Utilization of Prediction Data for Prospective Decision Customers Insurance Using the Classification Method of C.45 and Naive Bayes Algorithms

Dwiasnati, Saruni; Devianto, Yudo

doi:10.1088/1742-6596/1179/1/012023

Cited by 7 publications

(8 citation statements)

References 1 publication

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“…This study uses variables such as price, quality, number of products, place, and service. The results of this study resulted in an accuracy of the Naive Bayes algorithm of 90.11% and the C4.5 algorithm of 75.27% [5] .…”

Section: Issn : 1978-8282 Online Issn: 2655-4275mentioning

confidence: 80%

Performance Analysis of Tree-Based Algorithms in Predicting Employee Attrition

Pradana,

Rangga Pinastawa,

Maulana

et al. 2023

ccitj

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Based on data throughout 2022, there have been many reductions in employees both globally and Indonesia. The reduction was made due to adjustments with developments to keep the business afloat in increasingly fierce competition. However, reducing the number of employees is not an easy decision to make. This decision can have an impact on many aspects of the development and course of a business or company. To make a decision especially related to the aspect of termination of employment, it is necessary to consider carefully and thoroughly. Assessment and decision-making cannot be based on just one aspect, other aspects need to be seen to be taken into consideration. Additional aspects that can be selected to strengthen decision-making can be taken from the data. Data will not have any value without processing it with various approaches, one of which is the prediction process. Starting from the data, the prediction results will be more appropriate to make a decision. This study made a comparison of 3 decision tree algorithms, and produced a comparison of the three methods in terms of accuracy. The results of this study are the best accuracy for each algorithm C.45 = 83.44; Random Forests = 85.85; LMT = 88.29 with a linear precision value, and the best algorithm model with the highest accuracy is the Logistic Model Tree (LMT) algorithm.

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Section: Issn : 1978-8282 Online Issn: 2655-4275mentioning

confidence: 80%

Performance Analysis of Tree-Based Algorithms in Predicting Employee Attrition

Pradana,

Rangga Pinastawa,

Maulana

et al. 2023

ccitj

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“…Sebagai contoh, layanan untuk penjualan film, fitur ini dapat digunakan untuk memberikan rekomendasi yang sesuai dengan peringkat pengguna dan mendorong peningkatan penjualan. Fitur ini sangat berguna untuk menarik perhatian pengguna dan meningkatkan kualitas layanan dari aplikasi tersebut [2], [14], [15].…”

Section: Pendahuluanunclassified

Prediksi Rating Film Menggunakan Bayesian Regressor dan Gradient Boosting Regressor

Salamah¹

2022

JSAI

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Salah satu fitur yang cukup banyak dikembangkan untuk aplikasi adalah fiturpenilaian pengguna. Informasi tentang peringkat pengguna ini dapatdigunakan untuk memberikan rekomendasi terbaik tentang hal menarik bagipengguna lainnya. Sebagai contoh, layanan untuk penjualan film, fitur inidapat digunakan untuk memberikan rekomendasi yang sesuai denganperingkat pengguna dan mendorong peningkatan penjualan. Adapun tahapanpenelitian adalah Data Preprocessing, Feature Engineering, Modelling danEvaluation. Penelitian ini menggunakan metode yaitu Bayesian Regressor danGradient Boosting Regressor untuk memprediksi movie rating. Penelitian inimenggunakan TMDB 5000 Movie Dataset yang terdiri dari kurang lebih 4800data. Sebagai hasilnya, Gradient Boosting Regressor memiliki hasil yang lebihbaik dibandingkan Bayesian Ridge Regressor. Gradient Boosting Regressormemiliki nilai R^2 score sebesar 0.843.

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“…Data mining is the process of mining data to generate new knowledge from very large data [5]. In data mining, there is a classification process, including classifying the promotion of private schools in order to have good branding [6].…”

Section: Introductionmentioning

confidence: 99%

“…The C45 algorithm which is one of the algorithms in machine learning can be used to diagnose various types of diseases in the medical world, supported by other algorithms in machine learning [10][11][12]. Besides the C45 algorithm can also be combined with the naïve Bayes algorithm to analyze a social, academic problem, [5,13,14]. Many researchers combine and compare the c45 algorithm with other algorithms such as the comparative analysis of Naïve Bayes, K Nearest Neighbor and C.45 methods in weather forecasting that provide decision support [15].…”

Section: Introductionmentioning

confidence: 99%

Analysis of sales levels of pharmaceutical products by using data mining algorithm C45

Sovia

Muhammad

Arlis

et al. 2021

IJEECS

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<p>This research was conducted to analyze the level of sales of pharmaceutical products at a Pharmacy. This is done to find out the types of products that have high and low sales levels. This study uses the C45 Data Mining Algorithm concept that will produce a conclusion on the prediction of sales of pharmaceutical products through data processing obtained from sales transactions at pharmacies. This C45 algorithm will form a decision tree that provides users with knowledge about products that are in great demand by consumers based on sales data and predetermined variables. The final result of the C45 algorithm produces a number of rules that can identify the inheritance of a type of medicinal product. C45 algorithm is able to produce 20 types of categories that will be labeled goals based on the number of pharmaceutical products, since it can be concluded that C45 successfully defines 55% of the existing objective categories.</p>

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Utilization of Prediction Data for Prospective Decision Customers Insurance Using the Classification Method of C.45 and Naive Bayes Algorithms

Cited by 7 publications

References 1 publication

Performance Analysis of Tree-Based Algorithms in Predicting Employee Attrition

Performance Analysis of Tree-Based Algorithms in Predicting Employee Attrition

Prediksi Rating Film Menggunakan Bayesian Regressor dan Gradient Boosting Regressor

Analysis of sales levels of pharmaceutical products by using data mining algorithm C45

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