PENERAPAN HYPERPARAMETER TUNING ALGORITMA LSTM PADA DATA POTENSIAL BIOELEKTRIK TANAMAN

Plants are living things that have many secrets in them. So, many researchers want to know the secrets of plants. One that is very interesting is how plants can communicate with the surrounding environment through the activities of the plants themselves. Then, from this communication activity, plants produce electricity which we can use to study further the behavior of these plants, commonly known as bioelectric potential. Plant bioelectric potential is a process of plant physiological activity that can produce electrical energy even though low strength. This study will utilize the potential bioelectric signal to analyze further how plants behave at certain temperatures. The process of recording the potential bioelectric signal of our plants is done by using a prototype amplifier to detect the analog signal generated from the plant and then convert it into a digital signal so that it can be used and made into a dataset. The data that has been obtained is then transformed first before being analyzed using the Wavelet Transform method. After that, the data is analyzed using a deep learning algorithm, namely Long-Short Term Memory (LSTM). The algorithm will be modified and then evaluated between the baseline and hyperparameter tuning models. It is hoped that the algorithm model can analyze it better by applying hyperparameter tuning.