Parser is aprocess of classifying sentence structuresof a language. Parser receives a sentence and breaks it up into correct phrases. The purpose of this research is to develop a Malay single sentence parser that can help primary school studentsto learn Malay language according to the correct phrases. Thisis because research in Malay sentenceparsinghasnot gottenenough attention from researchers tothe extent ofbuildingparserprototypes. This research used top-down parsing technique,and grammar chosen was context-free grammar (CFG) for Malay language. However, to parse a sentence with correct phrase was a difficult task due to lack of resourcesfor obtainingMalay lexicon. Malay lexicon is a database that storesthousands of words with their correct phrases. Therefore, this research developeda Malay lexicon based on an articlefrom Dewan Masyarakatmagazine. In conclusion, this research can providehelpto the primaryschoolstudentsto organize correct Malay single sentences.
Expert system is a system that emulates experts to aid in decision making. This system can be applied in various categories such as diagnosis, prediction, interpretation, and others. Expert System to Diagnose Dengue Fever is a web-based system which is integrated with prolog language in order to provide rules for dengue fever detection. The aims of this research are to study dengue fever symptoms and other illnesses related to the fever, to design an inference engine, and to build an expert system. The challenges faced while developing this expert system were the complexity of prolog codes and their integration with the web development. In this system, rules were developed by prolog language which define dengue fever and accuracy based on input from the user. This system is expected to aid users in self-detecting early symptoms of dengue fever before seeing the doctors.