scholarly journals IMPLEMENTASI ALGORITMA APRIORI DALAM MENENTUKAN PERSEDIAAN OBAT

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Gusti Ahmad Syaripudin ◽  
Edi Faizal
Keyword(s):  
Data Mining ◽  
Programming Language ◽  
Association Rules ◽  
A Priori ◽  
Marketing Strategies ◽  
Apriori Algorithm ◽  
Drug Supply ◽  
Test Results ◽  
Computer Based ◽  
Algorithm Implementation

Computer-based transaction resulting in the accumulation of data in the database of an application. The data can be reprocessed to obtain important information. Data mining can be used to obtain valuable information for management purposes. The technique can be used are the rules of the association. One type of association rules is a priori algorithm. Application of a priori algorithm has been done in the analysis of sales. The research will be applied to the application pharmacies RMC. The programming language used for the algorithm implementation language is Java with Netbeans Platform 7.4 .DBMS used is MySQL. The test results showed a priori algorithm can be used to identify drugs that may be purchased in conjunction with other drugs, as well as showing the drug most widely sold and least by the set of combinations of items. Such recommendations can be used for management in determining drug supply and design marketing strategies quickly, accurately and efficiently.Keywords: java, apriori algorithm, netbeans, MySQL

scholarly journals Algoritma Apriori Untuk Penentuan Assosiasi Penjualan Barang

2021 ◽  
Vol 9 (1) ◽  
pp. 7
Author(s):  
Calvin Ivan Wiryawan ◽  
Yustina Retno Wahyu Utami ◽  
Didik Nugroho
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
A Priori ◽  
Basic Needs ◽  
Marketing Strategies ◽  
Apriori Algorithm ◽  
Growing Up ◽  
Minimum Support ◽  
Data Mining Algorithms ◽  
Mining Algorithms

The increasing of selling basic needs make the company has to provide a lot of goods. The data will be growing up with increasing the transaction at Sari Bumi store. All this time, the selling basic needs at Sari Bumi Store unstructured well so that needed an application with produce important information that can decide marketing strategies. In this research, Apriori algorithm is used to determine association rules. This method was chosen because it is one of the classic data mining algorithms to look for patterns of relationships between one or more items in one dataset. A priori algorithms can help companies in developing marketing strategies. The result of this research is combination between 4 item set with a minimum support of 30% and minimum confidence of 60%.Keywords: sale, staple, apriori algorithm

scholarly journals IMPLEMENTASI ALGORITMA APRIORI TERHADAP DATA PENJUALAN PADA PERUSAHAAN RETAIL

2019 ◽  
Vol 15 (1) ◽  
pp. 85-90 ◽  
Author(s):  
Jordy Lasmana Putra ◽  
Mugi Raharjo ◽  
Tommi Alfian Armawan Sandi ◽  
Ridwan Ridwan ◽  
Rizal Prasetyo
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
A Priori ◽  
Apriori Algorithm ◽  
Business World ◽  
Transaction Data ◽  
Retail Company ◽  
Special Strategy

The development of the business world is increasingly rapid, so it needs a special strategy to increase the turnover of the company, in this case the retail company. In increasing the company's turnover can be done using the Data Mining process, one of which is using apriori algorithm. With a priori algorithm can be found association rules which can later be used as patterns of purchasing goods by consumers, this study uses a repository of 209 records consisting of 23 transactions and 164 attributes. From the results of this study, the goods with the name CREAM CUPID HEART COAT HANGER are the products most often purchased by consumers. By knowing the pattern of purchasing goods by consumers, the company management can increase the company's turnover by referring to the results of processing sales transaction data using a priori algorithm

scholarly journals IMPLEMENTASI DATA MINING UNTUK MENGETAHUI POLA PEMBELIAN OBAT MENGGUNAKAN ALGORITMA APRIORI

2020 ◽  
Vol 17 (2) ◽  
pp. 396-402
Author(s):  
Nadya Febrianny Ulfha ◽  
Ruhul Amin
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
A Priori ◽  
Marketing Strategies ◽  
Business World ◽  
Association Pattern ◽  
Green Lake ◽  
Purchasing Patterns ◽  
The Relationship ◽  
Confidence Value

