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Pattern of E-marketplace Customer Shopping Behavior using Tabu Search and FP-Growth Algorithm Ayu Meida; Dian Palupi Rini; Sukemi Sukemi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 4: December 2019
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v7i4.1362

Abstract

Pattern of customer shopping behavior can be known by analyzing market cart. This analysis is performed using Association Rule Mining (ARM) method in order to improve cross-sale. The weakness of ARM is if processed data is big data, it takes more time to process the data. To optimize the ARM, we perform merging algorithm with Improved Tabu Search (TS). The application of Improved TS algorithm as optimization algorithm for preprocessing datasets, data filtering, and sorting data closely related products on sales data can optimize the ARM processing. The method of Association Rule Mining (FP-Growth) to determine frequent K-itemset, Support value and Confidence value of data which is already sorted on TS is based on patterns which often appear in the dataset so it generates rules as reference of decision making for company. To measure the level of power of rule which has been formed, the Lift Ratio value was calculated. Based on the calculation of 97 rules produced, the lift ratio produces values > 1 of 82.54% and based on processing time, it produces the fastest data search in 1.66 seconds. When compared with previous research that uses the hybrid method, for data retrieval based on processing time, it produces the fastest data search within 12.3406 seconds, 150 seconds and 50 seconds. Previous studies have only compared the processing time of data searching without regard to validation / accuracy of data search. The test results in this study obtained more optimal results than when compared with the results of previous studies, namely in time efficiency and data mining in real time and more accurate data validation.  As a conclusion, the resulting rule can be used as a reference in understanding shopping behavior patterns customer on the E-Marketplace.
Selection of Pressed Flower Supplier using the Analytic Network Process (ANP) Method Fadhilah Dirayati; Samsyuryadi Samsyuryadi; Sukemi Sukemi
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 13 No 1 (2021): JUPITER Vol. 13 No. 1 April 2021
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

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Abstract

Abstract Supplier has an important role because it will supply material in a long and consistent manner. The difficulty in choosing suppliers is because the company has many suppliers and each of them has advantages and disadvantages. The company requires that the supplied material is of good quality and is delivered on time. Mistakes in supplier selection can be very crucial, because they can have a direct impact on the continuity of the production process. Home Industry Camila is a small industrial company that is engaged in the production of household products. Currently, the company has six suppliers in the procurement of pressed flower raw materials for products made from resin. This study aims to determine the criteria for selecting suppliers and to choose the right supplier so that the risk of supplier selection errors can be minimized. This study uses the Analytic Network Process method with the Super Decisions application. Selection of welding wire supplier involves 6 criteria, 17 sub criteria and 6 alternatives.  Based on the results of data processing, each criterion weight is obtained from the highest value obtained on the delivery criteria (0.2366) and the lowest supplier relationship (0.0309).  This  can  be  interpreted  that  the  delivery  criteria  is  the  most important criterion among other criteria. Meanwhile, the results of the evaluation state that the supplier who chooses the highest weight isGreetings of Grace (GOG) with a criteria weight (0.4491) was then selected as a business partner as a pressed flower supplier in the Camila Home Industry. Keywords : Selection of Supplier and Analytic Network Process (ANP)
Decision Making for Acceptance of Physics Teachers with the Fuzzy TOPSIS Method Fadhilah Dirayati; Samsyuryadi Samsyuryadi; Sukemi Sukemi
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 13 No 1 (2021): JUPITER Vol. 13 No. 1 April 2021
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

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Abstract

Abstract Teachers are the most important human resource in educating students. At SMP Negeri 3 Palembang there is still a great need for teaching staff, namely professional physics teachers. The professional physics teachers selected are those who really have good potential in educating. Teacher selection has not been represented quantitatively so that it is still based on subjective views and thoughts. This study aims to provide a quantitative employee selection decision-making technique through the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Data obtained through interviews with teachers and HRD to get the weight of the criteria at each stage and implemented in teacher candidates. The results obtained were teacher candidate rankings for each stage of selection, so that the teacher was declared to have passed to the next stage or did not pass and could not continue to the next stage. The value with the lowest ranking and does not meet the special criteria will result in the candidate not passing. From the research results, the use of the fuzzy method can make it easier in subjective assessment, and the TOPSIS fuzzy calculation until the final stage results in 3 passing candidates. Keywords—Teacher Selection Decision Making, Fuzzy TOPSIS, Knockout System in Selection Stages