Abstract
This research discussed our experienced on building a machine learning model on the human aspect of information security awareness. The model was built through a classification and clustering approach using a broad outline process including importing data, handling incomplete data, compiling datasets, feature scaling, building models, and evaluating models. The dataset was arranged based on the results of a questionnaire referred to as the the Human Aspects of Information Security Questionnaire (HAIS-Q) to Indonesian society. The results of the classification model were evaluated by several methods, including k-fold Cross Validation analysis, Confusion Matrix, Receiver Operating Characteristics, and score calculation for each model. One of the algorithms in the classification used is the Support Vector Machine that has an accuracy performance of 99.7% and an error rate of 0.3%. One of the algorithms in clustering is the DBSCAN which has an adjusted rand index value of always close to 0.
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References
- Autori zadržavaju autorska prava i pružaju časopisu pravo prvog objavljivanja rada i licenciraju ga Creative Commons licencom koja omogućava drugima da dele rad uz uslov navođenja autorstva i izvornog objavljivanja u ovom časopisu.
- Autori mogu izraditi zasebne, ugovorne aranžmane za neekskluzivnu distribuciju rada objavljenog u časopisu (npr. postavljanje u institucionalni repozitorijum ili objavljivanje u knjizi), uz navođenje da je rad izvorno objavljen u ovom časopisu.
- Autorima je dozvoljeno i podstiču se da postave objavljeni rad onlajn (npr. u institucionalnom repozitorijumu ili na svojim internet stranicama) pre i tokom postupka prijave priloga, s obzirom da takav postupak može voditi produktivnoj razmeni ideja i ranijoj i većoj citiranosti objavljenog rada (up. Efekat otvorenog pristupa).