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Rumini .
UNIVERSITAS AMIKOM YOGYAKARTA
Computer Science & IT

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Study Program Selection Using the Fp-Growth and J48 Algorithm Nor Hikmah; Rumini .
Jurnal ICT : Information Communication & Technology Vol 21, No 1 (2022): JICT-IKMI, Juli 2022
Publisher : STMIK IKMI Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36054/jict-ikmi.v21i1.423

Abstract

The study program is an absolute thing and must be chosen by prospective new students when registering to become a student, the lack of knowledge of the courses offered by the campus becomes a difficulty in determining study programs that match their interests. The first research method of analyzing data uses the association rule to get the relationship of study programs with other study programs, and subsequently classifies the study program using decision tree j48, and is followed by examiners using confusion matrux. The results of this study are to use the association rule Fp-Growth method obtained 10 best rules, namely for the first rule D3 Informatics with International Relations. Of the 10 rules obtained as a reference or basis for determining classes on the j48 algorithm, from the results of the 10 rules, analyzed according to the rules applied in Amikom, then obtained into 11 classes where the rules are based on the origin of natural science or social studies schools. By using the j48 algorithm, 99.8% accuracy is obtained with the highest hierarchy in the decision tree, namely the D3 Informatics study program and for the origin school, namely IPS high school
Klasifikasi dan Pengaruh Trending Youtube Menggunakan Algoritma Neural Network dan Regresi Linear Norhikmah; Rumini .
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The development of social media is very influential which includes Facebook, Instagram, Twitter, YouTube and others. One of them is the social media YouTube which has a very important role for the public and community leaders. Youtube provides very interesting content for those who have channels and those who do not. Trending or not a YouTube channel based on likes, dislikes, comments, and video views. Trending data from YouTube can be processed data. The data processing technique that can be used in the process is classification. Classification is a data processing technique that divides objects into classes. Using the backpropagation neural network algorithm in the classification process, which can determine Youtube trending with a very good and quite good ratio. a dataset of 40,880 obtained the best modeling obtained in neuron 10, layer 4, epoch 2000, with an MSE value of 0.03 and 87% validation, with a duration of 24 seconds, followed by a multiple linear regression test which resulted in the equation Y=0.788 + 4.914X1 + 9.458X2 - 1.977X3 - 4.418X4 + e where the more views and likes, the more trending youtube is, and the more dislikes and comments, the trending status of youtube decreases with a significance value of 0.000 which means it has a very significant relationship or at a strong level.
Co-Authors Nor Hikmah Norhikmah Norhikmah