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Ahmad Ilham
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Journal of Intelligent Computing and Health Informatics (JICHI)
Published by Universitas Muhammadiyah Semarang
ISSN : 27156923     EISSN : 27219186     DOI : https://doi.org/10.26714/jichi
Core Subject : Health, Science, Engineering,
Computer Science & IT Dentistry Electrical & Electronics Engineering Medicine & Pharmacology Public Health
Journal of Intelligent Computing & Health Informatics (JICHI) was printed in March 2020. JICHI is a scientific review journal publishing that focus on exchanging information relating to intelligent computing and health informatics applied in industry, hospitals, government, and universities. All articles should include a validation of the idea presented, e.g. through case studies, experiments, or systematic comparisons with other approaches already in practice. Two types of papers are accepted: (1) A short paper that discusses a single contribution to a specific new trend or a new idea, and; (2) A long paper that provides a survey of a specific research trend using a systematic literature review (SLR) method, as well as a traditional review method. Topics of interest include, but are not limited to: Intelligent Computing Include Machine Learning; Reinforcement Learning; Computer Vision; Image Processing; Scheduling and Optimization; Bio-inspired Algorithms; Business Intelligence; Chaos theory and intelligent control systems; Robotic Intelligent; Multimedia & Application; Web and mobile Intelligence and Big Data, etc.) Health Informatics Include Electronic health record; E-Health Information; Medical Image Processing & Techniques; Data Mining in Healthcare; Bioinformatics & Biostatistics; Mobile applications for patient care; Medical Image Processing & Techniques; Hospital information systems; Document handling systems; Electronic medical record systems; standardization, and systems integration; ICT in health promotion programmes e-health Guidelines and protocols; E-learning & education in healthcare; Telemedicine Software- Portals-Devices & Telehealth; Public health & consumer informatics; Data Mining & Knowledge Discovery in Medicine; ICT for Patient empowerment; ICT for Patient safety; Medical Databanks-Databases & Knowledge Bases; Healthcare Quality assurance; Nursing Informatics; Evaluation & Technology Assessment; Home-based eHealth; Health Management Issues; Health Research; Health Economics Issues; Statistical Method for Computer Medical Decision Support Systems; Medical Informatics or medicine in general; Organizational, economic, social, clinical impact, ethical and cost-benefit aspects of IT applications in health care.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 4 Documents
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Search results for , issue "Vol 4, No 2 (2023): September" : 4 Documents clear
Time Optimization of Watermark Image Quality Using Run Length Encoding Compression Mahiruna, Adiyah; Rachmawanto, Eko Hari; Istiawan, Deden
Journal of Intelligent Computing & Health Informatics Vol 4, No 2 (2023): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v4i2.12058

Abstract

Internet technology continues to have a significant impact on digital media, such as text, images, audio, and video. One effect is the ease of exchange, distribution, and duplication of digital data; on the other hand, this ease raises the problem of digital data being protected by copyright or digital data confidentiality. Watermarking is a way to protect digital data rights. Extensive research on watermarking has been conducted, including a hybrid DWT-DCT-SVD approach. Several studies have found weaknesses in the message insertion process; for example, the time required to insert a watermark image is relatively long, particularly for large images. To address the problem of long message insertion times, this study applies a compression process to the original image before the watermark image insertion process. The original image to be inserted into the watermark image is compressed using the run-length encoding (RLE) algorithm. The results of RLE compression demonstrate that image file size is reduced significantly, which optimizes the watermarking process. The experimental results demonstrate that watermarked images with RLE compression preprocessing exhibit better imperceptibility and comparable or improved PSNR values. Specifically, the image "Elaine" showed a PSNR improvement from 28.7541 to 31.4502 with RLE compression. These findings demonstrate that combining DWT-DCT-SVD with RLE compression not only reduces watermarking time but also maintains or enhances image quality, providing a robust solution for digital copyright protection.
Modelling of Dengue Hemorrhagic Fever Disease in Semarang City Using Generalized Poisson Regression Model Septia, Siti Fajar; Hidayat, Muhamad Arif; Asyfani, Yusrisma; Haris, M. Al; Winaryati, Eny
Journal of Intelligent Computing & Health Informatics Vol 4, No 2 (2023): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v4i2.12769

Abstract

Dengue Hemorrhagic Fever (DHF) is an infectious disease that can be life- threatening within a relatively short period of time and can be fatal if not promptly treated. DHF in Indonesia ranks second as a dangerous seasonal disease. DHF remains a serious issue in the Central Java Province, particularly in Semarang City. The cases of DHF can be modeled using a Poisson regression model due to the characteristics of DHF cases, which involve count data with small occurrence probabilities. The Poisson regression model assumes equality between the mean and variance (equidispersion). However, the application of the Poisson regression model often encounters violations of the assumption of excessive variance (overdispersion), which necessitates addressing the violation, and one possible approach is to use the Generalized Poisson Regression model. Based on the analysis results, the Generalized Poisson Regression model could handle the overdispersion because the ratio of Pearson Chi-Square by degrees of freedom was 0.976, approaching a value of 1. It has also been proven to be more suitable for evaluating factors influencing the number of DHF cases, as it has a lower AIC value compared to Poisson models, with a value of 123.64. The variables that were found to have an impact on DHF cases in Semarang City based on the Generalized Poisson Regression model are the number of larval habitats (X1), the number of hospitals (X2), population density (X3), and the number of healthcare workers (X4).
Expert System for Diagnosis Pregnancy Disorders using Forward Chaining Method Based on Android Safitri, Dina; Safuan, Safuan; Assaffat, Luqman
Journal of Intelligent Computing & Health Informatics Vol 4, No 2 (2023): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v4i2.13013

Abstract

Technology's rapid evolution has extended its impact into the healthcare field, including the development of artificial intelligence-based expert systems designed to streamline the work processes of nurses and obstetricians. In this research, we use the forward chaining method to build an android-based expert system for diagnosing fetal disorders in pregnant women. This system is made for ease of use on mobile devices by targeting pregnant women where this application provides a self-detection mechanism for pregnancy abnormalities. The test results show a high level of respondent satisfaction with this expert system application, with an average score of 90.16%, indicating a strong acceptance of the quality and functionality of the application. It can be concluded that our proposed expert system application shows a positive response from respondents and is considered successful in providing pregnancy diagnosis services independently.
An Enhanced IS-LM Business Cycle Model for Increasing Income in a Dynamic Economy Diana, Arista Fitri; Rahmasari, Shafira Meiria; Mahardika, Dhimas
Journal of Intelligent Computing & Health Informatics Vol 4, No 2 (2023): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v4i2.13201

Abstract

This paper introduces an enhanced IS-LM business cycle model by integrating control parameters using the Pontiyagin Maximum Principle Method, aiming to maximize income within economic cycles. It develops a dynamic model incorporating import and consumption rates as controls, showcasing their impact on economic variables through simulations and analytical methodologies. The results exhibit a significant increase in income by up to 10% through the reduction of interest rates and capital stock. The efficiency of the proposed controls is visually demonstrated, providing a robust validation of the methodology used, aligning with prior research, and offering substantial insights into dynamic business cycle modelling for economic analysis and policy-making.

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