@article{ITNYREPOID3695,
          author = {Ani Apriani},
           title = {Fuzzy Soft Set for Rock Igneous Clasification},
       publisher = {IEEE Xplore},
         journal = {2018 International Symposium on Advanced Intelligent Informatics (SAIN)},
        abstract = {Abstract{--}Rock classification is one of the fundamental tasks in geological studies. This process normally requires a human expert to examine a sample the rocks. In this research, we employ machine learning algorithm, called Fuzzy Soft Set Classifier (FSSC) to classify igneous rock which based on their chemical
composition. This algorithm is hybridization of soft set theory and fuzzy for classifying numerical data. The results showed that the Fuzzy Soft Set Classifier is capable of precise classification of igneous rocks and achieved satisfactory result in terms of accuracy, precision and recall, respectively. 
Keywords{--}soft set; fuzzy soft set; classification; igneous rocks;},
             url = {https://repository.itny.ac.id/id/eprint/3695/}
}