Forecasting River Water Quality using Autoregressive Integrated Moving Average (ARIMA)

Dinna Yunika Hardiyanti, Hardini Novianty, Dinda Lestarini

2019

Abstract

Water quality affects the level of public health and the welfare of society. So it is necessary to keep the water clean. This study aims to predict the water quality of river X using the Arima method. The research uses the degree of acidity (pH), COD, and BOD data from 2007 to 2018. The forecasting results show that pH is 7.44, the COD value is 50.4184, and the BOD value is 3.310473. Therefore, in 2019, river X is in class III, which is the river is for freshwater fish cultivation, livestock, or crop irrigation.

Paper Citation

in Harvard Style

Hardiyanti D., Novianty H. and Lestarini D. (2019). Forecasting River Water Quality using Autoregressive Integrated Moving Average (ARIMA).In Proceedings of the International Conferences on Information System and Technology - Volume 1: CONRIST, ISBN 978-989-758-453-4, pages 158-163. DOI: 10.5220/0009907201580163

in Bibtex Style

@conference{conrist19,
author={Dinna Yunika Hardiyanti and Hardini Novianty and Dinda Lestarini},
title={Forecasting River Water Quality using Autoregressive Integrated Moving Average (ARIMA)},
booktitle={Proceedings of the International Conferences on Information System and Technology - Volume 1: CONRIST,},
year={2019},
pages={158-163},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009907201580163},
isbn={978-989-758-453-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conferences on Information System and Technology - Volume 1: CONRIST,
TI - Forecasting River Water Quality using Autoregressive Integrated Moving Average (ARIMA)
SN - 978-989-758-453-4
AU - Hardiyanti D.
AU - Novianty H.
AU - Lestarini D.
PY - 2019
SP - 158
EP - 163
DO - 10.5220/0009907201580163