The exchange of information on the Internet requires increased protection to avoid potential threats to privacy and security. This study identified the main issues in this regard: the need for simple and effective tools for encoding and decoding messages, and the need to understand Base64 encoding algorithms and concepts. However, to overcome this problem the author developed an application to encode and decode messages/text using the Base64 algorithm and the Python programming language. This application allows users to send secret messages/text securely via and convert the data into Base64 format for secure transmission via text media. It also covers the basics of cryptography, Base64 algorithms, and how to use the Python programming language to develop secure applications. The result of this research is a simple and effective encryption and decryption application. This application provides a solution for users to protect messages or text when they want to change confidential information by converting it to Base64 format. With this application, you can send secret messages or texts with the confidence that only authorized parties can read them. Implementing message encryption and decryption using the Base64 algorithm using Python is an important step in maintaining message privacy and security in the current digital era. This research succeeded in developing an application suitable for this purpose. Therefore, the next step is to improve the security of your application by implementing stronger encryption algorithms. Additionally, we provide a more comprehensive user guide to help users better understand cryptographic concepts. Further research may focus on integrating applications with broader Internet security protocols to address increasingly complex security threats.

Discord, which was originally created for the gamer community, can now be found used by hobby groups and communities that are used for shared learning purposes. But the downside is the gamer culture that comes with it. Rude and toxic words that are synonymous with the gamer community should be avoided in study group communities. Meanwhile, the facilities for minimizing harsh and toxic words are still limited to word filters that can be tricked so that they can still be sent to the chat room. This can trigger conflict and interfere with learning activities together. This paper proposed an information assistance chatbot that is able to answer question, and conflict prevention with detection toxic sentences using pre-processing from NLP (Natural Language Processing) and text classification so that the chatbot is able to limit toxic sentences a little more accurately than the word filter feature alone. Also, Chatbots are given the ability to determine the value / level of toxic conversations so that they are had been able to determine the punishment action to be carried out by warning, suspending, or even being issued for the most severe cases. In addition, by looking at the frequency of sending messages from several senders, which indicates toxic, it was able to determine when the conflict occurs. The result shows that chatbot can work fine to answer question and detecting toxic include do punishment to toxic sender. With 10% error on detecting conflict and 30% error on answer question. That 30% error false positive on make an answer that should not be answered.