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Vol.3 No.1 January 2022  

Buana Information Tchnology and Computer Sciences (BIT and CS) 

 

22 | Vol.3 No.1, January 2022 

 

Sales System Using Apriori Algorithm to Analyze  

Consumer Purchase Patterns 

 

Elfina Novalia1  

Study Program 

Information Systems 

Faculty of Engineering and Computer Science, 

Universitas Buana Perjuangan Karawang 

elfinanovalia@ubpkarawang.ac.id 

Apriade Voutama2 

Study Program 

Information Systems 

Faculty of Computer Science, 

Universitas Singaperbangsa Karawang 

Apriade.voutama@staff.unsika.ac.id 

Syahri Susanto3 

School of oil Technic  

Akademi Minyask & Gas Balongan 

syahri28@gmail.com  

 ‹β› 
 

Abstract—Penelitian ini bertujuan untuk membuat sebuah sistem 

penjualan untuk mendapatkan data pesanan tepat waktu, tidak 

terlambat sampai dalam hitungan hari, dan data menjadi 

terstruktur. Serta mengembangkan solusi untuk mengolah data 

transaksi penjualan yang akan semakin banyak menggunakan 

algoritma apriori untuk mengetahui pola pembelian konsumen 

sehingga dapat menjadi output untuk pengambilan keputusan 

atau pengetahuan. Penelitian ini menggunakan metode kualitatif 

untuk memperdalam pemahaman tentang fenomena yang ada 

saat ini sedalam mungkin. Hal ini menunjukkan pentingnya 

kedalaman dan detail dari data yang dipelajari. Pengembangan 

sistem menggunakan metode waterfall karena sangat sesuai 

dengan kebutuhan sistem yang akan dibangun. Dari hasil 

penelitian, perhitungan sampel data transaksi dengan total 12 

data pada tanggal 7-8 Agustus 2021 menggunakan alat Tanagra 

menghasilkan aturan asosiasi bahwa jika Anda membeli pusaran, 

Anda akan membeli Caraco dengan nilai support sebesar 58% dan 

nilai confidence 100%, memiliki nilai lift ratio sebesar 1,3 

menyatakan bahwa kedua produk tersebut memiliki keterikatan 

yang kokoh satu sama lain. Diikuti oleh jika Anda membeli 

Faraco, Anda akan membeli pusaran. Jika Anda percaya pada 

kristal, Anda akan membeli arco yang memenuhi kriteria 

parameter yang ditentukan dengan nilai dukungan minimum 20% 

dan kepercayaan minimum 50%. 

 

Keywords: Penjualan, Data Mining, Apriori Algorithms. 

 

Abstract—This study aims to create a sales system to get order 

data on time, not too late to result in days, and the data becomes 

structured. As well as develop solutions to process sales 

transaction data which will increasingly use a priori algorithms 

to find out consumer buying patterns so that they can be output 

for decision making or knowledge. This study uses a qualitative 

method to deepen understanding of the phenomena currently 

happening as profoundly as possible. This shows the importance 

of depth and detail of the data studied. The system development 

uses the waterfall method because it fits perfectly with the needs 

of the system to be built. From the results of the study, 

calculating a sample of transaction data with a total of 12 data 

on August 7-8, 2021, using the Tanagra tools resulted in a rule 

association that if you buy a vortex, you will buy a Caraco with 

a support value of 58% and a confidence value of 100%, having 

a lift ratio value of 1.3 stated that the two products have a solid 

attachment to each other. Followed by if you buy Faraco, you 

will purchase a vortex. If you believe in a crystal, you will buy 

an arco that meets the specified parameter criteria with a 

minimum support value of 20% and minimum confidence of 

50%. 

 

Keywords: Sales, Data Mining, Apriori Algorithms. 

