Penilaian Tingkat Kerentanan Air Tanah terhadap Pencemaran dengan Menggunakan Metode DRASTIC di Kecamatan Jogoroto Kabupaten Jombang

There are more than 70 small tofu factories in the Jogoroto District, which generate a large amount of liquid waste from tofu processing that has not been treated optimally. This certainly creates a potential for the waste to contaminate groundwater in the Jogoroto District. The assessment of groundwater vulnerability to contamination can be conducted using the DRASTIC method, which involves 7 parameters.In this study, there are 24 dug well points spread across the entire Jogoroto District, which were monitored periodically over a 5-month period, from July 2023 to November 2023. Based on the resulting groundwater vulnerability distribution map, laboratory tests on groundwater quality were carried out, using parameters from the Minister of Health Regulation No. 2 of 2023 concerning clean water and the Minister of Environment Regulation No. 5 of 2014 on effluent quality standards.The study found that the DRASTIC index value during the research period ranged from 140 to 212, with three levels of vulnerability: moderate, high, and very high. The high vulnerability level dominated the study area. However, based on the validation results, it was found that the groundwater quality in the Jogoroto District, Jombang Regency, is not contaminated.

Authors

Institutions

Publication Details

Journal
Journal of Educational Engineering and Environment
Published
2024-12-29
DOI
https://doi.org/10.36526/jeee.v3i2.4689
Primary Topic
Heavy Metal Pollution Remediation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Penilaian Tingkat Kerentanan Air Tanah terhadap Pencemaran dengan Menggunakan Metode DRASTIC di Kecamatan Jogoroto Kabupaten Jombang

Hari Siswoyo, Rini Wahyu Sayekti, Em Rafif Sultan Alfaridzi
Journal of Educational Engineering and Environment
Heavy Metal Pollution Remediation
article

Penilaian Tingkat Kerentanan Air Tanah terhadap Pencemaran dengan Menggunakan Metode DRASTIC di Kecamatan Jogoroto Kabupaten Jombang

Hari Siswoyo, Rini Wahyu Sayekti, Em Rafif Sultan Alfaridzi
article en

Abstract

There are more than 70 small tofu factories in the Jogoroto District, which generate a large amount of liquid waste from tofu processing that has not been treated optimally. This certainly creates a potential for the waste to contaminate groundwater in the Jogoroto District. The assessment of groundwater vulnerability to contamination can be conducted using the DRASTIC method, which involves 7 parameters.In this study, there are 24 dug well points spread across the entire Jogoroto District, which were monitored periodically over a 5-month period, from July 2023 to November 2023. Based on the resulting groundwater vulnerability distribution map, laboratory tests on groundwater quality were carried out, using parameters from the Minister of Health Regulation No. 2 of 2023 concerning clean water and the Minister of Environment Regulation No. 5 of 2014 on effluent quality standards.The study found that the DRASTIC index value during the research period ranged from 140 to 212, with three levels of vulnerability: moderate, high, and very high. The high vulnerability level dominated the study area. However, based on the validation results, it was found that the groundwater quality in the Jogoroto District, Jombang Regency, is not contaminated.

Journal of Educational Engineering and EnvironmentVol. 3(2)
University of Brawijaya (ID)
Openalex Percentile: Top 73%
Heavy Metal Pollution Remediation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.