<![CDATA[Insomnia among Generation Z students shows a high prevalence, exacerbated by academic pressure and excessive use of digital devices. Existing diagnostic systems have not specifically accommodated the characteristics of insomnia symptoms in this group transparently and clinically explainable. This study aims to design, implement, and test a web-based expert system for diagnosing insomnia using the Certainty Factor method, capable of mimicking psychological reasoning in diagnosing insomnia among Generation Z students. The basic knowledge was obtained from interviews with experts, covering three types of insomnia, namely transient, acute, and chronic insomnia, sixteen symptom indicators, and thirty five inference rules with Certainty Factor values directly determined by experts. The system was developed using Hypertext Preprocessor programming language and MySQL database, and data were collected through questionnaires from seventy Generation Z students. Testing was conducted through Black Box Testing and validation of system diagnostic results against expert diagnoses. Black Box Testing showed a one hundred percent functional success rate. Validation of system diagnostic results against expert assessments on seventy cases demonstrated one hundred percent agreement, proving that the system can produce diagnoses identical to expert assessments. All Generation Z students were diagnosed with chronic insomnia, with Certainty Factor values ranging from zero point two five eight one to one point zero zero zero zero, confirming the high prevalence of chronic insomnia among Generation Z students. This system contributes as an accurate, transparent, and accessible self-screening instrument without barriers of cost or social stigma. Keywords : expert system, insomnia diagnosis, generation Z students, certainty factor method, web]]>
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