Implementation Of Data Mining On Suzuki Motorcycle Sales In Gemilang Motor Prosperous With Apriori Algorithm Method

- The sale is part of the marketing that determine the survival of the company. With the sale, the company can achieve the goals or targets. To be a company that continues to grow in motorcycle sales, the company should be able to compete in increasing sales volume. Starting from the launch prodak the best in sophistication motorcycles, up to a very attractive price cuts the attention of consumers. Things like that already sanggat often do, so the company can still compete, Motorcycles is a two-wheeled transfortasi tool used more and more common people. From teenagers to old orag, not infrequently motorcycle including important sanggat needs. If we do not have it feels very hard in activity quickly. Make sales without any restriction of sales data accumulate, until finally overwhelmed the company in terms of taking care of customer files. To find the most sales required Apriori Algorithm. Apriori algorithm, including the type of association rules on Data Mining. One stage of association that can produce an efficient algorithm is with high frequency pattern analysis. In an association can be determined by two benchmarks, namely: Support and Confidence. Support "penunang value" is the percentage of combinations of items in a database, and Confidence "value certainty" is strong correlation between the items in an association's rules. Apriori algorithm, including the type of association rules on Data Mining. One stage of association that can produce an efficient algorithm is with high frequency pattern analysis. In an association can be determined by two benchmarks, namely: Support and Confidence. Support "penunang value" is the percentage of combinations of items in a database, and Confidence "value certainty" is strong correlation between the items in an association's rules. Apriori algorithm, including the type of association rules on Data Mining. One stage of association that can produce an efficient algorithm is with high frequency pattern analysis. In an association can be determined by two benchmarks, namely: Support and Confidence. Support "penunang value" is the percentage of combinations of items in a database, and Confidence "value certainty" is strong correlation between the items in an association's rules.


Introduction
Data Miningis a branch of computer science that is very widely studied and used by computer engineers and programmers. Data mining is a concept to discover knowledge or information that is very valuable in the Database. Data Mining apply mathematics, statistical techniques, and artificial intelligence to decipher and identify a case study in the research. Data mining is widely used as research material in terms of finding a pattern or value in suatau large data base. Data Mining Applications memproleh input data ie sales data, from the data obtained patterns and information for decision-making on Sejahtera Motor Gemilang in the future. Selection of the appropriate method or algorithm relies heavily on the purpose and process of Knowledge Discovery in Databases (KDD) as a whole. Data Mining Techniques for finding Associative rules or relationships between items called Association rule mining, One algorithm used to find the associative rule is Apriori Algorithm algorithm. Output of data mining can be used for decision-making process in the future. Sejahtera Motor Gemilang is an authorized dealer engaged in sales of Suzuki motorcycles and own service. In this era of technological advancement, a motorcycle is important to support the day-to-day activities. Although in motorcycle sales quite in demand, but often have problems to availability Unit or to place an order is often called pivot. Basically Suzuki Motor Gemilang yet to analyze specific data, for example in combining the booking unit in the same adjacent time, which would cause problems, so it does not know how the relationship between an item to another, and it will require precision and timing a lot. Apriori algorithm, help in the form of a combination candidate itemsthen testing whether that combination meets the minimum parameters of support and confidence which is the minimum threshold value provided by the user. Apriori algorithm can be used in the sales process in Sejahtera Motor Gemilang, to give the relationship between the sales transaction data, in this case is the motorcycle that will be purchased will generate customer data.

Theory
Data miningis a process that employs one or more machine learning techniques (machine learning) to analyze and extract knowledge (knowledge) automatically. (Fajar Astuti Hermawati, 2017: 03). Data miningidalah a term that can digynakan for the decomposition of a knowledge discovery in sebuhDatabase. Data mining is a process that uses statistical techniques, mathematics, artificial intelligence, and machine learning in extracting and identifying sanggat information useful, relevant knowledge from a variety of large databases. (Kusrini and Taufiq Emha Lutfi, 2009: 03). Data miningis a series of processes to explore additional value in the form of information that had been unknown to them manually from a database. Dihasilakan information obtained by extracting and recognizing the important or interesting patterns from data contained in the database. Data mining is a technique used to seek knowledge stored in large data bases, so often we called Knowledge Discovery in Databases (Retno Tri Vulandari, 2017: 01).

