Expert System Implementation for the Diagnosis of Skin Diseases

Using Forward Chaining Method

Cindy Pamela Cornelia Munaiseche, Julyeta Paulina Amelia Runtuwene, Vivi Peggie Rantung,

Gladly Caren Rorimpandey, Ferdinan Ivan Sangkop, and Parabelem Tinno Dolf Rompas

Department of Informatics, Universitas Negeri Manado, Tondano 95618, North Sulawesi, Indonesia

Keywords: Expert system, inference, forward chaining, skin disease, black box testing

Abstract: Expert system is a system that is trying to adopt human knowledge into a computer, so that the computer

can resolve the issue as was done by experts. The purpose of this study to design an application of expert

system for diagnosis the human skin diseases by using forward chaining method as one of inference

technique that aims to discover symptoms of the disease that is displayed in the form of questions. The skin

organ chosen because in the interaction between humans, skin is the first organ that used to shake hands,

touch, kiss, etc, so that some diseases can be transmitted only through touch or by interaction of skin with

skin, and many cases of skin diseases that resulted in death due to delayed handled. The expert system

application design consists of seven stages: preliminary studies, data collection, data analysis, system

design, system implementation, system evaluation (testing) and the last, drawing conclusions. Expert system

software application built to recognize the type of skin disease after consultation by answering a few

questions displayed by the system, and can infer the type of skin diseases suffered by the patient. Based on

the results of black box testing, the expert system application has been running with good.

1 INTRODUCTION

Expert system is a software designed specifically

based on Artificial Intelligence, where the system

seeks to adopt human knowledge to the computer so

that the computer can solve a particular problem by

imitating the work of the experts. Expert systems

development requires knowledge acquisition from

people, involving both knowledge engineers and

application domain experts in specialist

interactions with computing systems. Expert

systems may be used to provide support and

advice to a user of any complex information

system and hence to improve the human-computer

interface (Brian, 2010).

One of the medical problems occurring recently

is the imbalance between the number of patient and

the number doctor. Limitations of an expert (doctor)

sometimes become an obstacle for people who will

consult to get the best treatment solution associated

with the disease suffered. In addition, most people

are not trained medically so they do not know what

to do when they experience symptoms of illness. It

is unfortunate when the symptoms which can

actually be dealt with early develop into a more

serious disease due to lack of knowledge. People can

obtain knowledge about health from books or

internet sites. However, it is not easy to learn that

way because it takes a long time. In addition, these

sources cannot diagnose types of diseases as the

doctors do. In this case, expert system is presented

as an alternative in solving the problem.

There are different areas in medicine where an

expert system has been designed and implemented to

profers solution to health status stability in human.

Among these diverse areas includes an expert

system for Eye, Skin, Pregnancy, Blood Disorder

and several other human diseases. In previous study,

Gudu et al (2012) in their research for expert system

to diagnosis and treat hypertension in pregnancy

stated that the diagnostic and treatment expert

system for hypertension in pregnancy has so far

remained at the testing phase of its life cycle and is

yet to be implemented. Ayangbekun et al (2014)

develop an expert system for diagnosis of blood

disorder. There were two hospital which was taken

as the case study of the research. The information

was gathered from the hematology department and

Munaiseche, C., Amel, J., Rantung, V., Rorimpandey, G., Sangkop, F. and Rompas, P.

Expert System Implementation for the Diagnosis of Skin Diseases using Forward Chaining Method.

DOI: 10.5220/0009009902870291

In Proceedings of the 7th Engineering International Conference on Education, Concept and Application on Green Technology (EIC 2018), pages 287-291

ISBN: 978-989-758-411-4

287

the blood department of the two hospitals

respectively. The information gotten was analyzed

and manipulated based on the symptoms and causes

of the blood disorders and then turned into rules for

easy programming into the computer. In addition,

Ayangbekun et al (2015) also developed an expert

system for diagnosing brain diseases, using the

C#.NET programming language and Microsoft SQL

Server 2012 served as the RDBMS. From the study,

this application serves as a model tool that will

enable hospitals to effectively monitor patients

medical records without ambiguity.

The skin is the sense of touch and the widest

organ making up the human body which is located at

the outermost and covers the entire surface of the

body. Because of its outer location, the skin first

receives stimuli such as touch, pain, or bad

influences from outside. In interaction between

humans, the skin is the first organ used to shake

hands, touch, kiss, etc. while some diseases can be

transmitted only through touch, or the interaction of

skin with skin, or through the used media (towels,

clothes, jackets, handkerchiefs , etc.) by people who

have infectious skin diseases. Maybe many people

consider skin diseases to be trivial, but actually these

skin diseases can be very dangerous if they are not

handled. In fact, not a few cases of skin disease that

resulted in death due to delayed handled,

This study aimed to design an expert system

application for diagnosis skin diseases using forward

chaining and analyze the software functionality

requirements through blackbox testing. The scope of

the study is extended to 15 types of skin diseases

with 54 symptoms of the disease, arranged in 15

rules that were called the Rule-Based System.

