Customer Retention: Detecting Churners in Telecoms Industry using Data Mining Techniques

Ewieda, Mahmoud; Shaaban, Essam; Roushdy, Mohamed

doi:10.14569/ijacsa.2021.0120326

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…Data mining has an important function to help obtain useful information in increasing knowledge for users. Basically, data mining has six functions which refer to Larose quoted, namely (Rusydiyah et al, 2021;Ewieda et al, 2021): a. Description; aims to identify patterns that appear repeatedly in data and change these patterns into rules and criteria that are easy to understand so that they can be easily and effectively understood by the application domain so as to increase the level of knowledge in the system.…”

Section: Data Miningmentioning

confidence: 99%

Twitter Social Media Conversion Topic Trending Analysis Using Latent Dirichlet Allocation Algorithm

Musliadi

Zainuddin

Wabula

2022

JAETS

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In Indonesia, Twitter is one of the most widely used social media platforms. Because of the diverse and frequently shifting message patterns on this social media, it is extremely challenging and time-consuming to manually identify topics from a collection of messages. Topic modeling is one method for obtaining information from social media. The model and visualization of the results of modeling topics that are discussed on social media by the Makassar community are the goals of this study. The Latent Dirichlet Allocation (LDA) algorithm is used to model and display the results of this study. The modeling results indicate that the eighth topic is the most frequently used word in a conversation. In the meantime, the 7th and 6th topics emerged as the conversation's core based on the spread of the words with the highest term frequency. The study's findings led the researchers to the conclusion that in the Makassar community's social media discussions, capitalization and visualization using the LDA method produced the words with the highest trend and the topic with the highest term frequency.

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Section: Data Miningmentioning

confidence: 99%

Twitter Social Media Conversion Topic Trending Analysis Using Latent Dirichlet Allocation Algorithm

Musliadi

Zainuddin

Wabula

2022

JAETS

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Assessing the effectiveness of OTT services, branded apps, and gamified loyalty giveaways on mobile customer churn in the telecom industry: A machine-learning approach

Kirgiz,

Kiygi-Calli,

Cagliyor

et al. 2024

Telecommunications Policy

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Diabetic Prediction and Analysing Insulin Levels using Machine Learning

Rao¹,

Ganesh²,

Yadav³

et al. 2023

IJARSCT

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Diabetes is a chronic metabolic disorder that affects millions of people worldwide. The disease is characterized by high blood glucose levels, which can lead to a variety of health complications if left untreated. Early detection and management of diabetes are crucial to prevent complications and improve patient outcomes. In recent years, machine learning algorithms have been increasingly used to predict the risk of diabetes and provide personalized healthcare to patients. This paper aims to provide an overview of diabetic prediction using machine learning algorithms. Diabetes can be classified into two main types: type 1 and type 2 diabetes. Type 1 diabetes is caused by the destruction of insulin-producing cells in the pancreas, whereas type 2 diabetes is characterized by insulin resistance and impaired insulin secretion. Type 2 diabetes accounts for about 90% of all cases of diabetes. Early detection and management of diabetes are crucial to prevent complications and improve patient outcomes. Several risk factors have been associated with diabetes, including family history, age, ethnicity, obesity, sedentary lifestyle, and hypertension. Predicting the risk of diabetes using machine learning algorithms can help identify high-risk individuals and provide personalized healthcare to patients.

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Customer Retention: Detecting Churners in Telecoms Industry using Data Mining Techniques

Cited by 3 publications

References 9 publications

Twitter Social Media Conversion Topic Trending Analysis Using Latent Dirichlet Allocation Algorithm

Twitter Social Media Conversion Topic Trending Analysis Using Latent Dirichlet Allocation Algorithm

Assessing the effectiveness of OTT services, branded apps, and gamified loyalty giveaways on mobile customer churn in the telecom industry: A machine-learning approach

Diabetic Prediction and Analysing Insulin Levels using Machine Learning

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