Structures in Malaysia, particularly commercial buildings, have been exceeding the benchmark of building energy usage over the past few years. By maintaining thermal comfort of building under hot climate in Malaysia, air-conditioning system became a basic demand which incessantly operating to fulfil comfort requirement for the occupants in the library. Regards to this, research on energy efficiency using Building Information Modelling (BIM) software by simulating energy analysis was carried out in order to increase energy efficiency of the library. Mineral wool and Polyurethane Foam (P.U.F.) are the materials which proposed to apply in existing wall of building as the thermal insulation layer to increase thermal resistance when external heat transfer through the walls. The Objective of the study is to determine the existing building energy consumption and compare with energy analysis of mineral wool and polyurethane foam. The findings of the building energy analysis simulated by Green Building Studio (GBS) are then compared to discover the most appropriate walls for reducing the building’s energy consumption. P.U.F with its characteristics of high R-value and low U-value, obtain the most effective energy analysis which provide benefits of lowering total annual energy consumption of 294,651 , total annual energy cost of RM 107,645, and energy use intensity (EUI) of 121.7.

Keywords : Energy efficiency; Building Information Modelling (BIM); Mineral wool; Polyurethane Foam (P.U.F.); Green Building Studio (GBS)

Recently, the rise of sea level has caused an increase in rising tides that affected about three million locations around the world. The tide rising phenomenon has been occurring in Peninsular Malaysia since the 20th century. The purpose of this study is to determine the most critical station and forecast three stations located on the West Coast of Peninsular Malaysia. The Box Plot analysis method has been used in this study; the results shown that Bagan Datuk Station is the most critical station. This is due to the maximum tide’s value of Bagan Datuk Station experienced the highest increment of 0.45 m, compared to Port Klang station and Permatang Sedepa Station with only 0.2 m increment in 10 years. However, these three stations are also experiencing rising tides. Thus, the focus of managing coastal structures should be given to all these three stations as well. In addition, for forecasting, the Artificial Neural Network (ANN) forecasting model provides better forecasting results compared to the Autoregressive Integrated Moving Average (ARIMA) model for long-term forecast. In this study, the artificial Neural Network (ANN) forecasting model obtained value of RMSE 0.05642 at Bagan Datuk Station compared to the RMSE value of 0.0928 obtained from the ARIMA model at the same station. Besides, MAE value of ANN method, 0.04387 compared to the MAE value of ARIMA which is worth 0.06391 at Bagan Datuk Station. This study can conclude that the Artificial Neural Network (ANN) forecasting model is better in high tide forecasting.

Keywords: Tidal rising; Coastal flooding; Forecasting; Artificial Neural Network (ANN); ARIMA

The study was carried out to determine the classes and parameters that influence the water quality in the Straits of Johor using the Marine Water Quality Index (MWQI) method and the multi-variable statistical analysis, namely Principal Component Analysis (PCA). The MWQI method classifies the data sets according to four classes of contaminated, medium, good and very good classes. The data were studied from 2016 to 2017 according to two monsoon seasons – the northeast and southwest monsoons. The results for both seasons were compared to find out the difference. The results of the PCA analysis show the relationships between the parameters studied and determine which parameters are responsible for changing water quality standards. The results of the MWQI method reveals that all stations except WQ14 is in class 3 which is moderated while only WQ14 is in class 4 (contaminated). In terms of monsoon, the results of the analysis at the southwest monsoon station found that 25 out of 35 data were in class 3 while the other 10 were in class 4. In addition, MWQI analysis on the northeast monsoon found that 34 out of 35 data were in class 3 and only one was in class 4. These results show that the water quality in the northeast monsoon is better than in the southwest monsoon. The results from the PCA analysis indicates that fecal coliform, total suspended solids and phosphate influence the water quality at the southwest station while the dissolved oxygen and phosphate parameters influence the water quality at the northeast station due to high positive load values. In conclusion, MWQI was able to determine the class of water whilst PCA allowed the identification of types of parameters that affect the water quality. In conclusion, the two above methods can be used to determine pollution levels in water bodies.

