Decision Support System for Determining
Problematic Students Using the Analytic Network Process (ANP) Method
Fitri
Nuraida
Faculty of Science and Informatics, Universitas
Jenderal Achmad Yani, Indonesia
Email: [email protected]
In the world of
primary and secondary education in Indonesia, educational guidance and
counseling services aim to help students become individuals who can overcome
problems well. In general, teenage students cannot be separated from the
problems they face, especially during the transition period because these
problems can disrupt students' learning activities. Teacher Counseling Guidance
(BK) or counselor is a teacher who is obliged to provide direction and guidance
to students. One of the problems faced by schools is that it is difficult to
determine quickly and precisely which students really need to be given
direction and guidance immediately. In this research, a decision support system
was created using the Analytical Network Process (ANP) method for problematic
students who needed counseling services. ANP is a decision-making method that
has many or multiple criteria and methods. The result of this research is a
decision support system that can determine problematic students so that this
system can help schools, especially guidance and counseling
teachers/counselors, take the right approach to problematic students.
Keywords: ANP, guidance, teacher, counseling, method, student,
system
INTRODUCTION
School
rules and regulations are rules and regulations made by the school. Each school
has different regulations(Afrila,
Fitria, Amalia, Imrayani, & Safitri, 2023). In the world of
education, obeying school regulations or not breaking the rules is the main
aspect of forming students in creating self-understanding with personal skills
and learning outcomes, making students with good behavior and achievement as
well as school regulations so that student learning activities at school run
efficiently and effectively(Surya
& Wahyu, 2020).
SStudents are students who are experiencing a development
process and are vulnerable to existing problems(Afiani & Faradita, 2021). Problematic students are one of the factors that influence
the comfort of the teaching and learning process in the school environment.(Syaputra, Khairullah, Pahrizal, &
Mahfuzi, 2023). Understanding information about problematic students'
attitudes is a guide for making improvements to students in the future(Susanty, 2022). The student
violation in question can obtain data about the students' attitudes(Susanty,
2022). Students can be said to be good, not good, quite good,
not good, not good if the violation causes changes in the course of learning in
class.(Dwiyanti & Dermawan, 2020).
The
class teacher and guidance counselor who will carry out an analysis of
violations among students are expected to be able to find out information about
the attitudes and behavior that are violated by students, so that the class
teacher can take steps to overcome violations for students who have problems in
the form of tests or counseling guidance services.(Yuniarthe & Wahyudi, 2021). Awareness
of discipline should be able to grow and develop in students based on their own
awareness because even though teachers, homeroom teachers and school principals
are responsible for enforcing discipline among students, the implementation
must be based on the students' awareness and will.(Fandini,
Sulatani, & Susanto, 2018).
One
method that can make decisions that solve problems based on interrelated
criteria and cannot be structured hierarchically(Sanusi,
2023). Analytic Network Process (ANP) is a development method
of the Analytic Hierarchy Process (AHP) method. The ANP method can accommodate
a relationship between criteria and alternatives and relative measurements(Irawan,
2018).
Several
studies have studied problematic students and their violations, namely research
by FD Wihartiko, applying the Analytical Network Process (ANP) method to
display the ranking of sanctions at the Bogor Infokom Vocational School using a
point system for students who commit school violations and these points will be
processed for three once a month and an evaluation is carried out(Wihartiko,
Tosida, & Sentosa, 2018). Research by H. Sitohang, applies the
SAW method to determine students who commit violations at the Mulia Pratama
Medan Private Middle School using a system that provides information and can
also help by generating an alternative solution for students for each violation
committed.(Sihotang & Siboro, 2016). Research
by A. Widhiyanti, I. Candiasa, K. Aryanto, applies the implementation of
AHP-TOPSIS and Na�ve Bayes to make decisions in providing guidance to students
at SMAN 5 Denpasar which will give rise to a system that will determine which
students' priorities will come first given counseling guidance along with
treatment.
Based
on the explanation above, the author is interested in applying the ANP
(Analytic Network Process) method in determining problem students at Angkasa
Bandung High School. This research aims to develop an effective decision
support system with ANP to minimize student problems, with a focus on 2021
student data and certain assessment criteria such as subject grades, social
life, and violations. This research also limits the cases considered to the
light level and does not process serious cases such as serious crimes. The
output of this research is a system that can help schools determine problematic
students and the results will be published in national seminars and scientific
journals.
