Експертна система виявлення депресії у підлітків
Depression (major depressive disorder) is a common and serious medical illness that negatively affects how you feel, think, and act. Fortunately, it is treatable. Depression causes sadness and/or a loss of interest in activities once enjoyed. It can lead to various emotional and physical problems an...
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The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2022
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| author | Raharja, Bintang Samudera, Elfajar Bintang Lay, Ferry Hansun, Seng |
| author_facet | Raharja, Bintang Samudera, Elfajar Bintang Lay, Ferry Hansun, Seng |
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| description | Depression (major depressive disorder) is a common and serious medical illness that negatively affects how you feel, think, and act. Fortunately, it is treatable. Depression causes sadness and/or a loss of interest in activities once enjoyed. It can lead to various emotional and physical problems and decrease a person’s ability to function at work and home. Teenagers often experience this disorder because their emotions are still unstable. They also don’t have many chances to consult with a psychologist and doctor. Through this research, an expert system was created that implements knowledge from experts related to depression so that teenagers can do a self-test when needed. The expert system was developed using the Certainty Factor method for the knowledge inference engine. The system was tested iteratively and could achieve similar results with a domain expert. We hope that the system can detect early symptoms of depression among teenagers and minimize the negative impact it may cause. |
| doi_str_mv | 10.20535/SRIT.2308-8893.2022.2.12 |
| first_indexed | 2025-07-17T10:27:41Z |
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B. Raharja, E.B. Samudera, F. Lay, S. Hansun, 2022
ISSN 1681–6048 System Research & Information Technologies, 2022, № 2 143
UDC 62-50
DOI: 10.20535/SRIT.2308-8893.2022.2.12
EXPERT SYSTEM FOR DEPRESSION DETECTION
IN TEENAGERS
B. RAHARJA, E.B. SAMUDERA, F. LAY, S. HANSUN
Abstract. Depression (major depressive disorder) is a common and serious medical
illness that negatively affects how you feel, think, and act. Fortunately, it is treat-
able. Depression causes sadness and/or a loss of interest in activities once enjoyed. It
can lead to various emotional and physical problems and decrease a person’s ability
to function at work and home. Teenagers often experience this disorder because
their emotions are still unstable. They also don’t have many chances to consult with
a psychologist and doctor. Through this research, an expert system was created that
implements knowledge from experts related to depression so that teenagers can do a
self-test when needed. The expert system was developed using the Certainty Factor
method for the knowledge inference engine. The system was tested iteratively and
could achieve similar results with a domain expert. We hope that the system can de-
tect early symptoms of depression among teenagers and minimize the negative im-
pact it may cause.
Keywords: certainty factor, depression, detection, expert system, teenagers.
INTRODUCTION
The life of a human being goes through several phases change. This phase starts
from when humans are babies until humans die. In human growth, there is an ado-
lescent phase, namely the transitional phase of children to maturity in the age
range of 12 years to 20 years [1].
Adolescence in a child can have various dynamic changes, one of which is
emotion. Therefore, a teenager must be able to adapt to any changes that exist.
When a teenager cannot adapt or control himself over his emotions and thoughts,
it is not uncommon for a teenager to be depressed due to negative thoughts. De-
pression experienced by a teenager is not just a temporary feeling of stress and
sadness, but there is a serious condition that can permanently affect behaviour,
emotions, ways of thinking, and character that must be given special treatment to
overcome it [2].
For teenagers who are in that phase, they may find it difficult and confused
about who to go and consult to. This expert system that we designed aims to help
teenagers and parents to make an early diagnosis of depression that may occur in
a teenager. Our expert system is designed in the form of a website due to the ease
of internet access, particularly in Indonesia.
By conducting this research, we hope to help teenagers to find out the level
of depression they are experiencing. The other purpose of this system is to facili-
tate communication between parents and children regarding depression. With this
expert system, it is hoped that parents can facilitate further treatment for their
child if needed. To support this goal, the prediction results must have good accu-
racy. Here, we implement the Certainty Factor method in inferencing the knowl-
edge base to the final decision shown to the user.
