Article Per Year (5 Year)
p-Index From 2020 - 2025
2.108
P-Index
This Author published in this journals
All Journal Efisiensi : Kajian Ilmu Administrasi Jurnal Ilmiah Kursor JURNAL MEDIA INFORMATIKA BUDIDARMA InComTech: Jurnal Telekomunikasi dan Komputer JCES (Journal of Character Education Society) IJISTECH (International Journal Of Information System & Technology) The IJICS (International Journal of Informatics and Computer Science) KOMPUTIKA - Jurnal Sistem Komputer Jurnal Manajemen Informatika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Dharma Raflesia : Jurnal Ilmiah Pengembangan dan Penerapan IPTEKS IJISTECH JOMLAI: Journal of Machine Learning and Artificial Intelligence Jurnal Informatika: Jurnal Pengembangan IT
Prianto, Cahyo
Applied Bachelor Program Of Informatics Engineering Politeknik Pos Indonesia
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Social Sciences Other

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Jurnal Manajemen Informatika

 1 
Segmentasi Pelanggan Produk Digital Service Indihome Menggunakan Algoritma K-Means Berbasis Python Nisa Hanum Harani; Cahyo Prianto; Fikri Aldi Nugraha
Jurnal Manajemen Informatika (JAMIKA) Vol 10 No 2 (2020): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v10i2.2683

Abstract

Telekomunikasi Indonesia is one of the companies that prioritize customers, but there is no information about customer characteristics. In this research, an analysis of customer characteristics used as a basis for determining customer segmentation and customer profiling for digital products add on Indihome services using the K-Means Algorithm. Determination of the best number of clusters done using the Elbow method and a value of K = 3 obtained, so that customer data grouped into three segments. Customer data processing is divided into 3 simulations with the percentage of train data and test data 80% - 20%, 70% - 30% and 50% - 50%. The data used totaled 1392 records as a population where the data will used to find the characteristics of each data. Cluster evaluations carried out using the Silhouette Index, Davies Bouldin Index, and Calinski Harabasz Index methods. The results of the study show that the third simulation is the best based on cluster evaluation with 50% data train presentation and 50% data test where customer profiling is seen by analyzing the members of each cluster from the third simulation where cluster 0 has 396 customer members with a customer category that provides the biggest profit for the company, cluster 1 has members of 286 customers in the category of customers who unwittingly have great potential in providing benefits for the company, and cluster 2 has a member of 14 customers in the customer category that provides fewer benefits than the cost of providing services.
Pemetaan Pelanggan IndiHome Sebagai Daerah Sasaran Promosi (Studi Kasus : Witel Bandung) Nisa Hanum Harani; Cahyo Prianto; Andri Fajar Sunandhar
Jurnal Manajemen Informatika (JAMIKA) Vol 10 No 2 (2020): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v10i2.2738

Abstract

In this globalization era, marketing communication is very important to help increase sales promotion of indihome digital service products by utilizing customer location points that use indihome services. Currently there are many information systems that are used to support and solve problems in determining the location of a place. Determination of location can be done using mapping. The mapping of Indihome customers is done by utilizing a map provided by Google, the Google Maps API based on the address of the Indihome service customer. Therefore, we need a system to find out which areas use the most indihome services, so that it will make it easier to target promotions for indihome customers who have not used to add services to Indihome such as Movin, Indihome Gamers, Indihome Music, Indihome Music, Indihome Studies, Indihome Storage, Indihome Servers, Video Calls, and other additional packages. The results of this mapping can determine areas / regions that have the potential to be promoted in connection with the addition of indihome service products, so that it will have an impact on increasing customers and sales revenue of Add On products.
Co-Authors Alfadian Owen Andi Tenri Wali Andri Fajar Sunandhar Fikri Aldi Nugraha Hanna Theresia Siregar Harun Ar-Rasyid Indra Firmansyah Kezia Tirza Naramessakh Kezia Tirza Naramessakh Mariana Rospilinda Siki Muh Kusnadi Muhammad Rifqi Daffa Ulhaq Nawaf Naofal Nico Ekklesia Sembiring Nisa Hanum Harani Nisa Hanum Harani Nisa Hanum Harani Nurul Izza Hamka Rahayu, Woro Isti Rd Nuraini Rd.Nuraeni Siti Fatonah Roni Andarsyah Syafrial Fachri Pane