Keywords: Marine Water quality; MWQI method; PCA analysis

In this study, several analytical models were tested to forecast the surface ozone concentration using Artificial Neural Network (ANN), Multiple Linear Regression (MLR) and Time Series Regression (TSR). Four study areas were selected in this study, namely Seberang Jaya in Penang, Shah Alam in Selangor, Larkin in Johor and Kota Bharu in Kelantan. The main objective of this study is to determine the appropriate analytical models MLR and ANN for surface ozone forecasting in some zones of peninsular Malaysia, to forecast surface ozone concentration with TSR model in several zones of peninsular Malaysia and to compare the performance of each model by the performance index. The performance index that will be shown in this study for the model comparison are root mean square error (RMSE), mean square error (MSE) and determination of coefficient (R2). The ANN model showed better performance compared to the MLR and TSR models in the model comparison in each station. The station in Larkin, Johor provides high accuracy in forecasting surface ozone concentrations for each model with minimum MSE, 0.000009 ppm and RMSE, 0.0042 ppm compared to other stations. The value of R2 is 0.33 which is highest compared to station in Seberang Jaya and Kota Bharu.

Keywords: Artificial Neural Network; Multiple Linear Regression; Time Series Regression; ozone; performance index

The growth of air pollution as a serious concern throughout the country is influenced by several causes sourcing from transportation, combustion, and industrialization. These factors reduced the air quality which harms society, animals, and plants’ well-being. Surface ozone is one of the main causes of air pollution in developing areas around the world. Analysis of surface ozone by area and season variations increased during summer were associated with meteorological parameters such as atmospheric temperature and humidity, meanwhile, the concentration of surface ozone is low during the northeast monsoon season. In addition, the concentration of surface ozone also increases when there are other environmental influences such as the release of pollutants from anthropogenic activity. Therefore, a study will be carried out to identify the variation of surface ozone concentrations by region and monsoon season in peninsular Malaysia, especially in the northern, eastern, and western zones, to identify the highest duration for daily ozone concentration (O3) and to study the relationship between the monthly and annual surface ozone concentrations with meteorological parameters. The results in this study can be used to identify air quality and address the problem of air pollution so that human health and the environment are preserved by using the method of boxplot and line graph obtained from descriptive statistics.

Keywords: Surface ozone; temperature; humidity; monsoon seasons

The management of solid waste, particularly plastic bottle waste, is becoming increasingly important. The carelessness with which solid waste is managed will have a negative impact on human life. A study was conducted to assess the effectiveness of vocational college students in addressing the problem of discarded plastic bottles. The study was conducted online, with vocational students in Malaysia receiving a link containing animation videos and open-ended questions. The students are then asked for their thoughts on how to solve the problem presented in the video. This study enlisted the participation of 197 vocational college students. The students’ feedback was analyzed using thematic coding analysis in Atlas.ti version 22. According to the findings, this study can be divided into two categories which are initiatives to address the issue of plastic bottle waste dumping and the importance of good plastic bottle waste management and planning. Students’ perspectives on problem-solving initiatives were categorized into seven categories: reuse, awareness, recycling, reducing use, disposal, waste segregation, and enforcement. Furthermore, environmental concerns and health issues are two categories that emphasize the significance of proper plastic bottle waste management. In general, vocational college students are aware of the actions needed to address the real issue of plastic bottle waste. Students are also capable of proposing solutions that are appropriate and in line with government efforts such as the 3R, 5R, and waste segregation at source. Furthermore, students can connect the importance of solid waste management to environmental stewardship and public health.

Keywords: Waste management; plastic bottle; vocational college

Teaching and learning in higher education has gone through a series of transformation in recent decades. Engineering education is one area that would be crucial to undergo such transformation due to the complex nature of engineering application in industries today. The problem facing engineering graduates is the ability to competently solve real world problems using the knowledge learnt during their tertiary education. The learning approach towards problem solving and critical thinking weren’t sufficiently developed throughout the curriculum. One of the theories of learning that was considered was coined by Piaget, cognitive constructivism theory which uses cognitive tools and in collaboration with the environment learners are exposed to. By incorporating such student-centered learning with group learning would improve the students’ achievement in the learning outcome and increase the learning efficacy. This paper describes the application of Ignation Pedagogical Paradigm (IPP) being applied as a model framework in the teaching of one of the courses offered in Bachelor of Mechanical Engineering, i.e. Professional Practice towards strengthening their competencies. By applying a structured formative assessment centered learning environment, the instructor would be able to provide a more holistic learning experience to the students using the cognitive constructivism theory of learning. The results show that the proposed IPP framework is able to complement affectively with the learning theories for engineering education achieving the course outcomes and students would be able to improve their competency in solving complex problem.