B. Raharja, E.B. Samudera, F. Lay, S. Hansun
ISSN 1681–6048 System Research & Information Technologies, 2022, № 2 144
With this expert system, we hope that teenagers will have the courage to
carry out self-diagnosis with good accuracy so that they can communicate with
their parents for further treatment. For parents who are also worried about their
child, they can monitor the child’s actions and carry out a diagnosis with the
child. This system can also help psychologists in carrying out their duties more
quickly.
THEORETICAL BASIS
A. Expert System
An expert system is a computer-based system that can replace experts in solving
problems by using knowledge, facts, and reasoning techniques [3].The definition
of an expert system is a computer program that has expert knowledge of a specific
field. From these two definitions, it can be concluded that an expert system is a
program designed to have the knowledge to solve problems in a specific field like
an expert.
In the development of an expert system, there are two main structures,
namely the development environment and the consultation environment. The de-
velopment environment is useful for entering expert knowledge into the expert
system and the consultation environment is used by users to get results from the
knowledge of an expert via the system [4].
B. Scrum Method
Software Development Life Cycle (SDLC) is a cycle in making a system with the
aim of solving a problem effectively. With the proper use of SDLC, the resulting
system can be of high quality and in accordance with the wishes or objectives of
the formation of the system. According to Mulyani [5], SDLC is a set of logical
processes applied by a systems analyst to develop an information system that in-
volves requirements, validation, training, and discussion with system owners.
Scrum is basically one of the lightest Agile methods but can provide advan-
tages in setting the stages and control in the development of a system or product
[6]. This method relies on a collection of methods and practices that apply the
values and principles of the Agile Manifesto [7]. With the use of Scrum, there is a
sprint component which is a series of stages carried out in one process simultane-
ously. The main purpose of using Scrum is to get the Minimum Viable Product
(MVP) value at the end of each sprint [8].
C. Depression
Depression is a condition in which a person’s daily life is filled with feelings of
pain, disappointment, sadness, and emotional confusion. Depression can be
caused by trauma, guilt, isolation, and deep pain [9]. Depression can be concluded
as a continuous feeling of sadness that a person feels and impacts on a person’s
thoughts and actions that can be caused by the environment around them and
themselves.
In this study, we used 29 symptoms of depression in teenagers as mentioned
by Burns in Widians et al. [10]. Table 1 shows the list of those symptoms used in
this study.
Expert system for depression detection in teenagers
Системні дослідження та інформаційні технології, 2022, № 2 145
T a b l e 1 . Depression symptoms [10]
Code Symptom Code Symptom
G001 Sad G016 Feeling lonely
G002 Tiredness in doing activities G017 Feeling guilty
G003 Difficulty to focus G018 Often feel being punished
G004 Feeling bored G019 Self-hatred
G005 Daydreaming G020 Easily offended
G006 Not excited G021 Loss of appetite
G007 Often upset G022 Worried about one appearance
G008 Pessimistic about the future G023 Very sensitive
G009 Often cries without explainable
reasons G024 Prefer to be alone
G010 Insomnia G025 Having thoughts of suicide
G011 Often anxious G026 Difficulty to make a decision
G012 Disappointed with oneself G027 Difficulty to do activities well
G013 Often disturbed G028 Weight gain or loss
G014 Looks gloomy G029 Less confident
G015 Loss of interest in hobbies that
used to be liked
D. Certainty Factor
Certainty Factor (CF) is a method proposed by Shortliffe and Buchanan in 1975
to accommodate the exact reasoning of an expert [11]. An expert (for example:
doctor) often analyses information with the expressions “probably”, “most
likely”, “almost certain”. So that with the Certainty Factor method, it can describe
the level of confidence of an expert on the problem at hand. The basic formula to
calculate the confidence level of a rule is shown in [12]:
],[],[],[ ehMDehMBehCF
where ],[ ehCF is the certainty factor, ],[ ehMB is the measure of belief of hy-
pothesis )(h given evidence )(e , and ],[ ehMD is the measure of disbelief of hy-
pothesis )(h given evidence )(e .
