Decision Support System of Social Assistance in Bitung City

by using AHP Method

Alfrets Septy Wauran, Anthon Kimbal and Roby Lumbu

Department of Electrical Engineering, Manado State Polytechnic, Manado, Indonesia

Keywords: Bitung City, Decision Support System, AHP.

Abstract: Information and data from all SKPs under the Bitung City Government are integrated in a data center. So,

they can be accessed in real time by users, both government and community. There are several algorithms

that can process data and provide the desired information such as Data Mining, Artificial Intelligence and

Decision Support Systems. Decision Support System is a computer system application that can assist

decision makers in solving problems. In addition to population problems, a decision support system can

help government to solve social problems. In this study, we created a decision support system using the

Analytical Hierarchy Process (AHP) algorithm which will calculate optimal decisions in solving population

and social problem. This system will be used to calculate the priority of social assistance in Bitung City.

1 INTRODUCTION

Bitung City is a Maritime City which is the only

Special Economic Zone in Sulawesi. Bitung City is a

maritime city where most of the people depend on

the sea and beach products such as fishing industry,

coastal tourism, fish canning factories and ports. As

we know that Bitung City has the largest seaport in

Eastern Indonesia. Given its very strategic location

as a maritime city, most of the city's revenue comes

from the maritime sector. To improve the economy

and income of the people of Bitung City, the

government needs an integrated and reliable

information system. If it is not supported by a good

reliable information system, the management of

resources in Bitung City will not be optimal given

the limited human ability to manage information

manually. Therefore, this becomes a serious problem

because valuable data and information in Bitung

City cannot be accepted and utilized properly by the

community due to lack of knowledge and utilization

of information technology. To realize Bitung City as

a Digital City, an Integrated Big Data system is

needed to be able to quickly access data and

information stored in the Data Centre. The stored

data in the system can be a population data,

employment, correspondence and so on. These data

can be used to find solutions for all problems that

occur in the community. For example, population

data that must be assisted economically by the data

on fishermen that must be assisted in the

procurement of fishing equipment, fishery industry

data, scholarships for those who cannot afford but

excel, data on marine natural resources that can be

used for evaluation in inviting tourism investors, as

well as marine tourism data that can be developed or

new tourism potential areas according to the

appropriate parameters and criteria. In determining

the beneficiaries and analizing these investments,

they still use manual evaluation by decision-making

employees. This results are dishonest and subjective

results. Likewise, the results obtained by the

analizing of population data are very inaccurate due

to invalid data and limited human memory capacity

in determining the priority of beneficiaries.

Therefore, a computer application integrated with

Bitung City Big Data is needed in the form of a

Decision Support System. The Decision Support

System that will be made is using the AHP method

which is known to be very accurate in calculating

the statistical problem. Population data can be

retrieved and collected quickly. So, the data can be

used directly to be calculated and aggregated based

on criteria and as a final result is the order of

priorities and optimal decisions that must be taken.

This decision support system can solve many social

problem in Bitung City.

Wauran, A., Kimbal, A. and Lumbu, R.

Decision Support System of Social Assistance in Bitung City by using AHP Method.

DOI: 10.5220/0010958600003260

In Proceedings of the 4th International Conference on Applied Science and Technology on Engineering Science (iCAST-ES 2021), pages 1045-1048

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)

1045

2 RESEARCH LITERATURE

2.1 Decision Support System

Decision Support System (DSS) is a system that

interactively provides information, modeling, and

data manipulation where the system is used to assist

decision making in semi-structured and unstructured

problems, where no one knows for sure how

decisions should be made (Alter , 2002). Decision

Support Systems (DSS) are generally built to find a

solution to a problem with several available options

(alternatives) based on knowledge, or evaluate an

opportunity based on existing data. Where the

decision support system is called the DSS

application. To find solutions to certain unstructured

management problems, DSS applications use a

flexible, interactive, and adaptable CBIS (Computer

Based Information System) (Kusrini, 2007).

The objectives of the Decision Support System are

(Turban, 2005):

1. Assist managers in making decisions on semi-

structured problems.

2. Provide support for the manager's judgment and is

not intended to replace the manager's function.

3. Increasing the effectiveness of decisions taken by

managers more than improving their efficiency.

4. Computing speed.

5. Increased productivity.

6. Quality support.

7. Competitive.

8. Overcome cognitive limitations in processing and

storage.

