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All Journal JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Creative Information Technology Journal Techno Nusa Mandiri : Journal of Computing and Information Technology JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL ILMIAH INFORMATIKA JurTI (JURNAL TEKNOLOGI INFORMASI) Martabe : Jurnal Pengabdian Kepada Masyarakat Krea-TIF: Jurnal Teknik Informatika CSRID (Computer Science Research and Its Development Journal) Informasi Interaktif CCIT (Creative Communication and Innovative Technology) Journal Indonesian Journal of Business Intelligence (IJUBI) IJIIS: International Journal of Informatics and Information Systems Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Management and Sustainable Development Journal Journal of Applied Data Sciences International Journal of Computer and Information System (IJCIS) Jurnal Pengabdian Kepada Masyarakat Patikala Journal Computer Science and Informatic Systems : J-Cosys Jurnal Ilmiah Edutic : Pendidikan dan Informatika Jurnal Informatika: Jurnal Pengembangan IT ABDIKOM
Musthofa Galih Pradana
Universitas Pembangunan Nasional Veteran Jakarta
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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Journal : Informasi Interaktif

 1 
PERBANDINGAN METODE WEIGHTED PRODUCT DAN SIMPLE ADDITIVE WEIGHTING DALAM SELEKSI PENGURUS FORUM ASISTEN (STUDI KASUS : UNIVERSITAS AMIKOM YOGYAKARTA) Pradana, Musthofa Galih; Kusrini, Kusrini; Luthfi, Emha Taufiq
Informasi Interaktif Vol 4, No 2 (2019): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

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Abstract

The assistant forum is an organization built by AMIKOM Yogyakarta University which serves as an official forum for Practicum Assistants. In the Forum Assistant there are daily administrators in charge of managing the daily activities of the organization. In determining the day-to-day management, a selection process is conducted, so that the elected management is the right individual and able to make the Assistant Forum organization better. Because of the importance of the selection process, a system that is able to provide recommendations to determine eligible individuals is needed. administrator. There are many methods that can be used in decision support systems, including the Weighted Product method and Simple Additive Weighting. The data of the candidates for Forum Assistant will be applied to these two methods and a comparison is made of the ranking results of the Weighted Product method and Simple Additive Weighting. The results obtained from this study are ranking from the Weighted Product method and Simple Additive Weighting which produces the same ranking of 3 data from a total of 10 data tested or similarity percentage of 20%.Keywords: Selection, Decision Support System, Weighted Product, Selection.
PREDIKSI CUSTOMER CHURN PERUSAHAAN TELEKOMUNIKASI MENGGUNAKAN NAÏVE BAYES DAN K-NEAREST NEIGHBOR Kaharudin Kaharudin; Musthofa Galih Pradana; Kusrini Kusrini
Informasi Interaktif Vol 4, No 3 (2019): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

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Abstract

For a company it is very vital. Customers are the key to running a business that is run. But in reality there are loyal customers and some are churned out. Churn is defined as the tendency of customers to stop doing business with a company. It is important for companies to be able to identify customers who have a tendency to be churn customers. Then a report is needed to be able to identify and make decisions for management. Prediction method using Naïve Bayes method produces an accuracy of 76% and K-Nearest Neighbor produces information with a K = 1 value of 73%, K = 3 which is 76% and K = 5 by 78% It can be concluded that the K-Nearest Neighbor Method with K = 3 has a better value. The results of customer predictions for a company can be used to take an example for the customer so they will not churn.  Keywords: Prediction, Customer, Churn, Naïve Bayes, Telecomunication, K-Nearest Neighbor.
Co-Authors Adhien Kenya Anima Estetikha Andri Pramuntadi Anni Alvionita Simanjuntak Budi, Ryan Setya Dema Mathias Lumban Tobing Dhina Puspasari Wijaya, Dhina Puspasari Dwi Nyamiati, Retno Dyah Listianing Tyas, Dyah Listianing Emha Taufiq Luthfi Fadhli Suko Wiryanto Fandli Supandi Gutama, Deden Hardan Ha, Hoang Thi Henki Bayu Seta I Wayan Rangga Pinastawa Izzety, Aurel Jayanta Kaharuddin Kharisma Wiati Gusti Khoironi, Khoironi Khoirunnisa, Hilda Kusrini Kusrini Kusrini Kusrini Kusrini Kusrini MARTINI, NI PUTU DEVIRA AYU Mu, Jesselyn Muhamad Ridwan Muhamad Ridwan Muhammad Adrezo Muthia Zahrah, Nada Neny Rosmawarni Nindy Irzavika Niqotaini, Zatin Nurcahyo, Azriel Christian Nurhajar Anugraha Nurhuda Maulana Nurul Afifah Arifuddin Nyamiati, Retno Dwi Pamekas, Bondan Wahyu Prananto, Muhammad Teguh Pujo Hari Saputro Radinal Setyadinsa Rangga Pinastawa, I Wayan Rangga Saputra Ridlo Muttaqien Ridwan Raafi'udin Rifka Dwi Amalia Rifqi Hammad Rusiyono, Ruwet Setiawan, Deandra Satriyo Wahit Desta Prastowo Wari, Valtrizt Khalifah Yulianto Mustaqim Yusuf Hendra Pratama