Article Per Year (5 Year)
p-Index From 2021 - 2026
3.276
P-Index
This Author published in this journals
All Journal Bulletin of Electrical Engineering and Informatics Journal of Research and Advances in Mathematics Education Jurnal Manajemen & Keuangan Jurnal Ilmiah Peuradeun Narra J Proceedings of International Conference on Multidiciplinary Research International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET) Aceh International Journal of Science and Technology Ekonomikalia Journal of Economics Journal of Educational Management and Learning Infolitika Journal of Data Science Asian Journal of Public Health and Nursing Media Penelitian dan Pengembangan Kesehatan Geosfera Indonesia Journal on Mathematics Education
Hizir Sofyan
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 24 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 24 Documents
Search

 1   2   3 
Potential Effect of PISA Equivalent Questions Using the Context of Aceh Traditional Houses Usnul, Uliyatul; Johar, Rahmah; Sofyan, Hizir
JRAMathEdu (Journal of Research and Advances in Mathematics Education) Vol. 4, No. 2, July 2019
Publisher : Department of Mathematics Education, Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jramathedu.v4i2.8362

Abstract

The achievement of Indonesian students in PISA remains unsatisfactory, as evidenced by their scores that are below the baseline level set in PISA. One of the contributing factors is that Indonesian students are less trained in solving problems with characteristics such as in PISA items. Therefore, it is necessary to familiarize Indonesian students with PISA equivalent problems, but the availability of these questions is still limited, especially concerning reasoning ability. In addition, the use of context is also crucial, especially the local contexts, which can help students understand mathematical phenomena from the perspective of their life experiences. The purpose of this study was to develop the questions of PISA equivalent mathematical reasoning ability using the context of Aceh traditional houses. This research used formative evaluation type development research from Tessmer. The results of this study were 12 mathematical questions equivalent to PISA using the context of Aceh traditional house. The potential effect of the questions developed was analyzed based on the student's responses to the questionnaire, including two aspects: 1) students are interested and seriously working on the questions and 2) the students are interested in using the equivalent PISA questions in the future.
Development of Website-Based a Health Crisis Reporting System Rimadeni, Yeni; Sofyan, Hizir; Rahman, Safrizal; Pramana, Setia; Oktari, Rina S.
International Conference on Multidisciplinary Research Vol 4, No 1 (2021): ICMR
Publisher : Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (251.767 KB) | DOI: 10.32672/pic-mr.v4i1.3774

Abstract

Health crisis management is prioritized on health crisis risk reduction consisting of pre-health crisis stage, health crisis emergency response stage, and post-health crisis stage. Prevention and mitigation efforts at the pre-health crisis stage, in the context of our study, aim to develop an information system for health crisis management. Information system for health crisis, in general, is provided by the Health Agency. In this study, we discussed the system applied by the Health Agency of Aceh Tengah that still uses a manual information system for reporting during disasters. Hence, it causes a delay of the information updates despite the emergency situation. To overcome this problem, we proposed a newly developed health crisis management reporting system in disaster risk reduction. We used a Research and Development approach with Heuristic Review Analysis to assess the performance of the proposed system. The scope of the study was limited to the development of a new reporting system and system test on users. The research subjects were disaster officers and heads of 14 health centers involved in the health crisis reporting in Aceh Tengah. Improvements can be made in the future through trainings and system adjustments supported by institutional policies. Keywords: Health crisis, disasters, website, reporting system.
Development of Website-Based a Health Crisis Reporting System Yeni Rimadeni; Hizir Sofyan; Safrizal Rahman; Setia Pramana; Rina S. Oktari
International Conference on Multidisciplinary Research Vol 4, No 1 (2021): ICMR
Publisher : Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/pic-mr.v4i1.3774

