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All Journal Gunung Djati Conference Series
Muhammad Irfan Nur Imam
Teknik Informatika, UIN Sunan Gunung Djati Bandung
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Film Recommendation Analysis with Sequential Pattern Discovery Algorithm Using Equivalence classes (SPADE) Aisyah Amini Nur; Akbar Hidayatullah Harahap; Ihsan Muttaqin Bin Abdul Malik; Muhammad Irfan Nur Imam; Muhammad Thariq Sabiq Bilhaq; Angelyna Angelyna
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 (499.306 KB)

Abstract

Currently, the internet is the most essential thing in human life. So that there is a change in human needs, one of which is enjoying entertainment. With the internet, enjoying entertainment can be done anywhere and anytime, one of the entertainment is movies. With the internet, many service providers provide movie watching sites online. So that people become interested and use it a lot to watch movies online. With the increase in film fans, a film recommendation system is required to make a film recommendation pattern based on previous movie viewing. Therefore, this study aims to provide recommendations for viewing films using the pattern recognition method that often occurs. The technique used is sequence pattern mining using SPADE to find patterns from a group of data. SPADE's advantage is its speed in finding sequence frequencies that can be used as movie recommendation data from previous shows.
Classification of Heart Disease Diagnosis using the Random Forest Algorithm Akbar Hidayatullah Harahap; Ihsan Muttaqin Bin Abdul Malik; Muhammad Irfan Nur Imam; Muhammad Thariq Sabiq Bilhaq; Aisyah Amini Nur; Siti Lufia Dwi Agustini
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 (603.088 KB)

Abstract

The heart is an important part of the human body organs. But it does not rule out this heart problem and causes several symptoms, causing deadly heart disease. Therefore, many studies are used to obtain fast, precise and accurate heart disease diagnosis data. One of them is the classification of heart disease diagnoses using the Random Forest algorithm. This random forest algorithm method uses several unified decision trees. So that accurate results can be obtained regarding the diagnosis of this heart disease. The accuracy obtained from the experimental results using the Python programming language is 85.3%.
Premier League 2020 Player Data Clustering with the DBSCAN Algorithm Muhammad Thariq Sabiq Bilhaq; Aisyah Amini Nur; Akbar Hidayatullah Harahap; Ihsan Muttaqin Bin Abdul Malik; Muhammad Irfan Nur Imam; Muhammad Nur Sidiq
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 (378.69 KB)

Abstract

Premiere League is prestigious event that is in demand by many people. And player goals are very important in this regard. Research on the number of players based on this age can be done. One of which is by clustering. Clustering is a method for grouping objects according to their similarities. And the algorithm used DBSCAN. This algorithm can solve complex problems and has the right density so that it can help to get clustering data on this theme.
Co-Authors Aisyah Amini Nur Akbar Hidayatullah Harahap Angelyna Angelyna Ihsan Muttaqin Bin Abdul Malik Muhammad Nur Sidiq Muhammad Thariq Sabiq Bilhaq Siti Lufia Dwi Agustini