Safwati Ibrahim
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Preferred name
Safwati Ibrahim
Official Name
Safwati, Ibrahim
Alternative Name
Ibrahim, Safwati
Safwati, Ibrahim
Safwati, I.
Ibrahim, S.
Main Affiliation
Scopus Author ID
57191950629
Researcher ID
GDL-1857-2022

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  • Publication
    Comparative Study of Three Methods for Determining Weibull Parameters in Pauh Putra, Perlis
    ( 2021-06-11)
    Thiraphorn B.L.
    ;
    Leow Wai Zhe
    ;
    Mohd Irwan Yusoff
    ;
    Safwati Ibrahim
    ;
    Muhammad Irwanto Misrun
    ;
    Kumuthawathe Ananda-Rao
    ;
    Amelia A.R.
    This paper studied about analysis characteristics of wind speed at Pauh Putra, Perlis, where nearest to Chuping station, Perlis, Malaysia. The wind speed characteristics consist of monthly and annual wind speed in Perlis, Malaysia. By using Weibull distribution, three different methods to calculate the potential of wind power generation and analysis the characteristics of wind speed at Pauh Putra, Perlis. The results present the means wind speed is 1.0790 m/s and 1.1321 m/s for 2018 and 2019, respectively. The highest monthly mean wind speed occurred in February for both years, 2018 and 2019. Besides, the lowest monthly wind speed for 2018 in May and for 2019 in October. The Weibull distribution summarized the highest probability density is 120% in the wind speed, 1.1 m/s using the Maximum Likelihood Method (MLM) method for these two years. Furthermore, this research found that the Energy Pattern Factor (EPF) Method is stretched to the right, and its height decreased from other methods for both years based on the graph of the wind speed of probability density function. The Maximum Likelihood Method (MLM) for these two years is higher because its shape parameters are relatively higher based on the graph of the wind speed of probability density function.
  • Publication
    Development A Portable Solar Energy Measurement System
    ( 2021-07-26)
    Atika Z.
    ;
    Leow Wai Zhe
    ;
    Iszaidy I.
    ;
    Mohd Irwan Yusoff
    ;
    Safwati Ibrahim
    ;
    Muhammad Irwanto Misrun
    ;
    Wafi N.M.
    ;
    Saw S.X.
    This project presents the design and development a portable measurement device for measure and monitor solar panel parameters by using Internet of Things (IoT) concept. Solar energy measurement plays a very important role in the measurement of parameter reading for the determination of output generated, but the challenge is only performed manually at the work site using a clamp meter or a multimeter. Furthermore, it was very difficult to get the value at that time, and the data recovery error occurred. There are three specific objectives have been used for the project. Firstly, the relevant circuits for this project are design and built the circuit by using software. The output of the measurement solar irradiance, ambient temperature, solar panel temperature, current and voltage value were displayed on LCD. Next, IoT concept is used for solar panel measurement and monitoring. The value of the measurement and monitoring is used ThingSpeak cloud and ThingView application on the smartphone. It can be collected the portable solar for the energy measurement system can monitor on site, anywhere and anytime using IoT platform.
  • Publication
    Simulation study on photovoltaic panel temperature under different solar radiation using computational fluid dynamic method
    ( 2020-01-07)
    Leow W.Z.
    ;
    Mohd Irwan Yusoff
    ;
    Safwati Ibrahim
    ;
    Muhammad Irwanto Misrun
    ;
    Amelia A.R.
    ;
    Syafiqah Z.
    ;
    Muhammad Izuan Fahmi Romli
    ;
    Norfadilah Rosle
    The electrical production is the primary performance of any solar photovoltaic (PV) system. The PV panel operating temperature is inversely proportional to the electrical production of the PV panel. The operating temperature of PV panel is influenced by solar radiation absorbed and the ambient temperature. In the present work, Computational Fluid Dynamics (CFD) method is used to investigate a three-dimensional (3-D) model of a PV panel. It is also essential to estimate the thermal behaviour of the PV panel under various environmental conditions. The primary purpose of this current work is to analyse temperature distribution from the PV panel under given operating conditions. The model geometry is built by using CATIA design software. ANSYS software was simulated the different intensity of solar radiation that applied to the PV panel in order to observe the temperature distribution on each layers of the PV panel. The ambient temperature of the simulation is fixed 35C according to the maximum ambient temperature captured in Malaysia. The simulation results show that an increase in solar radiation intensity along with the PV panel operating temperature increase.
  • Publication
    Technologies of solar tracking systems: A review
    ( 2020-03-20)
    Amelia A.R.
