IMPLEMENTASI ALGORITMA NAÏVE BAYES UNTUK ANALISIS KLASIFIKASI SURVEI KESEHATAN MENTAL INDUSTRI TEKNOLOGI (STUDI KASUS: OPEN SOURCING MENTAL ILLNESS) - Reza Alfaresy Chaerudin (2022)
Mental health has become a highlight in our society's lives now, and it appears in every side of workplaces, including the technology industry. The consciousness regarding the importance of mental health among workers are still considered low, amd this doesn't preclude the tech industry themselves, which is why Open Source Mental Illness (OSMI), as an organization that is based on mental health works, commences survey to understand regarding the awareness of mental health issues amongst the tech industries' workers. The result of this survey has been released as a dataset, where this dataset then can be analyzed further with data mining using classification method as analysis of awareness regarding mental health based on the survey's data. The classification algorihm chosen for the analysis is Naïve Bayes, where the result of this classification then can be used further in deeper analysis regarding awareness of mental health issues in a form of prediction model. The dataset used for the analysis initially consisted of 1259 data record, where after preprocessing process, the dataset ends with 1254 record data. In this research, an experiment is done with the split of 30% of testing data and 70% of training data, where it is then obtained the accuracy result of 72%. The data mining analysis then continues in form of Python programming language, to achieve a simplistic prediction model which is then implemented in a simplistic website-based prediction system.