Application of Simple Additive Weighting (SAW) Method and

Decision Table in Decision Support System Determines the Level of

Problem Student Punishment Levels

Riyadi Purwanto

, Dwi Novia P., Ratih Hafsarah Maharrani

and Lutfi Syafirullah

Informatic Engginering Departement, Politeknik Negeri Cilacap, Dr. Soetomo Street, Cilacap, Indonesia

Keywords: Decision Support System, Simple Additive Weighting (SAW) Method, Decision Table, Punishment Rate,

Problematic Students.

Abstract: The teaching and learning process that runs cannot be separated from the various problems of students who

violate school rules. Giving punishments or sanctions to problematic students using a point system where the

value of points and sanctions vary according to the type of violation. Some of the problems that arise are that

the instrument is conventional, the calculation of violations is still in the form of paper based which is prone

to errors (human error) and the sanctions given are sometimes due to likes and dislikes. So that the decision

taken is not correct. Based on the problem, an application is made that can support decision making using the

Simple Additive Weighting (SAW) method and the Decision Table. the weighting of the violation points is

based on 3 (three) violations criteria, namely academic violations, aesthetic violations, and ethical violations.

Each criterion will be reduced to several sub-criteria. The SAW method is a problem solving method using a

weighted addition method based on certain criteria, while the Decision Table is a table that is used as a medium

for solving logic in a program. In this research.

1 INTRODUCTION

Information Technology plays an important role asa

medium of communication in supporting various

fields of business, government, and education.

Information technology can function as a media

support system in decision making (Purwanto, 2018).

One of the factors that influence the comfort of

teaching and learning in a school environment is

problematic students who violate school rules. The

role of the Guidance Counseling teacher as the front

guard must be fast and responsive in dealing with

problem students. Therefore, the Decision Support

System (DSS) can be implemented as a decision

support system in determining what actions schools

must take to these students, so that the decisions made

are potential and can be justified.

SMK N 1 Kawunganten is a public school located

in Cilacap Regency. The number of students currently

reaches ± 1,235 students who are distributed in 35

classes in various majors. The learning process that

https://orcid.org/0000-0001-7066-2905

https://orcid.org/0000-0002-4960-8944

runs at the school certainly cannot be separated from

the various problems of the students caused by the

indiscipline of compliance with school rules.

Various violations that are often committed by

students in schools include disciplined learning time,

disrespectful attitude and harming others, fighting,

smoking, consuming alcohol and drugs, watching

porn videos, promiscuity, and other forms of

violations. Therefore, the handling of problem

students is the responsibility of all schools, both

teachers and school leaders. Educational goals can be

optimally achieved if the school has school rules and

regulations (Utomo and Nursalim, 2019).

Policy at SMK N 1 Kawunganten in dealing with

problem students using a point system. Each violation

has a point value and sanctions that vary according to

the type of violation. At a certain point limit, the

school will determine the level and type of

punishment in the form of warning letters, parent

summons, suspension, and Drop Out (DO).

But now the instruments used are still

conventional. Calculation of the point of violation is

1194

Purwanto, R., P., D., Maharrani, R. and Syaﬁrullah, L.

Application of Simple Additive Weighting (SAW) Method and Decision Table in Decision Support System Determines the Level of Problem Student Punishment Levels.

DOI: 10.5220/0010962300003260

In Proceedings of the 4th International Conference on Applied Science and Technology on Engineering Science (iCAST-ES 2021), pages 1194-1202

ISBN: 978-989-758-615-6; ISSN: 2975-8246

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

still in the form of paper based that is prone to errors

(human error). Engineering punishment is very likely

to occur due to factors like and dislike. Thus the

decision taken becomes inappropriate. This causes

frequent complaints by students and parents to the

school.

Noting the problems that occur, it is necessary to

make an application that can help decision making.

To that end, researchers intend to create a Decision

Support System to Determine the Problematic

Punishment Rate for Students. Application

development uses the Simple Additive Weighting

(SAW) method and Decision Table. The SAW

method is a method of solving problems using a

weighted sum method based on certain criteria (Putra,

Aryanti and Hartati, 2018), while the Decision Table

is a table used as a medium for solving logic in a

program so that it is effectively used when the

conditions selected in the program are numerous

(Kristianto, 2017).