Competition in the business world requires entrepreneurs to think of finding a way or method to increase the transaction of goods sold. The purpose of this research is to provide drug stock data that is widely purchased by pharmacy customers at Kimia Farma, Green Lake branch in Jakarta. The algorithm used in this study is a priori to determine the relationship between the frequency of sales of drug brands most frequently purchased by customers. The association pattern formed with a minimum support of 40% and a minimum value of 70% confidence produces 17 association rules. The strong rules obtained are that if you buy a 500Mg Ponstan KPL @ 100, you will buy an Incidal OD 10Mg Cap with a support value of 59% and a confidence value of 84%. A priori algorithm can be used by companies to develop marketing strategies in marketing products by examining consumer purchasing patterns.

scholarly journals Application Of Pizza Sales Data Mining Using Apriori Method

SinkrOn ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 1 ◽  
Author(s):  
Rusdiansyah Rusdiansyah ◽  
Nining Suharyanti ◽  
Triningsih Triningsih ◽  
Muhammad Darussalam
Keyword(s):  
Data Mining ◽  
Data Collection ◽  
Association Rules ◽  
A Priori ◽  
Apriori Algorithm ◽  
Mining Method ◽  
Processed Food ◽  
Sales Data ◽  
Business Opportunity ◽  
Use Of Data

Pizza is a processed food originating from Italy and has been spread in various other countries including one of them in Indonesia. Pizza is a processed food that is currently sought after by various groups of people so as to make the pizza business opportunity very profitable, if it is run in a food business. Currently the pizza business has very favorable prospects when compared to other businesses. Moreover, the targeted target can be from all walks of life from children to adults. Pizza sales transactions that produce sales data every day, have not been able to maximize the use of sales data. Sales data is only stored as an archive, so it becomes a pile of data. Therefore the use of data mining is used to solve this problem. A priori algorithm is a data mining method by using minimum support parameters, minimum confidence and will analyze in the period of every month of sales transactions. This study produces data on the results of the process of association rules from the data collection of sales transactions. From the association rules it can be concluded that the pattern of pizza sales, where consumers more often buy Meatzza and Cheese Mania, as evidenced by the results of calculations using Apriori Algorithm and Rapidminer 5.3, with support of 30% and 60% confidence.

scholarly journals Implementasi Algoritma Apriori Pada Penyusunan Menu Makanan Rumah Makan Prasmanan

2020 ◽  
Vol 6 (2) ◽  
Author(s):  
Asep Budiman Kusdinar ◽  
Daris Riyadi ◽  
Asriyanik Asriyanik
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
High Frequency ◽  
A Priori ◽  
Apriori Algorithm ◽  
Frequency Pattern ◽  
Data Mining Techniques ◽  
Rule Method

A buffet restaurant is a restaurant that provides buffet food that is served directly at the dining table so that customers can order more food according to their needs. This study uses the association rule method which is one of the methods of data mining and a priori algorithms. Data mining is the process of discovering patterns or rules in data, in which the process must be automatic or semi-automatic. Association rules are one of the techniques of data mining that is used to look for relationships between items in a dataset. While  the apriori algorithm is a very well-known algorithm for finding high-frequency patterns, this a priori algorithm is a type of association rule in data mining. High- frequency patterns are patterns of items in the database that have frequencies or support. This high-frequency pattern is used to develop rules and also some other data mining techniques. The composition of the food menu in the Asgar restaurant is now arranged randomly without being prepared on the food menu between one another. The result of this research is  to support the composition of the food menu at the Asgar restaurant so that it is easier to take food menu with one another.  

