Optimization of Fuzzy System Inference Model on Mini Batch Gradient Descent

Optimization is one of the factors in machine learning to help model training during backpropagation. This is conducted by adjusting the weights to minimize the loss function and to overcome dimensional problems. Also, the gradient descent method is a simple approach in the backpropagation model to solve minimum problems. The mini-batch gradient descent (MBGD) is one of the methods proven to be powerful for large-scale learning. The addition of several approaches to the MBGD such as AB, BN, and UR can accelerate the convergence process, hence, the algorithm becomes faster and more effective. This added method will perform an optimization process on the results of the data rule that has been processed as its objective function. The processing results showed the MBGD-ABBN-UR method has a more stable computational time in the three data sets than the other methods. For the model evaluation, this research used RMSE, MAE, and MAP

The Pandemic A Leap Of Faith - Covid-19 Vaccine Fatwa in Indonesia Religious Institutions Independence and Rival Politics

Imagine where we are in 2019. We are still living in best possible way, we gather, we socialize, and we celebrate plenty of things together with our loved one without worry. The 2019 is just two years ago, but in certainly feels like longer than that. Now, we are at the year of 2021. The pandemic has beeb with us for 17 months now. The countres all over the worlds loosen and tighten its boreder as the pandemics evolve into certainty when the vaccinations held. Indees, the catastrophic of the pandemics didn't just leave us behind, many of us losing out loved one and in grief. Yet we are still hopeful of the future especialyy when Science nurtured our thinking while God is with all of us at heart