Random forest mode scoring
The evaluation metric used for classification .score is accuracy.
Your model has higher accuracy and lower precision. Looking at your confusion matrix, you have class imbalances which can lead to that result.
You should not change your evaluation metric to get better results. It is better to pick the evaluation that makes the most sense for the problem. Then improve the model through collecting more data, engineering better features, changing algorithms, or tuning hyperparameters.