2.2 Analitical Hierarkhi Process (AHP)

The main principle of the AHP method is to enter

human perception into a functional hierarchy. In

solving decision-making problems using the AHP

method, the following are the principles that must be

understood (Kusrini, 2007):

1. Create a Hierarchy

A complex system of problems can be better

understood by breaking it down into supporting

elements, arranging the elements hierarchically, and

combining them or synthesizing them.

2. Assessment of criteria and alternatives.

This assessment is carried out by pairwise

comparisons in the matrix. According to Saaty

(1988), a scale of 1 – 9 is the best representation for

expressing opinions on a problem.

3. Determine Priorities.

For each criterion and alternative, a pairwise

comparison must be made. The relative comparison

value of all alternative criteria can be adjusted

according to the predetermined judgment to produce

weights and priorities by manipulating the matrix or

by solving mathematical equations.

4. Logical Consistency (logical consistency)

Consistency is the first where similar objects can be

grouped according to uniformity and relevance.

Second, it concerns the level of relationship between

objects based on certain criteria.

Basically the procedures or steps in the AHP method

consist of (Kusrini, 2007):

1. Defining the problem and determining the desired

solution, then compiling a hierarchy of the problems

encountered.

2. Determine the priority of the elements.

3. Synthesis.

Consideration of synthetic pairwise comparisons to

produce overall priorities.

4. Measuring consistency

The final result of this step yields max

5. Calculate the consistency of the Index using the

following formula:

CI = (λ, max – n) / n (1)

where n = number of elements

6. Calculate the Consistency Ratio (CR) using the

following formula:

CR = CI/IR (2)

Where CR = Consistency Ratio

CI = Consistency Index

IR = Index Random Consistency

7. Check the consistency of the hierarchy with the

following tests:

If the CR value is more than 10% (0.1), then the

assessment of the data is inconsistent and must be

corrected. And if the CR value is less than or equal

to 10% (0.1), then the data assessment is correct.

3 RESULT

3.1 Dashboard (Main Page)

Figure 1: Dashboard.

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The figure 1 shown the main page of the decision

support system. User can get information about the

population data, decision support system, the system

process, and the result of the decision support

system

3.2 Information Page

This page consist of the information about the value

of criteria in the decision support system. The value

is shows the priority of the criteria.

Figure 2: Information Page.

3.3 Demography Data

This page shows the job of the people, salary,

additional salary, dependents, and expense. Base on

this criteria, we decide the value. This value will be

used to calculate the final mark and rank of the

person.

Figure 3: Demography Data.

3.4 Demography Data Entry

We will fill-in the data in the figure 4 completely to

calculate final value and the rank. There are the

fields of the name of the head of family, Regency

Registration Number, Occupation, the monthly

income, additional income, the number of family

and the monthly expense.

Figure 4: Demography Data Entry.

3.5 Value Criteria in AHP

We can set the value of criteria matrix by input the

all value in the empty box below. The figure below

is called ‘pairs matrix’. The priority of criteria are:

1. The Salary

2. Expense

3. The Dependents

4. Additional Salary

5. The Job

Figure 5: Pairs Matrix.

3.6 Process of Decision Support System

After fill-in the value of pair matrix, we can

calculate the valid of our AHP values. The values of

Consistency Index and Consistency Ratio must be

less then 1. So, the value of CI and CR below is less

than 1, it means that the matrix is good and can be

used.

Decision Support System of Social Assistance in Bitung City by using AHP Method

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Figure 6: Value CI dan CR.

3.7 Report of Rank Social Assesment

Finaly, we can calculate the all value of criteria

based on the value in pair matrix to get the final

value and rangking. It’s shown by the figure below.

There several value are not accept because they not

fulfil the criteria of social assist. The top ranking are

more priority than the ranking below. So we can

calculate the final value and list the ranking to show

who has the higher priority of social assist.

Figure 7: Report of Calculation and Ranking.

4 CONCLUSIONS

The Result shows that the decision support system

can calculate the value of criteria to get the final

score with its ranking of priority. In this system we

can decide the value of each criteria and have the

calculation of the validity of our pair matrix. By this

system the asesment of the social assistance will be

more fair and accurate because the people has no

interference to decide the score and ranking. This

system can make report automatically to have a

transparency result.

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