Weight Prediction Model of Red Tilapia (Oreochromis Niloticus) Using Linear Regression Algorithm

Red tilapia (Oreochromis sp) is one of the important fish in the aquaculture production world, and it's widely cultivated in Indonesia. This fish is in great demand because of its delicious and thick flesh. The production of red tilapia needs to be increased. One way to increase the production of red tilapia is by increasing the feeding. This study aimed to construct a linear regression model between the weight of the feed given and the weight of the red tilapia produced. The method used in this research is Machine Learning Lifecycle (MLL). This method consists of four stages: data acquisition, data preprocessing, model training, and model development. The research data was obtained from cultivating red tilapia for nine weeks in 12 aquariums. Model making is done using the programming language Python and Jupiter Notebook. The linear regression equation obtained is y = 15.51x+22.17. The model accuracy value is 0.798 using R-square. Based on the R-square, the model obtained is good. This model can later be applied to red tilapia aquaculture activities. Model scalability must be maintained so that model performance remains good. Red tilapia cultivators can utilize this study's results to produce maximum red tilapia production. At a broader level, this research aligns with higher policy objectives related to public engagement and co-creation with stakeholders as specified in Sustainable Development Goals (SDG) like SDG14 (life below water).