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Journal : JURIKOM (Jurnal Riset Komputer)

Pemanfaatan Algoritma Hebb Rule Mendiagnosis Kerusakan Elektroda Pada Proses Welding Frame Thermostat Alvendo Wahyu Aranski; Sestri Novia Rizki
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5335

Abstract

In the current era of technological development, developments in computer systems are very fast, computerized systems are needed at this time, including to diagnose electrodes in the welding process, frame thermostats on soulplate, because sometimes it's mechanical. Mechanics find it difficult to detect damage to machines due to the absence of a good computerized system. The use of SMAW (Shielded Metal Arc Welding) in the industrial world is quite widely used. With this machine humans are greatly helped by the need to make a metal object. So that with the frequent use of these tools, it will also be more vulnerable to damage to these tools. The machine technicians supplied by the company are not proportional to the number of machines. Therefore, to help solve the problem. The purpose of this research is to make it easier for mechanics to detect engine damage. This study uses the Hebb Rule method with the simplest learning method concept. In this method learning is done by fixing the weight values in such a way that if there are 2 connected neurons, and both are 'on' at the same time, then the weight between the two is increased. If the data is represented in a bipolar manner, then the weight is improved. Therefore this method is very useful in solving a problem that occurs. The final result of this research is 1, in which the network can understand the intended pattern. It has a value of 1 because it uses a binary number pattern, not bipolar.
Implementasi Data Mining Pada Penjualan Pakaian dengan Algoritma FP-Growth Rahmat Fauzi; Alvendo Wahyu Aranski; Nopriadi Nopriadi; Ellbert Hutabri
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.5795

Abstract

The amount of competition in the business world, especially in the sales industry, required developers to find a strategy that could increase sales and marketing of products sold, one of which was using clothing sales data with data mining. Data Mining was an iterative and interactive process to find new patterns or models that can be generalized for the future, valuable, and understandable in a massive database. HAS Stores in the arrangement of goods layout still place goods according to groups and types of goods, so that it has an impact on service and item search when consumers want to buy more than one item and are located far apart. Therefore, this study aims to apply the FP-Growth Algorithm to find out the most sold clothing sales at HAS Stores in Batam city. This study uses the Association Rule method by utilizing the FP-Growth Algorithm. This study aimed to apply the FP-Growth Algorithm to determine the most sold clothing sales at HAS Stores in Batam city. Through the mining process with the FP-Growth (Frequent Pattern Growth) algorithm, the types of clothes sold will be obtained, and how much inventory the store needs to provide the clothing stock. The results showed that the most sold clothing products were Gamis and Jilbab through the calculation of support 53,33% and confidence 100%. Regarding these results, marketing strategies can be focused on the product and set a layout that customers can easily see.