"Prediction System on Electricity Consumption using Web-Based LSTM Algorithm"
First, Data collection remaining electricity using Raspberry PI 3 + Module Camera. The data has been collected with a total of 522 data until 20 days.
Second, Converting the data remaining electricity into electricity usage each one hours.
Third, Pre-processing data, cleaning the data outliers and missing value. Then, transform the data electricity usage into time series. After this, Transform into Sequence model. you can see the picture in the below is after pre-processing.
Fourth, Modelling with LSTM Algorithm, Deep Learning approach. Tunning Hyperparameter and save the best model.
Fifth, Creating Program for Integrated System with best Model LSTM using API.
Sixth, Deploying and running program model LSTM into Cloud AWS EC2 using SSH.
Seventh, Create website prediction using Laravel Framework and Tailwind Framework. And then, hosting the website.
"Create a website hydro power plant and integrated system"
First, Create UI for easy to use by user (Headmen)
Second, Create Backed for Integrated System with LoRA Communication
"Implemetation YOLO Framework for Classification Medicine - Deep Learning Convolution Neural Network"