    ;
    Mohd Irwan Yusoff
    ;
    Safwati Ibrahim
    ;
    Leow Wai Zhe
    ;
    Mohd Hafizuddin Mat
    ;
    Mohamad Shukor Abdul Rahim
    Solar energy is abundantly in nature and sustainable energy resources around the world. The main challenge with the solar field is less amount of sun energy captured by using photovoltaic (PV) systems. The great performance of the PV systems can be achieved if the panel is kept perpendicular to the direction of the radiations of sun. Hence, solar tracker system is the method to keep the optimum position of the PV panel for always perpendicular to the solar radiation. This paper aims to review on various technologies of solar tracking to determine the best PV panel orientation. The various types of technologies of solar tracking system have been discussed which includes passive solar tracker, active solar tracker and chronological tracker system. The movement degrees of solar tracking system also have been addressed which consisting single-axis solar tracking system and dual-axis solar tracking system. This paper is also overviews the tracking techniques performance, construction, performance, advantages, and disadvantages of existing solar tracking system. The limitations of solar tracking systems are also highlighted for future action improvement. Through this research studies, the most favorable solar tracking system was identified as active solar tracker with the dual axis rotation.
  • Publication
    Evaluation of predictors for the development and progression of Diabetic Retinopathy among diabetes Mellitus Type 2 patients
    ( 2022-12)
    Syafawati Ab Saad
    ;
    Maz Jamilah Masnan
    ;
    Karniza Khalid
    ;
    Safwati Ibrahim
    Diabetic retinopathy is one of the microvascular complications caused by prolonged uncontrolled diabetes. It is believed that diabetic retinopathy correlates with certain predictors and risk factors that might worsen the disease, eventually causing visual loss and blindness among diabetes patients. There are some predictors and risk factors that attribute to the development and progression of diabetic retinopathy, such as the duration of diabetes and HbA1c trends. This study aims to evaluate the predictors and risk factors associated with the development and/or progression of diabetic retinopathy. Retrospective data were collected from a single healthcare facility in the northwest of Peninsular Malaysia. Patients included in this study were those with type 2diabetes mellitus diagnosed with diabetic retinopathy. The total number of patients involved in this study were 197, where 161 of them were newly diagnosed or with progressive diabetic retinopathy. The characteristics of diabetes patients with complication of diabetic retinopathy were described through descriptive statistics. Characteristics include demographics data such as age, gender, race and clinical data such as HbA1c readings HbA1c, estimated glomerular filtration rate (eGFR), urea and haemoglobin concentration (Hb). The results show that 7 predictors and risk factors are significant to the development and progression of diabetic retinopathy among diabetes patients. By using multinomial logistic regression, this study offers better understanding of the significant predictors and risk factors related to diabetic retinopathy.
  • Publication
    A Case Study of Coffee Sachets Production Defect Analysis Using Pareto Analysis, P-Control Chart and Ishikawa Diagram
    ( 2021-01-01)
    Idris N.I.
    ;
    Sin T.C.
    ;
    Safwati Ibrahim
    ;
    FadzliRamli M.
    ;
    Rosmaini Ahmad
    Nowadays, food and beverages companies in Malaysia are struggle to survive with their rival, hence improving quality and increase productivity are vital. This paper propose the method of analysis a coffee sachet production defectives by using statistical process control (SPC) tools and also to identify each types of defects with their root cause. This paper are using methodology of physical observation through examination of automated production flow line, then Ishikawa cause-and-effect diagram are created. The company valid information are obtained from the professional such as production managers, quality control executives and line supervisors, also staffs and operators that direct or indirectly involves the production line activities through interview and distributed feedback form. After that, a Pareto diagram analysis is done hence creating a control chart (p-chart) to illustrate the result analysis. The result shows there are high number of product defectives according to each type and waste production occur. The problem found was underweight, leaking, overweight, empty, unsealed and height out of the standard. The major causes of defectives coffee sachet and root causes of each defect types are specified which are human, machine, work methods, and materials. While the main root cause of underweight and leaking defect are caused by unskilled worker and improper adjustment at the machine each time before running the production.
  • Publication
    Product defect prediction model in food manufacturing production line using multiple regression analysis (MLR)
    ( 2021-07-21)
    Illa I.N.
    ;
    Tan Chan Sin
    ;
    Fadzli R.