Abstract

Health crisis management is prioritized on health crisis risk reduction consisting of pre-health crisis stage, health crisis emergency response stage, and post-health crisis stage. Prevention and mitigation efforts at the pre-health crisis stage, in the context of our study, aim to develop an information system for health crisis management. Information system for health crisis, in general, is provided by the Health Agency. In this study, we discussed the system applied by the Health Agency of Aceh Tengah that still uses a manual information system for reporting during disasters. Hence, it causes a delay of the information updates despite the emergency situation. To overcome this problem, we proposed a newly developed health crisis management reporting system in disaster risk reduction. We used a Research and Development approach with Heuristic Review Analysis to assess the performance of the proposed system. The scope of the study was limited to the development of a new reporting system and system test on users. The research subjects were disaster officers and heads of 14 health centers involved in the health crisis reporting in Aceh Tengah. Improvements can be made in the future through trainings and system adjustments supported by institutional policies. Keywords: Health crisis, disasters, website, reporting system.
Spatial Statistic Analysis of Earthquakes in Aceh Province Year 1921-2014: Cluster Seismicity Muzailin Affan; Muhammad Syukri; Linda Wahyuna; Hizir Sofyan
Aceh International Journal of Science and Technology Vol 5, No 2 (2016): August 2016
Publisher : Graduate Program of Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (674.877 KB) | DOI: 10.13170/aijst.5.2.4878

Abstract

The purpose of this study is to apply the analysis of spatial patterns of earthquakes in the province of Aceh by detecting clusters and looking for spatial patterns locally and globally during the period 1921-2014 using GIS (Geographic Information System). The selected techniques are Average Nearest Neighbor, Moran Global Index, the Getis-Ord General G, Anselin Local Moran Index, the Getis-Ord Gi*, and Kernel Density Estimation. Each technique is implemented using GIS so that calculations can be done efficiently and quickly. The results of this study indicate that (1) The techniques can detect clusters of dots on the spatial pattern of earthquakes; (2) Both globally and locally, it shows that earthquakes clustered in the southwestern heading to the northern part of the province; (3) An earthquake with a greater magnitude generally concentrated in the district of Simeulue, the western part of Aceh Besar and northwest of Sabang
Evaluation of atopic dermatitis severity using artificial intelligence Maulana, Aga; Noviandy, Teuku R.; Suhendra, Rivansyah; Earlia, Nanda; Bulqiah, Mikyal; Idroes, Ghazi M.; Niode, Nurdjannah J.; Sofyan, Hizir; Subianto, Muhammad; Idroes, Rinaldi
Narra J Vol. 3 No. 3 (2023): December 2023
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v3i3.511

Abstract

Atopic dermatitis is a prevalent and persistent chronic inflammatory skin disorder that poses significant challenges when it comes to accurately assessing its severity. The aim of this study was to evaluate deep learning models for automated atopic dermatitis severity scoring using a dataset of Aceh ethnicity individuals in Indonesia. The dataset of clinical images was collected from 250 patients at Dr. Zainoel Abidin Hospital, Banda Aceh, Indonesia and labeled by dermatologists as mild, moderate, severe, or none. Five pre-trained convolutional neural networks (CNN) architectures were evaluated: ResNet50, VGGNet19, MobileNetV3, MnasNet, and EfficientNetB0. The evaluation metrics, including accuracy, precision, sensitivity, specificity, and F1-score, were employed to assess the models. Among the models, ResNet50 emerged as the most proficient, demonstrating an accuracy of 89.8%, precision of 90.00%, sensitivity of 89.80%, specificity of 96.60%, and an F1-score of 89.85%. These results highlight the potential of incorporating advanced, data-driven models into the field of dermatology. These models can serve as invaluable tools to assist dermatologists in making early and precise assessments of atopic dermatitis severity and therefore improve patient care and outcomes.
Deep Learning-Based Bitcoin Price Forecasting Using Neural Prophet Noviandy, Teuku Rizky; Maulana, Aga; Idroes, Ghazi Mauer; Suhendra, Rivansyah; Adam, Muhammad; Rusyana, Asep; Sofyan, Hizir
Ekonomikalia Journal of Economics Vol. 1 No. 1 (2023): July 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/eje.v1i1.51

Abstract

This study focuses on using the Neural Prophet framework to forecast Bitcoin prices accurately. By analyzing historical Bitcoin price data, the study aims to capture patterns and dependencies to provide valuable insights and predictive models for investors, traders, and analysts in the volatile cryptocurrency market. The Neural Prophet framework, based on neural network principles, incorporates features such as automatic differencing, trend, seasonality considerations, and external variables to enhance forecasting accuracy. The model was trained and evaluated using performance metrics such as RMSE, MAE, and MAPE. The results demonstrate the model's effectiveness in capturing trends and predicting Bitcoin prices while acknowledging the challenges posed by the inherent volatility of the cryptocurrency market.
Leveraging Artificial Intelligence to Predict Student Performance: A Comparative Machine Learning Approach Maulana, Aga; Idroes, Ghazi Mauer; Kemala, Pati; Maulydia, Nur Balqis; Sasmita, Novi Reandy; Tallei, Trina Ekawati; Sofyan, Hizir; Rusyana, Asep
Journal of Educational Management and Learning Vol. 1 No. 2 (2023): December 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v1i2.132