Keywords: Engineering education; cognitive constructivism; Ignation Pedagogical Paradigm; formative assessment

A high-level method was obtained to solve the SEI model problem involving Symmetrization measures in numerical calculations through the Implicit Midpoint Rule method (IMR). It is obtained using Non-Standard Finite Difference Schemes (NSFD) with Extrapolation techniques combined. In solving differential equation problems numerically, the Extrapolated SEI model method is able to generate more accurate results than the existing numerical method of SEI model. This study aims to investigate the accuracy and efficiency of computing between Extrapolated One-Step Active Symmetry Implicit Midpoint Rule method (1ASIMR), Extrapolated One-Step Active Symmetry Implicit Midpoint Rule method (2ASIMR), Extrapolated One-Step Passive Symmetry Midpoint Rule method (1PSIMR) and the extrapolated Two-Step Passive Symmetry Midpoint Rule method (2PSIMR). The results show that the 1ASIMR method is the most accurate method. For the determination of the efficiency of 2ASIMR and 2PSIMR methods have high efficiency. At the end of the study, the results from the numerical method obtained show that Extrapolation using Non-Standard Finite Difference has higher accuracy than the existing Implicit Midpoint Rule method.

Keywords : Non-standard finite difference schemes;Extrapolation; SEI model; Implicit midpoint rule; Symmetrization

Permanent magnet synchronous motors (PMSM) are widely used in low to mid-power applications and high-performance drives. They are preferred over brush-type motors and gradually replacing induction motors in various fields of application due to its advantages. Many researchers are proposing new control methods of PMSM drive system. However, the PMSM system is nonlinear and consists of time-varying parameters with high-order complex dynamics. Due to these factors, researchers cannot rely only on simulation results to prove superiority of their proposed controllers. To validate the results obtained by simulation, experimental validation is necessary, where a closed-loop PMSM drive system prototype has to be developed. This paper describes the development of a PMSM drive system prototype with closed-loop current, speed and position feedback using dSpace DS1104 controller board for a 1.93kW three-phase interior-mounted permanent magnet synchronous motor used for experimental validation of a proposed modified fractional order sliding mode speed controller. Using this prototype, the performance of any newly proposed control methods in real applications can be verified. Appropriate signal acquisition procedures of the feedback signals, as described in this work, are crucial to ensure the accuracy of closed-loop performance of the developed drive system.

Keywords: Permanent magnet synchronous motor; prototype; closed-loop control

Momentum and thermal boundary layers stimulated by magnetohydrodynamic flow (MHD) on moving plate surface in single and multiwall carbon nanotubes (SWCNT and MWCNT) with slip and thermal radiation effects were studied. The mathematical modelling is developed to derive the governing partial differential equations. These models were transformed into a system of nonlinear ordinary differential equations via similarity transformation, which are then solved numerically using the boundary value problem with fourth-order accuracy (bvp4c) solver in MATLAB software. The effects of relevant parameters such as nanoparticle volume fraction, magnetic field, slip and thermal radiation on heat transfer are analyzed and discussed. It is found that dual solutions exist in opposing flows. The study also found that the heat flux on the moving plate increased with the increasing in slip effect. Also, the heat transfer rate in SWCNT-water is higher than that of MWCNT-water.

Keywords: Boundary layer; heat transfer; MHD; carbon nanotube

Nowadays, monitoring health systems in robust technology has been extensively applied in the sports field. Even though massive utilization of wearable device technologies aims to quantify athlete performance, inconsistent performance still exists between training sessions and competition. The rigorous discussion about the latest research in monitoring technological systems will help trainers obtain accurate data about athlete performance. This paper focuses on the athlete monitoring system in terms of psychological and physiological parameters and applications in individual sports based on Internet of Things (IoT) Technology. The study incorporates three factors: the parameters that affect athlete performance, multiple device sensors in sports health monitoring, and IoT technology’s application for athletes. Based on analysis and observation, efficient sports health monitoring can effectively enhance athlete performance in physiological and psychological conditions. An IoT system encompasses four main aspects: sensing, networking, data processing and application layer. These aspects provide real-time information on the athlete’s body condition during training and games. Therefore, this monitoring system greatly assists coaches in designing practical training and activities for athletes. It is highlighted that wearable health monitoring systems by IoT technology will be further built based on athlete requirements.

