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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Syntax Literate: Jurnal Ilmiah Indonesia SEEIJ (Social Economics and Ecology International Journal) Jurnal Pembelajaran Inovatif Gema Wiralodra Jurnal Cahaya Mandalika International Journal of Engineering, Science and Information Technology Jurnal Teknologi Sistem Informasi Innovative: Journal Of Social Science Research SmartComp Jurnal TAM (Technology Acceptance Model) International Journal of Advances in Artificial Intelligence and Machine Learning
Gunawan Wang, Gunawan
Bina Nusantara University
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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ELECTRONIC MEDICAL RECORD (EMR) DESIGN FOR HOSPITAL USING BLOCKCHAIN TECHNOLOGY Lee, Eugenius Hansel; Wang, Gunawan
Jurnal Cahaya Mandalika ISSN 2721-4796 (online) Vol. 4 No. 1 (2023)
Publisher : Institut Penelitian Dan Pengambangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/jcm.v4i1.1372

Abstract

Data leakage in indonesia is still regarded as being extremely common, which has led to a low level of confidence among indonesians when it comes to storing their personal data online. The use of blockchain is still not popular in Indonesia.These two technologies may be merged to produce the best technical outcomes, especially in the security area, thanks to technological advancements in the healthcare industry and blockchain technology. The implementation of the EMR blockchain is also capable of facilitating the reach of the patient's medical record history, allowing each patient who receives outpatient or other treatment at one of the XYZ hospitals to easily integrate their medical records when seeking treatment at other branches, even if XYZ hospital just recently acquired another hospital. Data transmission with the standard system is still in doubt since there is no guarantee of the security of the data because the security of the new branch hospital and the acquired hospital cannot be guaranteed securely. The EMR blockchain can help all hospitals in the future by easing their concerns and facilitating hospital system mobilization, particularly in the patient data department.
Gamification to Increase Interest in Learning Mathematics Rojabi, Muhammad Afdan; Wang, Gunawan
Jurnal Pembelajaran Inovatif Vol. 7 No. 1 (2024): Jurnal Pembelajaran Inovatif
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JPI.071.05

Abstract

This study explores the effectiveness of gamification in mathematics learning using the Quizizz platform. The study involved 20 sixth-grade students at MIS Wahdatul Ikhwan Bogor and employed an experimental method with a pretest-posttest design. The analysis results showed a significant improvement in students' learning outcomes after the implementation of gamification. The use of Quizizz not only enhanced students' understanding and performance but also increased their motivation to learn and reduced boredom. The paired sample t-test showed a significance value of 0.000, indicating a significant difference between pretest and posttest scores. These findings suggest that gamification is an effective approach to improving students' learning outcomes and engagement in the mathematics learning process. Teachers are highly encouraged to integrate gamification into their teaching methods to create a more engaging and effective learning experience.
Predictive Analysis of Malaria Cases in Indonesia Using Machine Learning Syabrina, Ratih; Wang, Gunawan
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v9i9.16714

Abstract

Malaria continues to pose a significant public health challenge globally, with Indonesia being among the countries most affected by the disease. Despite extensive efforts to control malaria transmission, the disease remains endemic in various regions, leading to substantial morbidity and mortality. Accurate prediction of malaria cases is crucial for guiding effective prevention and control strategies, particularly in resource-limited settings. This study investigates the application of machine learning (ML) techniques to predict malaria incidence in Indonesia, leveraging climatic, epidemiological, and socioeconomic data. Three ML algorithms, namely Random Forest, Support Vector Machine (SVM), and Artificial Neural Networks (ANN), are employed and evaluated for their predictive capabilities. The study spans from 2010 to 2021, incorporating diverse datasets from the Indonesian Meteorological, Climatological, and Geophysical Agency (BMKG), the Ministry of Health of Indonesia, and the Indonesian Bureau of Statistics (BPS). Results indicate that the ML models exhibit strong predictive performance, with Random Forest demonstrating the highest accuracy. The integration of multidimensional data sources enhances the robustness of the predictive models, enabling the identification of spatiotemporal patterns in malaria transmission dynamics. The findings underscore the potential of ML-based approaches in improving malaria surveillance and control efforts in Indonesia, offering valuable insights for public health decision-makers and stakeholders. Moreover, the study highlights the importance of data quality, model refinement, and interdisciplinary collaboration in addressing complex public health challenges such as malaria. By harnessing the power of advanced analytics and innovative methodologies, this research contributes to the ongoing efforts to combat malaria and alleviate its burden on communities and healthcare systems in Indonesia and beyond.
Penerapan Data Mining Untuk Prediksi Slot Time di Bandara Internasional di Indonesia : Algoritma J48 Suryaman, Renddy Wandhana; Wang, Gunawan
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 11, No 3 (2022): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v11i3.3595

Abstract

Dalam dunia penerbangan, keselamatan dan kelancaran arus lalu lintas penerbangan merupakan business core, dimana setiap pelayanan lalu lintas penerbangan diharapkan tidak terjadi delay yang disebabkan oleh terjadinya holding pergerakan pesawat baik di udara maupun di darat. Oleh karena itu slot time di bandara sangat penting untuk ketepatan pergerakan pesawat udara baik yang Departure maupun yang Arrival, hal ini dimaksudkan untuk menghindari terjadinya delay yang disebabkan penumpukan antrian pesawat yang akan berangkat dan pesawat yang akan mendarat, dengan banyaknya pergerakan pesawat udara di Bandara Internasional Soekarno Hatta, maka dibutuhkan analisa yang mendalam dengan Teknik data mining seperti algoritma J48 dan Decesion Tree serta Naïve Bayes.Keywords — Data mining, J48, Decision Tree, Naïve Bayes, Slot Time .
Co-Authors Ahmad Nurul Fajar Diyapradana, Taruna Gafar, Gery Abdel Jaber, Mustafa Musa Kurniawan, Michael Joseph Lee, Eugenius Hansel LI Cen Rojabi, Muhammad Afdan Setiawan, Alliefiandini Stanley Salim, Sebastian Suryaman, Renddy Wandhana Syabrina, Ratih Utama, Ditdit Nugeraha Wibowo, Florentia Novena