Rancang Bangun Inventarisasi Barang menggunakan Algoritma Apriori Sebagai Data Mining

2021 ◽  
Vol 5 (4) ◽  
pp. 354
Author(s):  
Aditya Prasetya ◽  
Septi Andriana ◽  
Ratih Titi Komalasari
Keyword(s):  
Data Mining ◽  
Programming Language ◽  
A Priori ◽  
Apriori Algorithm ◽  
Transaction Data ◽  
Important Thing ◽  
Minimum Support ◽  
Manual Method ◽  
The Times ◽  
Modern Era

Inventory activities become an important thing for business progress, along with the times, inventory activities become easier due to the large number of facilities and infrastructure to support activities, including the Ap Jaya Store which also competes in the modern era, but currently, inventory activities in stores Ap Jaya still uses the manual method, namely by recording inventory activities using a book then recapitulating one by one so that it takes a lot of time, along with these problems an inventory application is needed that can be used to support these activities, this inventory application is made using the a priori algorithm method as data mining and using the programming language PHP and MySQL as a database besides that the a priori algorithm can also be used for item recommendation systems, on testing with 20 transaction data with a minimum support value = 20% and a minimum confidence = 70% also from the results of the transaction. Tests carried out using the apriori algorithm and using applications that are made get the same results according to the requirements for support and confidence values.Keywords:Inventory, Data Mining, Apriori Algorithm

scholarly journals RANCANG BANGUN APLIKASI PERHITUNGAN ALGORITMA APRIORI BERBASIS WEBSITE

JURTEKSI ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 61-66
Author(s):  
Ricki Ardiansyah ◽  
Maha Rani ◽  
Devi Edriani
Keyword(s):  
Data Mining ◽  
A Priori ◽  
Apriori Algorithm ◽  
Test Results ◽  
Web Browser ◽  
Uml Modeling ◽  
Application Design

Abstract:  This journal explains how to design and build an application that can perform calculations using apriori algorithm. The workflow applied in this study is a sequential workflow (waterfall method). The application built is a website-based application that can be accessed using a web browser. To make application design in this research, UML modeling is used. The model that has been designed using UML will be implemented into PHP coding which can then be run via a web browser. The supporting tools used are XAMPP which provides apache and mysql services. From the test results, it is found that the application of apriori algorithm based on this website is able to perform calculations using the a priori algorithm accurately. These results are proven by comparing the results obtained from manual calculations with the results of calculations performed by this application using a sample of the same data. Keyword: apriori algorithm; data mining, modeling; mysql; php; uml Abstrak: Dalam jurnal ini dijelaskan bagaimana merancang hingga membangun sebuah aplikasi yang dapat melakukan perhitungan dengan menggunakan algoritma apriori. Adapun alur kerja yang diterapkan dalam penelitian ini adalah alur kerja yang berurutan (metode waterfall).  Aplikasi yang  dibangun adalah aplikasi yang berbasis website yang dapat dikases menggunakan web browser. Untuk membuat perancangan aplikasi dalam penelitian ini, digunakan pemodelan UML. Model yang telah dirancang dengan menggunkan UML akan diimplementasikan kedalam koding PHP yang nantinya dapat dijalankan melalui web browser. Adapun tools pendukung yang digunakan adalah XAMPP yang menyediakan service apache dan mysql. Dari hasil pengujian didapatkan bahwa aplikasi perhitungan algoritma apriori berbasis website ini mampu melakukan perhitungan dengan menggunakan algoritma apriori secara akurat. Hasil ini dibuktikan dengan cara membandingkan hasil yang didapat dari perhitungan manual dengan hasil perhitungan yang dilakukan oleh aplikasi ini dengan menggunakan sebuah sampel data yang sama. Kata kunci: algoritma apriori; data mining; mysql; pemodelan; php; uml 

scholarly journals Algorithm Implementation Of Interest Buy Apriori Data On Consumer Retail Sales In Industry

