scholarly journals Membangun Framework Repository Source Code Algoritma Komputer pada Platform Web

JURNAL TIKA ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 105-109
Author(s):  
Amrullah Amrullah ◽  
Mutasar Mutasar
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Image Processing ◽  
Expert System ◽  
Computer System ◽  
Source Code ◽  
Decision System ◽  
Information Searching ◽  
System Data ◽  
System Information

Era Revolusi Industri 4.0 programmer dihadirkan platform CMS, Web builder yang mempercepat pembuatan program seperti create templete responsive/dinamis, CRUD dan grafik namun belum adanya framework untuk membangun source code pada platform web yang memecahkan alur proses pada sebuah algoritma sehingga akan membantu programmer/peneliti dalam menyelesaikan masalah aritmatika/logical proses pada sebuah algoritma/metode jika di-implementasikan kedalam source code platform web HTML, PHP, CSS. Urgensi permasalahan ini harus adanya sistem repository yang menyediakan source code algoritma komputer meliputi (expert system, data mining, decision system, artificial intelligence, kriptografi/security computer, system information, searching, image processing). Adanya repository ini akan memberikan kemudahan dalam menghasilkan source code algoritma/metode komputer untuk dapat digunakan sebagai, modify,combine, comparation, example, trying, testing , implementation, sehingga akan mudah dalam penyelesaian program penelitian dan membantu mempercepat laju skill programmer/peneliti di perguruan tinggi.

scholarly journals Expert System for Diagnosis of Uterine Myomas using the Certainty Factor Method

2021 ◽  
Vol 1 (4) ◽  
pp. 103-108
Author(s):  
Syahrizal Dwi Putra ◽  
M Bahrul Ulum ◽  
Diah Aryani
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Expert System ◽  
Computer System ◽  
Decision Making Process ◽  
Certainty Factor ◽  
Uterine Myomas ◽  
Factor Method ◽  
Two Factors

An expert system which is part of artificial intelligence is a computer system that is able to imitate the reasoning of an expert with certain expertise. An expert system in the form of software can replace the role of an expert (human) in the decision-making process based on the symptoms given to a certain level of certainty. This study raises the problem that many women experience, namely not understanding that they have uterine myomas. Many women do not understand and are not aware that there are already symptoms that are felt and these symptoms are symptoms of the presence of uterine myomas in their bodies. Therefore, it is necessary for women to be able to diagnose independently so that they can take treatment as quickly as possible. In this study, the expert will first provide the expert CF values. Then the user / respondent gives an assessment of his condition with the CF User values. In the end, the values obtained from these two factors will be processed using the certainty factor formula. Users must provide answers to all questions given by the system in accordance with their current conditions. After all the conditions asked are answered, the system will display the results to identify that the user is suffering from uterine myoma disease or not. The Expert System with the certainty factor method was tested with a patient who entered the symptoms experienced and got the percentage of confidence in uterine myomas/fibroids of 98.70%. These results indicate that an expert system with the certainty factor method can be used to assist in diagnosing uterine myomas as early as possible.

Artificial Intelligence in Medical Science

2014 ◽  
pp. 11-23 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Decision Making ◽  
Signal Processing ◽  
Expert System ◽  
Knowledge Base ◽  
Medical Diagnosis ◽  
Medical Science ◽  
Inference Engine ◽  
Medical Decision

Applying Artificial Intelligence (AI) for increasing the reliability of medical decision making has been studied for some years, and many researchers have studied in this area. In this chapter, AI is defined and the reason of its importance in medical diagnosis is explained. Various applications of AI in medical diagnosis such as signal processing and image processing are provided. Expert system is defined and it is mentioned that the basic components of an expert system are a “knowledge base” or KB and an “inference engine”. The information in the KB is obtained by interviewing people who are experts in the area in question.

scholarly journals Knowledge Discovery from Medical Data and Development of an Expert System in Immunology

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 695
Author(s):  
Małgorzata Pac ◽  
Irina Mikutskaya ◽  
Jan Mulawka
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Expert System ◽  
Expert Systems ◽  
Knowledge Discovery ◽  
Experimental Verification ◽  
Medical Data ◽  
Practical Application ◽  
Wide Range ◽  
Bruton’S Disease

Artificial intelligence is one of the fastest-developing areas of science that covers a remarkably wide range of problems to be solved. It has found practical application in many areas of human activity, also in medicine. One of the directions of cooperation between computer science and medicine is to assist in diagnosing and proposing treatment methods with the use of IT tools. This study is the result of collaboration with the Children’s Memorial Health Institute in Warsaw, from where a database containing information about patients suffering from Bruton’s disease was made available. This is a rare disorder, difficult to detect in the first months of life. It is estimated that one in 70,000 to 90,000 children will develop Bruton’s disease. But even these few cases need detailed attention from doctors. Based on the data contained in the database, data mining was performed. During this process, knowledge was discovered that was presented in a way that is understandable to the user, in the form of decision trees. The best models obtained were used for the implementation of expert systems. Based on the data introduced by the user, the system conducts expertise and determines the severity of the course of the disease or the severity of the mutation. The CLIPS language was used for developing the expert system. Then, using this language, software was developed producing six expert systems. In the next step, experimental verification was performed, which confirmed the correctness of the developed systems.