The main contribution is the experts system for

diagnosing skin disease has become an expert

knowledge sharing tool to be used by other medical

personnel who are not specialists in diagnosis of

skin diseases, specially for hospitals that do not have

a dermatologist. The research’s novelty is the expert

system based on web and user friendly so that can be

accessed by everyone wherever and whenever easily

and using PHP programming language and MySQL

as the Relational Database Management System

(RDBMS). The advantage of this research, as a

guide for the patient in taking initial action if they

know the possibility of suffering skin disease (early

detection).

2 LITERATURE REVIEW

Expert system is a piece of software programmed

using Artificial Intelligence (AI) techniques. Such

systems use databases of expert knowledge to offer

advice or make decisions in such areas as medical

diagnosis and trading on the stock exchange

(Munaiseche et al., 2016). An expert system is a

system that employs human knowledge captured in a

computer to solve problems that ordinarily require

human expertise. Expert system seeks and utilizes

relevant information from their human users and

from available knowledge bases in order to make

recommendations. With the expert system, the user

can interact with a computer to solve a certain

problem. This can occur because the expert system

can store heuristic knowledge. Generally to develop

an expert system, a rule based method is required to

analyze and compute the knowledge base (Patra et.

al., 2010).

2.1 System Architecture

Expert system consists of domain expert, designer,

inference engine, knowledge base, user interface and

user. There is relationship between these

subdivisions which makes it expert system. The

domain expert is connected to the knowledge base in

order to give rules and fact. The domain experts are

normally the expert in the body or field. The

knowledge base stores the rule and fact collected.

The knowledge base is also connected to inference

engine in which is used to process the rule to deduce

another set of rule or fact.

The inference engine is normally designed by the

programmer or designer. The inference engine is

then connected to the user interface in which is used

to collect data from the users. This is also developed

by the designer. This trend can also be followed

backward. The user interface gives information to

the inference engine and the knowledge base for

user data to be processed. Also for the knowledge

base update, a need to contact the domain expert is

needed. All this can be represented below (Figure 1).

User

Interface

Inference

Engine

Knowledge

base

Domain

Expert

Description of

new cases

Advice and

Explanation

EXPERT SYSTEM

Figure 1: Expert system architecture (Ayangbekun, 2015)

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Application on Green Technology

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2.2 Medical Knowledge

The medical knowledge of specialized doctor is

required for the development of an expert system.

This knowledge is collected in two phases. In the

first phase, the medical background of skin diseases

is recorded through the creation of personal

interview with doctors and patients. In the second

phase, a set of rules is created where each rule

contains in IF part that has the symptoms and in

THEN part that has the disease that should be

realized. The inference engine (forward chaining) is

a mechanism through which rules are selected to be

fired. It is based on a pattern matching algorithm

whose main purpose is to associate the facts (input

data) with applicable rules from the rule base. The

search is done by using rules whose premise

matches the known facts to gain new facts and

continue the process until the goal is reached or until

there is no more rules whose premises match the

known facts as well as the facts obtained. Finally,

the skin diseases are produced by the inference

engine.

3 RESEARCH METHOD

This document was research procedures consist of:

preliminary study, data collection, data analysis,

system design, system implementation, system

evaluation, and drawing conclusion (Munaiseche et

al., 2018)

Preliminary Study. At this stage, the authors

collected information, study materials and data

sources related to expert systems, forward chaining

methods, rule-based reasoning, the types of skin

diseases in humans, symptoms of skin diseases and

treatment or preventive solutions.

Data Collection. Data sources used in expert

systems to diagnose skin diseases in humans include

data of the skin disease type, skin disease symptoms,

disease information and solutions provided. The data

required in this study were obtained from Literature

Study and Consultation/interview with experts, in

this case dermatologist.

Data Analysis. Based on the collected data, the

researcher conducted following analysis steps: 1)

Made a list and coded eye diseases along with

symptoms. This expert system software can

diagnose 15 types of eye diseases with 54 symptoms

of the disease; 2) Made Rule-Based System. In order

to recognize the type of skin disease, rules in expert

system tracing are required. There are 15 Rules and

a forward chaining hierarchy called the Rule-Based

System.

System Design. The design of this system

includes design process described by using decision

tree, context diagram explaining the relationship

between input / output between system with outer

world, data flow diagram (DFD), the design of the

database and user interface.

System Implementation. The activitiy

performed at this stage was the programming or

coding. This stage was the translation of the design

into the form of computer programming language.

This research employed PHP programming

language.