Abstract

This study explores the application of artificial intelligence (AI) and machine learning (ML) in predicting high school student performance during the transition to university. Recognizing the pivotal role of academic readiness, the study emphasizes the need for tailored interventions to enhance student success. Leveraging a dataset from Portuguese high schools, the research employs a comparative analysis of six ML algorithms—linear regression, decision tree, support vector regression, k-nearest neighbors, random forest, and XGBoost—to identify the most effective predictors. The dataset encompasses diverse attributes, including demographic details, social factors, and school-related features, providing a comprehensive view of student profiles. The predictive models are evaluated using R-squared, Root Mean Square Error, and Mean Absolute Error metrics. Results indicate that the Random Forest algorithm outperforms others, displaying high accuracy in predicting student performance. Visualization and residual analysis further reveal the model's strengths and potential areas for improvement, particularly for students with lower grades. The implications of this research extend to educational management systems, where the integration of ML models could enable real-time monitoring and proactive interventions. Despite promising outcomes, the study acknowledges limitations, suggesting the need for more diverse datasets and advanced ML techniques in future research. Ultimately, this work contributes to the evolving field of educational AI, offering practical insights for educators and institutions seeking to enhance student success through predictive analytics.
Infrastructure Management for Improved Learning Outcomes: Insights from Junior High Schools in Southwest Aceh, Indonesia Istakri, Dedi; Sofyan, Hizir; Ismail, Ismail
Journal of Educational Management and Learning Vol. 2 No. 1 (2024): May 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v2i1.169

Abstract

This qualitative study explores the management of facilities and infrastructure at two junior high schools in Southwest Aceh Regency, Indonesia (SMP Negeri 1 Susoh and SMP Negeri 2 Susoh) and examines its impact on learning quality. The research methodology includes observations, structured interviews, and documentation to collect data from key stakeholders such as principals, deputy principals, and teachers. The findings emphasize the critical role of detailed planning and collaboration among teachers, principals, and school development teams in aligning facility needs with curriculum requirements. Efficient use, storage, maintenance, and care of educational assets are essential for maximizing their functionality and longevity. The study also highlights the importance of comprehensive inventory management that adheres to regulatory guidelines to ensure effective resource control and supervision. However, the schools face challenges including limited land availability, insufficient funding, human resource constraints, and inadequate government support, which impede their ability to provide well-rounded learning environments. The study points out the necessity for ongoing improvement efforts by principals to adapt educational facilities to evolving educational demands. It recommends prioritizing investments in facilities, staff training, and policy enhancements to address these challenges and foster comprehensive educational development. Future research should assess the effectiveness of these management practices in various contexts and their long-term impact on student outcomes.
A Statistical Clustering Approach: Mapping Population Indicators Through Probabilistic Analysis in Aceh Province, Indonesia Sasmita, Novi Reandy; Khairul, Moh; Sofyan, Hizir; Kruba, Rumaisa; Mardalena, Selvi; Dahlawy, Arriz; Apriliansyah, Feby; Muliadi, Muliadi; Saputra, Dimas Chaerul Ekty; Noviandy, Teuku Rizky; Watsiq Maula, Ahmad
Infolitika Journal of Data Science Vol. 1 No. 2 (2023): December 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v1i2.130

Abstract

The clustering, one of statistical analysis, can be used for understanding population patterns and as a basis for more targeted policy making. In this ecological study, we explored the population dynamics across 23 districts/cities in Aceh Province. The study used the Aceh Population Development Profile Year 2022 data, focusing on the total population, in-migrants, out-migrants, fertility, and maternal mortality as variables. The study employed descriptive statistics to ascertain the data distribution, followed by the Shapiro-Wilk test to evaluate normality, which is crucial for selecting the appropriate statistical methods. The Spearman test was used to determine correlations between the total population and the variable as indicators. Probabilistic Fuzzy C-Means (PFCM) method is used for clustering. To optimize clustering, the silhouette coefficient was calculated using the Euclidean Distance and the elbow method, with the results analyzed using R-4.3.2 software. This study's design and methods aim to provide a nuanced understanding of demographic patterns for targeted policy-making and regional development in Aceh, Indonesia. Based on the data normality test results, only fertility (p-value = 0.45), while the other variables are not normally distributed. Spearman test was used, and the results showed that only in-migrants (p-value = 1.78 x 10-6) and out-migrants (p-value = 2.30 x 10-6) correlated to the Aceh Province population. Using the population variable and the two variables associated with it, it was found that 4 is the best optimum number of clusters, where clusters 1, 2, 3, and 4 consist of three districts/city, nine districts/city, four districts/city and seven districts/city respectively.
Unraveling Geospatial Determinants: Robust Geographically Weighted Regression Analysis of Maternal Mortality in Indonesia Rahayu, Latifah; Ulfa, Elvitra Mutia; Sasmita, Novi Reandy; Sofyan, Hizir; Kruba, Rumaisa; Mardalena, Selvi; Saputra, Arif
Infolitika Journal of Data Science Vol. 1 No. 2 (2023): December 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v1i2.133

