Optimalisasi Prediksi Indeks Kualitas Air di Indonesia dengan Menggunakan Machine Learning Melalui Pendekatan Metode Prophet

Didi Sangaji; Tata Sutabri

doi:10.62951/switch.v2i5.277

Authors

Didi Sangaji Universitas Bina Darma
Tata Sutabri Universitas Bina Darma

DOI:

https://doi.org/10.62951/switch.v2i5.277

Keywords:

Water Quality, Machine Learning, Prophet Model, Prediction

Abstract

The Water Quality Index (WQI) shows the condition of water quality in an area based on the status of water quality resulting from the measurement of physical, chemical and bacteriological parameters of a water body both rivers and lakes. Several machine learning techniques can be used to predict water quality in an area, one of which is through the prophet model approach which is able to provide fairly accurate predictions for the water quality index in Indonesia. The main objective of this research is to obtain a WQI prediction value as a baseline in the formulation of future environmental control activity policies using the prophet model. The result is that the predicted value of IKA for 2021-2023 generated through machine learning with the prophet model approach shows that the Mean Absolute Error (MAE) value: 7.01, Root Mean Square Error (RMSE): 8.61 and Mean Absolute Percentage Error (MAPE): 13.06%, which means that IKA prediction with the prophet model is effective in capturing annual patterns between historical data and future predictions.

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