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All Journal Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Brilliance: Research of Artificial Intelligence
M. Hamdani Santoso
Universitas Medan Area
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mathematics Other

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Wayang Image Classification Using MLP Method and GLCM Feature Extraction M. Hamdani Santoso; Diah Ayu Larasati; Muhathir Muhathir
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 1, No 2 (2020)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (526.902 KB) | DOI: 10.30596/jcositte.v1i2.5131

Abstract

Wayang is a form of shadow art that has been known to the Javanese people more than 1500 years ago. For Javanese people, the function of wayang is not only as a spectacle but also as a request, because in the wayang story there are values that are important to Javanese society. Wayang has developed from time to time, there are many types of wayang in Indonesia, with many types of wayang in Indonesia, of course preserving the art of wayang kulit is not an easy thing, especially because this traditional art is not yet very popular among young people, especially in the regionsburban. Today's young people use technology more in finding information, such as using laptops or smartphones. Because to make it easier for people who want to know about puppets and their types, a technology is created that can distinguish the types of puppets based on wayang images. So this research was made using the MLP (The Multi Layer Perceptron) method and its extraction feature GLCM (Gray-Level Co-Occurrence Matrix) with a total system accuracy of recognizing wayang image objects up to 73.4%.
Application of Association Rule Method Using Apriori Algorithm to Find Sales Patterns Case Study of Indomaret Tanjung Anom M. Hamdani Santoso
Brilliance: Research of Artificial Intelligence Vol. 1 No. 2 (2021): Brilliance: Research of Artificial Intelligence, Article Research November 2021
Publisher : ITScience (Information Technology and Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (692.984 KB) | DOI: 10.47709/brilliance.v1i2.1228

Abstract

Data mining can generally be defined as a technique for finding patterns (extraction) or interesting information in large amounts of data that have meaning for decision support. One of the well-known and commonly used association rule discovery data mining methods is the Apriori algorithm. The Association Rule and the Apriori Algorithm are two very prominent algorithms for finding a number of frequently occurring sets of items from transaction data stored in databases. The calculation is done to determine the minimum value of support and minimum confidence that will produce the association rule. The association rule is used to produce the percentage of purchasing activity for an itemset within a certain period of time using the RapidMiner software. The results of the test using the priori algorithm method show that the association rule, that customers often buy toothpaste and detergents that have met the minimum confidence value. By searching for patterns using this a priori algorithm, it is hoped that the resulting information can improve further sales strategies.
Co-Authors Diah Ayu Larasati Muhathir Muhathir