Sistem Pakar Deteksi Kerusakan Truk Mitsubishi Fuso Berbasis Desktop

2021 ◽  
Vol 11 (1) ◽  
pp. 1-4
Author(s):  
Heri Pratama ◽  
Sofika Enggari ◽  
Irzal Arief Wisky
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
Computer Program ◽  
Specific Problem ◽  
Expert Knowledge ◽  
Computer Programs ◽  
Thought Process ◽  
Made In

An expert system is a computer program that can mimic the thought process and expert knowledge in solving a particular problem. The implementation of this expert system is widely used in the field of artificial intelligence because expert systems are seen as a way of storing expert knowledge in certain fields in computer programs so that decisions can be made in making intelligent reasoning on a specific problem in this case the problem of detecting damage to Mitsubishi trucks. Fuso at Berdikari Motor Sibolga workshop.

scholarly journals The Performance of Stock Portfolios formed using Fuzzy Logic

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Amit K. Sinha 1 ◽  
Andrew J. Jacob 2
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Expert System ◽  
Expert Systems ◽  
Fuzzy Membership ◽  
Thought Process ◽  
Membership Functions ◽  
Fuzzy Membership Functions ◽  
Stock Portfolios ◽  
Financial Securities

Expert systems, a type of artificial intelligence that replicate how experts think, can aide unskilled users in making decisions or apply an expert’s thought process to a sample much larger than could be examined by a human expert. In this paper, an expert system that ranks financial securities using fuzzy membership functions is developed and applied to form portfolios. Our results indicate that this approach to form stock portfolios can result in superior returns than the market as measured by the return on the S&P 500. These portfolios may also provide superior risk-adjusted returns when compared to the market.

scholarly journals Rancang Bangun Sistem Pakar Diagnosa Penyakit Ayam Bangkok

2019 ◽  
Vol 5 (1) ◽  
pp. 52-61
Author(s):  
Aprih Widayanto ◽  
Joko Dwi Mulyanto ◽  
Ade Sulistyono
Keyword(s):  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
System Application ◽  
Expert Knowledge ◽  
Computer Programs ◽  
Knowledge Based ◽  
Informed Decisions

Abstract: Expert System is a knowledge-based program that offers quality solutions for problems within a certain domain. The implementation of expert systems is widely used for commercial purposes, because expert systems are seen as a way to store expert knowledge in certain areas in computer programs, so that they can make informed decisions and think intelligently. Using Android-based methods, this program is expected to represent experts in diagnosing Kip-Bangkok disease. Expert Systems Applications diagnosis chicken bangkok provide maximum convenience for the owner of the chickens Bangkok, so owners do not have chicken bangkok meet with specialists in person, the owner of the chicken bangkok open the computer and use this expert system application instead of the disease in poultry media consultation of experts in chickens bangkok. The expert system is used as a decision support and is used as a tool for someone who has no information about the types of diseases and symptoms in bangkok chicken, as well as preventative advice. From this problem this disease can be known on the basis of the symptoms found in chicken in Bangkok and to prevent deaths by giving appropriate prevention advice. Keywords: Expert system, Application, Diagnosis of the Chicken Disease of Bangkok

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 IDENTIFIKASI PENYAKIT PADA TERUMBU KARANG MENGGUNAKAN RIPPLE DOWN RULES

2018 ◽  
Vol 1 (2) ◽  
pp. 165-174
Author(s):  
Agus Cahyo Nugroho
Keyword(s):  
Coral Reef ◽  
Expert System ◽  
Expert Systems ◽  
Specific Problem ◽  
Specific Knowledge ◽  
Web Based ◽  
Human Thinking ◽  
Ripple Down Rules

Along with the development of technology, people developed a system that capable of adopting processes and human thinking as an expert system that contains specific knowledge so that everyone can use it to solve a specific problem, namely the diagnosis of coral reef disease. The purpose of this study is to develop an expert system for diagnosing coral reef disease  in the form of websites using PHP with a MySQL database. Expert system for diagnosing coral reef disease problem is using Ripple Down Rules (RDR) method has a goal to discover symptoms that appear in the form of questions that can diagnose the coral reef disease based on website. Web based expert system is able to recognize types of coral reef disease after consultation by answering a few questions that are displayed by the application of expert systems and can infer some types of coral  reef disease. Data coral reef disease that already known adapt to rules which are made for matching the symptoms of coral reef disease.

Fundamentals of creating MIVAR expert systems

2021 ◽  
Author(s):  
Oleg Varlamov
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Intelligent Systems ◽  
Autonomous Robots ◽  
Support Systems ◽  
Knowledge Bases ◽  
Computer Engineering

Methodological and applied issues of the basics of creating knowledge bases and expert systems of logical artificial intelligence are considered. The software package "MIV Expert Systems Designer" (KESMI) Wi!Mi RAZUMATOR" (version 2.1), which is a convenient tool for the development of intelligent information systems. Examples of creating mivar expert systems and several laboratory works are given. The reader, having studied this tutorial, will be able to independently create expert systems based on KESMI. The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

Mivar databases and rules

2021 ◽  
Author(s):  
Oleg Varlamov
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Knowledge Bases ◽  
Data Models ◽  
Active Network ◽  
New Model

