CLASSIFICATION OF FUNGUS TYPES USING THE K-NEAREST NEIGHBOUR ALGORITHM

  • Hanna Willa Dhany Universitas Pembangunan Pancabudi
Keywords: K-Nearest Neighbor, Classification , Accuracy.

Abstract

Mold is plants that don't have chlorophyll and life dependency with creature another life. Mushrooms also become decomposer ingredient organic food in the environment. As well as mushrooms too made ingredient food you can eaten by humans as complementary food because mold have a good taste and have good nutrition. (Hasanuddin ,2014). Mold have various type type around the world, incl mushrooms that can cause disease in humans as well as plants and also toxic. Study this need identification to data types poisonous mushrooms _ or not toxic so no difficulty in find information the with To do application to method K-Nearest Neighbor for more easy and efficient with accompanied results good accuracy _ so that get information to mold the more more easy . On research have conclusion from the tests carried out, in conclusion is Algorithm K-Nearest Neighbor is capable do Mushroom data classification Oyster use value k = 5 with results testing score accuracy by 71.42%. The amount of training data and testing data used influence score accuracy testing, increasingly lots of data used will the more accurate result.

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References

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Published
2022-12-09
How to Cite
Dhany, H. W. (2022). CLASSIFICATION OF FUNGUS TYPES USING THE K-NEAREST NEIGHBOUR ALGORITHM. INFOKUM, 10(5), 179-187. Retrieved from http://infor.seaninstitute.org/index.php/infokum/article/view/905