In
this research, the method used includes several important steps. First,
assessment criteria are determined, which include subject grades, attendance,
social life, discipline, obedience, and achievement. Data is collected in two
categories: criteria (subject grades, social life, violations) and alternative
(names of students). A literature study was carried out to find references
related to the ANP method, while the field study was applied to science and
social studies students at Angkasa Lanud Husein High School, Bandung.
Observations were carried out to collect student report card data as a
reference, followed by interviews with related parties. Data processing
includes software design which includes determining criteria, creating pairwise
matrices, weighting, and calculating scores to produce rankings of problematic
students.
The
Analytical Network Process (ANP) method is a method that can improve the
weaknesses of the ANP method in the form of a capability that supports the
relationship between criteria and alternatives.(Frastian, Katarina, & Heriyati, 2018).
Angkasa Lanud Husein Sastranegara High School is a school
under the auspices of the Ardhya Garini Foundation which was founded on May 19
1980. Starting with members of the Indonesian Air Force who served in the
Husein Sastranegara environment, at that time they had difficulty finding an
existing high school (SMA). In the Husein Sastranegara neighborhood
there are only junior high schools (SMP). The parents of these pre-soldiers had
to send their children to high school which was very far away, because the situation
became increasingly difficult, finally the families of these soldiers proposed
to the commander to establish a high school (SMA) in the area. This assumption
was accepted by Mrs. Dahlia M. Diran, as chairman of the Srihdya Garini
Foundation, branch V of Husein Sastranegara Air Base(Sofiati
& Sumarni, 2016).
This Angkasa High School is under the auspices of the
Ardhya Garini Foundation, the Adhi Upay Foundation and the educational
cooperation agency for Husein Sastranegara Air Base at the current location of
the high school. At the beginning of its establishment, Angkasa High School
only had 4 classes, due to the large number of sons and daughters of military
personnel who wanted to register. Eventually it was added to 5 classes and was
immediately inaugurated on August 30, 1980.(Yulizah, 2019).
The data used in this research is data taken from the
Counseling and Student Affairs Office of SMA Angkasa Lanud Husein Sastranegara
Bandung. This data was created in 2019/2020. The following is a table of
criteria and alternatives:
1.
Criteria
Table 1. Criteria
|
No |
Criteria |
|
1 |
a.
B. Indonesia b.
Mathematics c.
Biology d.
B. Germany e.
PIE f.
PKN g.
B. English h.
Physical education i.
SBK j.
Crafts k.
B. Sundanese |
|
2 |
Social
Spirit |
|
3 |
Violation |
2.
Alternative����������
Table1. Alternative
|
No |
Alternative |
|
1 |
Student1���� |
|
2 |
Student2 |
|
3 |
Student3 |
|
4 |
Student4 |
|
5 |
Student5 |
Alternative analysis
in this research focuses on alternative data which is a collection of
information about student choices to be assessed. This data consists of
problematic students at Angkasa Lanud Husein Sastranegara High School. This
research aims to select students who show behavior or academic performance that
indicates problems, using the ANP (Analytic Network Process) method to produce
rankings. ANP is a decision-making method that allows structured and objective
assessment and comparison.
In this research,
there are five main criteria used to assess problematic students, each with
relevant sub-criteria. These criteria include:
1. Subject Values
These criteria are
used to assess students' academic results in various subjects. This is
important because academic grades can indicate problems in a student's learning
process, even if they attend consistently. Sub-criteria in this criterion
include subjects such as Indonesian, Mathematics, Biology, German, Islamic
Religious Education (PAI), Citizenship Education (PKN), English, Physical and
Health Education (Penjas), Arts and Culture Skills (SBK) ,
Crafts, and Sundanese.
2. Social Spirit
This criterion
evaluates students' character, attitudes and social interactions both in the
school environment and outside of school. A good social spirit can reduce the
possibility of students committing violations. This evaluation is important to
understand students' attitudes and feelings that may influence their behavior.
3. Violation
This criterion
examines the frequency and types of discipline violations committed by
students. This type of violation includes internal violations determined by the
school and serves to assess the extent to which students follow existing rules.
Data collection involved gathering information through
observation and various sources such as subject grades, rule violations, and
student needs questionnaires (AKPD) provided by guidance and counseling
teachers and students at Angkasa Lanud Husein Sastranegara Bandung High School.
Following data collection, criteria for decision-making were established,
including subject grades, attendance, social life, discipline, and violations,
with each criterion assigned a weight based on its importance in student assessment.