In this study 3 (three) criteria for violations will

be made, namely: Academic Violation, Aesthetic

Violation, and Ethical Violation. Each criterion will

be reduced to several sub criteria. For this reason, this

study will use a Decision Table model that functions

to identify the multilevel decisions which will then be

normalized using the SAW method.

2 LITERATURE REVIEW

2.1 Related Research

Research related to the development of Decision

Support System applications has been conducted by

several researchers before with different methods,

objects, and scope of problems.

Previous research with the title Decision Support

System for Student Achievement Selection in SMK

PGRI 3 Malang Using Weighted Product (WP)

Method. The study was conducted with the aim of

building the Achievement Student Selection Decision

Support System with WP Method. The output of this

system is in the form of ranking information for high

achieving students based on criteria data and weight

data (Faisal, 2017).

Previous research with the title Support System

for Decision of Acceptance of New Students with the

SAW Method at SMK Kusuma Bangsa. The

parameters used are NEM, academic achievement,

non-academic achievement, and test results. This

decision support system is designed by ranking

method using SAW by finding the weight value of

each attribute, then an alternative ranking process is

carried out, namely prospective students who pass the

selection (Dzulhaq, Sutarman and Wulandari, 2017).

Previous research with the title Best Student

Selection Decision Support System with Analytical

Hierarchy Process Method. The developed system

can help objective decision making in determining the

best students based on five criteria, including report

card grades, attendance lists, spiritual attitudes, social

attitudes, and skills (Zaki, Setiyadi and Khasanah,

2018).

Different from previous studies. In this study,

researchers made DSS to determine the type and level

of punishment of problem students by using the SAW

method and the Decision Table. Information obtained

from this system is in the form of punishment

recommendations, namely verbal reprimands, written

reprimands (warning letters), parent summons,

suspension, and Drop Out (DO). Punishment is given

based on the total score point for each type of

violation committed by the student. In this study 3

(three) criteria for violations will be made, namely:

Academic Violation, Aesthetic Violation, and Ethical

Violation. Each criterion will be reduced to several

sub criteria. For this reason, this study will use a

Decision Table model that functions to identify the

multilevel decisions which will then be normalized

using the SAW method.

2.2 Basic Theory

2.2.1 Decision Support System

Decision Support System is part of a computer-based

information system that is included in the knowledge

management based system that can be used to support

decision making in an organization or company

(Nawir and Manda, 2018). Decision Support System

is also a system that provides the ability to solve

problems and communication for semi-structured

problems (Sugiyarti et al., 2018).

Decision making always correlates with the

uncertainty of the results of decisions taken.

Therefore, to reduce the uncertainty factor, the

decision requires valid information about the

conditions that occur, then processes the information

into several alternative problem solving as

consideration for deciding the steps to be carried out,

so that the decision taken is expected to provide

benefits (Siregar et al., 2018).

2.2.2 Simple Additive Weighting (SAW)

Method

SAW method is a method of solving problems known

as weighting sum method based on certain criteria

Application of Simple Additive Weighting (SAW) Method and Decision Table in Decision Support System Determines the Level of Problem

Student Punishment Levels

1195

(Putra, Aryanti and Hartati, 2018). The concept of the

SAW method is to find the weighted sum of each

alternative on all attributes(Kusumawardani et al.,

2019).

The SAW method only performs the

normalization process by having a matrix where

viewed from the columns and rows the highest value

is drawn or called the maximum value and the lowest

value is pulled in a row called the minimum value,

normalizing the value if the value of benefits or

including the criteria of benefits is done every row

value divided by the highest value owned by the row,

and if it is a criterion value in the form of the lowest

cost value of the row divided by row value

(Hutahaean and Badaruddin, 2020).

2.2.3 Decision Tables

Decision tables are tables that are used as a tool to

solve logic in a program. Decision tables are also

known as cause-and-effect tables that will be used to

obtain decision tables (Joosten, Permanasari and

Adji, 2020). Algorithms containing multilevel

decisions are difficult to draw directly with

pseudocode can be made in advance using the

Decision Table. This method is effectively used if the

conditions selected in the program are

numerous(Kristianto, 2017).

