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All Journal International Journal of Renewable Energy Development Proceeding Mulawarman International Conference on Tropical Public Health
Razak, Tajul Rosli
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Chemistry Energy Public Health

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Artificial Neural Network Prediction Model of Dust Effect on Photovoltaic Performance for Residential applications: Malaysia Case Study Ahmad, Emy Zairah; Jarimi, Hasila; Razak, Tajul Rosli
International Journal of Renewable Energy Development Vol 11, No 2 (2022): May 2022
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2022.42195

Abstract

Dust accumulation on the photovoltaic system adversely degrades its power conversion efficiency (PCE). Focusing on residential installations, dust accumulation on PV modules installed in tropical regions may be vulnerable due to lower inclination angles and rainfall that encourage dust settlement on PV surfaces. However, most related studies in the tropics are concerned with studies in the laboratory, where dust collection is not from the actual field, and an accurate performance prediction model is impossible to obtain. This paper investigates the dust-related degradation in the PV output performance based on the developed Artificial Neural Network (ANN) predictive model. For this purpose, two identical monocrystalline modules of 120 Wp were tested and assessed under real operating conditions in Melaka, Malaysia (2.1896° N, 102.2501° E), of which one module was dust-free (clean). At the same time, the other was left uncleaned (dusty) for one month. The experimental datasets were divided into three sets: the first set was used for training and testing purposes, while the second and third, namely Data 2 and Data 3, were used for validating the proposed ANN model. The accuracy study shows that the predicted data using the ANN model and the experimentally acquired data are in good agreement, with MAE and RMSE for the cleaned PV module are as low as 1.28 °C, and 1.96 °C respectively for Data 2 and 3.93 °C and 4.92 °C respectively for Data 3.  Meanwhile, the RMSE and MAE for the dusty PV module are 1.53°C and 2.82 °C respectively for Data 2 and 4.13 °C and 5.26 °C for Data 3. The ANN predictive model was then used for yield forecasting in a residential installation and found that the clean PV system provides a 7.29 % higher yield than a dusty system. The proposed ANN model is beneficial for PV system installers to assess and anticipate the impacts of dust on the PV installation in cities with similar climatic conditions.
Prognostic Scoring for Chronic Kidney Disease Among Type 2 Diabetes Patients in Malaysia: A Review of the i-CKD Tool Khebir, Muhammad Hariz ‘Ammar; Razak, Tajul Rosli; Hafidz, Muhammad Iqbal Abdul; Ismail, Nurhuda; Isa, Mohamad Rodi
Mulawarman International Conference on Tropical Public Health Vol. 2 No. 2 (2025): The 4th MICTOPH
Publisher : Faculty of Public Health Mulawarman University, Indonesia

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Abstract

Background : Chronic kidney disease (CKD) is a major complication of type 2 diabetes and contributes significantly to morbidity and healthcare costs in Malaysia. Early recognition of individuals at risk is essential, yet current clinical prediction practices remain inconsistent and are not systematically informed by combined clinical and biochemical parameters. A structured prognostic score offers a systematic approach to support early risk stratification and timely intervention. Objective : This review aims to synthesize evidence on the development and validation of the i-CKD prognostic scoring tool designed to predict chronic kidney disease risk among patients with type 2 diabetes in Malaysia. Research Methods/ Implementation Methods : This review will explore the staged development process of the i-CKD score, including the identification of key predictive factors, development of the scoring model, and subsequent internal and external validation. The methodological evaluation will emphasize the selection of predictors and statistical assessment of model discrimination and reliability throughout each phase. Results : A prognostic scoring tool (i-CKD score) will be developed and undergo internal and external validation to determine its predictive performance. Conclusion/Lesson Learned : This review underscores the value of structured risk stratification in the early detection and management of chronic kidney disease. While various prognostic tools have been proposed, limitations in standardization, validation, and clinical integration persist. The i-CKD score has the potential to strengthen clinical decision-making by supporting earlier identification of high- risk individuals.
Survival Analysis of Diabetic Retinopathy Among Type 2 Diabetic Patients: A Systematic Review Teruna, Muhammad Muaz Shahriman; Razak, Tajul Rosli; Yasin, Siti Munira; Ali, Abdullah Ashraf Rafique; Isa, Mohamad Rodi
Mulawarman International Conference on Tropical Public Health Vol. 2 No. 2 (2025): The 4th MICTOPH
Publisher : Faculty of Public Health Mulawarman University, Indonesia

