1. Implementacija informacijsko varnostne politike in zagotavljanje ozaveščenosti zaposlenih v UKC MariborAlem Jahić, 2025, master's thesis Abstract: Magistrsko delo obravnava zagotavljanje informacijske varnosti v UKC Maribor z namenom zagotavljanja neprekinjenega poslovanja in zmanjšanja možnosti varnostnih incidentov s poudarkom na skrbnem varovanju podatkov o pacientih. Informacijska varnost v zdravstvu sloni predvsem na zaposlenih, saj prav oni vsak dan delajo s podatki pacientov.
Problem zagotavljanja informacijske varnosti v UKC Maribor na eni strani rešujemo s tehničnimi rešitvami, kot so požarnimi zidovi, protivirusna zaščita, posodobljena strojna in programska oprema itd.
Na drugi strani so neozaveščeni uporabniki, ki so lahko vstopna točka za kibernetske napade, zato je ozaveščanje uporabnikov eden ključnih dejavnikov pri zagotavljanju informacijske varnosti.
Za raziskavo smo pripravili anketni vprašalnik, ki je bil anketirancem deljen s pomočjo orodja za spletno anketiranje 1KA. Statistično obdelavo podatkov smo izvedli s pomočjo programskih paketov Excel in SPSS. Druga faza raziskave je obsegala simulacijo napada na osnovi socialnega inženiringa, ki je bil izveden z uporabo namensko pripravljenih USB ključkov.
Poglavitni rezultati raziskave kažejo, da je na podlagi samoocene poznavanja obstoječe varnostne politike in ozaveščenosti na področju informacijske varnosti zaposlenih v UKC Maribor stanje sprejemljivo. Nadaljnji rezultati anketne raziskave in simulacije napada z USB ključki pa kažejo, da je stanje ravno nasprotno. Na podlagi teh rezultatov smo pripravili portal za ozaveščanje o informacijski/kibernetski varnosti, s katerim bomo izboljšali informacijsko ozaveščenost.
Keywords: informacijska varnost, varnostna politika, zdravstvo, socialni inženiring
Published in DKUM: 08.04.2025; Views: 0; Downloads: 14
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2. Factors influencing mathematics achievement of university students of social sciencesAlenka Brezavšček, Janja Jerebic, Gregor Rus, Anja Žnidaršič, 2020, original scientific article Abstract: The paper aims to investigate the main factors influencing the mathematics achievement of social sciences university students in Slovenia. A conceptual model was derived where three categories of variables were taken into account: attitude towards mathematics and math anxiety, engagement in learning activities, and attitude towards involving technology in learning mathematics. Data were collected for seven consecutive academic years and analysed using Structural Equation Modelling (SEM). The results showed a very high coefficient of determination for mathematics achievement (0.801), indicating that variables “Perceived Level of Math Anxiety”, “Self-Engagement in Mathematics Course at University”, and “Perceived Usefulness of Technology in Learning Mathematics”, together, explain 80.1% of the total variance. Based on our findings, we can conclude that teaching in secondary school is a crucial determinant for success in mathematics at university. It is essential to identify the best methods for secondary school math teachers which will help them give future students better entry-level knowledge for universities. These methods will, hopefully, also improve the level of mathematics self-confidence, as well as lower the level of math anxiety, which all considerably affect the performance of students in university mathematics.
Keywords: mathematical education, good practices in mathematics, mathematics achievement, education, influencing factors, university, social sciences, structural equation modelling (SEM)
Published in DKUM: 14.01.2025; Views: 0; Downloads: 6
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3. Comparative analysis of human and artificial intelligence planning in production processesMatjaž Roblek, Tomaž Kern, Eva Krhač Andrašec, Alenka Brezavšček, 2024, original scientific article Abstract: Artificial intelligence (AI) has found applications in enterprises′ production planning
processes. However, a critical question remains: could AI replace human planners? We conducted a
comparative analysis to evaluate the main task of planners in an intermittent process: planning the
duration of production orders. Specifically, we analysed the results of a human planner using master
data and those of an AI algorithm compared to the actual realisation. The case study was conducted
in a large production company using a sample of production products and machines. We were able
to confirm two of the three research questions (RQ1 and RQ3), while the results of the third question
(RQ2) did not meet our expectations. The AI algorithms demonstrated significant improvement with
each iteration. Despite this progress, it is still difficult to determine the exact threshold at which AI
outperforms human planners due to the unpredictability of unexpected events. Even though AI
significantly improves prediction accuracy, the inherent variability and incomplete input data pose a
major challenge. As progress is made, robust data collection and management strategies need to be
integrated to bridge the gap between the potential of AI and its practical application, fostering the
symbiosis between human expertise and AI capabilities in production planning.
