cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Ahmad Ilham
Contact Email
ahmadilham@unimus.ac.id
Phone
+6282225426654
Journal Mail Official
jichi.informatika@unimus.ac.id
Editorial Address
Jl. Kedungmundu Raya No. 18 Semarang, Jawa Tengah - Indonesia 50273
Location
Kota semarang,
Jawa tengah
INDONESIA
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 5 Documents
 1 
Search results for , issue "Vol 1, No 2 (2020): September" : 5 Documents clear
Android Based Expert System Application for Diagnose COVID-19 Disease: Cases Study of Banyumas Regency Hakim, Rosyid Ridlo Al; Rusdi, Erfan; Setiawan, Muhammad Akbar
Journal of Intelligent Computing & Health Informatics Vol 1, No 2 (2020): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i2.5958

Abstract

Since being confirmed by WHO, the status of COVID-19 outbreak has become a global pandemic, the number of cases has been confirmed positive, cured, and even death worldwide. Artificial intelligence in the medical has given rise to expert systems that can replace the role of experts (doctors). Tools to detect someone affected by COVID-19 have not been widely applied in all regions. Banyumas Regency, Indonesia is included confirmed region of COVID-19 cases, and it’s difficult for someone to know the symptoms that are felt whether these symptoms include indications of someone ODP, PDP, positive, or negative COVID-19, and still at least a referral hospital handling COVID-19. Expert system with certainty factor can help someone make a self-diagnose whether including ODP, PDP, positive, or negative COVID-19. This expert system provides ODP diagnostic results with a confidence level of 99.96%, PDP 99.99790%, positive 99.9999997%, negative 99.760384%, and the application runs well on Android OS
Supplier Selection Very Small Aperture Terminal using AHP-TOPSIS Framework Sumanto, Sumanto; Indriani, Karlena; Marita, Lita Sari; Christian, Ade
Journal of Intelligent Computing & Health Informatics Vol 1, No 2 (2020): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i2.6290

Abstract

There are several methods of decision making VSAT IT goods suppliers such as: Promethee, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Analytical Hierarchy Process (AHP). Decision-making in the selection of the best suppliers, we have the basis of assessment criteria, and we will also be faced with more than one alternative. If alternatives are only two, maybe still easy for us to choose, but if the alternative is a lot of choice, it is quite difficult for us to decide. Analytical Hierarchy Process (AHP) is a technique that was developed to help overcome this difficulty, because the Analytical Hierarchy Process (AHP) is a form of decision-making model with many criteria. One of the reliability of the Analytical Hierarchy Process (AHP) is able to perform simultaneous analysis and integrated between the parameters of qualitative or quantitative. In this study the authors use six criteria and alternatives 6, the results of these alternatives will be obtained perangkingan alternative used as a reference supplier selection VSAT IT goods company Total EP Indonesie
Applied Exponential Smoothing Holt-Winter Method for Predict Rainfall in Mataram City Pertiwi, Dewi Darma
Journal of Intelligent Computing & Health Informatics Vol 1, No 2 (2020): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i2.6330

Abstract

Weather conditions in the city of Mataram tend to be erratic and difficult to predict, such as the condition of rainfall data in 2018 which changes over a certain period of time so that the weather is difficult to predict accurately. In this study, we propose the Exponential Smoothing Holt-Winter method to forecast rainfall in the city of Mataram, so that it can be a decision support for various interested sectors. This method has been tested using secondary data from the Mataram City Central Bureau of Statistics for the period January 2014 to 2018 and evaluated using Mean Absolute Deviation (MAD), Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). The results of this study indicate that using the Exponential Smoothing Holt-Winter method yields better results, each of which is MAPE 142.3, MAD 95.6 and MSD value 24988.7 and the data smoothing value is obtained for the smallest combination value of α 0.2, β 0.1, and γ 0.1. It can be concluded that the proposed method can provide better information and can be used to predict rainfall in Mataram City for the next 12 periods.
Modeling Spatial Error Model (SEM) On Human Development Index (IPM) In Central Java 2018 Wati, Aprilia Dwi Anggara; Khikmah, Laelatul
Journal of Intelligent Computing & Health Informatics Vol 1, No 2 (2020): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i2.6341

Abstract

The Human Development Index (HDI) is a human development index that is used to achieve the development outcomes of a region. HDI is formed by 3 basic dimensions, namely the health dimension as seen from the indicator of life expectancy at birth, the dimension of knowledge seen from a combination of indicators of average length of schooling and expectation of school years and dimensions of decent living standards as seen from the indicator of average per capita expenditure has been adjusted. The development of HDI in Central Java shows an increase every year. In 2018 the HDI figure for Central Java Province reached 71.12% and increased by 0.6% from the previous year. This is because the large HDI figures in an area are influenced by the large HDI numbers in adjacent areas. The location / area factor is thought to have a spatial dependence effect on the HDI figure. This problem can be overcome by using spatial regression by including the relationship between regions into the model. The spatial regression approach used in this study is the Spatial Error Model (SEM). The weighting matrix used in this study is Queen Contiguity (intersection between sides and corners). This study provides results that the variables that significantly influence HDI are poverty and school enrollment rates.
Modeling of Tuberculosis Case In Central Java 2018 With Three Knot Point Hapsari, Dina Fristantiningtyas Wiliyani; Khikmah, Laelatul
Journal of Intelligent Computing & Health Informatics Vol 1, No 2 (2020): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i2.6348

Abstract

Tuberculosis is a contagious disease caused by infection with the bacteria Mycobacterium Tuberculosis or known as Acid-Resistant Bacteria (BTA). Central Java is one of the provinces that has a high number of tubuerculosis cases in Indonesia. In 2018, Central Java was in second place after West Java in the highest number of Tuberculosis cases in Indonesia with the number of Tuberculosis cases of all types of 67,941 cases. Many variables can affect the number of TB cases. Therefore, a study was conducted in the form of modeling to determine the variables that affect the number of tuberculosis cases in Central Java. Based on data obtained from the Central Java Provincial Health Office in 2018, it shows that the pattern between the number of tuberculosis cases and the variables that are thought to influence it is not linearly related, then a spline regression approach is carried out. The results of this study indicate that the best spline regression model is to use three point knots with significant variables, namely population density and malnutrition. The value of ????2 obtained is 54.6%.

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2020 2020


Reset
Filter By Issues
All Issue Vol 6, No 2 (2025): September Vol 6, No 1 (2025): March Vol 5, No 2 (2024): September Vol 5, No 1 (2024): March Vol 4, No 2 (2023): September Vol 4, No 1 (2023): March Vol 3, No 2 (2022): September Vol 3, No 1 (2022): March Vol 2, No 2 (2021): September Vol 2, No 1 (2021): March Vol 1, No 2 (2020): September Vol 1, No 1 (2020): March More Issue