METODE ALGORITMA C4.5 DAN NAÏVE BAYES UNTUK KLASIFIKASI TINGKAT KESEJAHTERAAN KESEHATAN MASYARAKAT PEKANBARU

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dc.contributor.authorAnggraini, Mila
dc.contributor.supervisorAdnan, Arisman
dc.date.accessioned2021-12-27T07:07:53Z
dc.date.available2021-12-27T07:07:53Z
dc.date.issued2021-06
dc.description.abstractThe level of public health welfare in a country can determine the quality and circumstances of the country. The purpose of this study is to classify the level of public health welfare of Pekanbaru City in 2019. The study used C4.5 and Naïve Bayes algorithms with k-fold cross validation to predict the accuracy of classification and performance evaluation measure as evaluation of both models. Performance evaluation measure results with k-fold cross validation show that models with Naïve Bayes have better classification results than C4.5 algorithm models. This is because Naïve Bayes' accuracy, precision, sensitivity and specificity are greater than the C4.5 algorithm by 100%. This is also because Naïve Bayes obtained the result from the probability value of each attribute being free of each other.en_US
dc.description.sponsorshipProgram Studi S1 Statistika Jurusan Matematika Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Riauen_US
dc.identifier.otherwahyu sari yeni
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/10358
dc.language.isoenen_US
dc.publisherperpustakaan URen_US
dc.subjectalgorithm, Naïve Bayesen_US
dc.subjectk-fold cross validationen_US
dc.subjectperformance evaluation measureen_US
dc.subjecthealth wellbeing levelen_US
dc.titleMETODE ALGORITMA C4.5 DAN NAÏVE BAYES UNTUK KLASIFIKASI TINGKAT KESEJAHTERAAN KESEHATAN MASYARAKAT PEKANBARUen_US
dc.typeArticleen_US

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