Keywords: Athlete performance; biosensor; internet of things; monitoring system; wearable sensor

ABSTRACTMaterial selection is one of the main factors in the building structure. In this study, an alternative method was implemented using fractal analysis method. The use of this method can be used for cost savings and accident rates to identify the mechanical properties of each material. The purpose of this research is to study the time series resulting from experiments using piezo film sensors using fractal analysis and investigating the properties of different mechanical materials (poisson ratios) with different impact forces using fractal dimensions. There are four types of selected materials namely brass, copper, mild steel and stainless steel which is in round in shape. Different impact forces are generated by using an impact hammer and subsequently a vibration signal is obtained from a piezo film sensor. Using Matlab software, analysis using the fractal method was performed. The fractal dimension was obtained from the gradient values of the log-log plot and the fractal dimension was calculated for each impact force applied to each specimen. Then, fractal dimension values were compared using CES Edupack2012 for characterization of the properties of each material. It can be concluded that the value of fractal dimension increases when the impact forces increase too whereas a decrease in the poisson ratio occurs when the fractal dimensions of each material increase.

Keywords: Costing box; impact forces; piezofilem sensor; vibration signal; poisson ratio

The aim of the study was to determine the feasibility of implementing a ducted propeller system for small scale drones. 5” propeller drones are common in first person view (FPV) drone racing and cinematography, increasing the likelihood of injury due to untrained pilots, of which the majority are laceration injuries due to the propeller blades. Furthermore, the addition of a duct improves the thrust output of the entire system. A few key parameters are identified, of which were manipulated to determine the optimum values through a series of ANSYS Fluent CFD simulations. Introducing a duct is shown to reduce the lift a propeller produces; however, the reduction is offset by the lift generated by the duct. Blade tip clearance was investigated, with the optimum value found to be 0.25 mm, producing the most lift from the duct and least reduction of propeller lift, and with thrust outputs up to 35.568% more in some cases compared to open propeller. It was observed that increasing the BTC significantly reduced duct lift. Diffuser length simulations provided unconclusive results, with the duct lift varying depending on the diffuser length. However, the optimum diffuser length was determined to be 65 mm with respect to thrust outputs. In comparison, inlet lip radius shows a clear pattern, deviating from the optimum value of 16.5 mm reduces the duct lift produced, with smaller values severely decreasing performance.

Keywords: Propeller drone; ANSYS Fluent; parametric; diffuser

This study focuses on the domain to evaluate graduates’ abilities in TVET system. The reason why this study conducted is to help graduates, university and other stakeholder to overcome the employability crisis among their graduates. Thirteen experts were participated in this Focus Group Discussion. The Focus Group Discussion is a technique used in identifying, discussing and brainstorming the criteria, domain and characteristics through experts’ opinion. The approach used in this study is discussion by Webex platform. After analyzing the data findings in Focus Group Discussion using SPSS software, researcher found that out of thirteen, twelve domains reached a good consensus and agreement. This study is believed to encourage current undergraduates to develop high level future learning skills, competencies and other related abilities regarding their employability and foster training in this area by educational institutions so that can benefit their students.

Keywords: Employability skills; graduates; Focus Group Discussion; TVET; expertise

Solid waste management and environmental care are essential in all countries to ensure sustainability at all times. But awareness on the importance of both is not yet satisfactory. This is evidenced by the increasing amounts of solid waste generated and the lack of oversight due to public community involvement. The purpose of this study is to investigate the sustainability of public awareness on solid waste management and environmental care among the population of Malaysia. This study uses an online questionnaire for the data collection process. The logistic regression method is used to analyze the data. A total of 422 respondents represented by 20.9% were male while 79.1% were female. The results showed that only 37.91% of respondents were aware of solid waste management and concern for the environment. In fact, more than 50% of respondents are still less aware of solid waste management and environmental concerns. This shows that most of the communities in Malaysia had a lack awareness on the importance of waste management and environmental care. The culture and values of individual responsibility play an important role in ensuring that environmental sustainability is maintained. Solid waste management and environmental care coalitions need to have broad coverage across the country so that all communities are aware and understand the shared responsibility for waste management and environmental care. This awareness will help achieve the national agenda through Joint Prosperity as well as the Sustainable Development Goals by 2030.

