http://infor.seaninstitute.org/index.php/infokum/index JURNAL INFOKUM, Volume 10, No.1, Desember 2021 ISSN : 2302-9706 INFOKUM is licensed under a Creative Commons Attribution-Non Commercial 4.0 International License (CC BY-NC 4.0) 148 ALGORITHM ANALYSIS TO DETERMINE THE ORDER OF GOODS AT THE COMPANY PT. SAGAMI INDONESIA MEDAN Amran Sitohang, Olven Manahan STMIK Pelita Nusantara Amranryan89@gmail.com Abstract The amount of competition in the business world, especially in the electronics industry, requires developers to find a strategy that can increase product orders at electronic companies. With daily printing activities, the data will increase over time. The data not only serves as an archive for the company, the data can be utilized and processed into useful information for increasing product orders. The data not only serves as an archive for the company, the data can be utilized and processed into useful information for increasing product orders. A priori algorithm is a market basket analysis algorithm that is used to generate association rules. Association rules can be used to find a relationship or cause and effect. Association rules can be generated with a priori algorithm. An a priori algorithm that aims to find frequent itemsets is run on a set of data. Market basket analysis is one of the techniques of data mining that studies consumer behavior in buying goods simultaneously at one time. The purpose of this research is to analyze product order data to form a pattern of itemsets combination using a priori algorithm, to form rules with association rules, to implement data mining by using Tanagra 1.4 tools. Stages of this research method have several stages including literature study, field research (field research), analysis, discussion of analysis based on the method used, Article Info Received : 29 September 2021 Revised : 29 October 2021 Accepted : 19 November 2021 Keywords: Data Mining; Association Rules; Apriori Algorithm; Knowledge; Market Basket Analysis 1. Introduction The amount of competition in the business world, especially in the electronics industry, requires developers to find a strategy that can increase product orders at electronic companies. With daily printing activities, the data will increase over time. Therefore, every company must have a good data processing system so that the data generated from these transactions can be useful to be made into a monthly or annual report. The data not only serves as an archive for the company, the data can be utilized and processed into useful information for increasing product orders. Data mining is a process that employs one or more computer learning techniques (machine learning) to analyze and extract knowledge automatically. Knowledge Discovery in Databases is the application of scientific methods to data mining. In this context data mining is one step of the KDD process. (Source: Fajar Astuti Herawati, 2018: 3).The a priori algorithm is the most famous algorithm for finding high frequency patterns.Formation of candidate itemset, candidate k-itemset is formed from the (k-1)-itemset combination obtained from the previous iteration. One way of the a priori algorithm is the pruning of candidate k-itemsets whose subsets containing k-1 items are not included in the high- frequency pattern with length k-1.Calculation of support from each candidate k-itemset. Support from each candidate k-itemset is obtained by scanning the database to count the number of transactions