Chemical compounds identification of Liquid Chromatography-Mass Spectrometry data is challenging, especially anticancer compound identification from the Rodent Tuber sample. This paper proposed a novel model for anticancer compound identification of a sample of Liquid Chromatography-Mass Spectrometry Rodent Tuber data. Data sampling was done by linear systematic sampling. The model begins with data labeling which was giving a name to the compound followed by data labeling of the status

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... r compound or not utilizing webscrapping technique. After the data was labeled, the anticancer compound was identified from the data. This model was successfully identifying the most dominant anticancer compounds contained in the sample of Liquid Chromatography-Mass Spectrometry Rodent Tuber data.