The weight value of each alternative was determined using a weight table,
categorizing course marks into ranges such as below 75 (Not Good), 75-82
(Fair), 83-90 (Good), and above 91 (Very Good). A pairwise comparison matrix
was then used to compare priorities between criteria, aiding in determining the
relative weight of each criterion. After comparison, the normalization matrix
was calculated by dividing values in the comparison matrix by the number of
columns, with the eigenvalue derived as the average of the normalization
results to determine the final priority of the criteria. Finally, the
consistency ratio was calculated to ensure the comparisons were consistent,
using the Consistency Index (CI) and Consistency Ratio (CR) formulas to measure
the consistency of the decisions made.
This system involves one main actor, namely the user, who
has access to manage the data and features in the system, including student
data, users, criteria, and criteria analysis. The business use case describes
the interaction between the user and the system which is designed to produce
decisions regarding problematic students by providing data management and
calculation features using the ANP method. Use case diagrams explain
interactions between actors and systems, while use case scenarios describe operational
details such as login, management of criteria and student data, as well as ANP
processes, including how users interact with the system and the system's
reactions to user actions. The activity diagram shows the flow of activities
between the user and the system, including management of criteria and student
data as well as the ANP process, illustrating the interaction of various system
components to achieve goals. Sequence diagrams describe interactions between
objects in the system to achieve certain goals, such as managing criteria data,
students, and ANP calculations, as well as how information is processed and
transferred between objects. Class diagrams visualize the system structure in
terms of technical components, including tables used to store student data,
criteria, and grades, as well as relationships between classes in the system.
The database design is designed to store the required information, including
criteria tables, students, criteria values, and users, with an efficient table
design to ensure data can be accessed easily and supports system functions. The
design and design of this system aims to create an effective decision aid tool
in assessing problematic students, ensuring all relevant aspects are
considered, and providing accurate and reliable output.
Implementation
And Testing
At
the implementation stage, the software is developed according to the previous
design using a personal computer to facilitate the testing process. This software
is web-based, built with the PHP programming language and using the Studio Code
or Notepad++ tools, while Google Chrome is used as a browser, and the MySQL
database and Apache Web Server are integrated through the XAMPP application.
The database is implemented following the design that has been created, with
the MySQL database as the basis. The implementation includes various tables
such as Criteria, Criteria_Value, Students, Student_Criteria_Value,
Student_Value, Alternatives, Alternative_Values, and User. Each table is
organized to store the required information according to the system being
developed, ensuring a data structure that suits the application needs. The
interface implementation in this system includes several key components
designed to manage various functions. The Login Interface is the first page
displayed when the system is started, where the admin can access the system by
entering the registered email and password. The Criteria interface allows users
to manage student criteria with create, update, read, and delete functions. The
Student Interface is designed to manage student data with create, update and
delete options. The ANP process is implemented to calculate and display the
matrix after criteria selection, while the Alternative Node interface is used
to select alternative data and display the relevant matrix. Finally, the User
interface allows managing user data with create, update, and delete functions.
Testing
is an activity carried out to test a system that has been built. This is done
with the aim of testing the quality of the system whether it is in accordance
with the design or not. The testing carried out in this research is by using
Black Box Testing which focuses on functional testing of the software and
identifying bugs to be fixed before release.
CONCLUSION
Based
on research conducted by applying the Analytic Network Process (ANP) method, it
can be concluded that this method is able to produce values and
ranking order. Although ANP provides a measurement scale for determining
priorities, this method relies heavily on user input, such as admins or
decision makers who must have knowledge and experience related to the choices
made, considering that the ANP calculation process involves many stages. In
analyzing and designing a decision support system to determine problematic
students, this research aims to display a ranking sequence for problematic
students, where the system created produces data about students who require
special treatment as recommendations for decision makers. The implementation of
ANP at Angkasa Lanud Husein Sastranegara High School was successful by
determining the reference criteria for decision making, rating the suitability
of each alternative for each criterion, assigning value weights to the
criteria, normalizing the matrix, and ranking using the superlimit matrix to
find the largest value for each alternative. System testing using black box
testing shows 100% results, indicating the system is running well and can
display the ANP calculation results. Determining problematic students produces
an accuracy of 55% with the top 10 rankings according to school determination.
However, this research still has errors and limitations, so it is recommended
for further system development, such as adding alternative data export features
to avoid inputting data one by one, as well as improving the user interface to
make it more attractive.
