Pembentukan Model Stokastik Box-Jenkins dan Aplikasi dalam Industri Utiliti

• Main Author: Syariza, Abdul Rahman
• Format: Thesis
• Language: English; English
• Published: 2003
• Subjects: QA273-280 Probabilities. Mathematical statistics
• Online Access: https://etd.uum.edu.my/1154/1/SYARIZA_BT._ABDUL_RAHMAN.pdf; https://etd.uum.edu.my/1154/2/1.SYARIZA_BT._ABDUL_RAHMAN.pdf; https://etd.uum.edu.my/1154/

The objective of this study is to build a stochastic Box-Jenkins model for electricity demand in Perlis. In the process of building stochastic Box-Jenkins model, first series of the differentiation was used for every sector in this research to obtain the set of stationary series data. To accomplish the second objective, the factors affecting the electricity demand was measured for domestic, commercial, industry and street lighting sector in Perlis. The factors that have been measured in this research are the monthly temperature of surrounding, total of monthly rain, festive seasons, increasement in the number of resident the development of state economic and the development in the surrounding area. The study gave the value of short term forecasting for electricity demand in Perlis. Only domestic sector signified a seasonal pattern and occupied Seasonal ARIMA Box-Jenkins model while commercial, industry and street lighting sector were significant and occupying ARIMA Box-Jenkins model. After analyzing the factors affecting the electricity demand, we bund that stationary and randomness affected these factors consistently and significantly. This study discovered that domestic sector is affected by the increasement in the number of residents and the number of houses, the festive seasons, the surrounding temperature and the number of raining days. For commercial sector, the demand is affected by the development of state economic and festive seasons. Industry sector is effected by the development of state economic and also by CIMA. TNB’s main consumer that deputize cement industry in Perlis state. Meanwhile Street lighting sector is affected by the development of infrastructure and the festive seasons.