This information system is based on a website that functions as a data processor obtained from the bot register. The integration of the system uses NGROK access which can unify local public access routes or in one go. The use of XAMPP as a web server can support the use of NGROK. NGROK server has a time duration in one use, which is about 8 hours. Users will get a domain URL when accessing NGROK. This domain URL is so unique that each session will change. The case study we are using leads to the registration system for new members of the East Java Veteran UPN robotics community, which so far still uses Google Form as a means of registering and spreadsheets as data storage media. The need for an innovation which can simplify work, especially during the Covid-19 period, therefore we created an innovation in the form of a bot register that can integrate with the website through NGROK access combined with the MySQL Local Database so that this software is expected to provide access registration directly without having to fear data loss and can also provide secure data management.
Not a few people suffer from diabetes, diabetes is usually caused by genetic inheritance from parents and grandparents. Not only from heredity but many criteria or characteristics can determine a person has diabetes. This research was conducted by looking for a dataset on Kaggle that contains criteria for someone diagnosed or undiagnosed with diabetes such as age, gender, weakness, polyuria, polydipsia, and others. Furthermore, from these criteria, predictions are calculated using the Naive Bayes classification method where this method is one of the data mining techniques. This prediction calculation uses the Python programming language. From these criteria, each criterion is grouped with similarities and the results of the program that have been made can diagnose someone with diabetes. The prediction calculations that have been carried out have resulted in 90% accuracy, 93% precision, 89% recall, 92% specificity, and 91% F1-Score.
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