2020 ◽  
Vol 4 (1) ◽  
pp. 48-56
Author(s):  
Ahmad Fachrurozi ◽  
Mufid Junaedi ◽  
Jordy Lasmana Putra ◽  
Windu Gata
Keyword(s):  
Data Mining ◽  
Data Processing ◽  
A Priori ◽  
Data Repository ◽  
Future Market ◽  
Apriori Algorithm ◽  
Retail Sales ◽  
Sales Data ◽  
Market Needs ◽  
Algorithm Implementation

This data processing has the aim to increase the company's turnover, because by being aware of how the interest in buying goods works, the company can buy products other than the main products that it buys. In increasing company revenue can be done using the Data Mining process, one of which uses a priori algorithm and association techniques. With this a priori algorithm found association technique which later can be used as a pattern of purchasing goods by consumers, this study uses a data repository of 958 data consisting of 45 transactions. From the results obtained goods with the name Paper Chain Kit 50's Christmas is a product that is often bought by consumers and it is known that the most frequent combination patterns are the Retro Spot Paper Chain Kit and the Paper Chain Kit 50's Christmas. So that with known buying patterns, the company manager can predict future market needs, and can calculate the stock of goods that must be reproduced, and goods whose stock must be reduced, and also with the results of the association the manager can manage the layout of the product to be better.Keywords: Apriori Algorithm, Sales Data, Retail.

scholarly journals Simple Modification for an Apriori Algorithm With Combination Reduction and Iteration Limitation Technique

2020 ◽  
Vol 3 (2) ◽  
pp. 89
Author(s):  
Adie Wahyudi Oktavia Gama ◽  
Ni Made Widnyani
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
A Priori ◽  
Frequent Itemset ◽  
Apriori Algorithm ◽  
Simple Modification ◽  
Scanning Process ◽  
Iteration Methods ◽  
Short Time

Apriori algorithm is one of the methods with regard to association rules in data mining. This algorithm uses knowledge from an itemset previously formed with frequent occurrence frequencies to form the next itemset. An a priori algorithm generates a combination by iteration methods that are using repeated database scanning process, pairing one product with another product and then recording the number of occurrences of the combination with the minimum limit of support and confidence values. The a priori algorithm will slow down to an expanding database in the process of finding frequent itemset to form association rules. Modification techniques are needed to optimize the performance of a priori algorithms so as to get frequent itemset and to form association rules in a short time. Modifications in this study are obtained by using techniques combination reduction and iteration limitation. Testing is done by comparing the time and quality of the rules formed from the database scanning using a priori algorithms with and without modification. The results of the test show that the modified a priori algorithm tested with data samples of up to 500 transactions is proven to form rules faster with quality rules that are maintained.Keywords: Data Mining; Association Rules; Apriori Algorithms; Frequent Itemset; Apriori Modified;

Analisa Algoritma Apriori Untuk Peminjaman Buku Pada Perpustakaan SMA 1 Silima Pungga-Pungga Parongil

2019 ◽  
Vol 4 (1) ◽  
pp. 154-160
Author(s):  
Oktaviani Manurung ◽  
Penda Sudarto Hasugian
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
High Frequency ◽  
A Priori ◽  
Apriori Algorithm ◽  
Minimum Support ◽  
Minimum Requirements ◽  
To Come

ABSTRACT The library has the role of helping students to love reading books. The availability of books in various fields motivates students to come to visit the library, students can read or borrow library books. For this reason, library officers apply the rules for visiting the library. The Apriori algorithm is a part of data mining, namely the search for high frequency patterns such as activities that often appear simultaneously. The pattern that will be analyzed is the pattern of borrowing any books that are often borrowed so that librarians know the information of books that are often borrowed. With the application of a priori algorithms, book data is processed to produce a book borrowing pattern. After all the high frequency patterns were found, then association rules were found that met the minimum requirements for associative confidence A → B minimum confidence = 25%. Rules for sequential final association based on minimum support and minimum confidence, if borrowing an IPA, then borrowing MTK Support = 15%, Confidence = 42.8%. Keywords:Patterns of borrow of books, Library, Apriori Algorithms

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