This study aims at analyzing, comparing and selecting the best predictive model based on organic waste generation at the UiTM Tapah Campus administration cafe. The data collection period begins Monday through Friday from 4th Mac 2019 until 20th April 2020. There are 2 bins that are labeled as Bin 1 and Bin 2 at the Administration Cafe on the UiTM Tapah Campus. Using the Risk Simulator Software, the Moving Average Model, Exponential Smoothing Model, and Holt-Winters Model were adapted and analyzed. The best model is chosen based on error compare meaning. There are three statistical errors in this study which are used for comparison purposes as RMSE, MSE, and MAD. As a result, the lowest error values for both Bin 1 and Bin 2 are shown on the Moving Average model. Therefore, the Moving Average Model can be concluded at Administration Cafe in UiTM Tapah Campus as the best equipped model based on current organic waste generation. The best model will be used in future at Administration Cafe in UiTM Tapah Campus to predict organic waste generation.
The study is focusing on the environmental care components in solid waste management among students at UiTM Campus Tapah. This study is conducted through a questionnaire and involved a total of 354 students. The environment care components are consisting of knowledge, practice, attitude, perception and awareness. Statistical analysis of mean score and t-test are conducted in order to analyze the data collected. The results of the survey are highlighted that majority of the UiTM Tapah students had high knowledge level towards environmental care; and had very good practice in environment cleanliness; had a moderate concern on attitude, and the majority of the students had moderate perception in term of understanding and practicing solid waste separation and finally majority of students know their personal accountability towards environment care based on awareness component. As a conclusion, environmental care among students shows positive responses in Awareness, Practice, Attitude, Knowledge and Perception towards sustainable solid waste management in future.
In today's rapidly changing, technology-driven world, digital literacy has become increasingly important. As the use of technology continues to grow, it is vital that students possess the necessary skills to effectively navigate and utilize digital tools. Formal education students guided and assessed by instructors help develops a nation. Digital literacy requires creativity, security, and social awareness. This research's biggest problem is classifying students' digital literacy to meet the increased need for digitally proficient employment. To give students the skills they need to succeed in today's digital environment, it's important to know how to classify students by digital literacy. Thus, the goal of this study is to analyse digital literacy, determine skill and attitude levels, and examine the relationship between skill and attitude among UiTM students. The study sampled 364 students. Voluntary sampling to manage sample composition. Two types of analyses been conducted to achieved research objectives. Descriptive Analysis comes prior to Spearman Rank Correlation. The study assessed students' digital literacy by examining their computer and internet skills and attitude towards technology. 50% of respondents had "Sometimes" to "Every time" application skills. The study also found a weak positive correlation (0.300) between computer and internet skills and technology attitude, indicating room for improvement in encouraging students to use technology. The correlation was significant at 0.01 (p=0.000). University students, mostly women, were surveyed on their digital skills and technology use. Most participants used computers daily and were competent. Students liked technology and preferred using their computers at home. The study indicated a weak positive correlation between digital skills and attitude, suggesting space for improvement in encouraging technology use.
Cognitive is relating to cognition. It refers to the method by which knowledge is acquired and manipulated. Usually, cognition is mental. The mental processes associated with phenomena such as concentration, logic, thought and evocation. Generally, characterized as reflects the mind. It is not observable directly, but it must be inferred. Malaysian educators trying so hard to make sure all students master or at least having good knowledge in Mathematics. Investigation on cognitive levels towards performance of Mathematics score among secondary school’s students is the main purpose of the study. A secondary data was used for the process of investigation. A total of 118 secondary school’s students in Tapah were involved randomly. The analyses were started using multiple linear regression with the aid of IBM SPSS version 24. Results show that cognitive levels significantly affect the performance of Mathematics score. These cognitive levels include Knowledge (C1), Comprehension (C2), Proficient (C3), Synthesis (C5), and Analysis (C6). Among five levels of cognitive, results show that Comprehension (C2) or in other words understanding of facts and ideas give the highest impact towards the performance of Mathematics score. If the students do not understand well in topics covered from Mathematics, they will not perform well in Mathematics. In this situation, both teachers and students play an important role to make better results in Mathematics.
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