PENILAIAN KOMPARATIF MODEL SARIMA DAN LSTM UNTUK KNOWLEDGE DISCOVERY AIR QUALITY INDEX PADA KOTA GURUGRAM

SOFIAH, NANDA AULIA and Tania, Ken Ditha (2024) PENILAIAN KOMPARATIF MODEL SARIMA DAN LSTM UNTUK KNOWLEDGE DISCOVERY AIR QUALITY INDEX PADA KOTA GURUGRAM. Undergraduate thesis, Sriwijaya University.

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Abstract

Gurugram, an urban center in India, experiences elevated levels of air pollution as a result of rapid urbanization and intensified industrial operations. Air pollution, responsible for 25% of all deaths in underdeveloped countries, can lead to long-term health conditions such as lung cancer and cardiovascular disease. Precise forecasting of the Air Quality Index (AQI) is crucial for the implementation of effective environmental and public health measures. The objective of this project is to evaluate the precision of Gurugram's Air Quality Index (AQI) predictions by employing two machine learning algorithms, namely SARIMA and LSTM. This study aims to gain knowledge discovery by comparing the accuracy of SARIMA and LSTM models in forecasting AQI for Gurugram that can be utilized for safeguarding public health and detecting potential emergencies at an early stage. Discoveries indicate that although the LSTM model has a higher degree of error variability (with a root mean square error of 63.163 compared to 61.999 for SARIMA), it surpasses SARIMA in terms of average forecast accuracy (with a mean absolute error of 40.948 versus 45.758).

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Air Quality Index, Gurugram, Prediksi Machine Learning Algorithm, Knowledge Discovery
Subjects:	T Technology > T Technology (General) > T58.6-58.62 Management information systems > T58.6 General works Industrial engineering Information technology. Information systems (General) Management information systems -- Continued T Technology > T Technology (General) > T58.6-58.62 Management information systems > T58.62 Decision support systems Cf. HD30.213 Industrial management
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Nanda Aulia Sofiah
Date Deposited:	02 Jan 2025 02:12
Last Modified:	02 Jan 2025 02:12
URI:	http://repository.unsri.ac.id/id/eprint/162057

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