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All Journal International Journal of Advances in Intelligent Informatics EMITTER International Journal of Engineering Technology Jurnal Informatika Upgris JURNAL MEDIA INFORMATIKA BUDIDARMA JTERA (Jurnal Teknologi Rekayasa) InComTech: Jurnal Telekomunikasi dan Komputer Jurnal Eksplora Informatika Technomedia Journal Jurnal Tekno Insentif Jurnal Telematika Jurnal Teknologi Terapan Dinasti International Journal of Education Management and Social Science Mobile and Forensics Jurnal Teknik Industri Terintegrasi (JUTIN) Journal of Applied Data Sciences Journal of Dinda : Data Science, Information Technology, and Data Analytics JEECS (Journal of Electrical Engineering and Computer Sciences)
Syafrial Fachri Pane, Syafrial Fachri
Politeknik Pos Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Neuroscience

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GURILEM : A Novel Design of Customer Rating Model using K-Means and RFM Awangga, Rolly Maulana; Pane, Syafrial Fachri; Wijayanti, Diana Asri
EMITTER International Journal of Engineering Technology Vol 7 No 2 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v7i2.325

Abstract

A rating system or reviews are generally used to assist in making decisions. Rating system widely used as a technique in the recommendation of one of them used by the customer, as in determining the resort to be used. However, the credibility of the rating looks vague because the rating could only represent some points of service. So that customer preference with each other is very different. Personalized recommendation systems offer more personalized advice, precisely knowing the preferences or tastes of the customers. Especially for customers who have a transaction history or reservation as at their resorts provide good information used by managers to design a recommendation model for their customers. In this study aims to create a model of resort recommendations based on a rating of frequency. This frequency is the number of resort use by the customer within the specified time frame. With the frequency can represent the preferences of customers. The RFM method is used to measure the reservation frequency value of the customer. The K-Means method is used to categorize customer data with its frequency and classify the type of resort. Recommendation resort to the customer based on the dominant use in one of the resort types. The recommended type of resort based on the similarity between the types of resorts used with other types of resorts.
Co-Authors Adiwijaya Agus Purnomo Alfian Akbar Gozali Ekra Sanggala Faisal Abdullah Fajri, Ravi Rahmatul Fathonah, Rd. Nuraini Siti Fatonah, Nuraini Siti Ferdinan, Dani Gia Ginasta, Nava Habibi, Roni Haq, Dzikri Izzatul Harani, Nisa Hanum Helmi Setyawan, Muhammad Yusril Khaera Tunnisa, Khaera Kurniawan, Alit Fajar Kurniawan, Cahya Mahmud Dwi Sulistiyo Poetra, Chandra Kirana Prianto, Cahyo Ramadhan, Bachtiar Reksiyano, Rendy Dwi Rionald, Valen Rolly Maulana Awangga, Rolly Maulana Siregar, M. Amran Hakim Talan, Maylinda Christy Yosefina Vegita, Yola Wijayanti, Diana Asri Zain, Rofi Nafiis