    ;
    Safwati Ibrahim
    ;
    Rosmaini Ahmad
    ;
    Mohd Fathullah Ghazli@Ghazali
    This paper aims to develop an improved general mathematical model by focusing on human factors variables that related to the product defect in the manufacturing production line. This is because many studies found that almost 40% of total defects resulted from the operator error and the defects are usually not obvious and neglected. The objective to have defect prediction mathematical model to satisfy as early quality indicator of the manufacturing flow production line and assist the quality control team in manufacturing industries. Thus, the human factor variables will be investigate thoroughly and final model can be used to predict product defect on the line to improve product quality. Product defects quantity are identified and analyzed to determine the potential predictors for developing the mathematical model. A case study is offered that illustrates in a spice packaging semi-automated production line the effect that complexity variables have on assembly quality. By using Minitab, Multiple Regression analysis is conducted to model the relationship between the input variables towards response variables. From the analysis, the predicted data showed reasonable correlation with the observed data improved with adjusted R-Sq from 2.6% to 7.9%. Hence, the regression equation obtain is selected to be the prediction mathematical model for defects based on human factor input variables.
  • Publication
    Assessment of wind power potential in the North region of Malaysia, Chuping Perlis
    ( 2023-01-01)
    Thiraphorn B.L.
    ;
    Leow Wai Zhe
    ;
    Safwati Ibrahim
    ;
    Irwan Y.M.
    ;
    Muhammad Irwanto Misrun
    ;
    Tan X.J.
    ;
    Ananda-Rao K.
    The wind turbines is a main device that convert the kinetic energy from blades to electrical energy. Before installing wind turbines, the Weibull probability distribution must be calculated to determine the certain wind speed probability. Many problems will come if there no analysis the characteristics of wind in selected location, such as wind speed that not suitable for building wind farm to supply the population in that area. Shape and scale factors, which be controlled in a variety of ways, influence the Weibull distribution. Many studies have looked into which of the various Weibull parameter estimation methods is the most dependable. However, because the results of these investigations were inconsistent, research into more trustworthy Weibull parameter estimation methods is still ongoing. An analysis of data collected Chuping, Perlis for two years was conducted in this study (from 2018 to 2019). By using statistical analysis to evaluate the Weibull distribution method, this study used three methods to compared the Weibull parameters and identified the most reliable and effective method to obtain the Weibull probability distribution by using a three approach that compares the variances of RMSE, MSE and R2, which provides comprehensive insight into level error and volatility. Modified maximum likelihood method, graphical method, and power density method are the three methods used in this study. Therefore, the graphical method has the best accuracy in the wind speed distribution prediction, several methods such as the modified maximum likelihood method, and the power density method have the worst prediction of the wind speed distribution based on all the statistical method variances for this region.
  • Publication
    A review of detecting outlier in a circular regression model
    ( 2020-03-20)
    Ramlee, Intan Mastura
    ;
    Safwati Ibrahim
    ;
    Leow Wai Zhe
    ;
    Mohd Irwan Yusoff
    Circular data is very relevant and important application technique in many fields such as physical science, medical science and others. During the last few years, writers have shown a deep interest of outlier detection in the circular regression model. In this case, authors have a tendency to study and explore in detail about the outlier detection in circular regression model. This paper aims to review the outlier detection methods in circular regression model. Here, we concentrate the attention on the methods of identifying outlier in this model. These survey of circular regression models in which many interesting properties and is good enough to detect the occurrence of outlier. Through the survey may highlight the significant of methods to detect outliers in circular regressions model and provide guideline for future work to look into the research gap.
  • Publication
    Predictor selection for progression and development of diabetic nephropathy among diabetes mellitus type 2 patients
    ( 2023-04-24)
    Syafawati Ab Saad
    ;
    Maz Jamilah Masnan
    ;
    Karniza K.
    ;
    Safwati Ibrahim
    The prevalence of diabetic nephropathy is thriving worldwide such as in the United States, Europe and Asia. Diabetic nephropathy or commonly known as "diabetic kidney disease"(DKD) is characterized by the present of albuminuria, hypertension and progressive renal failure. A variety of predictors are associated with the development, progression and severity of diabetic nephropathy. This study divides diabetes patients with diabetic nephropathy into three groups; Group 1 (diabetes patients who were diagnosed with diabetic nephropathy with the same stage for a certain period of time until the current follow-up), Group 2 (diabetes patients who were diagnosed with diabetic nephropathy without obvious clinical findings but have shown disease development) and Group 3 (diabetes patients who were diagnosed with diabetic nephropathy at a certain stage for a period time but progressively worsen over time during the current follow-up). The purpose of this study is to evaluate the predictors that are associated to patients in Groups 2 and 3. Retrospective data were collected from a healthcare center located in northern peninsular Malaysia. A total of 194 patients were included in this study. Characteristics of data include demographics information such as age, gender, race and clinical data such as glycosylated haemoglobin (HbA1c), estimated glomerular filtration rate (eGFR), urea and haemoglobin concentration (Hb). Findings show that few predictors and risk factors are significant to the development and progression of diabetic nephropathy. This study is important to reveal the significant predictors and risk factors as healthcare professionals can identify patients with risk for diabetic nephropathy and may reduce the morbidity and mortality among patients.