Reset
Filter By Issues
All Issue Vol 10, No 2 (2026) Vol 10, No 1 (2026) Vol 9, No 3 (2025) Vol 9, No 2 (2025) Vol 9, No 1 (2025) Vol 8, No 3 (2024) Vol 8, No 2 (2024) Vol 8, No 1 (2024) Vol 7, No 3 (2023) Vol 7, No 2 (2023) Vol 7, No 1 (2023) Vol 6, No 3 (2022) Vol 6, No 2 (2022) Vol 6, No 1 (2022) Vol 5, No 3 (2021) Vol 5, No 2 (2021) Vol 5, No 1 (2021) Vol 4, No 3 (2020) Vol 4, No 2 (2020) Vol 4, No 1 (2020) Vol 3, No 3 (2019) Vol 3, No 2 (2019) Vol 3, No 1 (2019) Vol 3, No 1 (2019) Vol 2, No 3 (2018) Vol 2, No 3 (2018) Vol 2, No 2 (2018) Vol 2, No 2 (2018) Vol 2, No 1 (2018) Vol 2, No 1 (2018) Vol 1, No 3 (2017) Vol 1, No 1 (2017) Vol 1, No 3 (2017) Vol 1, No 2 (2017) Vol 1, No 2 (2017) Vol 1, No 1 (2017) More Issue