2.2.4 School Rules

School rules are provisions that govern life at school

and contain sanctions against violators. Violations of

school rules can be grouped into four categories,

namely academic violations, administrative

violations, aesthetic violations, and ethical violations

(Utomo and Nursalim, 2019)

3 RESEARCH METHODS

The method used in the development of the Decision

Support System to determine the level of punishment

of problematic students is grouped into four main

components, namely research materials, research

tools, research paths, and system design.

3.1 Research Materials

Research materials include:

1) Data obtained from analysis studies at SMK

Negeri 1 Kawunganten through interviews.

2) Data obtained from study literature or scientific

references.

3) Analysis of data or documents from research

objects to find out how the system works to be

built.

4) Information regarding the development of a

Decision Support System that was previously

carried out.

3.1.1 Research Tool

In this study, research tools are needed, namely

computer devices with sufficient specifications and

internet access devices.

3.1.2 Research Path

Application development in this study uses the

waterfall method which consists of several phases /

stages (Bassil, 2012), as shown in Figure 1.

Figure 1: Waterfall Model (Bassil, 2012).

Figure 1. shows the phases / stages that can be

explained as follows:

1) Analysis Phase

There are several analysis activities, including:

a. Analysis of the problem (existing condition)

b. Analysis of information about the types of

student violations, point weight violations as

well as the mechanisms and procedures for

punishment of problematic student students at

SMK N 1 Kawunganten. In the process of

information analysis, data collection is also

needed for research activities, either by

interviewing or copying the data needed.

c. User analysis is to determine user needs.

d. Technology analysis is to determine the

system requirements both software and

hardware.

2) The design stage

This stage will make the design of the system

design include:

a. Flowchart flow system,

b. Systems analyst modeling

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c. Relationship table

d. Database system design

e. Make up design (system display)

3) Implementation Phase

The system design that has been made will be

implemented in the coding program so that a

Decision Support System application is

created.

4) Testing Phase

After the application is made the next stage is

the system testing phase.

5) Maintenance Phase

At this stage improvements will be made if the

application does not function (error).

3.1.3 System Design

The system to be developed can be shown in the

flowchart as follows:

Figure 2: Flowchart System.

Figure 2 explains the flow of the decision support

system that will be developed. In the figure, there are

two users who use the application, namely the

counseling teacher and the head master. The

counseling teacher can input the types of violations

and the weight of each of these violations.

Furthermore, each student's violation will be input

through the application and the number of violation

scores will be calculated to determine the level of

punishment. If, the violation score exceeds the

stipulated limit, head master will give punishment in

accordance with the stipulated provisions. However,

if the student's violation score is less than the

maximum limit, the student will not give punishment.

To explain in more detail about the interaction

between users and the system, a use case is made as

shown in Figure 3.

Figure 3: Use Case System.

Figure 3 describes the use case of the system to be

developed. Use Case describes the interaction of

actors with the existing system.

4 RESULT AND DISCUSSION

4.1 Decision Table Making

In this research discusses the level of punishment of

problematic students where an assessment of

violations will be carried out by students using a

combination of decision tables and SAW.

Punishment is given based on the total accumulated

total score of each point for each type of violation

committed by the student in one semester. As a first

step, a decision table will be made which will be used

as a tool to solve the logic in the program. In making

decision tables, references and actions will be given

to students if they commit violations. The

Application of Simple Additive Weighting (SAW) Method and Decision Table in Decision Support System Determines the Level of Problem

Student Punishment Levels

1197

classification of violations that are often carried out

by students up to the actions to be taken by the school

in handling these violations can be summarized in the

table below :

Table 1: Violation Points.

No.

