<![CDATA[Autism Spectrum Disorder (ASD) is a developmental disorder that affects communication, social interaction, and behavior. In Indonesia, autism diagnostic services still rely entirely on experts, thus limiting service effectiveness, particularly at the Disability Services and Inclusive Education Unit (UPTD). This study aims to develop an expert system based on the forward chaining method to diagnose autism quickly, precisely, and accurately. The methods used include data collection through field observations, interviews with experts, and literature review. The system was built using the Java programming language and a MySQL database, with 46 symptoms and four types of disorders as its knowledge base. The inference process was carried out using if-then rules and forward chaining techniques to generate initial diagnoses and recommendations. The results showed that this expert system was capable of independently diagnosing based on user symptom input and producing diagnostic output with high efficiency. This system also simplifies the expert's task because it can be used as an aid, not a replacement, in the diagnostic process. In conclusion, the expert system developed can improve service effectiveness, accelerate the diagnostic process, and reduce dependence on the presence of in-person experts. This system can be an innovative solution to support technology-based inclusive services. Keywords: expert system, autism, forward chaining, diagnosis, UPTD disability services]]>
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