How to cite (IEEE): -. Mambang, & F. Marleny "Image Prediction of Exact Science and Social Science Learning Content with Convolutional Neural Network," JOIV : International Journal on Informatics Visualization, vol. 6, no. 4, , pp. 749-754, Dec. 2022. https://doi.org/10.30630/joiv.6.4.923

How to cite (APA): Mambang, -., & Marleny, F. (2022). Image Prediction of Exact Science and Social Science Learning Content with Convolutional Neural Network. JOIV : International Journal on Informatics Visualization, 6(4), 749-754. https://doi.org/10.30630/joiv.6.4.923

How to cite (Chicago): Mambang, -, AND Marleny, Finki Dona. "Image Prediction of Exact Science and Social Science Learning Content with Convolutional Neural Network" JOIV : International Journal on Informatics Visualization [Online], Volume 6 Number 4 (31 December 2022) https://doi.org/10.30630/joiv.6.4.923

How to cite (Vancouver): Mambang -, & Marleny F . Image Prediction of Exact Science and Social Science Learning Content with Convolutional Neural Network. JOIV : International Journal on Informatics Visualization [Online]. 2022 Dec; 6(4):749-754. https://doi.org/10.30630/joiv.6.4.923

How to cite (Harvard): Mambang, -., & Marleny, F. ,2022. Image Prediction of Exact Science and Social Science Learning Content with Convolutional Neural Network. JOIV : International Journal on Informatics Visualization, [Online] 6(4), pp. 749-754. https://doi.org/10.30630/joiv.6.4.923

How to cite (MLA8): Mambang, -, & Finki Dona Marleny. "Image Prediction of Exact Science and Social Science Learning Content with Convolutional Neural Network." JOIV : International Journal on Informatics Visualization [Online], 6.4 (2022): 749-754. Web. 28 Mar. 2023 , https://doi.org/10.30630/joiv.6.4.923

BibTex Citation Data :

@article{JOIV923,
    	author = {- Mambang and Finki Dona Marleny},
    	title = {Image Prediction of Exact Science and Social Science Learning Content with Convolutional Neural Network},
    	journal = {JOIV : International Journal on Informatics Visualization},
    	volume = {6},
    	number = {4},
    	year = {2022},
    	keywords = {Image; exact and non-exact; learning content; CNN; deep learning.},
    	abstract = {Learning content can be identified through text, images, and videos. This study aims to predict the learning content contained on YouTube. The images used are images contained in the learning content of the exact sciences, such as mathematics, and social science fields, such as culture. Prediction of images on learning content is done by creating a model on CNN. The collection of datasets carried out on learning content is found on YouTube. The first assessment was performed with an RMSProp optimizer with a learning rate of 0.001, which is used for all optimizers. Several other optimizers were used in this experiment, such as Adam, Nadam, SGD, Adamax, Adadelta, Adagrad, and Ftrl. The CNN model used in the dataset training process tested the image with multiple optimizers and obtained high accuracy results on RMSprop, Adam, and Adamax. There are still many shortcomings in the experiments we conducted in this study, such as not using the momentum component. The momentum component is carried out to improve the speed and quality of neural networks. We can develop a CNN model using the momentum component to obtain good training results and accuracy in later studies. All optimizers contained in Keras and TensorFlow can be used as a comparison. This study concluded that images of learning content on YouTube could be modeled and classified. Further research can add image variables and a momentum component in the testing of CNN models.},
        	issn = {2549-9904},    	pages = {749--754},    	doi = {10.30630/joiv.6.4.923},
        	url = {https://joiv.org/index.php/joiv/article/view/923}
    }
    

Refworks Citation Data :

@article{{JOIV}{923}, author = {Mambang, -., Marleny, F.}, title = {Image Prediction of Exact Science and Social Science Learning Content with Convolutional Neural Network}, journal = {JOIV : International Journal on Informatics Visualization}, volume = {6}, number = {4}, year = {2022}, doi = {10.30630/joiv.6.4.923}, url = {} }