KLASIFIKASI KARAKTERISTIK CUSTOMER CHURN DI TELEKOMUNIKASI INDUSTRI UNTUK MENINGKATKAN RETENSI PELANGGAN MENGGUNAKAN ALGORITMA DECISION TREE ID3

DAMANIK, STEVAN DESENA and Jambak, Muhammad Ihsan (2023) KLASIFIKASI KARAKTERISTIK CUSTOMER CHURN DI TELEKOMUNIKASI INDUSTRI UNTUK MENINGKATKAN RETENSI PELANGGAN MENGGUNAKAN ALGORITMA DECISION TREE ID3. Undergraduate thesis, Sriwijaya University.

[thumbnail of RAMA_57201_09031282025093.pdf] Text
RAMA_57201_09031282025093.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (3MB) | Request a copy
[thumbnail of RAMA_57201_09031282025093_TURNITIN.pdf] Text
RAMA_57201_09031282025093_TURNITIN.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (1MB) | Request a copy
[thumbnail of RAMA_57201_09031282025093_0205046801_01_front_ref.pdf] Text
RAMA_57201_09031282025093_0205046801_01_front_ref.pdf - Accepted Version
Available under License Creative Commons Public Domain Dedication.

Download (960kB)
[thumbnail of RAMA_57201_09031282025093_0205046801_02.pdf] Text
RAMA_57201_09031282025093_0205046801_02.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (78kB) | Request a copy
[thumbnail of RAMA_57201_09031282025093_0205046801_03.pdf] Text
RAMA_57201_09031282025093_0205046801_03.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (192kB) | Request a copy
[thumbnail of RAMA_57201_09031282025093_0205046801_04.pdf] Text
RAMA_57201_09031282025093_0205046801_04.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (150kB) | Request a copy
[thumbnail of RAMA_57201_09031282025093_0205046801_05.pdf] Text
RAMA_57201_09031282025093_0205046801_05.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (12kB) | Request a copy
[thumbnail of RAMA_57201_09031282025093_0205046801_06_ref.pdf] Text
RAMA_57201_09031282025093_0205046801_06_ref.pdf - Bibliography
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (131kB) | Request a copy
[thumbnail of RAMA_57201_09031282025093_0205046801_07_lamp.pdf] Text
RAMA_57201_09031282025093_0205046801_07_lamp.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (1MB) | Request a copy

Abstract

Ignorance of telecommunications companies regarding the reasons and characteristics of customer churn causes telecommunications companies to suffer huge losses. This makes customer churn a big problem for telecommunications companies. This study uses data mining with classification techniques as a solution to analyze customer churn characteristics. This research will use Rapid Miner and the ID3 algorithm to carry out the data mining process. . The purpose of this research is to find out what are the characteristics of customer churn so that companies can make policies that can retain customers and increase customer retention. This research is based on CRISP-DM. Data taken from kaggle.com with 21 attributes and 7034 rows of data and data preparation will be carried out. From the research results it is known that there are 5 attributes that have a considerable influence on customer churn, namely contracts, InternetService, TotalChares, tenure, PaperlessBilling, MultipleLines, StreamingMovies. And from the results of this study has an accuracy rate of 79.53%.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Data Mining, Karakteristik Customer Churn, Algoritma ID3, Perusahaan Telekomunikasi, Rapid Miner
Subjects: T Technology > T Technology (General) > T1-995 Technology (General)
Divisions: 09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User: Stevan Desena Damanik
Date Deposited: 15 Jan 2024 06:06
Last Modified: 15 Jan 2024 06:06
URI: http://repository.unsri.ac.id/id/eprint/138006

Actions (login required)

View Item View Item