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All Journal EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Transformasi: Jurnal Pengabdian Masyarakat Seminar Nasional Informatika (SEMNASIF) Paradigma INOVTEK Polbeng - Seri Informatika JURNAL PENGABDI SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Informatika Universitas Pamulang Sebatik SENTIA 2017 Journal of Humanities and Social Studies EDUMATIC: Jurnal Pendidikan Informatika To Maega: Jurnal Pengabdian Masyarakat SKANIKA: Sistem Komputer dan Teknik Informatika Research lembaran publikasi Ilmiah Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Jurnal Mahasiswa Ilmu Komputer Jurnal Pengabdian Pada Masyarakat Telematika MKOM Jurnal Ticom: Technology of Information and Communication Jurnal Pengabdian Masyarakat Tekno
Reva Ragam Santika
Teknik Informatika, Fakultas Teknologi Informasi, Universitas Budi Luhur
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Journal : EDUMATIC: Jurnal Pendidikan Informatika

 1 
Implementasi Machine Learning Dalam Penentuan Rekomendasi Musik Dengan Metode Content-Based Filtering Putra, Aldy Istna; Santika, Reva Ragam
Jurnal Pendidikan Informatika (EDUMATIC) Vol 4, No 1 (2020): Edumatic : Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

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Abstract

The industry that is experiencing significant development is the music industry. An example of its development is the many online music service providers of application platforms. The amount of data stored makes it difficult to analyze existing data, the presence of Machine Learning is felt to be able to answer these challenges. Improving user experience is important to attract users to use the applications they have. The recommendation system is one way to improve that. This research aims to create a system that can present music recommendations according to user preferences so that the user's comfort level will increase. The system developed in this research uses the Extreme Programming method with several stages, namely planning, design, coding, and testing. This research utilizes Machine Learning in searching for data patterns and Content-Based Filtering (CBF) methods in finding recommendations. The recommendation system with the CBF method can produce a song similarity level of up to 0.6684, as well as the value of precision reaching 0.125 and 0.200 at recall. The results of Performance Testing and System Testing obtained stated that the recommendation system can run well with an average response time 3.5 seconds. The conclusion of this research is that the recommendation system using the CBF method can produce recommendations that are in accordance with user preferences, but with not too much data. More effective algorithms are needed for larger data.
AHP dan WP: Metode dalam Membangun Sistem Pendukung Keputusan (SPK) Karyawan Terbaik Ramadhan, Ahmad Gilang; Santika, Reva Ragam
Jurnal Pendidikan Informatika (EDUMATIC) Vol 4, No 1 (2020): Edumatic : Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

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Abstract

The best employee selection is an award given by the company to employees who can encourage all employees to improve their performance. However, for the assessment is usually still done subjectively and manually, and at least the support system in making decisions into this problem can be a problem. This study aims to build a decision support system in the selection of the best employees in accordance to the requirements specified by the company by using the Prototype model. Meanwhile, the method applies to test the consistency and accuracy of this system use the Analytical Hierarchy Process (AHP) and Weighted Product (WP). In selecting the best employees, there are several criteria to be assessed, namely: Knowledge, Ability, Attitude, Attendance, and Cooperation, as well as the number of subjects of this study consisting of five people. Our findings show that the accuracy rate of this system is below 10%, and the consistency index value is correct, so it can be used with a relative number of initial weights = 1. After testing or testing, the results obtained are all components or modules in this system already successfully and properly used as it should be.
AHP dan WP: Metode dalam Membangun Sistem Pendukung Keputusan (SPK) Karyawan Terbaik Ramadhan, Ahmad Gilang; Santika, Reva Ragam
Jurnal Pendidikan Informatika (EDUMATIC) Vol 4, No 1 (2020): Edumatic : Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

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

Abstract

The best employee selection is an award given by the company to employees who can encourage all employees to improve their performance. However, for the assessment is usually still done subjectively and manually, and at least the support system in making decisions into this problem can be a problem. This study aims to build a decision support system in the selection of the best employees in accordance to the requirements specified by the company by using the Prototype model. Meanwhile, the method applies to test the consistency and accuracy of this system use the Analytical Hierarchy Process (AHP) and Weighted Product (WP). In selecting the best employees, there are several criteria to be assessed, namely: Knowledge, Ability, Attitude, Attendance, and Cooperation, as well as the number of subjects of this study consisting of five people. Our findings show that the accuracy rate of this system is below 10%, and the consistency index value is correct, so it can be used with a relative number of initial weights = 1. After testing or testing, the results obtained are all components or modules in this system already successfully and properly used as it should be.
Co-Authors Aburizal K Achmad Solichin Aditya Maulana Habibi Akbar, Kafi Kurnia Alif Ramadhan Anang Kurniawan Anita Diana Ari Irawan Ari Saputro Asef Solehuddin Atik Ariesta Auliatunnisa Kamila Bima Cahya Putra Chandra, Joko Christian Diah Qisqadartunissa Dian Anubhakti Dolly Virgian Shaka Yudha Sakti Farida Ariyani, Pipin Ferdiansyah Ferdiansyah Hendri Irawan Hidayah, Zainur Iman Permana Juanita, Safitri Khoiri, Achmad Kurnia Ramadhan Liswandi, Liswandi M. Ikhsan Abdillah Mochamad Andri Mohamad Yanuar Wardinnansah Musodo, Krisna Adiyarta Putra, Aldy Istna PUTRA, RICKY WIDYANANDA Ratna Ujiandari Samuel Hansen Saputro, Ari Syamsiar, Syamsiar Titin Fatimah Wiharto, Yudi Wulandari, Retno Yani Prabowo