Abstract: This research paper aimed to determine the crop bearing capability of bitter melon or bitter gourd more commonly called “Ampalaya” in the Filipino language. Images of bitter melon leaves were gathered from Ampalaya farms and these were used as main data of the research. The leaves were classified as good and bad through their description. The research used Machine Learning Algorithm through Convolutional Neural Network. Training of data was through the capabilities of Keras, Tensor Flow and Python worked together. In conclusion, increasing number of images could enable a machine to learn the difference between a good and a bad Ampalaya plant when presented an image for prediction.

Marizel B. Villanueva and Ma. Louella M. Salenga. “Bitter Melon Crop Yield Prediction using Machine Learning Algorithm”. International Journal of Advanced Computer Science and Applications (IJACSA) 9.3 (2018). http://dx.doi.org/10.14569/IJACSA.2018.090301

@article{Villanueva2018,
title = {Bitter Melon Crop Yield Prediction using Machine Learning Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090301},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090301},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {3},
author = {Marizel B. Villanueva and Ma. Louella M. Salenga}
}