Keywords: Sustainable public awareness; solid waste management; environmental care; logistic regression

The stability period for post-closure dump and landfill sites in Malaysia is of least concern among scholars and policy makers. The current policy to manage these sites are based on the conventional practices by the local authorities and agencies which do not take into account the sustainability or how environmentally friendly these practices are. The aims of this paper are to identify the most suitable forecasting method for time series data of CO2 emission, to conduct simulation exercise to indicate the stability period of sanitary landfill by using the CO2 emission, and to examine the current policy for the post-closure landfill sites and its current practice in the country. Datasets were obtained from literature and simulation was conducted for the Air Hitam Sanitary Landfill, Puchong, Selangor. The results indicate that the Double Exponential Smoothing is the most suitable forecasting method and another 120 years are required for the gas emission to reach stability, which is in September 2127. The current policy on post-closure dump and landfill sites in Malaysia are explored and other potential options are also discussed.

Keywords: Forecasting method; landfill gas stabilization; post-closure sanitary landfill

The steady two-dimensional flow and heat transfer past a moving plate in a hybrid nanofluid with magnetic fileds slip and thermal radiation effect were studied. The continuity, momentum and energy eqautions for this study are transformed into similarity equations via similarity transformations. Then, the similarity equations are solved numerically using bvp4c solver in Matlab software. The effects of several parameters on the skin friction coefficient and the local Nusselt number are presented and discussed. The results showed that dual solutions exist for a certain range for the nanoparticle volume fraction parameters. It also found that the heat transfer rate increased with the increasing magnetic field effect parameters. Regression analysis was also performed to estimate the value of the local Nusselt number

Keywords: Heat transfer; hybrid nanofluid; similarity equation; regression analysis

Presently, graduates of institutions of higher learning are found to be passive and not competent in carrying out the tasks assigned to them. The number of graduates that fail in a job interview has increased. One of the contributing factors is their ineffective communication skill during the interview, thus failing to exhibit their generic skills abilities in convincing the potential employer. As a proactive move to improve this issue, an initiative was carried out by the Faculty of Engineering and Built Environment (FKAB), Universiti Kebangsaan Malaysia (UKM) to introduce and implement problem-based learning (PBL) activities in the engineering mathematics courses. With the PBL method implemented at the early stage of the study period, the student’s ineffective communication issue can be addressed effectively. It is anticipated that the deployment of the PBL method can generally improve students’ soft skills, especially communication ability in meeting the demand and expectations of industry employers. The objectives of this study are to evaluate the effectiveness of the PBL implementation, thus identifying the benefits and the challenges of the PBL 5 Ladders of Active Learning strategy. In this study, the PBL activity was implemented in the Engineering Mathematics III (Differential Equation) course. To analyse the students’ feedback toward the implementation of the Five Ladders of Active Learning strategy and Self-Directed Learning method, the Rasch Measurement Model application software called Winstep was used. The results showed that the challenges faced during the PBL implementation are the readiness of lecturers as facilitators, the acceptance, and the readiness of students towards the learning process of the 5 Ladders of Active Learning strategy, the conducive learning environment, the crafting and constructing of PBL problems/triggers, the students’ reflection, and the PBL evaluation methods. To ensure that engineering students can master mathematics and generic skills as intended in the program, these challenges must be tackled effectively.

Keywords: Problem based learning; engineering mathematics courses; self-directed learning; 5 ladders of active learning; Rasch Measurement Model

The research is about emotion recognition and analysis based on Micro-blog short text. Emotion recognition is an important field of text classification in Natural Language Processing. The data of this research comes from Micro-blog 100K record related to COVID-19 theme collected by Data fountain platform, the data are manually labeled, and the emotional tendencies of the text are negative, positive and neutral. The empirical part adopts dictionary emotion recognition method and machine learning emotion recognition respectively. The algorithms used include support vector machine and naive Bayes based on TFIDF, support vector machine and LSTM based on wod2vec. The five results are compared. Combined with statistical analysis methods, the emotions of netizens in the early stage of the epidemic are analyzed for public opinion. This research uses machine learning algorithm combined with statistical analysis to analyze current events in real time. It will be of great significance for the introduction and implementation of national policies.