 

I. INTRODUCTION   

  Technological developments from time to time continue 
to develop very quickly. Likewise, what happened in the 
industrial era 4.0, where we are currently in an age that can 
be made easier to find and get what information we need 
through cyberspace as if the world is in our own hands. 
Technology brings significant changes to its users. 
Technology has both positive and negative impacts. In the 
industrial world, technology has an essential role in 
maintaining and caring for important data owned by a 
company agency. 

  Distributor UD Bangun Persada is a subsidiary of PT 
Triton Paint located in Malang City, East Java. PT Triton 
Paint is a company engaged in paint production. Various 
kinds of paints produced include wall paint, iron paint and 
wood. Distributor Cat UD Bangun Persada, located in the 
Karawang area, is a subsidiary of the West Java main office 
in the Cirebon area. Currently, it has six employees consisting 
of 1 sales head, one admin, three sales and one courier. As 
well as having material shops that are members of the UD 
Bangun Persada Paint Distributor, this number will continue 
to increase from time to time. Areas that become distribution 
centres for UD Distributors build Persada such as Karawang, 
Purwakarta, Bekasi and other areas. 

  UD Bangun Persada Paint Distributor only markets paint 
products produced by PT TRITON PAINT. In addition, it 
does not market products from other companies. In the case 
of sales transactions, they still record in writing, namely by 
way of sales recording what is ordered by the consumer on 
the order form. Then the structure is given to the admin or 
hung on the shelf. After that admin inputs consumer orders, 
several problems are found, including the sales data being not 
on time, and sales data is still often carried by sales and not 
stored in a structured manner. From sales data that is 
increasingly piling up, a solution can be made to be processed 
as well as possible using apriori algorithm data mining to find 
out consumer purchasing patterns, namely the itemset pattern 



 

23 | Vol.3 No.1, January 2022 

 

to determine the attachment of one item pattern to another 
item that can produce information that can be used for 
decision making. decisions and gain knowledge. 

II. METHOD 

A. System  

A system is a procedural network of interconnected ones 

that collectively perform operations or achieve certain goals 

[1]. The system is a procedure or interrelated elements that 

have input, process, and output for the system to achieve its 

goals [2]. 
 

B. Information 

 Information is data that has been classified, processed or 
interpreted for use in decision making. Information 
processing systems convert data into information or process 
unnecessary data to be useful to the recipient[3]. Information 
is data that is processed in a format that is more useful and 
meaningful to the recipient, and data is a source of 
information that describes actual events [4] 
C. Sales 

Sales are receipts obtained from the delivery of 

merchandise or from the delivery of services on the stock 

exchange as consideration items, namely in the form of cash, 

cash equipment or other assets [5]. Sales is the gathering of a 

buyer and seller with the aim of exchanging goods and 

services based on valuable considerations, such as money 

considerations [6].  
 

D. Apriori Algorithm 

 The Apriori algorithm is a method for finding the pattern 
of relationships between one or more elements in a data set, 
the Apriori algorithm is known as the market basket. The a 
priori algorithm can understand the buying patterns of 
consumers in the case that there is a 50% chance that 
consumers will buy goods A and B and then goods and C [7]. 
Apriori is a class algorithm that helps learn association rules. 
It works against transactions. The algorithm tries to find a 
common subset of a data set. A minimum threshold must be 
met for the association to be confirmed[8].  
 

E. Tanagra 

 Tanagra is free software for academic and research 
purposes. This research involves several methods in data 
mining ranging from data exploration analysis, statistical 
learning, machine learning to databases [9]. Tanagra is one of 
the data mining software in which several data mining 
methods are provided, starting from exploring data analysis, 
statistical learning, machine learning and databases. Unlike 
most data mining software, tanagra is an open source based 
software where everyone can access the source code, and add 
their own algorithms, as long as he agrees and conforms to 
the software distribution license.[10]. 
 

F. Waterfall 

The waterfall model is the simplest SDLC (Software 

Development Life Cycle) model. This model is only suitable 

for software development with specifications that do not 

change [1]. Waterfall provides a sequential or sequential 

software lifeflow approach starting from the analysis, design, 

coding, testing and support stages[11]. 
 