Abstract

Maternal Mortality Rate (MMR) in Indonesia has experienced a concerning annual increase, reaching 4,627 deaths in 2020 compared to 4,221 in 2019. This upward trajectory underscores the urgency of investigating the factors contributing to MMR. Recognizing the spatial heterogeneity and outliers in the data, our study employs the Robust Geographically Weighted Regression (RGWR) method with the Least Absolute Deviation approach. Using secondary data from the 2020 Indonesian Health Profile publication, the research seeks to establish province-specific models for MMR in 2020 and identify the key influencing factors in each region. Standard regression analyses fall short in addressing the complexities present in the data, making the RGWR approach crucial for understanding the nuanced relationships. The chosen RGWR model utilizes the Least Absolute Deviation method and a fixed kernel exponential weighting function. Notably, this model maintains a consistent bandwidth value across all locations, showcasing its robustness. In evaluating the model variations, the exponential fixed kernel weighting function emerges as the most optimal, boasting the smallest Akaike Information Criterion (AIC) value of 23.990 and the highest coefficient of determination  value of 93.66%. The outcomes of this research yield 24 distinct models, each tailored to the unique characteristics of every province in Indonesia. This nuanced, location-specific approach is vital for developing effective interventions and policies to address the persistently high MMR. By providing insights into the complex interplay of factors influencing maternal mortality in different regions, the study contributes to the groundwork for targeted and impactful public health initiatives across Indonesia.
Co-Authors A.A. Ketut Agung Cahyawan W Agus Hendra Al Rahmad Ahmad Watsiq Maula Apriliansyah, Feby Arif Saputra, Arif Asep Rusyana Bahrun Bahrun Binti Firdaus, Shausan Dahlawy, Arriz Dimas Chaerul Ekty Saputra Earlia, Nanda Elly Elly Erliza Noor Ghazi Mauer Idroes Hamdani M. Syam, Hamdani Heru Fahlevi Ibrahim, Husaini Idroes, Ghazi M. Irvanizam, Irvanizam Ismail Ismail Istakri, Dedi Jamil, T. M. Kemala, Pati Khairul, Moh Kruba, Rumaisa Linda Wahyuna M. Marthoenis Mardalena, Selvi Marshanda, Devira Marzuki Marzuki Maulana, Aga Maulydia, Nur Balqis Mikyal Bulqiah, Mikyal Mudatsir Mudatsir Muhamad Safiih Lola Muhammad Adam, Muhammad Muhammad Nasir Muhammad Subianto Muliadi Mustaqim Muzailin Affan Naidi Faisal Nasir Usman Nur Azmi, Nur Nurdjannah J. Niode Oktari, Rina S. Oktari, Rina Suryani Oktavia, Rini Pramana, Setia Purwoko, Agus RAHAYU, LATIFAH Rahmadhania Rahmah Johar Rahmi Inayati Rasyid, Jusnaini Ridha, Syahrul Rina S. Oktari Rinaldi Idroes Rusli Yusuf Safrizal Rahman Safrizal Rahman, Safrizal Salmawaty Arif Sasmita, Novi Reandy Suhendra, Rivansyah Syaridin, Syaridin Syazana, Nurul Syukri, Shara Tahlil, Teuku Tatsara, Nidya Teuku Rizky Noviandy TRINA EKAWATI TALLEI Ulfa, Elvitra Mutia Usman, Said Usman, Tarmizi Usnul, Uliyatul Yeni Rimadeni Yolanda Yolanda, Yolanda Yopi Ilhamsyah Yunus, Saifuddin