Keywords: Micro-blog; emotion recognition; COVID-19; natural language processing

Qualitative content analysis can be applied to analysing textual words written in different types of reflection assignments. Thus, the aim of this research is to investigate the adoption of problem-based learning (PBL) learning to understanding the knowledge and level of awareness of chemical engineering students regarding graduate unemployment in Malaysia. Participants are 88 second-year students enrolled on the Differential Equation course at the National University of Malaysia. With technological breakthroughs in computerised text analysis that enable researchers to collect and analyse large amounts of textual data, content analysis employing an inductive approach is used to analyse students’ PBL reflective writing which expresses whether all the main factors of graduate unemployment can be identified. The result reveals that almost 80% of participants were unable to meet the requirement of the first stage of PBL, which is to identify the critical learning issue i.e., unemployment factors. This group of students only managed to identify person-related factors associated to unemployment: working experience and soft skills. Only 15 participants, however, have successfully identified all six factors influencing graduate employability. Practical learning, entrepreneurial skills, internal audit and basic qualifications of graduates, along with soft skills and working experience are the main components of the higher education curriculum that have a significant impact on the unemployment problem of graduates in Malaysia if they are revised. The findings have important implications for how the institution can properly plan and take appropriate actions to raise unemployment awareness among students at an early stage of their study.

Keywords: Problem-based learning; content analysis; student’s awareness; differential equations; graduate unemployment

Currently, the construction of high-rise buildings is increasing as the modernization of the city. Especially in the heart of Kuala Lumpur City, construction is more focused on the construction of high-rise buildings due to over-crowded areas. To meet demand due to the activity, the number of tower cranes brought into Malaysia has increased. The tower crane is used to lift construction items and requires a solid base to ensure tower crane stability. Analysis obtained from the Department of Occupational Safety and Health (DOSH), the rate of accidents involving in particular the use of cranes tower cranes occurred due to the failure of the crane foundation. The main objective in carrying out this project is to ensure the stability of the foundations for ensuring the safe use of tower cranes in reducing accident site, determine the calculation of the basic design of the site and the last one is to analyze the stability of the soil through the interaction between the soil and the basic structure of the site. Design calculations from qualified engineers as well as engineering software for analysis tests are an important element in the success of this research project. Among the parameters required are ground properties information for the installed tower cranes, engineering drawings for tower crane structure and Plaxis 3D computer software for analysis purposes. The implication of this project is to achieve the department’s quality policy in providing and maintaining a quality, safe and healthy work and system without any harm and risk.

Keywords: Departmental of Occupational Safety and Health (DOSH); tower crane foundation, micropile, deflection, settlement

Compaction is an important engineering process that ensures the stability of soils by compressing them to a predefined strength. However, in most construction projects, particularly large-scale projects, achieving the appropriate compaction properties, such as optimum moisture content (OMC) and maximum dry density (MDD), it requires time and high cost. Predicting the compaction characteristics from the Atterberg limit, which involves simpler and faster testing techniques, becomes an important task in this scenario. The purpose of this study is to study the comparison of the multiple linear regression (MLR) method with the response surface method (RSM) and artificial neural network (ANN) to determine an accurate, efficient and simple technique to predict soil compaction parameters. For this research, 29 samples were subjected to a variety of laboratory testing. All of the parameters’ statistical relationships were analyzed. In this research, techniques are used, and the findings of these studies are discussed and analysed. To see the performance and accuracy of the model, the criteria for validation of the model used are based on the value of coefficient of determination (R2), absolute mean error (MAE), mean square error (MSE) and mean square root error (RMSE). A comparison with the test data revealed that the coefficient of determination (R2) of ANN model predictions was greater than those of other models. In addition, the findings indicate that the accuracy of ANN models are superior to the statistical models MLR and RSM.