G. Data collection techniques 

  This method is compiled based on the results of the 
analysis of the research model that will be used, the results of 
the selection of system development, the waterfall model is 

used [12]. Literature study is done by looking at books, 
journals and previous scientific works to learn and find out 
information related to the author's research. Observation or 
observation is one of the primary data collection techniques 
by directly observing an activity carried out [13]. Interviews 
are primary data collection techniques by directly face to face 
with the interviewee[13]. 
 

H. System development method 

 

Figure 1 Research Flowchart 

Analysis of the data to be searched, such as supporting 

data for system development and observing how the sales 

process and sales transaction data processing, as well as 

requiring sales transaction data samples for the a priori 

algorithm calculation process using Tanagra tools which can 

find out patterns of consumer buying associations, and 

references These calculations will be compared with the a 

priori algorithm calculations in the system. The need for 

transaction data samples with the aim of understanding the 

attributes on the sales form and selecting attributes for the 

purpose of data mining processes. In the data analysis stage, 

the sample of transaction data is calculated using the Tanagra 

tools with a minimum reference of 20% support and 50% 

minimum confidence. The result is the conclusion of the rule 

association that is formed from the calculation of transaction 

data using the Tanagra tools. 

  The design stage is the design of the system to be built. 
This design uses the UML (Unified Modeling Language) 
model, consisting of several steps, such as Use Case 
Diagrams, Activity Diagrams, Sequence, and Class 
Diagrams. Implementation from the design stage into coding 
in a programming language. The Programming language 
used is PHP Java and uses a MySQL database and the 
Codeigniter framework. Whitebox testing is focused on the 
internal system, namely the source code of the program [14]. 
Blackbox testing is done by testing system applications that 
involve users, which aims to find out the shortcomings of the 
application system that has been built. Maintenance At this 
stage, the care that has been developed is carried out. This 
treatment is to prevent errors found in the system carried out 
on the method according to the software requirements to keep 
it stable[15]. 

III. RESULTS AND DISCUSSION 
 

A. Data Analysis 

      The data analysis process uses the Tanagra tools, in the 

early stages of determining a sample of transaction data. To 

find the rule association, determine the minimum support 

with 20% criteria while the minimum confidence is 50%.  
 



 

24 | Vol.3 No.1, January 2022 

 

 

Figure 2 Sample Transaction Data 

      Before using the Tanagra tools, in the next stage, 

converting transaction data as shown above into binary 

format with the following results: 

 

Figure 3 Tabular Format 

 After converting the data into binary format, the next step 
is to upload the binary format data into the Tanagra tool. 

 

Figure 4 Tanagra Dashboard 

 Then in the next process click define status 1, select the 
attribute that will be processed for mining, then select ok.

 

Figure 5 Define Status 1 

 Then at the bottom select the association menu, then drop 
frequent itemsets into define status 1. In frequent itemsets 1, 
right click, then select parameters. As has been determined in 

the early stages of the parameters for a minimum support of 
20%. Then select ok. 

 

Figure 6 Frequent Itemsets 1 

The next step is right click on Frequent Items 1. click 

execute, right click on frequent itemsets 1 then select view. 

then the itemset minimum support 20% will appear as 

follows. 

 

 

Figure 7 Results of 20% Support Itemsets 

 Then select the association menu again and select A 
priori, then drop into define status 1. right click on A priori, 
select parameters then input minimum support 20% and 
minimum confidence 50% then press ok. 

 

Figure 8 Input Support and Confidence Value 

 The next step right click on A priori. press execute, right 
click then view. Then the results of the rule association will 
appear with a minimum support of 20% and a minimum of 
50% confidence as follows. 

