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Efektivitas Karbon Aktif Dari Batu Bara Muda dalam Menurunkan COD pada Air Limbah Industri Tahu Febri Juita Anggraini; Arsapita, Rara; Yasdi, Yasdi
INSOLOGI: Jurnal Sains dan Teknologi Vol. 2 No. 2 (2023): April 2023
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v2i2.1822

Abstract

Lignite is the lowest quality coal and cannot be traded in the market. One alternative is that lignite coal has a better use value, lignite coal can be used as a material for making activated carbon. Coal which has become activated carbon can be applied to tofu industrial waste water as an adsorbent in absorbing chemical oxygen demand contained in tofu industrial waste water. The purpose of this study was to determine the characteristics of activated carbon from lignite,opium conditions and isotherm modeling. The method used in the manufacture of activated carbon from lignite is to use an activator in the form of 2 M NaOH with a carbonization temperature of 500°C using variations of 60 minutes and 90 minutes, then the activated carbon is soaked in 2 M HCl solution. Results from carbon characteristics The active lignite coal meets the requirements of SNI 06-3730-1995, the optimum time for reducing COD is 15 minutes with %removal of 66%, the optimum pH for reducing COD is pH 5 with %removal of 63.84% and the isotherm model follows the Harkin isotherm model - Jura with an average relative error of 13.024.
Sebaran Particulate Matter (PM10, PM2,5, PM1, PM0,1) di SMP Negeri 1 Kota Jambi Menggunakan Model CFD (Computational Fluid Dynamics) Febri Juita Anggraini; Annisa Shalsabila; Zuli Rodhiyah
INSOLOGI: Jurnal Sains dan Teknologi Vol. 2 No. 4 (2023): Agustus 2023
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v2i4.2269

Abstract

One source that contributes greatly to urban air quality is traffic. The proximity of schools to vehicles will put students at greater risk of exposure to high concentrations of particulate matter. SMP Negeri 1 Jambi City is an education center located in an urban area and adjacent to a busy road. CFD models are good at modeling the movement of pollutants in urban areas by taking into account the influence of buildings. The purpose of this study is to determine the concentration of PM10, PM2.5, PM1, and PM0.1 at SMPN 1 Jambi City based on direct measurement results and CFD modeling results and then see how accurate the modeled PM concentrations are when compared to the results of direct measurements. The results showed that the average concentrations of PM10, PM2.5, PM1, and PM0.1 from direct measurements were 20.66 µg/m3, 11.79 µg/m3, 8.74 µg/m3, and 1.96 µg/m3, respectively, while the modeling results showed lower average concentrations. The ratio of the difference between the measured and modeled PM concentrations is in the range of 11.67 - 233.45% and with the percentage of RMSPE obtained >30% (invalid), where the requirement for a modeling to be valid so that the results can be trusted in explaining the actual phenomenon is when the validity percentage is <30%.
Analisis Risiko Kebisingan di Sekolah Dasar Negeri 47/VI Kota Jambi Akibat Arus Lalu Lintas Suci Anggela Febrianti; Febri Juita Anggraini; Zuli Rodhiyah
INSOLOGI: Jurnal Sains dan Teknologi Vol. 3 No. 6 (2024): Desember 2024
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v3i6.4460

Abstract

The high volume of transportation activity in Jambi City, particularly in front of SD Negeri 47/VI, generates noise that contributes to noise pollution. This research aims to determine the noise level and determine the risks posed by noise due to traffic flow. The noise value is measured by a Sound Level Meter and the number of vehicles is measured by a Hand Tally Counter. This research uses a questionnaire given to students and will be analyzed using the Odds Ratio (OR) risk analysis method. The results of noise level measurements exceed the Quality Standards of PERMEN LH NO.48 of 1996, with the highest measurement results occurring on tuesday at L1 measurements (06.30-08.00 am) at sampling point D (classrooms that are close to the noise source) with the noise level being 65.92 dBA. The results of the analysis of noise risks that can be caused are, feeling disturbed by noise with an OR value of 10.9, difficulty hearing with an OR value of 1.6, communication disorders with an OR value of 3.5, difficulty concentrating with an OR value of 3.9 and psychological disorders with OR 0.4.
Estimation of the Carbon Footprint of Campus Activities at the Faculty of Science and Technology, Universitas Jambi, After the Covid19 Pandemic Windi Mulia Nofta Fani; Febri Juita Anggraini; Viareco, Hariestya
JURNAL KESEHATAN LINGKUNGAN Vol. 17 No. 2 (2025): JURNAL KESEHATAN LINGKUNGAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jkl.v17i2.2025.146-158

Abstract

Introduction: The Covid19 pandemic altered campus activity patterns, impacting energy use and transportation. As operations resumed, universities became significant contributors to carbon emissions. Without intervention, these emissions risk accelerating environmental harm. This study estimates the post-pandemic carbon footprint of campus activities to provide a foundation for emission reduction strategies at the Faculty of Science and Technology, Universitas Jambi. Methods: This quantitative descriptive study used surveys and observations at Universitas Jambi (2023) with 132 respondents via stratified sampling. Emissions were estimated using GHG Protocol scopes 1–3 and IPCC 2019 factors. Carbon-related variables were analyzed and mapped using Vensim to visualize interrelations in campus emission activities. Results and Discussion: The post-pandemic carbon footprint of campus activities at the Faculty of Science and Technology, Universitas Jambi, totaled 490.9 tons CO₂-eq in 2023. Scope 2 emissions from electricity use dominated at 78.54%, followed by Scope 3 (commuting and paper usage) at 20.29%, and Scope 1 at 1.16%. Transportation, particularly student commuting, was the largest contributor within Scope 3. Scenario simulations using Vensim revealed that carpooling and car-free day programs could reduce emissions significantly. Behavior-based interventions, including energy-saving practices and digital document usage, were identified as effective strategies to improve sustainability in daily academic operations. Conclusion: The findings support the development of targeted emission reduction strategies aligned with post-pandemic campus conditions. Its integrated approach contributes a data-driven framework for sustainable policy planning, especially for post-pandemic institutions in tropical and developing country contexts.