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Risnandy Maulana
Teknik Informatika, UIN Sunan Gunung Djati Bandung
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Implementation of the Prefixspan Algorithm for Recommended Cinema Showings Adellia Rahmasari; Dimas Adi Putra Pratama; Nisvy Sya`'bana Nugraha; Risnandy Maulana; Dinda Meysya Rochma
Gunung Djati Conference Series Vol. 3 (2021): Mini Seminar Kelas Data Mining 2020
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (233.936 KB)

Abstract

Along with technological developments that cause the amount of information available is also getting closer, at this time there are approximately 16.3 ZB data or the equivalent of one trillion GB. The purpose of this research is to see how the application of the Prefixspan algorithm for Sequential Pattern Mining (a method for obtaining an ordered pattern). The data used is Movie Meta Data in which there are several columns including genre, director, film etc. With this data, we purpose viewers to present recommendation films to be shown in theaters based on audience enthusiasm from the processed data.
Implementation of the ID3 Algorithm for Classification of Car Quality Dimas Adi Putra Pratama; Nisvy Sya`'bana Nugraha; Risnandy Maulana; Adellia Rahmasari; Ahmad Fauzi
Gunung Djati Conference Series Vol. 3 (2021): Mini Seminar Kelas Data Mining 2020
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (647.432 KB)

Abstract

Transportation like a car is needed by most of family. Cheap, economical and comfortable family cars have been sold in the market. However, buyers must be careful in finding the car they want. To get the best car, many factors are taken into consideration, such as price, seating, and comfort. Comfort is the main thing in owning a car. There are cars that are expensive but do not have comfort, and vice versa. Therefore, we discuss how the Iterative Dichtomizer Three (ID3) Algorithm can be implemented for the classification process of any car with quality according to price, seat and passenger comfort.
Implementation of Hierarchical Clustering Algorithm for Mall Customer Data Clustering Risnandy Maulana; Dimas Adi Putra Pratama; Nisvy Sya`'bana Nugraha; Adellia Rahmasari
Gunung Djati Conference Series Vol. 3 (2021): Mini Seminar Kelas Data Mining 2020
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (284.101 KB)

Abstract

In certain cities there are large malls that must store information on customers who often come to the mall and have cards that can. In their information card there is some information including: gender, age, expenditure and annual income. The customer uses the information card when he makes various purchases at the mall, so that the mall automatically has the spending spirit of all customers who come. We have to segment these customers based on the customer details provided. So we will create a cluster customer using Hierarchical Clustering. By using the grouping in this study so as to produce a very appropriate strategy for a group of customers. Thanks to this unsupervised learning technique, companies can also adjust their marketing strategies more efficiently and focus on the customers with the highest revenue. Customers are segmented into different groups according to their annual expenses and income.
Co-Authors Adellia Rahmasari Ahmad Fauzi Dimas Adi Putra Pratama Dinda Meysya Rochma Nisvy Sya`'bana Nugraha