Research methods
This stage is looking for a combination of items that meet the minimum requirements and the value of the support in the database. Support an item value is obtained by the following formula.

Support (A) = ℎ
Meanwhile, the support of two items obtained from the formula 2 below:

Analysis of High Frequency Pattern
Stages of the process of grouping data that can be performed on the a priori algorithm degan entering of data processing and then processed in the formation of itemset resulting combination selected. Priori algorithm stages in the process of data mining system is as follows: a) Pattern Analysis of High Frequency At this stage, where the search for a combination of items that meet a minimum requirement and value of support in the database. Support an item value is obtained by the following formula. Smash FI-110 SH 5 Table 2.
From table 2, then take as much as 20 transactions representing the overall data. In which the data will determine the value (support = 20% Confidence = 50%). Which meant that a consumer who buys GR and GS has a 50% chance to also buy NX. This rule is quite singnifikat because it represents 20% of the overall transaction records. The calculation is as follows:  From table 4, it will look for ≥ 20% minimum support of 20 sales transactions. From these results we will obtain data that meet the minimum support are:   From Table 6, the next will seek the support of ≥ 20% minimum of 20 makadiperoleh sales transaction data that meets the minimum value of support: Furthermore, to find association rules then do steps confidence value calculation of each item listed in Table 7, based on the following formula:  Furthermore, let's say the minimum value ≥ 50% confidence, then aturanasosiasi formed are as follows: From the stages are carried out, the items that meet the support and confidence≥ 50%, so that by the rules of the association which is formed from table 9, is. It can be concluded as follows: a) If you buy products Suzuki GSX-150R, it will buy products Suzuki GSX-150S. With support at 55% and 64% Confidence. b) If you buy products Suzuki GSX-150R, it will buy Suzuki Nex-II products. With the support of 110% and 129% Confidence.

Results and Discussion
From these results it obtained the discussion of a display program as beriku.Implementation of this sale transaction analysis applications using Visual Studio 2010 with the programming language used is Visual Basic .Net and Crystal Report. a) Form Item Form item serves to display data items of goods sold on PT. Sejahtera Motor Gemilang. In this form, the admin can add items by selecting the Add button, change the items by selecting the Change button and delete the data by selecting the Remove button. Transaction form display data on the sales transactionPT. Sejahtera Motor Gemilang. In this form, the admin can add transaction by choosing the Add button, change the items by selecting the Change button and delete the data by selecting the Remove button. After admin selecting the plus button on the form of the transaction, the system will display the form added transactions. The transaction code will be generated automatically by the system. Admin and then enter the name of a transaction and then select the items that go into the sales transaction. To perform the analysis, the admin will include the value of Min Min Support and Confidence. After that, select the calculate button to perform the analysis with Apriori algorithm. To save the results of this analysis, it can choose the save button and print.  The analysis results are displayed using Crystal Report to then be printed as a report on the analysis.

Conclusion
From the results of research by the author, the conclusions drawn and suggestions as follows: a) The existing data on Sejahtera Motor Gemilang can be decomposed properly, without any buildup again. b) Apriori algorithm is able to determine the Association Rule on sales of Suzuki motorcycles. c) Sejahtera Motor Gemilang greatly assisted by the Motorcycle Sales Application. d) It is expected that in future studies, decomposition motorcycle sales data can be done online. e) Apriori algorithm can find Association Rule on Suzuki's motorcycle sales, by calculating the value of Support and Confidence. f) Visual Basic 2010 application with MySQL storage is very helpful in creating perogram motorcycle sales.