A genetic algorithm approach for predicting ribonucleic acid sequencing data classification using KNN and decision tree

Arowolo, Micheal Olaolu; Adebiyi, Marion O.; Adebiyi, Ayodele Ariyo

doi:10.12928/telkomnika.v19i1.16381

Cited by 15 publications

(6 citation statements)

References 15 publications

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“…The Decision Tree method is a technique used in data mining, machine learning, and data analysis to make decisions based on a tree structure that describes the consequences of various decisions and conditions (Somantri & Dairoh, 2019) (Arowolo, Adebiyi, Ariyo, & Okesola, 2021). Decision trees are a very intuitive algorithm and are often used because of their ability to make decisions that are easy to interpret (Alsaadi, Khlebus, & Alabaichi, 2022).…”

Section: Metode Decision Treementioning

confidence: 99%

Analysis of the Level of Public Satisfaction on the Tiktok Application as an E-Commerce

Irmayani,

Sinaga,

Masrizal

2023

SinkrOn

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Online shopping has become one of the alternatives used by society today. This happens because doing online shopping saves a lot of time. There are many online shops in Indonesia and are used by many people, such as Shopee, Lazada and Tokopedia. But now there is an application that initially only acted as a social media platform, but now also doubles as an E-commerce application, namely TikTok. TikTok has now become an E-commerce application. The prices given are also very cheap and there are lots of promotions given to customers. But there are still some people who don't want to shop online on TikTok on the grounds that the goods are not good. So from these 2 things, research needs to be made to determine the level of public satisfaction with the TikTok application as an E-commerce. The aim of this research is to see how many people are satisfied shopping on TikTok. This research was carried out using a classification model in data mining using the K-Nearest Neighbor (kNN) method and the Decision Tree method. The classification results obtained were 119 community data (for representation of 96.74%) and for people who were dissatisfied with the TikTok application as an E-commerce it was 4 community data (for representation of 3.25%). These results provide the conclusion that many people are satisfied shopping on the TikTok application as E-commerce

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Section: Metode Decision Treementioning

confidence: 99%

Analysis of the Level of Public Satisfaction on the Tiktok Application as an E-Commerce

Irmayani,

Sinaga,

Masrizal

2023

SinkrOn

View full text Add to dashboard Cite

show abstract

“…In this study, modifications of analytical data have been implemented in MATLAB data mining tool [32] [33]. In order to find a definitive decision, effective functional set-up and use of study variables and effective performance metrics are important.…”

Section: Evaluation Criteria and Experimantal Setupmentioning

confidence: 99%

Customer Churn Prediction in Telecommunication Industry Using Classification and Regression Trees and Artificial Neural Network Algorithms

Abdulsalam

Arowolo

Saheed

et al. 2022

IJEEI

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Customer churn is a serious problem, which is a critical issue encountered by large businesses and organizations. Due to the direct impact on the company's revenues, particularly in sectors such as the telecommunications as well as the banking, companies are working to promote ways to identify the churn of prospective consumers. Hence it is vital to investigate issues that influence customer churn to yield appropriate measures to diminish churn. The major objective of this work is to advance a model of churn prediction that helps telecom operatives to envisage clients that are most probable to be subjected to churn. The experimental approach for this study uses the machine learning procedures on the telecom churn dataset, using an improved Relief-F feature selection algorithm to pick related features from the huge dataset. To quantify the model's performance, the result of classification uses CART and ANN, the accuracy shows that ANN has a high predictive capacity of 93.88% compared to the 91.60% CART classifier.

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“…In this study, the MATLAB data mining tool has been used to change analytical data [32,33]. To find a clear answer, it's important to have a good functional setup, use study variables, and have good performance metrics.…”

Section: Evaluation Criteria and Experimental Setupmentioning

confidence: 99%

A Churn Prediction System for Telecommunication Company Using Random Forest and Convolution Neural Network Algorithms

Abdulsalam

Ajao

Balogun

et al. 2022

EAI Endorsed Trans Mob Com Appl

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INTRODUCTION: Customer churn is a severe problem of migrating from one service provider to another. Due to the direct influence on the company's sales, companies are attempting to promote strategies to identify the churn of prospective consumers. Hence it is necessary to examine issues that influence customer churn to yield effective solutions to minimize churn. OBJECTIVES: The major purpose of this work is to create a model of churn prediction that assists telecom operatives to envisage clients that are more probably to be prone to churn. METHODS: The experimental strategy for this study leverages the machine learning techniques on the telecom churn dataset, employing an improved Relief-F feature selection algorithm to extract related features from the enormous dataset. RESULTS: The result demonstrates that CNN has a high prediction capability of 94 percent compared to the 91 percent Random Forest classifier. CONCLUSION: The results are of enormous relevance to the telecommunication business in improving churners and loyal clients.

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A genetic algorithm approach for predicting ribonucleic acid sequencing data classification using KNN and decision tree

Cited by 15 publications

References 15 publications

Analysis of the Level of Public Satisfaction on the Tiktok Application as an E-Commerce

Analysis of the Level of Public Satisfaction on the Tiktok Application as an E-Commerce

Customer Churn Prediction in Telecommunication Industry Using Classification and Regression Trees and Artificial Neural Network Algorithms

A Churn Prediction System for Telecommunication Company Using Random Forest and Convolution Neural Network Algorithms

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