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Analytics

Mika Navieri Artasasta; Sulastri Sulastri

Jurnal Elektronika dan Komputer 2024 STEKOM PRESS

PT Astra International BMW Semarang is a company operating in the automotive sector with 3 supporting pillars, namely Sales, Aftersales and Spare Parts for BMW car units. The availability of spare parts is one of the determining factors for consumer satisfaction with the company because if the spare parts stock is empty it will cause consumer disappointment with the company. By using spare parts sales transaction data for the period January 2019 – June 2023, totaling 52,162, it will be utilized using data mining association techniques with the a priori algorithm and the eclat algorithm. The problem in this research is how to find out consumer purchasing patterns so that there is no shortage or empty stock of spare parts in the warehouse. This research aims to determine the association of spare parts purchasing patterns in sales transactions so that partman get recommendations in making decisions about providing priority types of spare parts. This research methodology uses CRISP-DM (Cross-Industry Standard Process for Data Mining) and is implemented with the R programming language with R studio software. In 3 trials using the Apriori algorithm and 3 trials with the Eclat algorithm, The result with the highest confidence appears in a combination of 3 itemsets with minimum support 0.01 and confidence 0.9, namely if a customer buys B11.42.8.593.186 (Set oil-filter Mx) and B83.12.5.A1A.683 (Washer Cleaner) then they will also buy Z99000000333 ( BMW Engine Oil) with confidence 1.00 or 100%. From the results of this association's analysis, it can be used as advice for the management of PT Astra International BMW Semarang in managing spare parts stock.

Dila Aulia Putri; Yani Maulita; Hermansyah Sembiring

Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi 2024 Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Police Sector (Polsek) is one of the agencies that provide protection, order and ensure public safety in the sunggal area. The number of cases of criminal acts that occur makes residents feel unsafe and always feel threatened in certain areas in the Sunggal sub-district, the pattern of criminal acts that often occur due to several factors, one of which is due to the lack of security in the area so that many criminal acts occur as well as behaviour that has been planned by the perpetrator to achieve their goals by planning, preparing, implementing, disposing of evidence, even hiding or escaping depending on the type of crime committed based on the characteristics of the perpetrator, and the situation or context in which the crime occurred. Therefore, it is necessary to analyse techniques from existing criminal data using the a priori algorithm method to find patterns of relationships between variables that can assist agencies in taking action for public safety. Based on the research conducted, the above case is tested with a minimum support = 10%, confidence = 100% so that the results of the rule that meets the support and confidence values are obtained: ‘If the criminal act is theft then the job is self-employed’, then giving value is successful with 15% support, 100% confidence. And ‘If the age of 17-25 years, the criminal act is Theft then the job is unemployed’, then giving value is successful with 10% support, 100% confidence.

Richa Orellia; Akim M.H. Pardede; Imeldawaty Gultom

Saturnus: Jurnal Teknologi dan Sistem Informasi 2024 Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Student behavior is the actions of students which are influenced by their attitudes and responsibilities at school. Student behavior is a very important factor in determining student achievement in learning. Students who have personalities that improve skills, knowledge, attitudes, habits, understanding, skills, thinking power and other abilities will more easily increase their concentration in learning, and it will be easier to achieve the students' goals. At SDN 053960 MARYKE there are still students who do not know that student behavior greatly influences their level of achievement. Therefore, it is necessary to educate students from an early age so that students can be more responsible for the rules given by teachers at school, and students must understand that the attitude they carry out at school is assessed in improving their achievement, as well as their presence is very influential. his level of achievement at school. Therefore, there is a need for a solution to overcome the problems that exist at SDN 053960 MARYKE by utilizing data mining to collect data and then it will be processed using the a priori method with variables contained in the correlation between student behavior and student achievement levels. The a priori algorithm is able to determine min support and confidence in these variables will later show the relationship between student behavior and student achievement levels, so that researchers will get the best best rules and be able to produce the latest information..

Anggi Canita Simanjuntak; Miranda Elisabet Sitanggang; Muhairoh Indah Cahyani; Nita Syahputri

Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi 2024 Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Data mining is a technique to dig up new information from a data warehouse, information is seen as very important and valuable because by mastering information it is easy to achieve a goal, this makes everyone compete to obtain information, as well as in trading businesses such as the Iblite Luxury store.  This store is located in Medan close to residents' houses, Sales transaction data will continue to grow, causing data storage to be even larger. Sales transaction data is only used as an archive without being properly utilized. Basically, a dataset has very useful information. Market basket analysis with a priori algorithm is one of the data mining methods that aims to find association patterns based on consumer shopping patterns, so that it can be known what items of goods are purchased in a At the same time, the results of this study found that the highest support and confidence values were Ysl and Chanel with a support value of 50% and confidence of 75%.