Keywords: artificial intelligence, machine learning, production processes, production planning, production scheduling
Published in DKUM: 04.12.2024; Views: 0; Downloads: 18
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4. A bibliometric network analysis of green information technology and green information systems researchAnja Žnidaršič, Daria Maltseva, Alenka Brezavšček, Matjaž Maletič, Alenka Baggia, 2021, original scientific article Abstract: Background: In recent years, the concepts of Green Information Technology and Green Information Systems (Green IT/IS) have attracted the attention of many researchers. Several environmental and sustainability studies have suggested that smart usage of Green IT/IS is one of the most important enablers for sustainable development in organizations and plays an essential role in greening the planet.
Objectives: This paper aims to examine the development of the Green IT/IS field based on the published works. The focus is on analysing the keywords of related papers obtained from the Web of Science database.
Methods/Approach: Based on the twomode network of papers and keywords, the analysis of co-occurrence of keywords is provided. The most frequent keywords discovered by the temporal network analysis are presented from the perspective of the most prominent journals.
Results: The main pillars of knowledge in Green IT/IS research are highlighted, and a chronological map of the field is provided.
Conclusions: Green IT/IS's studied field shows constant growth in the last decades, and the results indicate the trends of future development in the field. The paper is one of the first studies that apply the bibliographic network analysis approach to the field of Green IT/IS.
Keywords: green information system, green information technology, bibliographic networks
Published in DKUM: 14.11.2024; Views: 0; Downloads: 10
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5. Izsiljevalski virusi kot pomembna kibernetska grožnja za organizacijeJernej Kogovšek, 2024, undergraduate thesis Abstract: Organizacije so pod vedno večjim pritiskom napadov izsiljevalskih virusov. V napadih
napadalci zašifrirajo podatke in sisteme organizacije. Uspešni napadi lahko ohromijo
poslovanje organizacije za več tednov, poleg tega lahko povzročijo nepopravljivo škodo
na informacijskih sistemih organizacij. Napadalci so za svoje napade finančno motivirani
in posledično skoraj vedno iščejo odkupnino. Razmahnil se je poslovni model izsiljevalskih
virusov kot storitve, kjer razvijalci viruse prodajajo zainteresiranim posameznikom in
manjšim hekerskim grupam. Posledično število napadov in njihova škoda raste iz leta v
leto.
V diplomski nalogi preučujemo izsiljevalske viruse, njihovo delovanje, posledice in
ekonomični model hekerskih skupin. Raziskujemo tudi, kako napadalci pridobijo dostope
do sistemov. S pomočjo literature in analize primerov ugotavljamo, kaj je šlo narobe in
prav v odmevnih incidentih. S tem želimo ugotoviti in priporočati dobre prakse
organizacijam. Z uporabo orodja POWER BI Desktop analiziramo podatkovno bazo
podjetja Comparitech, kjer so beležili potrjene napade z izsiljevalskimi virusi od leta 2018
naprej do prvega tedna avgusta 2024. Cilj naloge je ugotoviti, kako naj se organizacije
pripravijo in reagirajo na grožnje izsiljevalskih virusov.
Keywords: izsiljevalski virusi, socialni inženiring, varnostni incidenti, napadi, organizacije
Published in DKUM: 04.10.2024; Views: 0; Downloads: 29
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6. Analiza prehodnosti na študijskih programih prve stopnje z uporabo markovskih verigRok Stojanovič, 2024, undergraduate thesis Abstract: Prehodnost študentov med letniki, trajanje študija, delež študentov, ki uspešno zaključi študij, delež takih, ki obupa ipd., so kazalniki, ki jih potrebuje vsaka izobraževalna ustanova in so osnova za uspešno upravljanje študijskih programov kakor tudi za njihov nadaljnji razvoj.
Za določitev relevantnih kazalnikov študijskega programa smo uporabili markovske verige. Naš cilj je bil izdelati stohastični model, ki bi ga lahko uporabili za analizo uspešnosti študentov in njihovega akademskega napredka v slovenskem visokošolskem okolju.
Na podlagi teorije markovskih verig smo razvili matematični model, ki omogoča vrednotenje in spremljanje deleža študentov, ki napredujejo skozi različne letnike študijskega programa, časa, ki ga študent preživi v posamezni fazi študija, deleža študentov, ki uspešno diplomirajo, kakor tudi deleža študentov, ki se izpišejo iz študijskega programa.
Model smo uporabili na primeru visokošolskih in univerzitetnih študijskih programov, ki se izvajajo na Fakulteti za organizacijske vede Univerze v Mariboru. Vhodne podatke za matematični model smo črpali iz študentskih evidenc. Podatke smo obdelali s programom Microsoft Excel, kjer smo opravili tudi vse izračune. Rezultate smo ustrezno analizirali in interpretirali. Prav tako smo podali smernice za integracijo modela v informacijski sistem AIPS Univerze v Mariboru.