Clasificati

Criteria Point

Punishment

and Action

1. Academic

Violation

Late for

school

2 Reprimand

and

Counselin

Not present

without a

certificate

5 Reprimand

and

Counselin

Leave

school

during class

time

5 Reprimand

and

Counseling

Not

following

the flag

ceremon

10 coaching

and

Counseling

Activate the

handphone

while

learning is in

ress

5 Reprimand

and

Counseling

2. Aesthetics

Violation

Not dressed

in uniform

or school

attributes in

accordance

with the

rovisions

2 Reprimand

and

Counseling

Does not

carry out

cleanliness

2 Reprimand

and

Counseling

Long-haired

/ long-haired

male

students or

hair dyes

3 Reprimand

and

Counseling

Damaging

or crossing

out school

facilities

5 Reprimand

and

Counseling

Princess

students

wear jewelry

or dress up

excessivel

2 Reprimand

and

Counseling

Using

tattoos or

body

piercings

that are not

riate

50 Warning

Letter II,

coaching

and calling

parents

3. Ethics

Violation

Harrasing

teacher in

the school

50 Warning

Letter II,

coaching

and calling

arents

Carrying

and smoking

in the school

environment

15 Warning

Letter I

Drinking

alcohol and

dru

abuse

100 Drop Out

Committing

or engaging

in criminal

actions

against

others

Carry sharp

weapons

that can

endanger

and threaten

the safety of

others

100 Drop Out

Students

proven to

steal

Bringing,

showing and

distributing

orno

30 Warning

Letter II,

coaching

and calling

parents

Students

become

pregnant or

impregnate

other

students

80 Warning

Letter I and

Skorsing

Based on the table, a decision table can be made using

the help of a table that contains the relationship

between several attributes that affect certain attributes

with the following steps:

1. Determination of the conditions to be selected, in

the condition of giving punishment to students

who are in trouble there are 3 pieces of conditions

to be selected namely:

a) Academic Violations

b) Aesthetic Violations

c) Ethics Violations

Referrals given by the school include loud

reprimands, regular reprimands, sanctions,

guidance and dispensation

2. Based on the number of conditions selected, it can

be determined the number of possible events that

occur, in this case as many as: N = 23 = 8 possible

events

3. Then it is formulated that there are 5 (five) actions

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to be taken along with the maximum point limit:

1) No violation occurs if the total accumulated

number of violations <= 10

2) Warning Letter I (counseling & coaching) if

the total accumulated number of violations <=

3) Warning Letter II (summons of parents) if the

total accumulated number of violations <= 50

4) Warning Letter III (suspension) if total

accumulated violations <100

5) Drop Out if total accumulated violations >=

100

4. Fill in the condition entry

5. Fill in the action entry

Table 2: Action Entry.

Condition / Action Rules

1 2 3 4 5 6 7 8

Academic Violations >

maximum violations Y Y Y N N Y N N

Aesthetic Violations >

maximum violations Y Y N Y N N Y N

Ethics Violations >

maximum violations Y N Y Y Y N N N

No violations X

Warning Letter I X X X

Warning Letter II X X

Warnin

Letter III X

Dro

Out X

4.2 Calculation Process in the SAW

Method

After making a decision table, the next step is to

perform calculations using the SAW method, where

this method is known as the weighted sum method.

For example here a sample of 10 students will be

taken to calculate the steps as follows:

a) There are 3 basic criteria that become a reference

in making decisions, namely:

1) C1 = Academic violation

2) C2 = Aesthetic violation

3) C3 = Ethical violation

b) Determination of criteria weights

Weights for each criterion are: C1 = 30%, C2 =

20%, and C3 = 50%. Determination of this weight

by looking at which criteria will be given a

maximum and minimum value based on

consideration of the existing point factors

c) Table of alternative values of students (candidates)

will be taken as a random sample 1 class of 30

people, there are :

Table 3: Value Alternative.