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Abstract

Background : Diabetic retinopathy (DR) is a major preventable microvascular complication of type 2 diabetes mellitus (T2DM) and a leading cause of visual impairment. Understanding survival time to DR onset and its modifiable predictors is essential for optimizing screening and management. This review synthesizes recent cohort and observational evidence on DR incidence, progression, and prognostic factors in adults with T2DM. Objective : This study aims to systematically review survival time to the onset or progression of diabetic retinopathy in adults with type 2 diabetes mellitus, evaluate prognostic factors influencing retinopathy-free survival, and compare survival patterns across populations and study designs to inform future prognostic models and prevention strategies. Research Methods/ Implementation Methods : A systematic search was conducted for articles published between 2016 and 2025 across major databases including PubMed, Scopus, ScienceDirect, and the Cochrane Library. Studies were included if they applied longitudinal, cohort, or survival analysis methods to assess the risk or progression of DR among T2DM patients. Seventeen eligible studies were identified, covering diverse populations across Asia and Europe. Data were extracted on study design, sample size, follow-up duration, key predictors, and outcomes. Findings were synthesized narratively due to heterogeneity in statistical models and outcome definitions. Results : Across the included studies, the cumulative incidence of DR ranged from 8% to 42% over follow-up periods of 3 to 15 years. Significant predictors of DR onset and progression included poor glycaemic control (HbA1c ≥ 7.5%), longer diabetes duration, hypertension, dyslipidaemia, and obesity indices. Novel biomarkers such as the glycaemic risk index (GRI), neutrophil-to-lymphocyte ratio, and vitamin D deficiency demonstrated emerging prognostic potential. Conversely, metformin use and higher physical activity levels were protective against DR development. Time-to-event analyses revealed that patients maintaining a tight glycaemic range (3.9–7.8 mmol/L) and regular physical activity exhibited longer DR-free survival. Geographic variations were observed, with higher incidence reported in East and Southeast Asian cohorts compared to European populations. Conclusion/Lesson Learned : This systematic review highlights the multifactorial determinants influencing the survival and progression of diabetic retinopathy among individuals with T2DM. Glycaemic variability, metabolic dysregulation, and inflammatory markers remain strong predictors of reduced DR-free survival, while lifestyle modification and pharmacological control confer protective benefits. These findings underscore the importance of integrated, longitudinal monitoring and early preventive strategies in diabetic eye care. Future survival models should incorporate composite risk indices and real-world data to improve prediction accuracy and clinical applicability.
Prognostic Models for Recurrent Bacteriologically ConfirmedTuberculosis: Evidence and Applications in Malaysia Rameli, Nur Adila Che; Razak, Tajul Rosli; Ismail, Nurhuda; Ismail, Ahmad Izuanuddin; Teruna, Muhammad Muaz Shahriman; Salleh, Muhammad Muzzammil Mohamad; Yusoff, Mohamad Zuhair Mohamed; Khebir, Muhammad Hariz ‘Ammar; Sallehhu, Muhammad Irfan Mohd
Mulawarman International Conference on Tropical Public Health Vol. 2 No. 2 (2025): The 4th MICTOPH
Publisher : Faculty of Public Health Mulawarman University, Indonesia