Moreover, Certainty Factor formula for one premise is shown in CF[h,e] =
= CF[t]*CF[rule] = CF[user]*CF[expert], while for two or more premises is
shown in [13]–[15]:
,0 xor 0 if,
})||,||{min1(
,0, if), 1(
,0, if), 1(
),(
21
21
21
21121
21121
21
CFCF
CFCF
CFCF
CFCFCFCFCF
CFCFCFCFCF
CFCFCFc (1)
where ][eCF is the certainty factor of given evidence which can be represented as
certainty factor given by user, ][ruleCF is the certainty factor rule given by an
expert, CFc is the combined certainty factor from the other two known certainty
factor following the rules (1).
B. Raharja, E.B. Samudera, F. Lay, S. Hansun
ISSN 1681–6048 System Research & Information Technologies, 2022, № 2 146
METHODOLOGY
In this research, we use Scrum method. Scrum itself uses an approach from an-
other method, namely Agile. Scrum helps teams to solve problems, by having
strong communication between team members [16]. Steps in the Scrum Method
are follows:
1. Define the team.
2. Determine the processing time.
3. Define roles in the team.
4. Collect various problems.
5. Start a sprint. Sprint is a series of work carried out to solve a problem, es-
pecially the creation of a new product.
Our research is assisted by qualitative data collection methods. Qualitative
research is a type of research whose findings are not obtained through statistical
procedures or other forms of calculation and seeks to understand and interpret the
meaning of an event of human behavior interaction in certain situations according
to the researcher’s own perspective [17]. We use interviews and literature study as
data collection tools.
1. Interview. In addition to observations, direct interviews were also con-
ducted with experts who have special knowledge about depression in adolescence.
2. Literature Study. In this method, searches and learning are carried out
from various kinds of literature, and documents that can support the work of this
project, including from books, scientific articles, scholarly journals, and also from
various internet websites that provide information that is relevant with the study.
RESULTS AND DISCUSSION
A. Implementation Results
Based on the research and iterative development procedure, there are several fur-
ther development from the initial design of the system which is finalize as fol-
lows. Firstly, there is homepage as main display when the site is accessed (Fig. 1).
There is a “Get Started” button which will lead to the Identification menu to per-
form a diagnosis.
On the Identification page as
shown in Fig. 2, users can fill in the
symptoms provided for the calcula-
tion process to be carried out using
the Certainty Factor method. There is
a total of 29 questions being used in
this study. When finished inputting
symptoms, the user can click the but-
ton with the magnifying glass icon at
the bottom right of the screen to
display the results of the diagnosis
(Fig. 3).
Fig. 1. Homepage of the system
Expert system for depression detection in teenagers
Системні дослідження та інформаційні технології, 2022, № 2 147
Fig. 2. Identification page
There is also a page which show the basic information about depression as
shown in Fig. 4. On this page, users can read information about the level of de-
pression, details of the depression level, and some suggestions that have been
provided. The system prototype may be found at https://uasexpertsystem.
000webhostapp.com/.
Fig. 3. Analysis result
B. Raharja, E.B. Samudera, F. Lay, S. Hansun
ISSN 1681–6048 System Research & Information Technologies, 2022, № 2 148
B. Evaluation and Discussion
We conducted several evaluation methods, including the usability test of the built
system and expert evaluation from a psychologist who has a legal license to per-
form his practice as an expert in this domain. Table 2 shows the usability test re-
sults on three main functionalities provided in the system.
T a b l e 2 . Usability test results
System component Results
Main menu
The main menu is simple and easy to use where when the user
wants to identify depression, they can click the “Get Started” or
“Identify” button on the menu bar on the left
Identification
menu
Has clear instructions for identification and easy-to-read writing.
