prikaz prve stranice dokumenta Segmentacija klijenata s obzirom na korištenje usluge oročenja sredstava u banci s pomoću metoda rudarenja podataka
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master's thesis
Segmentacija klijenata s obzirom na korištenje usluge oročenja sredstava u banci s pomoću metoda rudarenja podataka
2016. urn:nbn:hr:145:036513
Palinkaš, Ivan
Josip Juraj Strossmayer University of Osijek
Faculty of Economics and Business in Osijek
Chair of Quantitative Methods and Informatics

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Palinkaš, I. (2016). Segmentacija klijenata s obzirom na korištenje usluge oročenja sredstava u banci s pomoću metoda rudarenja podataka (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:145:036513

Palinkaš, Ivan. "Segmentacija klijenata s obzirom na korištenje usluge oročenja sredstava u banci s pomoću metoda rudarenja podataka." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek, 2016. https://urn.nsk.hr/urn:nbn:hr:145:036513

Palinkaš, Ivan. "Segmentacija klijenata s obzirom na korištenje usluge oročenja sredstava u banci s pomoću metoda rudarenja podataka." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek, 2016. https://urn.nsk.hr/urn:nbn:hr:145:036513

Palinkaš, I. (2016). 'Segmentacija klijenata s obzirom na korištenje usluge oročenja sredstava u banci s pomoću metoda rudarenja podataka', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek, accessed 15 November 2024, https://urn.nsk.hr/urn:nbn:hr:145:036513

Palinkaš I. Segmentacija klijenata s obzirom na korištenje usluge oročenja sredstava u banci s pomoću metoda rudarenja podataka [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek; 2016 [cited 2024 November 15] Available at: https://urn.nsk.hr/urn:nbn:hr:145:036513

I. Palinkaš, "Segmentacija klijenata s obzirom na korištenje usluge oročenja sredstava u banci s pomoću metoda rudarenja podataka", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek, Osijek, 2016. Available at: https://urn.nsk.hr/urn:nbn:hr:145:036513

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Metadata
TitleSegmentacija klijenata s obzirom na korištenje usluge oročenja sredstava u banci s pomoću metoda rudarenja podataka
Title (english)Segmentation of customers due to the use of the term deposit service in the bank by using data mining methods
AuthorIvan Palinkaš
MentorMarijana Zekić Sušac (mentor)
Committee memberMarijana Zekić Sušac (predsjednik povjerenstva)
Committee memberJosip Mesarić (član povjerenstva)
Committee memberĐula Borozan (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Economics and Business in Osijek
(Chair of Quantitative Methods and Informatics)
Osijek
Defense date and country2016-09-21, Croatia
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Economics
Business Informatics
Abstract
Ovaj rad se bavi upotrebom neuronskih mreža u analizi baze podataka banke kako bi se prepoznali budući korisnici jedne bankarske usluge, dugoročne oročene štednje. Podaci su prikupljeni s pomoću tele marketing kampanje koju je provela banka u razdoblju od 2008. do 2010. godine. Na kraju marketing kampanje, uspješnost pristanka na uslugu oročenja je bila 8% što je za banku nedovoljno učinkovito. U ovom radu će se prikazati kako se pomoću neuronskih mreža može povećati uspješnost marketing kampanja. Neuronske mreže pripadaju u metode rudarenja podataka i koriste se za problem klasifikacije i predviđanja. U sklopu ovog rada, koristeći neuronske mreže kao sredstvo traženja veza među podacima u bazi izgradit će se model za klasifikaciju klijenata u dvije skupine: (1) potencijalni korisnici usluge oročenja sredstava i (2) oni koji će odbiti uslugu oročenja sredstava u toj banci. Takav model može se koristiti za segmentaciju klijenata, a njegova uporaba može dovesti do veće stope odgovara na marketinške kampanje. Testirano je više modela neuronskih mreža promjenom raspodjele uzoraka, aktivacijskih funkcija i funkcija greške, te je na temelju stope točnosti klasifikacije izabran najuspješniji model koji se preporuča za uporabu. Uz prikaz rezultata svih istraživanja, prikazat će se i objasniti matrica konfuzije najbolje mreže i analiza osjetljivosti. Na kraju su dane smjernice za uporabu modela i za daljnja istraživanja.
Abstract (english)
This paper deals with the usage of neural networks in the database analysis in order to identify future banking services users with, long-term deposits. Campaigns have been lead and information has been collected with help of telemarketing in the period from 2008. to 2010. At the end of last marketing campaign, the successful rate of the long-term deposit consent was 8%, which is insufficiently effective for the bank. This paper will show how with neural networks, success of marketing campaigns can be increased. Neural networks are one of methods for data mining and they are used to solve problems of classification and prediction. As part of this work, using neural networks as a means of finding connections between data in the database, model will be built for classification of clients into two groups: (1) potential users of term deposits and (2) those who will refuse term deposits service in the bank. This model can be used for segmentation of clients, and its use can lead to higher rates of responding to a marketing campaign. Models of neural networks where tested by changing sample distribution, activation and error function, and based on the classification accuracy rate, the best neural network is determined for usage. With the presentation of the research results, the best neural network confusion matrix and sensitivity analysis will also be shown and explained. At the end, guidelines are given for the use of the model and for further research.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:145:036513
Study programmeTitle: Business economy; specializations in: Business Informatics
Course: Business Informatics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra ekonomije (magistar/magistra ekonomije)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2016-10-25 15:36:07