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NFFFFFFFFFFFFFFFFFFFFF FFFFFFFFFFFFFFFFFFFFFF FFFFFF F Güldiyar ÇETİN 100303038 Özgür ÖZERTEN 100303020 Furkan YALÇIN 1

NFFFFFFFFFFFFFFFFFFFFFFFFFF FFFFFFFFFFFFFFFFFFFFFFF F G ü ldiyar Ç ETİN 100303038 Ö zg ü r Ö ZERTEN 100303020 Furkan YAL Ç IN 100303001

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Page 1: NFFFFFFFFFFFFFFFFFFFFFFFFFF FFFFFFFFFFFFFFFFFFFFFFF F G ü ldiyar Ç ETİN 100303038 Ö zg ü r Ö ZERTEN 100303020 Furkan YAL Ç IN 100303001

NFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF

Güldiyar ÇETİN 100303038

Özgür ÖZERTEN 100303020

Furkan YALÇIN 100303001

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AYTEMİZ Organization Aytemiz extending the 1960 Group of

Companies is one of the last half-century period of high primary success rate of community. Continue the Group's 50 years of continuous development of our line, energy and industrial sectors have a significant weight.

Chemical and manufacturing industries, Aytemiz Group of Companies are the other key areas of work. Group in recent years, entered the electricity generation business from renewable sources; has started many projects, especially in the field of hydroelectric power plants.

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Goal Identification

A data analysis was collected weekly from the company and then main problem was determined.

Main problem: Aytemiz find less the amount of

fuel taken from the company by the number of customers per week.

Questionnaire study was conducted to find the cause of this main problem

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Creating a target data setPurpose of data mining is

selected only related problem's data and that to the analysis.

Therefore, only the data were determined to be a solution to the problem in database.

Thus, the target data set was created.

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Let's look briefly some determinants of survey questions.

The survey occurs 15 questions. These questions to determine the target data sets are listed as follows:

Which do you prefer the petrol station to get petrol or LPG?

How much do you get petrol or lpg per week?

How much do you spend the average of fuel cost per week?

Which do you prefer payment options?

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Data Preprocessing

If firm have missing data what will firm do? Therefore, the strategies decided for handling missing data fields in this section.

This strategies are;Aytemiz to customers who prefer the

company was offered the opportunity to register for free card.

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The purpose of this application are listed as follows:

The host computer to be automatically backed up in the company of customer information.

To classify customers (ex: which customer are loyal?)

To determine the intensity intervals during the day. Thus, the number of employees is determined in petrol.

To determine the number of the customer to benefit from promotions

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Data Mining

Process of semi-automatically analyzing large database to find patterns that are:

Valid: hold on new data with some certainty.

According to the Aytemiz company fuel averaging (weekly):78,83 TL. (valid data can see in excel)

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Novel: Non-obvious to the system.As a result of the Aytemiz Company

applied discount promotion between 12pm-7am; a price of fuel decreased 4.30 TL to 3.99 TL. (novel data can see in excel)

According to the Aytemiz Company the average of salary given to the fuel: 95.58 TL (weekly)

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ClassificationWe have classified our customers

as a result of data mining.

Most of people start to work life average of 25 years old. From this age, needs increased for car. As a result, our model was accepted as the lower limit 25 years old.

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Classification: Decision Trees

AGE < 25

Spend < 100 TL Spend < 100 TL

BAD GOOD BAD GOOD

NOYES

YES NO YES NO

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We can see data about status according to the good or risky chart in excel.

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ClusteringCluster is a group of objects that

belong to the same class.The most obvious differences

between the clustering and classification are ;

In the classification limits were determined with certainty.

The main advantage of clustering over classification is that, it is adaptable to changes.

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Rule: if weekly income > 100 TL then good else risky

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We can see data about status according to the clustering chart in excel.

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ASSOCIATIONAssociated with fuel oil and

service for increase company’s revenue.

Now, briefly talk about from this strategies;

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1) Vehicle interior washing. ( who buy fuel oil over 50 TL, vehicle interior washing 5 TL )

2) Vehicle exterior washing. ( who buy fuel oil over 50 TL, vehicle exterior washing 3 TL )

3) Fuel oil and engine oil.

4) Fuel oil and cleaning cloth.

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Also “support “and “confidance” level is added to this associations.

Associations: (fuel oil, interior washing, exterior washing)

Support: 0.3

It means 30% of all customers buy fuel oil, interior washing or exterior washing.

Confidance for ( fuel oil ) (exterior washing, interior washing) is 80%.

It means 80% of the customers who buy fuel oil also, buy interior or exterior washing service.

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EstimationAytemiz company, before don’t making

fuel oil discount, according to the number of incoming customer sold fuel oil was less than normally. When collaborative studies done for data mining at Aytemiz company, what is happen of problem that It is understood. Therefore, it is necessary to improve have been made at firm. According to made improvements result of 13.44% was growth in revenues at Aytemiz Company.

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