The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in this new model of data and rules is shown, which has linear computational complexity relative to the number of rules. MOGAN is a development of Rule - Based Systems and allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format. An example of creating a mivar expert system for solving problems in the model area "Geometry"is given. Mivar databases and rules can be used to model cause-and-effect relationships in different subject areas and to create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with the transition to"Big Knowledge". The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

Social Modeller

2008 ◽  
pp. 199-210
Author(s):  
Panagiotis Linardis
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Specific Problem ◽  
Scientific Field ◽  
Computer Applications ◽  
The Internet ◽  
Amount Of Information ◽  
Intelligent Software ◽  
Systematic Development ◽  
Practical Level

Computer applications and especially artificial intelligence (AI) in archaeology is a scientific field that emerged in the late 1970s. This fact came in response to several simultaneous needs, opportunities and interests that result from the systematic development of methodologies relative to excavating, recording and restoration of findings, and also the increasing amount of information gathered in excavation areas. One of the first uses of artificial intelligence on a practical level was the coupling of expert archaeological knowledge with computerbased applications such as expert systems (ES), in order to simulate archaeologist’s reasoning for a specific problem. Nowadays, the evolvement of the Internet provides a novel platform convenient for the development of new intelligent software and for offering valuable services in archaeology (Gardin, 1988; Huggett & Ross, 2004; Huggett & Ryan, 1994; & Wilcock, 1985, 1990).

Artificial intelligence: a new tool for forest management

1990 ◽  
Vol 20 (4) ◽  
pp. 428-437 ◽  
Author(s):  
Peter Kourtz
Keyword(s):  
Artificial Intelligence ◽  
Forest Management ◽  
Expert Systems ◽  
Computer Science ◽  
Solution Structure ◽  
Visual Recognition ◽  
Knowledge Engineering ◽  
Expert Knowledge ◽  
Low Cost ◽  
Process Models

Articicial intelligence is a new science that deals with the representation, automatic acquisition, and use of knowledge. Artificial intelligence programs attempt to emulate human thought processes such as deduction, inference, language, and visual recognition. The goal of artificial intelligence is to make computers more useful for reasoning, planning, acting, and communicating with humans. Development of artificial intelligence applications involves the integration of advanced computer science, psychology, and sometimes robotics. Of the subfields that artificial intelligence can be broken into, the one of most immediate interest to forest management is expert systems. Expert systems involve encoding knowledge usually derived from an expert in a narrow subject area and using this knowledge to mimic his decision making. The knowledge is represented usually in the form of facts and rules, involving symbols such as English words. At the core of these systems is a mechanism that automatically searches for and pieces together the facts and rules necessary to solve a specific problem. Small expert systems can be developed on common microcomputers using existing low-cost commercial expert shells. Shells are general expert systems empty of knowledge. The user merely defines the solution structure and adds the desired knowledge. Larger systems usually require integration with existing forestry data bases and models. Their development requires either the relatively expensive expert system development tool kits or the use of one of the artificial intelligence development languages such as lisp or PROLOG. Large systems are expensive to develop, require a high degree of skill in knowledge engineering and computer science, and can require years of testing and modification before they become operational. Expert systems have a major role in all aspects of Canadian forestry. They can be used in conjunction with conventional process models to add currently lacking expert knowledge or as pure knowledge-based systems to solve problems never before tackled. They can preserve and accumulate forestry knowledge by encoding it. Expert systems allow us to package our forestry knowlege into a transportable and saleable product. They are a means to ensure consistent application of policies and operational procedures. There is a sense of urgency associated with the integration of artificial intelligence tools into Canadian forestry. Canada must awaken to the potential of this technology. Such systems are essential to improve industrial efficiency. A possible spin-off will be a resource knowledge business that can market our forestry knowledge worldwide. If we act decisively, we can easily compete with other countries such as Japan to fill this niche. A consortium of resource companies, provincial resource agencies, universities, and federal government laboratories is required to advance this goal.

Critical Review of Expert System Validation in Transportation

1997 ◽  
Vol 1588 (1) ◽  
pp. 104-109 ◽  
Author(s):  
Gary S. Spring
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Critical Review ◽  
Ad Hoc ◽  
Evaluation Process ◽  
Performance Levels ◽  
System Validation ◽  
Overall Evaluation ◽  
Definition Of ◽  
Made In

Expert system validation—that is, testing systems to ascertain whether they achieve acceptable performance levels—has with few exceptions been ad hoc, informal, and of dubious value. Very few efforts have been made in this regard in the transportation area. A discussion of the major issues involved in validating expert systems is provided, as is a review of the work that has been done in this area. The review includes a definition of validation within the context of the overall evaluation process, descriptions and critiques of several approaches to validation, and descriptions of guidelines that have been developed for this purpose.

Expert Systems and Special Education

1986 ◽  
Vol 53 (3) ◽  
pp. 235-239 ◽  
Author(s):  
Alan M. Hofmeister ◽  
Joseph M. Ferrara
Keyword(s):  
Special Education ◽  
Expert System ◽  
Expert Systems ◽  
System Development ◽  
Computer Programs ◽  
Development Tools ◽  
Potential Applications

Expert systems are computer programs designed to replicate human expertise in a variety of areas. This article discusses the characteristics of these programs as well as recently available expert system development tools. The article also suggests potential applications for expert systems within the field of special education. Finally, the article reviews recent efforts to apply expert systems technology to special education problems.

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