Decision Tree: Customer Churn Analysis for a Loyalty Program Using Data Mining Algorithm

<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>

Download Full-text

Analysis of Hepatitis C Virus using Data Mining Algorithm -Apriori, Decision Tree

International Journal on Bioinformatics & Biosciences ◽

10.5121/ijbb.2017.7301 ◽

2017 ◽

Vol 7 (3) ◽

pp. 01-11

Author(s):

Ha Yeong Jeong ◽

Tae Seon Yoon

Keyword(s):

Data Mining ◽

Hepatitis C Virus ◽

Hepatitis C ◽

Decision Tree ◽

Data Mining Algorithm ◽

Mining Algorithm ◽

Using Data

Download Full-text

Penerapan Data Mining Untuk Prediksi Penjualan Wallpaper Menggunakan Algoritma C4.5

10.31227/osf.io/x6svc ◽

2018 ◽

Author(s):

Juna Eska

Keyword(s):

Data Mining ◽

Decision Tree ◽

Added Value ◽

Data Mining Algorithm ◽

Material Quality ◽

Mining Algorithm ◽

C4.5 Algorithm ◽

Using Data ◽

Wall Decoration ◽

Price Algorithm

Wallpaper wallpaper or wallpaper wall is a wall decoration with a variety of motifs and colors. Wallpaper isused to change the appearance of a space to be more beautiful and has added value. Plain house walls tend tomake the occupants of the house feel bored because of the monotonous wall appearance. For that, having theinitiative to design the wall of the house with wallpaper into a bright idea that should be tried. Coloring thewalls of the house with wallpaper can add a beautiful impression on a room, so the room looks more expressive.Various motifs, colors, and wallpaper styles can be selected. Therefore, the seller must be more careful toprovide wallpaper which will be a lot of devotees, so it is necessary to recommend the type of wallpaper typeusing Classification method is done using data mining algorithm C4.5. data required is the best wallpaperbrand data, color, motif, material quality, size, and price. Algorithm C4.5 is a data classification algorithm oftype of decision tree. The decision tree The C4.5 algorithm is constructed with several stages including theselection of attributes as roots, creating branches for each value and dividing instances in branches. Thesestages will be repeated for each branch until all the cases on the branch have the same class. From thecompletion of the decision tree there will be some rules.

Download Full-text

Predicting customer churn in mobile industry using data mining technology

Industrial Management & Data Systems ◽

10.1108/imds-12-2015-0509 ◽

2017 ◽

Vol 117 (1) ◽

pp. 90-109 ◽

Cited By ~ 16

Author(s):

Eui-Bang Lee ◽

Jinwha Kim ◽

Sang-Gun Lee

Keyword(s):

Data Mining ◽

Decision Tree ◽

Online News ◽

Partial Least Square ◽

Churn Prediction ◽

Mining Technology ◽

Content Type ◽

Customer Churn ◽

Mobile Industry ◽

Using Data

Purpose The purpose of this paper is to identify the influence of the frequency of word exposure on online news based on the availability heuristic concept. So that this is different from most churn prediction studies that focus on subscriber data. Design/methodology/approach This study examined the churn prediction through words presented the previous studies and additionally identified words what churn generate using data mining technology in combination with logistic regression, decision tree graphing, neural network models, and a partial least square (PLS) model. Findings This study found prediction rates similar to those delivered by subscriber data-based analyses. In addition, because previous studies do not clearly suggest the effects of the factors, this study uses decision tree graphing and PLS modeling to identify which words deliver positive or negative influences. Originality/value These findings imply an expansion of churn prediction, advertising effect, and various psychological studies. It also proposes concrete ideas to advance the competitive advantage of companies, which not only helps corporate development, but also improves industry-wide efficiency.

Download Full-text