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Rosnalini Mansor
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Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

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Forecasting of Electricity Consumption and Supply for Campus University using Time Series Models Rosnalini Mansor; Bahtiar Jamili Zaini; Chong Shi Yee
International Journal of Supply Chain Management Vol 8, No 5 (2019): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (383.656 KB)

Abstract

Electricity is an important energy source in university as lecture classes need electricity supply to function. It is also important for the development of the university. Since electricity consumption is a necessity of a university’s operation, the forecast of electricity consumption on the university campus should be made. This is essential for the development of the university as the treasury department can manage the funding from the government according to the value forecasted to make full use of the funding in the university’s development. There are several forecasting methods used in this study, including time series regression, seasonal exponential smoothing, Box-Jenkins (SARIMA), decomposition and the naïve method. Error measurements used to evaluate the performance of forecasting model were mean square error (MSE), root mean square error (RMSE), mean absolute percentage error (MAPE) and geometric root mean square error (GRMSE). The results of this study showed that the seasonal exponential smoothing model was the best in the 1-step ahead and 2-step ahead forecasting while SARIMA (0,2,2)(0,2,1)12 was the best in the 3-step ahead forecast. The overall performance of seasonal exponential smoothing was the best in this study. Throughout this study, suggestions were made for the next study regarding electricity consumption in university to consider factors such as semester breaks and students’ activities in order to examine its effect in electricity consumption.
PLS Equation Model of Student Loyalty based on Gender in IR 4.0 Environment Bahtiar Jamili Zaini; Rosnalini Mansor; Norhayati Yusof; Mohammad Nizam Sarkawi
International Journal of Supply Chain Management Vol 8, No 5 (2019): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (439.907 KB)

Abstract

Students loyalty and attrition is an important issue for university authorities.  Earlier studies have discovered that many factors influencing student loyalty towards their higher learning institutions such as student satisfaction, university image, student trust, and service quality. However, these factors have high relationship correlated with each other. Therefore, this study used the Partial Least Square (PLS) to create a path model which shows the relationship between all factors related to student loyalty. The results from this study revealed that student satisfaction is the most important factors that influence student loyalty, followed by image of university and student commitment. Analysis based on gender shows that female student model have a same pattern with overall student loyalty model but the male student loyalty model is simpler just consist student satisfaction. On the other hand, factors technology, social environment and quality of instructor gave a great influence towards student satisfaction. Therefore, in order to improve student loyalty, university should keep on improving to satisfy students’ requirement.
Co-Authors Bahtiar Jamili Zaini Chong Shi Yee Mohammad Nizam Sarkawi Norhayati Yusof