No abstract

Emergency Vehicles (EV) consists of fire and rescue engines is expected able to perform its function efficiently especially in the case of fire incident. Even though the fire incident rarely to happen, but the arrival on time of the fire engine at the incident location is very crucial as it can save human lives and loss of valuables. This paper is intended to measure the Key Performance Index (KPI) by measuring the response time of the fire fighter to respond to an emergency case. This study attempts to quantify the duration of the time taken of an EV begins when the emergency call is answered until it reached to the incident location. Emergency Vehicles (EV) consists of fire and rescue engines is expected able to perform its function efficiently especially in the case of fire incident. Even though the fire incident rarely to happen, but the arrival on time of the fire engine at the incident location is very crucial as it can save human lives and loss of valuables. This paper is intended to measure the Key Performance Index (KPI) by measuring the response time of the fire fighter to respond to an emergency case. This study attempts to quantify the duration of the time taken of an EV begins when the emergency call is answered until it reached to the incident location. A qualitative approach was adopted, and data were obtained through in-depth interviews from 10 respondents who are mainly the officers in the fire station. The findings found that external factors such as road factors, parking, weather, inaccurate address, and population density were the main contributing factors that made the stations' response times did not meet its key performance indicator (KPI). Additionally, the internal factors are the main factors that contribute to the success of the key performance indicator response time. Therefore, this study recommends the authorities involved take action to rectify the problems. The result of this study hopefully can be extended to include the elements of traffic management and intersection in measuring EV response time in the future.

This study attempts to examine the effect of online learning readiness dimensions (Computer and internet self-efficacy, self-directed learning, learning control, learning motivation, online communication self-efficacy) on course satisfaction as well as the effect of course satisfaction and academic performance. This study develops a framework for relating academic performance to prior research and underlying theories. The sample size is 306 undergraduates in UiTM Sabah Branch consists of Kota Kinabalu and Tawau campuses. Data will go through a survey using stratified sampling from 6 different faculties and analyze with descriptive and inferential statistics. The findings suggested that (CIS) was critical for online learning and was significantly related to student achievement in online education. We also discovered that students' readiness for online learning had a significant effect on course satisfaction (CS), and that students' motivation for learning (MFL) and course satisfaction (CIS) have a direct influence on course satisfaction in terms of online learning readiness. The current study proposes some areas for future research, such as conducting a survey of lecturers who are currently participating in online education. When the pandemic is over, a mixed-methods study, such as a post-pandemic study, could be conducted.