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All Journal Sistemasi: Jurnal Sistem Informasi Creative Information Technology Journal Faktor Exacta Jurnal Mantik Penusa JURIKOM (Jurnal Riset Komputer) Jurnal ICT : Information Communication & Technology Respati Madani : Indonesian Journal of Civil Society Jurnal Abdi Masyarakat Indonesia Aptekmas : Jurnal Pengabdian Kepada Masyarakat MUALLIMUN : JURNAL KAJIAN PENDIDIKAN DAN KEGURUAN
Norhikmah Norhikmah
Sistem Informasi, Fakultas Ilmu Komputer, Universitas AMIKOM Yogyakarta, Indonesia
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Journal : Jurnal ICT : Information Communication

 1 
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

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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.
Pemilihan Program Studi Menggunakan Algoritma FP-Growth dan J48 Norhikmah; Rumini
Jurnal ICT: Information Communication & Technology Vol. 22 No. 1 (2022): JICT-IKMI, Juli 2022
Publisher : LPPM STMIK IKMI Cirebon

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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
Analisis Breadth-First Search dan Algoritma Certainty Factor untuk Diagnosa Penyakit Pada Mahasiswa Norhikmah; Nita Helmawati; Wiji Nurastuti
Jurnal ICT: Information Communication & Technology Vol. 23 No. 1 (2023): JICT-IKMI, Juli 2023
Publisher : LPPM STMIK IKMI Cirebon

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The problem that often occurs, especially among students, is a lack of knowledge about disease symptoms, which can lead to difficulties in making an initial diagnosis and require assistance from medical experts. Students often have busy schedules and do not have enough time to undergo regular health check-ups, resulting in symptoms of diseases being overlooked and not detected quickly. Some students may not have access to adequate healthcare services, especially those living in remote areas or outside the city. Students often do not realize the importance of maintaining their health and undergoing regular health check-ups, which can worsen their health conditions. Therefore, a system is needed to assist students in quickly and accurately diagnosing diseases. This research aims to develop a disease diagnosis system for students using the breadth-first search method and certainty factor algorithm. This method utilizes calculations based on similarity divided by predetermined weights. Certainty factor (CF) is a clinical parameter value provided by experts to indicate the degree of confidence in a fact or rule. In this study, disease symptoms are inputted into an expert system and calculated using the certainty factor method to diagnose the type of disease suffered by students. The research results show that the developed expert system successfully diagnoses the type of disease with an accuracy of 97.5%.
Co-Authors Acihmah Sidauruk Adytyo Wahyu Nugroho Aldis Gandi Mitra Sanjung Ali Mustofa Alvien Muhammad Kannabi Anggit Dwi Hartanto Cut Tesya Iftillah Anggun Pratiwi Dewi Pratama Mastha Cahyaningrum Donni Prabowo Fintas Yulianti Ika Nur Fajri Kusrini Kusrini M. Rudyanto Arief Mu’alif Lihawa Neela Afifah Nita Helmawati Nita Helmawati Nor Latifah Nurlaila Nurlaila Randani Randani Rifqhy Rayhan Andi Riga Pratama Rumini Rumini . Rumini Rumini Sulistyo Pradana Vidyana Arsanti Wiji Nurastuti Wiwi Widayani