REFERENCES
Afiani, Kunti Dian Ayu, & Faradita,
Meirza Nanda. (2021). Development of
"MEB" Media in Fostering a Nationalist Sense in Elementary
Mathematics Learning. JBPD: Journal of Basic Education, 5(1), 31�41.
Afrila, Dinda Suci, Fitria, Nurul, Amalia, Dian, Imrayani,
Nagita Pebi, & Safitri, Desi. (2023). Comparison of Student Discipline
Levels towards School Rules in Improving Quality at SMAN 1 Muaro Jambi and SMAN
1 Jambi City. Educational Science Journal, 13(2), 399�407.
Dwiyanti, Fitrotin, & Dermawan, Dodik Arwin. (2020).
Development of a Guidance and Counseling Information System Using the Simple
Multi Attribute Rating Technique to Determine Handling of Student Violations.
IT-Edu: Journal of Information Technology and Education, 5(01), 67�76.
Fandini, Puspha, Sulatani, Sultani, & Susanto, Didi.
(2018). Group counseling services using behavioral contract techniques to
foster students' disciplined character at SMA PGRI 2 Banjarmasin for the
2017/2018 academic year. BK An-Nur Student Journal: Different, Meaningful,
Noble, 4(1), 13�20.
Frastian, Nahot, Katarina, Dona, & Heriyati, Heriyati.
(2018). The lecturer performance decision support system uses the Analytical
Network Process (ANP) method at the university. National Seminar and
Multidisciplinary Panel Discussion on Research Results and Community Service
2018, 1(1).
Irawan, Yuda. (2018). Web-Based Decision Support System for
Determining Scholarship Acceptance at Darul Huda Islamic High School Using the
Analytical Hierarchy Process (AHP) Method. Journal of Computer Science, 7(1),
1�6.
Sanusi, Achmad. (2023). Education for Wisdom: Reconsidering
value systems, learning and intelligence. Scholarly Nuance.
Sihotang, Hengki Tamando, & Siboro, Maria Santauli.
(2016). Decision Support System Application for Determining Problematic
Students Using the Saw Method at the Mulia Pratama Private Middle School in
Medan. Journal of Informatics Pelita Nusantara, 1(1).
Sofiati, Nunung Ayu, & Sumarni, Dewi. (2016). The
Influence of Service Quality and Teacher Performance on Student Satisfaction at
Angkasa Lanud Husein Sastranegara Vocational School, Bandung City. Indonesian
Journal of Development, 15(2), 1�18.
Surya, Candra, & Wahyu, Asep. (2020). Information System
for Calculating Student Violation Points Using the Simple Additive Weighting
(SAW) Method (Case Study at As-Shofa Vocational School, Tasikmalaya Regency).
Technoinfo Journal, 14(1), 59�65.
Susanty, Fitri. (2022). The Role of Guidance and Guidance
Teachers in Implementing Guidance and Counseling and Overcoming Student
Delinquency at SMA IT Raudhatul Ulum Sakatiga, Ogan Ilir Regency. BIBLIOGRAPHY:
Journal of Language and Education, 2(3), 90�110.
Syaputra, Purwanto Hidayat, Khairullah, Khairullah, Pahrizal,
Pahrizal, & Mahfuzi, AR Wallad. (2023). Application of the Weighted Product
Method in Determining Problematic Students at SMAN 05 Seluma. Infotama Media Journal, 19(2), 244�255.
Wihartiko, Fajar Delli, Tosida, Eneng
Tita, & Sentosa, Lola Jaman. (2018).
Decision Support System Action Strategy for Student Violations Using the
Analytical Network Process Method. Computing: A Scientific Journal of Computer
Science and Mathematics, 15(1), 102�110.
Yulizah, Rensi. (2019). The Influence of the Contextual
Learning Model on Student Learning Outcomes in Basic Competencies for Recording
Transactions in General Journals. (Case Study of Class Xi Ips Students at
Angkasa Lanud Husein Sastranegara Bandung, 2013/2014). Journal of Accounting
& Financial Education, 3(2), 41�50.
Yuniarthe, Yodhi, & Wahyudi, Rifan. (2021). Decision
Support System (DSS) Prototype Uses Case Based Reasoning (CBR) Method to Assess
School Students' Discipline Level. Explore: Journal of Information Systems and
Telematics, 12(2), 239�246.
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