SISTEM PAKAR MENDIAGNOSA VIRUS MAYORA DENGAN METODE VARIABLE CENTERED INTELLIGENT RULE SYSTEM (VCIRS)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Siti Nurhena ◽  
Nelly Astuti Hasibuan ◽  
Kurnia Ulfa
Keyword(s):  
Artificial Intelligence ◽  
Immune System ◽  
Expert System ◽  
Expert Systems ◽  
Dengue Hemorrhagic Fever ◽  
Hemorrhagic Fever ◽  
Visual Basic ◽  
Artificial Intelligence Techniques ◽  
Individual Needs ◽  
Rule System

The diagnosis process is the first step to knowing a type of disease. This type of disease caused by mosquitoes is one of the major viruses (MAVY), dengue hemorrhagic fever (DHF) and malaria. Sometimes not everyone can find the virus that is carried by this mosquito, usually children who are susceptible to this virus because the immune system that has not been built perfectly is perfect. To know for sure which virus is infected by mosquitoes, it can diagnose by seeing symptoms perceived symptoms. Expert systems are one of the most used artificial intelligence techniques today because expert systems can act as consultations. In this case the authors make a system to start a diagnosis process with variable centered intelligent rule system (VCIRS) methods through perceived symptoms. With the facilities provided for users and administrators, allowing both users and administrators to use this system according to their individual needs. This expert system is made with the Microsoft Visual Basic 2008 programming language.Keywords: Expert System, Mayora Virus, Variable Centered Intelligent Rule System (VCIRS)The diagnosis process is the first step to knowing a type of disease. This type of disease caused by mosquitoes is one of the major viruses (MAVY), dengue hemorrhagic fever (DHF) and malaria. Sometimes not everyone can find the virus that is carried by this mosquito, usually children who are susceptible to this virus because the immune system that has not been built perfectly is perfect. To know for sure which virus is infected by mosquitoes, it can diagnose by seeing symptoms perceived symptoms.Expert systems are one of the most used artificial intelligence techniques today because expert systems can act as consultations. In this case the authors make a system to start a diagnosis process with variable centered intelligent rule system (VCIRS) methods through perceived symptoms.With the facilities provided for users and administrators, allowing both users and administrators to use this system according to their individual needs. This expert system is made with the Microsoft Visual Basic 2008 programming language.Keywords: Expert System, Mayora Virus, Variable Centered Intelligent Rule System (VCIRS)

scholarly journals A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1128
Author(s):  
Chern-Sheng Lin ◽  
Yu-Ching Pan ◽  
Yu-Xin Kuo ◽  
Ching-Kun Chen ◽  
Chuen-Lin Tien
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Color Space ◽  
Color Difference ◽  
Color Space Conversion ◽  
Before And After ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Algorithm ◽  
Time Image ◽  
Cooking Conditions

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

scholarly journals OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

scholarly journals Putting the world back to work: An expert system using big data and artificial intelligence in combating the spread of COVID-19 and similar contagious diseases

Work ◽  
2020 ◽  
Vol 67 (3) ◽  
pp. 557-572
Author(s):  
Said Tkatek ◽  
Amine Belmzoukia ◽  
Said Nafai ◽  
Jaafar Abouchabaka ◽  
Youssef Ibnou-ratib
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Expert System ◽  
Population Monitoring ◽  
High Definition ◽  
Contagious Diseases ◽  
The World ◽  
General Guide ◽  
The Impact ◽  
Back To Work

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population monitoring for analysis and prediction. The massive data generated through the use of big data and artificial intelligence can play an important role in addressing this unprecedented global health and economic crisis. OBJECTIVES: The objective of this work is to develop an expert system that combines several solutions to combat COVID-19. The main solution is based on a new developed software called General Guide (GG) application. This expert system allows us to explore, monitor, forecast, and optimize the data collected in order to take an efficient decision to ensure the safety of citizens, forecast, and slow down the spread’s rate of COVID-19. It will also facilitate countries’ interventions and optimize resources. Moreover, other solutions can be integrated into this expert system, such as the automatic vehicle and passenger sanitizing system equipped with a thermal and smart High Definition (HD) cameras and multi-purpose drones which offer many services. All of these solutions will facilitate lifting COVID-19 restrictions and minimize the impact of this pandemic. METHODS: The methods used in this expert system will assist in designing and analyzing the model based on big data and artificial intelligence (machine learning). This can enhance countries’ abilities and tools in monitoring, combating, and predicting the spread of COVID-19. RESULTS: The results obtained by this prediction process and the use of the above mentioned solutions will help monitor, predict, generate indicators, and make operational decisions to stop the spread of COVID-19. CONCLUSIONS: This developed expert system can assist in stopping the spread of COVID-19 globally and putting the world back to work.

Sign in / Sign up

Export Citation Format

Share Document