Background. Malaria remains problematic the main in areas of all areas of East Nusa Tenggara, so is highest of annual malaria incidence (AMI) showed 189,7 %o in 2000 years.The clinical diagnostic is carried out the based symptoms , because that shortage of microscopical examination. Objective, of this to study was spesific symptoms identification develoving malaria algorithm of the according between clinical symptoms and positive patient.Methode. To design cross sectional study and descriptively to major symptoms in high case incidence area (HIA) of Wairasa helth centers.The measuring and followings : interobserver realibility of questioner and clinical examination of malaria suspect, interobserver realibility in the interpretation of microscopic examination, significance of correlation between clinical symptoms by the parasitaenia, and symptoms combination to develoving malaria algorithm.Result. The results malaria algorithm were follows : interobserver realibility of questionnaire and clinical examination of malaria in suspect case were high (Kappa value 0,66 - 1,00). The multivariate statistic analysis and validation showed demam, sakir kepala, pucat, pegal badan are significantly related to parasitaemia, so bivariate statistic analysis combination follows : (a) demam, .vakir kepa/a, (b) demam, pncar, (c) demam, pegal badun, (d) sakif kepula, pucat, (e) .sakit kepala, pegal badan, (f) demam, sakit kepala, pucat, (g) demam, sakit kepala, pegal badan dan (h) demam sakit kepala, pucat, pegal badan.Conclusions. It was concluded that malaria algorithm consisting a combinations of demam and sakit kepala are significantly related to malaria as a local spesific symptoms of the confirmed proofs that is statistically significant with the interobserver realibility is highest.