 

Figure 9 Results of the Rule Association 

  From the results of mining calculations using Tanagra 
tools with minimum support parameters of 20% and 



 

25 | Vol.3 No.1, January 2022 

 

minimum confidence of 50%, conclusions can be drawn that 
produce association rules. if you buy a vortex, you will buy a 
varaco with a support value of 58% and a confidence value 
of 100%. Having a lift ratio value of 1.3 indicates that the two 
products have a strong attachment to each other. Followed by 
varaco => vortex, crystal => arco that meets the 
predetermined parameter criteria. 

B. System Design 

 The system design is the result of the implementation of 
the system analysis stage, in system modeling using UML 
(Unified Modeling Language) diagrams which consist of Use 
Case Diagrams, Activity Diagrams, Sequence Diagrams and 
Class Diagrams, the following are the results of the system 
design analysis. 

a) Use Case Diagram 
 Use Case admin The admin use case describes the role of 
actors who have access to the system, such as having access 
rights to login, managing customer data, managing product 
data, managing transactions, managing transaction data for 
data mining processing purposes, managing mining processes 
to generate association rules, managing results. mining, 
reports and can manage user management. The sales use case 
describes the role of actors who have access to the system, 
such as having login access rights, and managing sales 
transactions for product orders from customers. 

 Use Case Sales coordinator describes the role of actor 

activities who have access to the system, and have login 

access rights. The sales coordinator can manage transaction 

data for mining processing purposes, manage the mining 

process to generate association rules, and manage reports. 
 

 

Figure 10 Use Case Diagram 
 

b) Activity Diagram  
 This activity is carried out by the admin to process sales 

transaction data using the apriroi algorithm, the admin selects 

the a priori submenu and then the processing mining form 

appears. After that select the transaction date range to be 

processed then input the minimum support and minimum 

confidence then submit the process, then the system displays 

the association rule that has been processed by mining. 

 

c) Sequence Diagram  

 This activity is for admins when doing the sales 

transaction data mining process. 

 

 

Figure 11 Apriori Process Sequence Diagram 
 

d) Class diagram  

Class diagram Is a description of the system structure 

consisting of database attributes used in building a system, 

the following is a description of the class diagram. 

 

Figure 12 Class Diagram 

A. System Implementation  

The following is the association rule resulting from the 

system calculation. 

 

 

 

Figure 13 Rule Association Counting System 

The following is the association rule resulting from the 

calculation of the tanagra tools. 

 

 

Figure 14 Rule Association Tanagra 



 

26 | Vol.3 No.1, January 2022 

 

Every user who has logged in according to their access rights 

will be immediately directed to the dashboard page. 
 

 

Figure 15 Dashboard Pages 

The Transaction page is a process page for finding 

association rules, this page can be accessed by admin and 

sales coordinators. 
 

 

Figure 16 Sales Transaction Page 

Mining Process page is a process page to find association 

rules, this page can be accessed by admin and sales 

coordinator. 
 

 

Figure 17 Mining Process Pages 

The mining results page is a history of the results of the 

association rule search, this page can be accessed by admin 

and sales coordinators 

 

 

Figure 18 Mining Results page 

IV. CONCLUSION 

The results of calculations using the Tanagra tool with 

a total of 12 transaction data from August 7-8, 2021, produce 

a rule association: if you buy a vortex, you will buy a Caraco 

with a support value of 58% and a confidence value of 

100%. A lift ratio value of 1.3 indicates that the two products 

have a solid attachment to each other. You are followed by 

Caraco => vortex, crystal => arco that meets the 

predetermined parameter criteria. After conducting an 

experimental calculation using the Tanagra tool and then 

comparing it with a system calculation and producing 

almost similar measures, the sales system using the a priori 

algorithm data mining follows the needs. So that UD 

Bangun Persada distributors can find out the product is 

purchasing patterns of their members in the sales 

application. Then the sales application generates sales data 

in real-time, and the sales data becomes structured so that 

you can view reports as needed. 

 

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