Designing User Interface with UML and CRUD Concept for IoT-Based Water Quality Analysis Tool

Rahutomo, Reza; Hermantoro,; Krisdiarto, Andreas Wahyu; Uktoro, Arief Ika; Suparyanto, Teddy; Pardamean, Bens

doi:10.1109/chiuxid54398.2021.9650608

Cited by 1 publication

(1 citation statement)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Groundwater water quality monitoring is very crucial to ensure safe water for the domestic water resource. Internet-of-Things (IoT) for water quality monitoring systems has provided a more efficient and cheaper system, compare to the laboratory-based testing approaches [20,21]. Therefore, further study should be performed on the application of IoT-based water quality monitoring systems for groundwater in Jakarta.…”

Section: Manganese Contaminationmentioning

confidence: 99%

Evaluation of Trends for Iron and Manganese Concentrations in Shallow Groundwater, Jakarta City

Parrangan

Wijayanti

Soekotjo

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

Groundwater is one of the sources of clean water in DKI Jakarta. However, it was found that there is a decrease in groundwater quality. The objective of this study is to evaluate trends for iron and manganese concentration in shallow groundwater in Jakarta City from 2017-2020. Based on groundwater quality testing data, analysis and evaluation of groundwater causation were carried out by a spatial map of the distribution of DKI Jakarta groundwater quality. The results of the analysis show that some groundwater quality parameters experience fluctuations in the concentration of contaminants. Spatial maps produced through geographic information systems represent the distribution of patterns of groundwater quality distribution that occurred in the period 2017-2020 and 2022 using interpolation techniques. The amounts of manganese and iron in the groundwater of Jakarta are slightly higher than the permissible limits of national standards guidelines.

show abstract

Section: Manganese Contaminationmentioning

confidence: 99%