After identifying the user, he gets information about the identified
depression and gets suggestions that can be applied by the user
Depression
Type menu
It has an easy-to-understand display where there are types
of depression, a “Details” button that displays a description
of depression, and a “Suggestion” button that displays suggestions
for selected depression sufferers
The evaluation with experts was carried out for the first time on November
17th, 2021. During the evaluation process, a calculation test was carried out three
times with the following results as shown in Table 3.
T a b l e 3 . First evaluation result
Iteration # Result Expectation
1 Severe Depression (1%) Middle Depression
2 Severe Depression (12%) Mood Disorder
3 Severe Depression (1%) Severe Depression
From the results of the calculation test above, it was found that there was an
error in the calculation formula and a mismatch of the Certainty Factor value for
the knowledge based used in this study. Therefore, several changes were made so
that the calculation results got the final value as shown in Table 4.
Fig. 4. Types of depression
Expert system for depression detection in teenagers
Системні дослідження та інформаційні технології, 2022, № 2 149
T a b l e 4 . Optimization result
Iteration # Result Expectation
1 Middle Depression (98%) Middle Depression
2 Mood Disorder (100%) Mood Disorder
3 Severe Depression (100%) Severe Depression
CONCLUSION
In this study, we have successfully built an expert system for diagnosing depres-
sion in teenagers. The system knowledge is inferenced by the Certainty Factor
method and could diagnose the level of depression based on the existing knowl-
edge base that is quite accurate. Based on the evaluation results, the system gives
results that are in line with expert expectations.
In the future, this research can still be developed by increasing the level of
complexity and variations in the value of trust and the value of distrust that is
more specific with the latest symptoms in the depression level detection. Other
inference methods, ranging from Forward and Backward Chaining [18] to Fuzzy-
based [19] or even Machine Learning-based such as the Long Short-Term Mem-
ory [20], might be applied in comparison with this study result.
ACKNOWLEDGEMENTS
We would like to extend our gratitude for the support given by Universitas Mul-
timedia Nusantara during the study.
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Received 23.02.2022
INFORMATION ON THE ARTICLE
Bintang Raharja, Multimedia Nusantara University, Tangerang, Indonesia, e-mail:
bintang.raharja@student.umn.ac.id
Elfajar Bintang Samudera, Multimedia Nusantara University, Tangerang, Indonesia, e-
mail: elfajar.bintang@student.umn.ac.id
Ferry Lay, Multimedia Nusantara University, Tangerang, Indonesia, e-mail:
ferry.lay@student.umn.ac.id
Seng Hansun, ORCID: 0000-0001-6619-9751, Multimedia Nusantara University, Tan-
gerang, Indonesia, e-mail: seng.hansun@lecturer.umn.ac.id
ЕКСПЕРТНА СИСТЕМА ВИЯВЛЕННЯ ДЕПРЕСІЇ У ПІДЛІТКІВ / Б. Рахарджа,
Е.Б. Самудера, Ф. Лей, С. Хансун
Анотація. Депресія (великий депресивний розлад) є поширеним і серйозним
медичним захворюванням, яке негативно впливає на самопочуття, на те, як
думаєте і як дієте. На щастя, це піддається лікуванню. Депресія викликає по-
чуття смутку та/або втрату інтересу до діяльності, яка колись приносила насо-
лоду. Це може призвести до різноманітних емоційних і фізичних проблем і
знизити здатність людини функціонувати на роботі та вдома. Цей розлад часто
трапляється у підлітків, оскільки їхні емоції більш нестабільні. У них також не
так багато шансів проконсультуватися з психологом і лікарем. Завдяки цьому
дослідженню створено експертну систему, яка реалізує знання експертів,
пов’язаних з депресією, щоб підлітки могли проводити самоперевірку, коли це
необхідно. Експертну систему розроблено з використанням методу фактора
визначеності для механізму виведення знань. Систему перевірено ітеративно,
подібних результати отримано і за допомогою експерта в галузі. Сподіваємося,
що система зможе виявити ранні симптоми депресії серед підлітків і мінімізу-
вати негативний вплив, який вона може спричинити.
