20.500.12556/DKUM-37783 ANALIZA LASTNOSTI USPEŠNIH ŠTUDENTOV S PODATKOVNIM RUDARJENJEM ANALYZING STUDENTS' SUCCESS FACTORS WITH DATA MINING V nalogi poskušamo odkriti povezave med lastnostmi študentov in njihovim študijskim uspehom. Opisan je celoten proces zbiranja ter analize podatkov in relacij, ki vplivajo na študijski uspeh posameznika. Začnemo s kratkimi navodili o sestavi ankete in nadaljujemo s sestavo svoje. Pridobljene podatke najprej analiziramo z uporabo statistike. Uporabljene metode na kratko opišemo in jih nato izvedemo nad zbranimi podatki. Proces izvajanja, ki je opravljen v programu IBM SPSS Statistics, je tudi predstavljen. Nazadnje uporabimo podatke v podatkovnem rudarjenju. V predstavitvi podatkovnega rudarjenja se posebej posvetimo nalogi klasifikacije in njenim tehnikam. V orodju Weka z odločitvenimi drevesi ugotavljamo povezanost med karakteristikami študentov in njihovim študijskim uspehom. In the assignment we try to discover correlations between students’ characteristics and their academic success. We describe the whole process of collecting and analyzing data and relations which impact the students’ success. We start with short instructions on how to build a survey and continuing to build our own. Collected data is first analyzed with statistics. Used methods are shortly described and afterwards executed in a program called IBM SPSS Statistics. Finally the data is used in data mining, presentation of which is mainly focused on the classification task and its techniques. Using Weka we built decision trees to find out if there are any connections between students’ characteristics and their study success. podatkovno rudarjenje statistična analiza SPSS Weka data mining statistical analysis SPSS Weka true true false [M. Kompara] Slovenski jezik Angleški jezik Diplomsko delo/naloga 2012-09-10 18:13:03 2012-11-27 08:12:25 2022-04-24 22:07:11 2021-04-18 03:36:08 2012 0 Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.6(043.2) 16504598 URN:SI:UM:DK:CLQ1X35M UNI_Kompara_Marko_2012.pdf UNI_Kompara_Marko_2012.pdf 1 57752F78B94C4AA1739405B02963DF08 bdf30b106cb5a7b82d938cfa49f37de3d0b469d5c259931bac5575026f3f7d88 5540ce44-7c08-11eb-bb7a-00155d0001ca 20.500.12556/dkum/e2193b31-c860-4e3f-8b12-7cbeb8119dcd https://dk.um.si/Dokument.php?lang=slv&id=50100 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0