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Abstract

Background : Bacteriologically confirmed recurrent tuberculosis (TB) continues to become a hurdle to TB elimination efforts. Patients experiencing recurrence face poorer treatment outcomes, higher mortality and increased risk of community transmission. Early identification of high-risk individuals for recurrence is important to support targeted surveillance, timely clinical follow-up and optimised preventive strategies. A prognostic risk score offers a systematic approach to risk-stratifying and promotes proactive intervention before disease reactivation. Objective : To develop and validate a prognostic bacteriologically-confirmed recurrent TB risk score Methods : Research The process will be conducted in three phases: identification of independent predictors associated with bacteriologically confirmed recurrent TB and development of the risk score, internal validation and external validation. Predictor selection and model development will be using multivariable regression techniques. Model performance will be assessed through discrimination and calibration indices and will be evaluated across phases.Methods/ Implementation Results :This study will produce a validated bacteriologically confirmed Recurrent TB risk score tool. The parameters of sensitivity, specificity, receiver operative characteristics, will be calculated and compared to determine the performance of the tool. Conclusion/Lesson Learned : This study will be able to identify high risk individuals prior to recurrence and has the potential to guide targeted monitoring, strengthen TB control efforts and reduce TB burden. Findings also support evidence based risk stratification for other infectious disease with recurrence potential.
Factors Associated with Ischemic Heart Disease (IHD) among Type 2 Diabetes Mellitus Patients: Evidence from the National DiabetesRegistry of Johor, Malaysia Salleh, Muhammad Muzzammil Mohamad; Kasim, Sazzli Shahlan; Razak, Tajul Rosli; Azahar, Nazar Mohd; Ismail, Norzaher; Yusoff, Mohamad Zuhair Mohamed; Khebir, Muhammad Hariz ‘Ammar; Teruna, Muhammad Muaz Shahriman; Rameli, Nur Adilla Che; Moh, Muhammad Irfan
Mulawarman International Conference on Tropical Public Health Vol. 2 No. 2 (2025): The 4th MICTOPH
Publisher : Faculty of Public Health Mulawarman University, Indonesia

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Abstract

Background : IHD remains a leading cause of mortality among individuals with type 2 diabetes mellitus (T2DM). Despite the availability of extensive registry data, limited local evidence exists regarding factors associated with IHD among Malaysian diabetic populations. Objective : This study aimed to identify demographic, clinical, and pharmacological associated factors of IHD using data from the National Diabetes Registry (NDR) of Johor, Malaysia. Research Methods/ Implementation Methods : A cross-sectional analysis was conducted using NDR data from 11,082 adults with T2DM registered between 2019 and 2021. Sociodemographic, clinical, biochemical, and medication variables were analyzed. Univariable and multivariable logistic regression identified independent associated factors of IHD, expressed as adjusted odds ratios (aORs) with 95% confidence intervals (CIs). Results : The prevalence of IHD among T2DM patients was 10.4% (95% CI=9.8, 11.0). Independent predictors of IHD included age ≥60 years (aOR = 1.57, 95% CI: 1.33–1.86), male sex (aOR = 1.46, 95% CI: 1.25–1.71), Chinese ethnicity (aOR = 1.60, 95% CI: 1.28–1.98), hypertension (aOR = 1.86, 95% CI: 1.38–2.51), dyslipidaemia (aOR = 1.47, 95% CI: 1.16–1.86), diabetes duration > 10 years (aOR = 1.35, 95% CI: 1.10–1.65), and diabetic retinopathy (aOR = 1.52, 95% CI: 1.28–1.79). Non- use of calcium channel blockers (aOR = 1.52, 95% CI: 1.32–1.76) increased IHD risk, while paradoxical inverse associations were noted for non-use of aspirin, ticlopidine, and beta-blockers, likely reflecting confounding by indication. Glitazone use showed a strong association with IHD (aOR = 10.46, 95% CI: 1.423, 76.960), possibly due to small sample bias. Conclusion/Lesson Learned : IHD prevalence among Malaysian diabetics is substantial and driven by multiple modifiable and demographic factors. Integrating artificial intelligence (AI) predictive models within the NDR using these variables could enhance early risk stratification and targeted cardiovascular prevention.
Co-Authors Ahmad, Emy Zairah Ali, Abdullah Ashraf Rafique Azahar, Nazar Mohd Hafidz, Muhammad Iqbal Abdul Isa, Mohamad Rodi Ismail, Ahmad Izuanuddin Ismail, Norzaher Ismail, Nurhuda Jarimi, Hasila Kasim, Sazzli Shahlan Khebir, Muhammad Hariz ‘Ammar Moh, Muhammad Irfan Rameli, Nur Adila Che Rameli, Nur Adilla Che Salleh, Muhammad Muzzammil Mohamad Sallehhu, Muhammad Irfan Mohd Teruna, Muhammad Muaz Shahriman Yasin, Siti Munira Yusoff, Mohamad Zuhair Mohamed