Alternative Name

Criteria

C1 C2 C3

Maulana Alif

Anugerah

17 4 0

A2 Peter Sulaeman 10 9 80

Nandya Saphira

Esfandian

7 24 15

A4 Arya Mahardika 5 14 0

Lucky Wiratama

anda

22 53 50

A6 Gracia Vini 12 7 0

A7 Ckasinta Winda Santi 27 22 30

Yolanda Novitra

Setiawan

2 8 50

A9 Hazana Delfani 30 7 15

A10

Rosyanda Sastie

attri

15 17 18

A11 Afinda Andi Pra

o 10 2 0

A12

Akhmad Rofiq

Mustofa

15 4 0

A13 Azis Satria Putra 2 5 15

A14 Cah

a Romadhon 5 7 15

A15 Dendi Fajar Efendi 2 2 0

A16 Farid Al A'rof 2 9 0

A17

Azka Raihan Tahta

Aunillah

2 10 0

A18 Bara Bima Hestya 17 15 0

A19 Dafi' Al Khayyan 5 5 15

A20

Juan Dwi Bhakti

Nugroho

5 5 15

A21 Aan Wili Krisyanto 15 10 0

A22 Abdul Khalim 20 17 0

A23 Achmad Fuad

25 12 0

A24 Andi Wah

u Perdana 5 4 0

A25 Atha S

arif Pri

anto 5 4 0

A26 Bagas Artha Jati 25 22 15

A27 Bagas Prayogo 0 7 0

A28 Banu Muarif 2 9 0

A29

Bayu Mangun

Kusumo

2 12 0

A30 Beni Setiawan 12 12 0

d) Determine the value of each weight

Table 4: Weighted Value.

Total points

of violation

The weight value is based on the

total number of subscribers of the

total violation

oints

–

20 1

–

45 2

–

75 3

–

99 4

>100 5

e) Based on the data suitability value between the

Application of Simple Additive Weighting (SAW) Method and Decision Table in Decision Support System Determines the Level of Problem

Student Punishment Levels

1199

alternatives with the criteria in the table above,

and with the weight of the existing values, a

decision matrix (X) can be made and a

normalization calculation is carried out to obtain

a normalized value matrix of each existing value.

The values are shown in tabular form as follows:

Table 5: Normalization Calculation.

Alternative

Decision matrix

value

Normalized value

matrix

C1 C2 C3 C1 C2 C3

A1 1 1 1 0,5 1 0,25

A2 1 1 4 0,5 1 1

A3 1 2 1 0,5 0,50,25

A4 1 1 1 0,5 1 0,25

A5 2 3 3 1 0,330,75

A6 1 1 1 0,5 1 0,25

A7 2 2 2 1 0,5 0,5

A8 1 1 3 0,5 1 0,75

A9 2 1 1 1 1 0,25

A10 1 1 1 0,5 1 0,25

A11 1 1 1 0,5 1 0,25

A12 1 1 1 0,5 1 0,25

A13 1 1 1 0,5 1 0,25

A14 1 1 1 0,5 1 0,25

A15 1 1 1 0,5 1 0,25

A16 1 1 1 0,5 1 0,25

A17 1 1 1 0,5 1 0,25

A18 1 1 1 0,5 1 0,25

A19 1 1 1 0,5 1 0,25

A20 1 1 1 0,5 1 0,25

A21 1 1 1 0,5 1 0,25

A22 1 1 1 0,5 1 0,25

A23 2 1 1 1 1 0,25

A24 1 1 1 0,5 1 0,25

A25 1 1 1 0,5 1 0,25

A26 2 2 1 1 0,5 0,25

A27 1 1 1 0,5 1 0,25

A28 1 1 1 0,5 1 0,25

A29 1 1 1 0,5 1 0,25

A30 1 1 1 0,5 1 0,25

f) To simplify the action to be performed, a range

of values is determined from the sum of each

criteria.

Table 6: Range of Criteria.

Action Value Ran

No Violation 0 - 0,59

Warnin

Letter I 0,60 - 0,72

Warning Letter II 0,73 - 0,84

Warning Letter III 0,85 - 0,97

Drop Out >=0,98

g) The last is calculating the value of preference

weights for each alternative, accompanied by a

reference to the action to be taken.

In the system developed, the process of calculating

the violation score of each student can be shown in

Figure 4.

Figure 4: Calculation of student violation and action.

Figure 4, shows the calculation of the score of

violations committed by each student. In the picture,

the scores of each score are seen and show the actions

given to the problematic students.

The detailed calculation of each student's violation

score is shown in Figure 5.

Figure 5: Calculation of details each student violation score.

Figure 5, shows the calculation of the violation score

of each student in detail.

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Table 7: Final Calculation aPnd Action.

