PENERAPAN CHATBOT SEBAGAI ALAT DIAGNOSIS INDIKASI PENYAKIT SETRES DENGAN MENGGUNAKAN METODE BACKWARD CHAINING

Abstract

Stress is a common psychological condition that often goes unrecognized in its early stages. If left unaddressed, it can negatively impact both physical and mental health. In response to this issue, this study developed a chatbot capable of performing an initial self-diagnosis of stress symptoms. The system was built using the backward chaining method, which enables reasoning to begin from a diagnostic conclusion and trace back to supporting facts. The implementation utilized Python as the programming language and diagnostic rules based on commonly observed symptoms. Initial testing indicated that the chatbot is responsive and able to provide relevant stress level indications based on user input. Its simple interface ensures ease of use for the general public. The application of backward chaining has proven effective in supporting early stress detection without the need for direct consultation with professionals.