Izrada modela predviđanja fluktuacija zaposlenika korištenjem prediktivne analitike

master's thesis

• Title (english): Model for predicting employee fluctuations using predictive analytics
• Author: Luka Kosec
• Mentor: Mirjana Pejić Bach (mentor)
• Committee member: Mirjana Pejić Bach (predsjednik povjerenstva)
• Committee member: Ivan Strugar (član povjerenstva)
• Committee member: Jovana Zoroja (član povjerenstva)
• Granter: University of Zagreb; Faculty of Economics and Business; (Department of Informatics); Zagreb
• Defense date and country: 2020-09-30, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Economics; Business Informatics

Abstract

Ovaj rad bavi se otkrivanjem znanja iz baza podataka na području ljudskih resursa. Globalna digitalizacija utjecala je na iznimno povećanje zapisa podataka te uzrokovala nastajanje novih znanosti i tehnika na području podatkovne znanosti. Razvijaju se razni algoritmi, tehnike i alati prediktivne analitike uz pomoć kojih se poboljšava poslovna strategija u tvrtkama i reduciraju troškovi na svim poljima poslovanja. Otkrivanje znanja u bazama podataka je evoluirajući koncept koji se bavi istraživačkom analizom podataka. Ono ima za zadatak razviti model razumijevanja podataka, izvući znanje iz podataka, kreirati određenje radnje za daljnje postupanje i stvoriti nove podatke za nove modele. Analitika u području ljudskih resursa danas odstupa od tradicionalnih i klasičnih metoda zapošljavanja i vođenja ljudskih resursa te se obraća modernim tehnologijama prediktivne analitike temeljene na konceptu podatkovne znanosti, Velikih podataka, Strojnog učenja te Umjetne inteligencije.

Abstract (english)

This thesis deals with the discovery of knowledge from databases in the field of human resources. Global digitization has led to an extraordinary increase in data records and caused the emergence of new sciences and techniques in the field of data science. Various algorithms, techniques and tools of predictive analytics are being developed with the help of which business strategy in companies is improved and costs are reduced in all fields of business. Knowledge discovery in databases is an evolving concept that deals with research data analysis, which aims to develop a model of understanding data, extract knowledge from data, create action definitions for further action and create new data for new models. Analytics in the field of human resources today deviates from traditional and classical methods of hiring and managing human resources and turns to modern technologies of predictive analytics based on the concept of data science, Big Data, Machine Learning and Artificial Intelligence.

• Keywords: digitalizacija; podatkovna znanost; otkrivanje znanja u bazama podataka; umjetna inteligencija; prediktivna analitika
• Keywords (english): digitalization; data science; knowledge discovery in databases; artificial intelligence; predictive analytics
• Language: croatian
• URN:NBN: urn:nbn:hr:148:540949
• Study programme: Title: Business Economics; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra ekonomije (magistar/magistra ekonomije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Access restricted to students and staff of home institution
• Created on: 2020-10-01 00:18:24