Alter

native

Criteria Total

of each

criteria

Action

C1 C2 C3

A1 0,15 0,20 0,13 0,48 No

Violation

A2 0,15 0,20 0,50 0,85 Warning

Letter III

A3 0,15 0,10 0,13 0,38 No

Violation

A4 0,15 0,20 0,13 0,48 No

Violation

A5 0,30 0,07 0,38 0,74 Warning

Letter II

A6 0,15 0,20 0,13 0,48 No

Violation

A7 0,30 0,10 0,25 0,65 Warning

Letter I

A8 0,15 0,20 0,38 0,73 Warning

Letter I

A9 0,30 0,20 0,13 0,63 Warning

Letter I

A10 0,15 0,20 0,13 0,48 No

Violation

A11 0,15 0,20 0,13 0,48 No

Violation

A12 0,15 0,20 0,13 0,48 No

Violation

A13 0,15 0,20 0,13 0,48 No

Violation

A14 0,15 0,20 0,13 0,48 No

Violation

A15 0,15 0,20 0,13 0,48 No

Violation

A16 0,15 0,20 0,13 0,48 No

Violation

A17 0,15 0,20 0,13 0,48 No

Violation

A18 0,15 0,20 0,13 0,48 No

Violation

A19 0,15 0,20 0,13 0,48 No

Violation

A20 0,15 0,20 0,13 0,48 No

Violation

A21 0,15 0,20 0,13 0,48 No

Violation

A22 0,15 0,20 0,13 0,48 No

Violation

A23 0,30 0,20 0,13 0,63 Warning

Letter I

A24 0,15 0,20 0,13 0,48 No

Violation

A25 0,15 0,20 0,13 0,48 No

Violation

A26 0,30 0,10 0,13 0,53 No

Violation

A27 0,15 0,20 0,13 0,48 No

Violation

A28 0,15 0,20 0,13 0,48 No

Violation

A29 0,15 0,20 0,13 0,48 No

Violation

A30 0,15 0,20 0,13 0,48 No

Violation

4.3 System Testing

System testing is done by white box testing method.

Tests carried out by 10 respondents with results as

shown in Table 8.

Table 8: System Testing.

No. Assessment

Test Res ult

NA A SA

1. Calculation of point weight

scores for each type of

violation becomes more

recise and accurate

0 3 7

2. Can reduce the risk of

miscalculation and

rakapitulation points

violations caused by human

erro

0 2 8

3. Can avoid the existence of

engineering punishment

caused by

like and dislike factors

0 2 8

4. The validity of the level of

punishment or sanctions

information that will be given

problematic students are more

guaranteed and in accordance

with the type violations

committed (accurate)

0 5 5

5. Can help the school (elements

of the school leadership) in

making the right decision and

can be accounted fo

0 4 6

Amount 0 16 34

Percentage (%) 0 32 68

Notes :

NA = Not Agree

A = Agree

SA = Strongly Agree

Table 8, shows the results of the system testing

conducted by 10 respondents. Based on the results of

testing that has been done, in general the system can

assist leaders in making decisions against students

who have problems and provide penalties in

accordance with the violations that have been

committed.

Application of Simple Additive Weighting (SAW) Method and Decision Table in Decision Support System Determines the Level of Problem

Student Punishment Levels

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5 CONCLUSION

Based on research that has been done by developing

a decision support system to determine the

punishment of problem students using the decision

table and the SAW method and testing the system

with 10 respondents, the results show 68% of

respondents strongly agree that with the decision

support system, the calculation of point weight scores

from each type of violation to be more precisely and

accurately, the risk of miscalculation and

rakapitulation points violations caused by human

error can be minimized, punitive engineering caused

by like and dislike factors can be avoided, the validity

of the level of punishment or sanctions that will be

given problematic students are more guaranteed and

in accordance with the type violations committed,

school leaders can make the right decisions and can

be accounted for.

Suggestions that can be made for the development

of the system in further research is the need to develop

an sms gateway function that can provide information

on student violations automatically to parents of

guardians and actions taken by the school against

students with problems. Thus, guardian parents can

find out information on violations committed by their

children.

REFERENCES

Bassil, Y. (2012) ‘A Simulation Model for the Waterfall

Software Development Life Cycle’, International

Journal of Engineering & Technology, 2(5), pp. 2049–

3444. doi: 10.15680/ijircce.2015.0305013.