Preliminary Study

1. Forward Chaining Method

2. Rule-based Reasoning

3. Types, symptoms of skin diseases and

treatment or preventive solution

Data Collection

Literature Study

Data of types and symptoms of skin disease

and treatment or preventive solution

Interview with Expert

(Dermatologist)

Data Analysis

1. Giving code the types and symptoms of each skin desease

2. Creating a Knowledge Table

3. Creating a Rule-Based System (Knowledge Represenation)

System Design

1. Process design (Decision Tree)

2. Context and Data Flow Diagram

3. Database design

Conclusions

System Implementation

Programming/Coding (PHP and MySQL)

System Evaluation (Black Box Testing)

Figure 2: Research procedures

System Evaluation. The evaluation of this

expert system uses black box testing. This

evaluation aims to find out a function erroron the

software that has been built. In addition, this test was

carried out by trying all the possibilities that

happened and done repeatedly. If the test found an

error, it will be traced and corrected all errors that

occur.

Expert System Implementation for the Diagnosis of Skin Diseases using Forward Chaining Method

289

Conclusion. A conclusion will be drawn from

the results of these evaluations based on the results

of testing (black box testing) of the expert system.

The research prossedure is shown in Figure 2.

4 RESULT AND DISCUSSION

4.1 Result

This research results in a web-based expert system

that can recognize the type of skin disease in humans

based on the symptoms experienced by patients.

This system performs analysis based on the

dialogue between the system with the user/patient.

The web-based expert system of skin disease

diagnosis is designed by using PHP programming

language and MySQL for database processing. Some

interfaces from the skin disease diagnosis expert

system are shown in Figure 3 and Figure 4.

Figure 3: The main page interface (home menu)

The main page interface of the application

(Figure 3) consist of five Menus (Home, Daftar

Penyakit, Konsultasi, Login Pakar and Kontak).

Figure 4: Interface of admin menu

Interface of admin page (Figure 4) consist of

eight menus (Input Penyakit, Input Gejala, Input

Relasi, Ubah Penyakit, Ubah Gejala, Laporan

Penyakit, Laporan Gejala dan Logout).

4.2 Discussion

Testing is an important part of a software

development. Testing is intended to find errors on

the system and ensure that the system built is in

accordance with what is pre-planned. Tests are

carried out to ensure quality and also find out the

weaknesses of the software. The purpose of this test

is to ensure that the software built has quality

reliable, namely being able to present the principal

studies of the analysis specifications, design and

coding of the software itself.

Tests performed on the functionality of this

software use the Black Box method. This test is a

test that focuses on the functional requirements of

software. The purpose of testing with the Black Box

method is to find malfunctions in the software that

has been built. In addition, this test is done by trying

all the possibilities that occur and are done

repeatedly. If an error is found in the test, a search

and repair will be carried out to correct the error.

Blackbox testing includes: expert login testing,

data filling, expert consultation and testing of system

diagnostic results, which are made in several test

scenarios. Based on the results of black box testing,

the expert system application has been running with

good. However, it does not rule out the possibility of

errors when the application is used in a real

environment. In addition, the software built is free of

syntax errors and according to expected

functionality.

5 CONCLUSIONS

From this study some conclusions can be drawn,

namely:

1. Build an expert system applications to diagnose

skin diseases in humans can use the search

process with the forward chaining as a inference

method.

2. Patients can immediately consult a software

system without having to consult with a expert

(dermatologist) on condition that they have to

3. The system can only diagnose one patient in

consultation and can only recognize and

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Application on Green Technology

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diagnose the type of skin disease in the truth

table of the disease.

4. Admin can manipulate data rules or rules.

5. Based on the results of black box testing that has

been done, it can concluded that this application

that has been built has been running with good.

However, it does not rule out the possibility of

errors when the application is used in a real

environment.

REFERENCES

Brian, R., Gaines, 2010. Designing Expert System for

Usability, Available from:

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.

1.1.414.583&rep=rep1&type=pdf

Gudu, J., Gichoya, D., Nyongesa, P., Muumbo, A., 2012.

Development of a Medical Expert System as an Expert

Knowledge Sharing Tool on Diagnosis and Treatment

of Hypertension in Pregnancy. Int. J. of Bioscience,

Biochemisry and Bioinformatic, Vol 2(5) pp. 297-300

Ayangbekun, O. J., Olatunde, A. Ii., Bankole, F. O., 2014.

An Expert System for Diagnosis of Blood Disorder,

Int. J. of Comp. Applic. (ISSN: 0975-8887), Vol 100,

pp 36-40

Ayangbekun O. J., Jimoh I. A., 2015. Expert System for

Diagnosis Neurodegenerative Diseases. Int. J. of

Comp. and Inf. Technol., Vol 04, pp. 694-698

Munaiseche, C. P. C., Liando O. E. S., 2016. Evaluation of

Expert System Application Based On Usability

Aspects. IOP Conference Series: Materials Science

and Engineering, Vol 128, pp 1-10

Patra, P. S. K., Sahu, D. P., Mandal I., 2010. An Expert

System for Diagnosis of Human Diseases. Int. J. of

Comp. Applications, Vol 1(13), pp 71-73

Munaiseche, C. P. C., Kaparang, D. R., Rompas, P. T. D.,

2018. An Expert System for Diagnosing Eye Diseases

using Forward Chaining Method. IOP Conference

Series: Materials Science and Engineering, Vol

306(1), pp 1-10

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