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All Journal JIPN (Journal of Informatics Pelita Nusantara) Jurnal Nasional Komputasi dan Teknologi Informasi TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Journal of Intelligent Decision Support System (IDSS) INFOKUM Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Pengabdian kepada Masyarakat Nusantara KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Info Sains : Informatika dan Sains Innovative: Journal Of Social Science Research
Hasugian, Penda Sudarto
STMIK Pelita Nusantara, Medan
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Journal : Journal of Intelligent Decision Support System (IDSS)

 1 
Application of Data Mining in Determining Sales Patterns at 212 Mart Supermarkets in Lubuk Pakam Using the Apriori Algorithm Anzelia Anzelia; Penda Sudarto Hasugian
Journal of Intelligent Decision Support System (IDSS) Vol 3 No 4 (2020): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Data mining is a search and analysis on a very large database so that an interesting pattern is found with the aim of extracting information and knowledge that is accurate and potential, as well as understandable and useful from a large database. In this final project, one of the data mining techniques is implemented, namely the a priori algorithmcan define the rule pattern of the data set. The data in this study aims to determine the pattern of sales at 212 mart supermarkets in Lubuk Pakam. This research is obtained from the results of transaction data in the form of consumer purchase receipts, the data used are 10 transaction data with 43 total products. From the results of manual calculations, there are 23 rule association results in accordance with the minimum limit values ​​for support and confidence that have been determined and the highest analysis results are found in french fries and chitato with a minimum support of 30% and 100% confidence. The results of the data mining process obtained can be used for the arrangement or arrangement of layout patterns that are adjusted to the association rules to suit consumer purchasing patterns.
The Application of C4.5 Algorithm to Prediction Sales at PT. Sumber Sayur Segar Fadhila Fadhila; Penda Sudarto Hasugian
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 1 (2022): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v5i1.45

Abstract

Fresh vegetables, fruits and fresh meat are one of the basic needs for human life. The need for fresh vegetables, fruits and meat is one of the most important factors for buyers before making a purchase transaction. Likewise with the needs of fresh vegetables, fruit and meat needed by restaurants, cafes, hospitals, hotels and so on. With the increasing number of requests from customers for the needs of fresh vegetables, fruit and meat, companies engaged in the supply and sale of these necessities need to record sales transactions so that there are no stock vacancies and excess stock of goods. Therefore, companies must be more careful in providing fresh vegetables, fruits and meat which are in great demand, so it needs a data processing in the form of data mining using the C4.5 algorithm. In this study, the predicted sales transactions are the last three months of January, February and March 2021. Then for the sales prediction criteria used are in the form of price, type of goods, type of unit and month of sale so that from these criteria can be obtained sales transactions that are selling or not selling. Data mining is a process of mining important information from a very large data. While the C4.5 algorithm is a data classification that has numeric and categorical attributes, where the results of the classification process in the form of rules can be used to predict the value of discrete type attributes from new records. The system was built using the PHP programming language and MySQL as the database. This study obtained predictive results which were implemented in the form of a decision tree, namely the category of types of vegetables belonging to the best-selling sales transactions.
Expert System to Diagnose Eye Disease Due to Frequently Using Computer with Bayes Theorem Method Taozara Laia; Penda Sudarto Hasugian
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 1 (2022): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v5i1.46

Abstract

Eye disease due to frequent use of computers is one of the dangerous diseases in health because if not treated quickly it will result in blindness. These eye diseases can be diagnosed through the symptoms that arise in humans or through their clinical picture, through these symptoms an expert system can be made to make a diagnosis. An expert system is a system that seeks to adopt human knowledge to a computer that is built to solve problems like an expert. The expert system made in carrying out the diagnosis uses the Bayes theorem method to calculate the probability of an event occurring based on the influence obtained from the results of observations and experts. The system was built using PHP and MySQL programming as a database. The method used for tracing is Bayes' theorem. While the results of the diagnosis will inform about the results of the diagnosis containing a list of symptoms entered, information on the results of the rules regarding the eye disease suffered and information about possible treatments that can be carried out as well as treatment solutions.
Co-Authors Agustina Simangunsong Amran Sitohang Anzelia Anzelia Arjon Samuel Sitio Devri Tarigan Dhini Andika Diana Sari Muliani Saragih Fadhila Fadhila Feryanto Ginting Fristi Riandari Hasugian , Paska Marto IRMA YOLANDA SITORUS Jijon Raphita Sagala John Foster Marpaung Kristiani Romili Sitanggang Lela Dwi Ani Lincah Situmorang Martua Sitorus Melia M Melisa Van Breukelen R. Mahdalena Simanjorang Sianipar, Baringin Simangunsong, Agustina Sulindawaty, Sulindawaty Taozara Laia W. S. Usha Nantheni Wasindo Hutahaean