Dzulhaq, M. I., Sutarman and Wulandari, S. (2017) ‘Sistem

Pendukung Keputusan Sistem Pendukung Keputusan

Penerimaan Siswa Baru Dengan Metode Simple

Additive Weighting Di SMK Kusuma Bangsa’, Jurnal

Sisfotek Global, 7(2), pp. 50–55.

Faisal, M. (2017) ‘Sistem Pendukung Keputusan Seleksi

Siswa Berprestasi di SMK PGRI 3 Malang

Menggunakan Metode Weighted Product (WP)’,

Journal of Information and technology, 05(01), pp.

119–124.

Hutahaean, J. and Badaruddin, M. (2020) ‘Sistem

Pendukung Keputusan Pemilihan Sekolah SMK Swasta

Penerima Dana Bantuan Menerapkan Metode Simple

Additive Weighting ( SAW )’, Jurnal Media

Informatika Budidarma, 4(April), pp. 466–471. doi:

10.30865/mib.v4i2.2109.

Joosten, J., Permanasari, A. E. and Adji, T. B. (2020) ‘The

use of decision table for reducing complex rules in

software testing’, IOP Conference Series: Materials

Science and Engineering, 732(1). doi: 10.1088/1757-

899X/732/1/012086.

Kristianto, A. (2017) ‘Sistem Pendukung Keputusan

Penentuan Mahasiswa Bermasalah Menggunakan

Metode Ahp’, Jurnal Gaung Informatika, 10(1), pp.

55–66.

Kusumawardani, R. et al. (2019) ‘Implementasi Metode

Simple Additive Weighting (SAW) Pada Sistem

Pendukung Keputusan Untuk Menyeleksi Saham

Prima’, Jurnal Riset Informatika, 1(3), pp. 1–6.

Nawir, S. and Manda, R. (2018) ‘Web Based Application

for Decision Support System with ELECTRE Method

Web Based Application for Decision Support System

with ELECTRE Method’, in 2nd International

Conference on Statistics, Mathematics, Teaching, and

Research. IOP. doi: 10.1088/1742-6596/1028/1/

012054.

Purwanto, R. (2018) ‘Rancang Bangun Decision Support

System (DSS) Untuk Membantu Menentukan Hasil

Seleksi Pegawai Pada Politeknik Negeri Cilacap

Dengan Menggunakan Metode Perbandingan

Eksponensial (MPE)’, Jurnal Informatika: Jurnal

Pengembangan IT, 3(2), pp. 190–199. doi:

10.30591/jpit.v3i2.861.

Putra, A. S., Aryanti, D. R. and Hartati, I. (2018) ‘Metode

SAW ( Simple Additive Weighting ) sebagai Sistem

Pendukung Keputusan Guru Berprestasi ( Studi Kasus :

SMK Global Surya )’, in Seminar Nasional Teknologi

dan bisnis 2018. Bandar Lampung: IIB Darmajaya, pp.

85–97.

Siregar, D. et al. (2018) ‘Multi-Attribute Decision Making

with VIKOR Method for Any Purpose Decision’,

Journal of Physics: Conference Series, 1019(1). doi:

10.1088/1742-6596/1019/1/012034.

Sugiyarti, E. et al. (2018) ‘DECISION SUPPORT

SYSTEM OF SCHOLARSHIP GRANTEE

SELECTION USING DATA MINING’, International

Journal of Pure and Applied Mathematics, 119(15), pp.

2239–2249.

Utomo, S. B. and Nursalim, M. (2019) ‘Pelanggaran Tata

Tertib Sekolah Siswa Kelas X SMA Negeri 1 Menganti

Serta Penanganannya Oleh Guru Bimbingan Dan

Konseling’, Jurnal Mahasiswa Unesa, p. hlm. 12.

Zaki, A., Setiyadi, D. and Khasanah, F. N. (2018) ‘Sistem

Pendukung Keputusan Pemilihan Siswa Terbaik

Dengan Metode Analytical Hierarchy Process’, Jurnal

Penelitian Ilmu Komputer, System Embedded & Logic,

6(1), pp. 75–84. doi: 10.35141/jvt.v2i1.455.

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