Judul: PENENTUAN SENSITIVITAS INSULIN (SI) DAN EFEKTIVITAS GLUKOSA (SG) PADA MINIMAL MODELTERMODIFIKASI MENGGUNAKAN ALGORITMA PSOUNTUK KASUS OBESITAS
Abstrak: Obesitas merupakan kondisi terdapat penimbunan lemak tubuh yang berlebihan. Obesitas dapat menyebabkan terganggunya produksi insulin atau adanya resistansi terhadap insulin sehingga menimbulkan penyakit diabetes tipe 2.Sensitivitas insulin dan toleransi terhadap glukosa dapat kembali ditingkatkan dengan melakukan olahraga. Pada subjek obesitas, model matematika yang paling sesuai dengan mekanisme sistem pengaturan glukosa dan insulin adalah Minimal Model Bregman. Model ini telah banyak digunakan untuk memperkirakan sensitivitas insulin (SI) dan efektifitas glukosa (SG) dari data Frequently Sampled Intravenous Glucose Tolerance Test (FSIVGTT). Parameter pada model ini ditentukan mengunakan algoritma Particle Swarm Optimization (PSO) yang meniru perilaku kawanan serangga. Dengan memasukkan parameter yang didapatkan pada model yang digunakan, Minimal Model Bregman dapat memfitting data eksperimen dengan nilai koefisien korelasi 90% pada subjek obesitas.
Keyword: glucose effectiveness, insulin sensitivity, minimal models,obesity, particle

Judul: Penentuan efektivitas glukosa dan sensitivitas insulin menggunakan modifikasi minimal model dan particle swarm optimization
Abstrak: Diabetes mellitus is a condition when the concentration of glucose in the blood is chronically higher (hyperglycemia) than the normal value in the body. In diabetics, glucose metabolism process does not work well characterized by intervals of glucose effectiveness (Sg) and insulin sensitivity (Si) beyond the limits of the value of healthy people. Glucose metabolism in the body system is affected by the ability of glucose uptake in a network without the help of insulin and insulin secretion process. Mechanism of regulation of glucose in the blood can be explained with minimal modification of the proposed model in this study both for the case of healthy people and people with diabetes. Optimization is used to obtain these parameters are Particle Swarm Optimization algorithm which mimics the behavior of insect swarms. So that modified minimal model and Particle Swarm Optimization algorithm can be used to detect diabetes based on the value of Sg and Si obtained. The results of the modified model is not much different from the experimental data which is shown by the value of R2 or correlation between the simulation and the experimental data exceed 80% for all subjects.
Keyword: particle, diabetes mellitus, insulin sensitivity, glucose effectiveness

Judul: Codiaeum Malesia
Abstrak: The Malesian genus Codiaeum has been revised based on the morphological character using available herbarium collections in Herbarium Bogor iense and loan specimens from Rijksherbarium Leiden. The study is based on the observation of 350 specimens. Eleven species have been recognized, namely Codiaeum variegatum, C. luzonicum, C. palawanense, C. trichocalyx, C. megalanthum, C. cilliatum, C. affine, C. tenerifolium dan C. hirsutum, C. macgregorii, C. ludovicianum. number of species is found in the Philippines The highest (8 species), Two species (C. tenerifolium and C. ludovicianum) endemic in Lousiade Archipelago of the New Guinea and C. affine endemic in Banguey Island. C. variegatum is widespread by nature or in cultivation almost in all of Malesian region. C. cillia tum is a species in the earliest level among the other species according to 20 selected characters.
Keyword: Codiaeum, Malesia