Keywords: Maximum dry density; optimum moisture content; artificial neural networks; atterberg limit; multiple linear regression

TVET is crucial for developing countries in preparation for the 21st-century skills demand. In preparing for those demands, TVET-Institutions is actively engaged in producing a skilled workforce to accommodate the country’s labour market needs. Therefore, an ongoing initiative has been taken in improving and upgrading the current TVET-Institutions to increase a workforce that meet the industry need. However, some of the current TVET-Institutions’ directors came from different background and some of them is not from the engineering or Technical Vocational Education and Training (TVET) administration backgrounds, of which the nature of managing the college is primarily different. Therefore, this study was conducted to suggest an improvement on TVET-Institutions in managing TVET-Institution and industry partnership, which empowered the industry as one of the vital stakeholders. A qualitative research design using the survey design approach, was adopted in this study. The instrument used is survey form. The questionnaires distributed to the respondents through Google Form are open -ended questions. Census sampling and purposive sampling techniques were selected in this research for choosing the right respondents. A total of 87 respondents were selected in this research, consists of experts from Malaysian TVET association bodies, government, and industries. The data were analyzed using Atlas.ti software. This research produces a model as a guide for the way forward to overcome the barriers. This research proposes knowledge expansion on the theory and concept of industry-led knowledge and competency among TVET-Institutions’ directors who can lead to the suggestion of academic and socio-economy increment.

Keywords: Technical vocational education and training; industry; barriers; partnership

A photovoltaic (PV) system is a renewable energy system intended to convert sunlight into the usable electricity. Due to the rapid world infrastructure development, the demand for electricity is increasing drastically. One of the promising energy resources is the PV. The required energy demand can be provided by the increase of PV system deployment. Thus, as part of the design, development and implementation of a new PV system, a system design simulation is essential. This is to ensure that the designed system works properly according to design specifications. For this reason, a PV mathematical model is necessary in the development process of the PV system especially in the MATLAB/Simulink software environment. With the developed PV model, the PV system design and simulation is made handy, thus escalates the future energy demand. This work describes the development of the PV mathematical model in the MATLAB/Simulink software environment based on the PV related equations. The equations are formed by the consideration of the equivalent circuit of PV cell. The developed PV model characteristics such as the Power-Voltage (P-V) and Current-Voltage (I-V) curves are obtained as the simulation output in MATLAB/Simulink. The obtained characteristics are compared to the actual PV model A 100W RNG-50D Renogy, as to verify the effectiveness and closeness of the developed PV model to the real PV module. In addition, in the simulation, a dc-dc boost converter is also designed and integrated with the PV model as to verify the PV module and capability as a PV power source. The simulation results with the dc-dc boost converter DC-DC integration have shown that the developed PV model is very effective to be used for the PV system simulation.

Keywords: Photovoltaic system; DC-DC converter; P-V characteristics; I-V characteristics; MATLAB/SIMULINK

Job readiness questionnaire was developed to measure the level and important element for hospitality graduate. A pilot study was conducted in order to determine the reliability and validity of the questionnaire. There are six constructs were identified such as communication, problem solving, ICT, organization and leadership teamwork, workplace attitude, self-management, and technical skills for this questionnaire. A total of 30 lecturers from Kolej Vokasional Setapak were selected to participated in this survey. Rasch Measurement Model (i.e., PTMEA CORR, item fit, item polarity) was used to analyse the responses using Winsteps. This study found that PTMEA CORR has a positive value, in which items are able to differentiate the capabilities of the respondents. Besides, the results of infit and outfit mean square are ranged between 0.60 and 1.4. The quality of items is high because the reliability value is also high. In addition, the separation of item and person is at the acceptable range. However, statistical data shows that 8 out of 122 items have been dropped.

Keywords: Pilot study; validity; reliability; instrument; Rasch Measurement Model; construct; job readiness

The constant rainfall is important for equatorial regions. The extreme rainfall shows our nature is facing climate change significantly and this needs to be paid attention by researchers hence the effects of disasters can be avoided as early as possible. Therefore, it is important to understand the rain pattern for the existing data so that forecasting can be done. This article discussed how to transform abnormal data into normal data and then analyze the data using the spline cubic analysis method. The study found that by using the transformation algorithm, the best r value is obtained. Cubic spline analysis shows that there are 30 rainfall stations in peninsular Malaysia where there are significant changes in rainfall patterns.

Keywords: Cube spline; log transformation; time series; rainfall data; seasonal pattern