Analysis of identifying mushroom species using RapidMiner / Fatnin Hanun Nor Sarizan ... [et al.].

• Main Authors: Nor Sarizan, Fatnin Hanun (Author), Mustapha, Muhammad Firdaus (Author), Kairan, Omar (Author), Mohd Bakhary, Nurulain Nabilah (Author), Azmira, Nurin Hannani (Author), Ab Hamid, Siti Haslini (Author)
• Format: Book
• Published: Unit Penerbitan UiTM Kelantan, 2021-12.
• Subjects: Article; PeerReviewed
• Online Access: Link Metadata
• Notes: https://ir.uitm.edu.my/id/eprint/54427/1/54427.pdf
• Keywords: Study and teaching. Research; Statistical data; SB Plant culture

Identify analysis basically consists of defining the characteristics and categorizing the class of dataset. This study helps in improving the information of mushroom characteristics by removing the unnecessary information and identify the species of mushroom; edible or poisonous. The process to identify mushroom species data is started by using Tableau to visualize the data. The data is prepared first before undergoing the process of modelling using decision tree as the descriptive analysis. Testing the model and cross validation are applied in this process to get the predictive analysis of mushroom species data. Then, the result is gathered by checking the accuracy of the performance of the data. Overall process is done using RapidMiner in order to get an accurate performance of the data. The process of visualization and modelling is needed to analyse the data and get an accurate performance of the result. Therefore, the mushroom species will be easily classified and categorized based on the characteristics either it is edible or poisonous. The result of the proposed model achieved 99.81% accuracy for predicting the species of the mushrooms; edible or poisonous.