Ключові слова: фактор визначеності, депресія, виявлення, експертна система,
підлітки.
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| id | journaliasakpiua-article-251599 |
| institution | System research and information technologies |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2025-07-17T10:27:41Z |
| publishDate | 2022 |
| publisher | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
| record_format | ojs |
| resource_txt_mv | journaliasakpiua/97/e33bc8fdb3a46cc71a87376e80c39b97.pdf |
| spelling | journaliasakpiua-article-2515992022-10-17T22:12:39Z Expert system for depression detection in teenagers Експертна система виявлення депресії у підлітків Raharja, Bintang Samudera, Elfajar Bintang Lay, Ferry Hansun, Seng certainty factor depression detection expert system teenagers фактор визначеності депресія виявлення експертна система підлітки Depression (major depressive disorder) is a common and serious medical illness that negatively affects how you feel, think, and act. Fortunately, it is treatable. Depression causes sadness and/or a loss of interest in activities once enjoyed. It can lead to various emotional and physical problems and decrease a person’s ability to function at work and home. Teenagers often experience this disorder because their emotions are still unstable. They also don’t have many chances to consult with a psychologist and doctor. Through this research, an expert system was created that implements knowledge from experts related to depression so that teenagers can do a self-test when needed. The expert system was developed using the Certainty Factor method for the knowledge inference engine. The system was tested iteratively and could achieve similar results with a domain expert. We hope that the system can detect early symptoms of depression among teenagers and minimize the negative impact it may cause. Депресія (великий депресивний розлад) є поширеним і серйозним медичним захворюванням, яке негативно впливає на самопочуття, на те, як думаєте і як дієте. На щастя, це піддається лікуванню. Депресія викликає почуття смутку та/або втрату інтересу до діяльності, яка колись приносила насолоду. Це може призвести до різноманітних емоційних і фізичних проблем і знизити здатність людини функціонувати на роботі та вдома. Цей розлад часто трапляється у підлітків, оскільки їхні емоції більш нестабільні. У них також не так багато шансів проконсультуватися з психологом і лікарем. Завдяки цьому дослідженню створено експертну систему, яка реалізує знання експертів, пов’язаних з депресією, щоб підлітки могли проводити самоперевірку, коли це необхідно. Експертну систему розроблено з використанням методу фактора визначеності для механізму виведення знань. Систему перевірено ітеративно, подібних результати отримано і за допомогою експерта в галузі. Сподіваємося, що система зможе виявити ранні симптоми депресії серед підлітків і мінімізувати негативний вплив, який вона може спричинити. The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2022-08-30 Article Article application/pdf https://journal.iasa.kpi.ua/article/view/251599 10.20535/SRIT.2308-8893.2022.2.12 System research and information technologies; No. 2 (2022); 143-150 Системные исследования и информационные технологии; № 2 (2022); 143-150 Системні дослідження та інформаційні технології; № 2 (2022); 143-150 2308-8893 1681-6048 en https://journal.iasa.kpi.ua/article/view/251599/261779 |
| spellingShingle | фактор визначеності депресія виявлення експертна система підлітки Raharja, Bintang Samudera, Elfajar Bintang Lay, Ferry Hansun, Seng Експертна система виявлення депресії у підлітків |
| title | Експертна система виявлення депресії у підлітків |
| title_alt | Expert system for depression detection in teenagers |
| title_full | Експертна система виявлення депресії у підлітків |
| title_fullStr | Експертна система виявлення депресії у підлітків |
| title_full_unstemmed | Експертна система виявлення депресії у підлітків |
| title_short | Експертна система виявлення депресії у підлітків |
| title_sort | експертна система виявлення депресії у підлітків |
| topic | фактор визначеності депресія виявлення експертна система підлітки |
| topic_facet | certainty factor depression detection expert system teenagers фактор визначеності депресія виявлення експертна система підлітки |
| url | https://journal.iasa.kpi.ua/article/view/251599 |
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