Investigation Public Holiday is Factor Affecting Dengue Cases by Using Arima and Arimax Model in Selangor and Sarawak from 2015 to 2019

Authors

  • Nur Dayana Abdul Rahman Department of Physical and Mathematical Science, Faculty of Science, Universiti Tunku Abdul Rahman, 31900 Kampar, Perak, MALAYSIA https://orcid.org/0009-0009-8130-3145
  • Loshini Thiruchelvam Department of Physical and Mathematical Science, Faculty of Science, Universiti Tunku Abdul Rahman, 31900 Kampar, Perak, MALAYSIA https://orcid.org/0000-0001-7080-4854
  • Nur Balqishanis Zainal Abidin Faculty of Computing & Informatics, Multimedia University, Persiaran Multimedia, 63100 Cyberjaya, Selangor, Malaysia Centre for Advanced Analysics, CoE Artificial Intelligence, Multimedia University, Persiaran Multimedia, 63100 Cyberjaya, Selangor, MALAYSIA , Centre for Advanced Analysics, CoE Artificial Intelligence, Multimedia University, Persiaran Multimedia, 63100 Cyberjaya, Selangor, MALAYSIA
  • Sarat Chandra Dass School of Mathematical and Computer Sciences, Heriot–Watt University Malaysia, Putrajaya https://orcid.org/0000-0002-7376-0436
  • Balvinder Singh Gill National Public Health Laboratory (MKAK), Sungai Buloh. Ministry of Health Malaysia. https://orcid.org/0000-0002-0738-2991
  • Nur Amalina Mat Jan Department of Physical and Mathematical Science, Faculty of Science, Universiti Tunku Abdul Rahman, 31900 Kampar, Perak, MALAYSIA. https://orcid.org/0000-0002-5782-7506
  • Vijanth Sagayan Asirvadam Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, 31750 Seri Iskandar, Perak, MALAYSIA. https://orcid.org/0000-0002-7912-414X

DOI:

https://doi.org/10.22452/

Keywords:

Box Jenkins, dengue, Malaysia, prediction models, ARIMAX

Abstract

This study investigated the relationship between dengue cases and human movement, as represented by public holidays in Malaysia for two states, Selangor and Sarawak, using a weekly dataset from 2015 to 2019. This study developed dengue prediction models by employing Autoregressive Integrated Moving Average (ARIMA) and ARIMA with public holiday as the exogenous variable (ARIMAX) time series models. The Box Jenkins approach for model development with Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) selection criteria are applied to select the optimum model by using the training dataset. This study, however, found the positive effect of human movement during public holidays is only apparent in three study areas; Klang and Sabak Bernam districts in Selangor state and Sibu division in Sarawak. The AIC and BIC values for Klang, Sabak Bernam, and Sibu were (-573.51, -556.89), (-162.93, -146.32), and (-446.64, -420.06), respectively. Despite this, the difference in the AIC and BIC values between ARIMA and ARIMAX models in other study areas is not large, and the study further found that the ARIMAX model of each study area did not fail to perform comparably well, with some study areas showing better accuracy scores when compared to their counterpart ARIMA model in the testing dataset. This concludes that public holidays, specifically the effect of human movement during that period, are significant factors for predicting dengue cases.

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Published

30-06-2026

Issue

Vol. 45 No. Sp1 (2026): Special Issue: FAST-UTHM GLOBAL NEXUS CONFERENCE 2024 - 9th International Conference on the Application of Science and Mathematics (SCIEMATHIC) 2024

Section

Special Issue - FAST-UTHM Global Nexus Conference 2024

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