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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Informatika Universitas Pamulang ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JiTEKH (Jurnal Ilmiah Teknologi Harapan) Bulletin of Computer Science Research Journal of Informatics Management and Information Technology Prosiding Snastikom Hello World Blend Sains Jurnal Teknik Prioritas : Jurnal Pengabdian Kepada Masyarakat
Liza, Risko
Unknown Affiliation
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering

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Klasifikasi User Berdasarkan Trafik Http/Https Menggunakan Metode Naïve Bayes Prayoga, Eko; Diansyah, T.M; Liza, Risko
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 7, No 1 (2023): April 2023
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v7i1.15698

Abstract

Along with the times and accompanied by advances in information and communication technology, it is undeniable that at this time all activities use information technology. One of the activities is to use the internet. The research will conduct a classification based on internet usage data obtained through questionnaires using data mining techniques. The attributes that will be used in doing the classification are Name, Age, Gender, Last Education. The method used is the Naïve Bayes method, which is one of the classification techniques in data mining. Based on the research conducted, it was concluded that based on internet user data used as training data, the Naïve Bayes method succeeded in classifying 32 data from 50 data tested. So the Naïve Bayes method succeeded in predicting the magnitude of the percentage of accuracy by 64%. Keywords : Data Mining, Classification, Naïve Bayes
Pemanfaatan Algoritma K-Means Clustering Pada Sistem Rental Mobil Maesaroh, Sri Wulandari; Diansyah, T.M; Liza, Risko; Lubis, Yessi Fitri Annisa
Journal of Informatics Management and Information Technology Vol. 5 No. 3 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i3.391

Abstract

PT. Station Armada Indonesia is one of the companies engaged in the car rental service sector. With the many types of car choices offered, it is not uncommon for many customers to feel confused in choosing what type of car suits their needs. This problem is often experienced by customers who are confused by the many choices of car types available. In this study, the k-means algorithm was used to group cars based on several attributes. The k-means algorithm can be used to group car type data to help provide recommendations for choosing a car type. The purpose of this study is to make it easier for customers to choose the type of car that is most in demand and as material for PT. Station Armada Indonesia to respond better to market changes and achieve better results. Grouping car rental fleets based on rental prices and mileage by utilizing the k-means algorithm can help PT. Station Armada Indonesia group car types. From the grouping results, two cluster groups were obtained with the character of the first cluster being less in demand by customers and the second cluster group being the most in demand by customers. So that the company can easily prepare the type of fleet that is most in demand. In the application of data mining methods using k-means is very helpful and makes it easier for PT. Station Armada Indonesia to develop more effective marketing and offering strategies. By grouping car types with the implementation of k-means can facilitate customer knowledge in choosing car types based on customer needs.
Co-Authors Alfiandi, Tedi Ardiansyah, Muhammad Fahri Ariangga, Afrilian Diansyah, T M Diansyah, T. M. Diansyah, T.M Dodi Siregar Fitriana, Liza Ginting, Budi Haida Dafitri, Haida Harahap, Herlina JUNAIDI Lubis, Yessi Fitri Annisa Maesaroh, Sri Wulandari Muhammad Arifin Nur Wulan, Nur Prayoga, Eko Rachmat Aulia, Rachmat Ramli Ramli Ritonga, Din Aswan Amran Sarjana Sarjana Sarudin, Sarudin Siddiq, Daffa Maulana Suriati, Suriati Tengku Mohd Diansyah, Tengku Mohd Williyandi, Rizky Yessi Fitri Annisah Lubis Yulfitra, Yulfitra