Article Per Year (5 Year)
p-Index From 2019 - 2024
0.408
P-Index
This Author published in this journals
All Journal Leuser Journal of Environmental Studies
Sunarti Abd Rahman
Faculty of Chemical & Process Engineering Technology, Universiti Malaysia Pahang, Lebuhraya Persiaran Tun Khalil Yaakob, 26300 Gambang, Kuantan, Pahang, Malaysia
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Energy Environmental Science Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Method Validation for Pesticide Residues on Rice Grain in Aceh Besar District, Indonesia Using Gas Chromatography-Electron Capture Detector (GC-ECD) Agus Winarsih; Rinaldi Idroes; Utari Zulfiani; Muhammad Yusuf; Mahmudi Mahmudi; Saiful Saiful; Sunarti Abd Rahman
Leuser Journal of Environmental Studies Vol. 1 No. 1 (2023): July 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v1i1.37

Abstract

Analysis of pesticide residues in rice in Aceh Besar District using the Gas Chromatography – Electron Capture Detector (GC-ECD) method has been carried out. This study aims to validate the analytical method and determine the pesticide residue levels of Dichlorvos, Dimethoate, Bifenthrin, and λ-Cyhalothrin in rice samples. Rice samples in branded rice were taken from the Districts of Want Jaya, Indrapuri, Darussalam, Suka Makmur, Simpang Tiga, Kuta Baro, and ground using a grinder. The powder sample was extracted by the QuEChERS method and analyzed by GC-ECD. The results of the linearity test have met the requirements with the coefficient of determination (R2), which is an average of 0.98. The LOD values ranged from 0.013 to 0.017 mg/kg, while the LOQ ranged from 0.022 to 0.079 mg/kg. The results of precision and reproducibility (% RSD, n = 6) show the values of 0.56 - 1.26% and 1.14 - 2.19%, respectively, and the accuracy value (%Recovery) shows the results of 99.71 - 101.84%, with an RSD value of 2.42 - 3.59%, meet the requirement of 20%. The results of the analysis of the sample showed that sample A had a large %Recovery value in the Dichlorvos analyte, namely 139.10%, with the calculation that the Dichlorvos analyte contained 0.0206 mg/Kg. This value has not passed the MLR set by the European Food Safety Authority, which is 0.2 mg/Kg. In the other rice samples, no pesticide residue analytes were detected. The calculation of %Recovery of each analyte in the spiked sample ranged from 80-101%, which indicated that the pesticide residue analysis carried out had good accuracy, namely the requirement of 70-120%.
Urban Air Quality Classification Using Machine Learning Approach to Enhance Environmental Monitoring Ghazi Mauer Idroes; Teuku Rizky Noviandy; Aga Maulana; Zahriah Zahriah; Suhendrayatna Suhendrayatna; Eko Suhartono; Khairan Khairan; Fitranto Kusumo; Zuchra Helwani; Sunarti Abd Rahman
Leuser Journal of Environmental Studies Vol. 1 No. 2 (2023): November 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v1i2.99

Abstract

Urban areas worldwide grapple with environmental challenges, notably air pollution. DKI Jakarta, Indonesia's capital city, is emblematic of this struggle, where rapid urbanization contributes to increased pollutants. This study employed the CatBoost machine learning algorithm, known for its resistance to overfitting and capability to handle missing data, to predict urban air quality based on pollutant levels from 2010 to 2021. The dataset, sourced from Jakarta's air quality monitoring stations, includes pollutants such as PM10, SO2, CO, O3, and NO2. After preprocessing, we used 80% of the data for training and 20% for testing. The model displayed high accuracy (0.9781), precision (0.9722), and recall (0.9728). The feature importance chart revealed O3 (Ozone) as the top influencer of air quality predictions, followed by PM10. Our findings highlight the dominant pollutants affecting urban air quality in Jakarta, Indonesia and emphasizing the need for targeted strategies to reduce their concentrations and ensure a cleaner and healthier urban environment.
Co-Authors Aga Maulana Agus Winarsih Eko Suhartono Fitranto Kusumo Ghazi Mauer Idroes Khairan Khairan Mahmudi Mahmudi Muhammad Yusuf Rinaldi Idroes Saiful Saiful Suhendrayatna Suhendrayatna Teuku Rizky Noviandy Utari Zulfiani Zahriah Zahriah Zuchra Helwani