Keywords: visokošolsko izobraževanje, prehodnost študentov, sistematična analiza, markovske verige, informacijski sistem.
Published in DKUM: 04.10.2024; Views: 0; Downloads: 21
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7. Has the COVID-19 pandemic affected mathematics achievement? : a case study of university students in social sciencesAnja Žnidaršič, Alenka Brezavšček, Gregor Rus, Janja Jerebic, 2022, original scientific article Abstract: This study examines the effects of COVID-19-related measures on the mathematics achievement of university students in social sciences in Slovenia. Our particular concern was to compare two student populations (pre-pandemic and pandemic) in terms of factors affecting student performance in mathematics courses. Data were collected over nine consecutive academic years (from 2013–2014 to 2020–2021) and analyzed using two-stage structural equation modelling (SEM). The analyses confirmed that the conceptual model developed before the pandemic was applicable during the pandemic period. For both populations (pre-pandemic and pandemic), mathematics confidence, perceived level of math anxiety, background knowledge from secondary school, and self-engagement in mathematics courses at university were confirmed as factors influencing mathematics achievement. Moreover, both populations perceived the effects of the factors in the same way, and the magnitude of the effects is comparable. The rather high values of determination coefficient for mathematics achievement (greater than 0.66 for both student populations) indicate that the variables “Perceived Level of Math Anxiety” and “Self-Engagement in Mathematics Course at University” together explain a significant proportion of the total variance before and during the pandemic. Consequently, the results of our case study indicated that pandemic measures did not have a significant impact on our students’ mathematics achievement. Although a more in-depth study of a broader sample of academic courses would be needed to confirm our findings, our experience indicates that mathematics courses at the tertiary level of education can be successfully delivered online.
Keywords: COVID-19, mathematics achievement, university students, social sciences, pre-pandemic population, pandemic population, comparison, multi-group structural equation modeling (MG-SEM)
Published in DKUM: 09.07.2024; Views: 112; Downloads: 11
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8. Učinkovitost algoritmov umetne inteligence pri mikroplaniranju proizvodnjeVukašin Radisavljević, 2024, undergraduate thesis Abstract: Diplomsko delo se osredotoča na analizo podatkov v kontekstu uporabe umetne inteligence pri mikroplaniranju proizvodnje. Na podlagi analize pridobljenih podatkov smo identificirali zakonitosti in trende, ki se nanašajo na učinkovitost sistema za napredno planiranje in razporejanje proizvodnje z umetno inteligenco Qlector LEAP. Opažamo korelacije med relativno napako planiranja s Qlector LEAP-om in številom poskusov planiranja, pri čemer opažamo določene trende za določene izdelke. Primerjamo učinek planiranja Qlector LEAP-a tudi z učinkom planiranja po normativih. Razprava se osredotoča tudi na tehnološke, kadrovske in organizacijske dejavnike ter priporoča organizacijske ukrepe za izboljšanje učinkovitosti planiranja z LEAP-om. Kljub izzivom pri dokazovanju hipotez je razprava pokazala možnosti za nadaljnje raziskave, ki vključujejo kvantifikacijo zanesljivosti planiranja z LEAP-om in preučevanje drugih modulov Qlector LEAP-a. Skupaj s postavljenimi organizacijskimi ukrepi diplomsko delo zagotavlja osnovo za nadaljnje raziskave na tem področju.
Keywords: umetna inteligenca, strojno učenje, mikroplaniranje proizvodnje, sistem za napredno planiranje in razporejanje proizvodnje, merjenje učinka
Published in DKUM: 13.06.2024; Views: 189; Downloads: 46
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10. Ozaveščenost zaposlenih o napadih z izvabljanjem geselTil Schweiger, 2024, undergraduate thesis Abstract: V diplomskem delu smo predstavili najpogostejše kibernetske napade, motive, metode in tehnike, s katerimi izvedejo napad na informacijski sistem. Na kratko smo predstavili tudi finančno organizacijo, v kateri smo izvedli raziskavo. Raziskava je bila izvedena v dveh fazah. Najprej smo izvedli simulacijo napada z izvabljanjem, da bi ugotovili, koliko zaposlenih bo lažnemu napadu nasedlo. V drugi fazi pa smo izvedli anketo, katere namen je bil ugotoviti, kako učinkoviti so zaposleni pri prepoznavanju lažnih in avtentičnih elektronskih sporočil. Rezultati so pokazali, da trenutni ukrepi v organizaciji ne zadoščajo, saj preveliko število zaposlenih še vedno ne prepozna napadov. Za izboljšanje stanja smo organizaciji predlagali nekaj ukrepov, ki bodo pripomogli k doseganju višje stopnje ozaveščenosti zaposlenih.
Keywords: kibernetska varnost, socialni inženiring, napad z izvabljanjem, finančna organizacija
Published in DKUM: 28.05.2024; Views: 216; Downloads: 27
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