Judul: Identifikasi Daun Shorea menggunakan Voting Feature Interval 5 dengan Discrete Wavelet Transform
Abstrak: Shorea belongs to the Dipterocarpaceae family. Shorea wood is the best timber and has high commercial value in wood industrial trading. However, the large variety of Shorea becomes the main challenge for its identification. This research aimed at developing Shorea’s identification system using its leaves, by considering that leaf is more practical to identify, easily obtained, available all the time and is suitable for observations in the form of image. The system was developed by using Voting Feature Interval 5 based on Discreate Wavelet Transform. Ten species of Shorea were identified. It was revealed that the best accuracy was 71%.
Keyword: Voting Feature Interval 5, Shorea, Discreate Wavelet Transform

Judul: Identifikasi Jenis Shorea (Meranti) Menggunakan Algoritme Voting Feature Intervals 5 Berdasarkan Karakteristik Morfologi Daun
Abstrak: Shorea (Meranti) is the major timber-producing genera of the family Dipterocarpaceae. Dipterocarpaceae produce very high quality timber in the tropical rain forest region of Asia and has very high commercial value in the world industry. However, certain species of shorea are known to have low quality wood. Hence, the selection process of shorea species is essential in producing high quality shorea timber. There are 194 types of shorea species, which makes it difficult and impractical to identify each species manually. Only people with significant amount of experience can effectively identify different shorea species. This research aims to automatically identify shorea species based on the morphological characteristic of their leaves using Voting Feature Intervals 5 (VFI5). The data used in this research is obtained using manual measurement from shorea plants in Bogor Botanical Gardens. We use 5 species of shorea each having 10 instances for a total of 50 instances. Each instance is characterized by using the following morphological characteristics: length of the leaf, width of the leaf, venation of the leaf, surface of the leaf, tip of the leaf, base of the leaf, circumference, wide, angle, and amount of veins. Each characteristic is used as a feature for processing using VFI 5 algorithm. The best accuracy obtained in this research is 88%.
Keyword: 

Judul: Hubungan Tingkat Kecukupan Protein dan Zat Besi (Fe) dengan Kadar Hemoglobin Ibu Hamil di Kota Bogor
Abstrak: Levels of hemoglobin is one of the most common indicator used to determine the status of iron deficiency anemia, which is closely related by intake of protein and iron that increased and must be adequate during pregnancy. The aim of study was to explain relationship between %RDA of protein and iron with levels of hemoglobin at pregnant mother in Bogor City. The design of this study was cross-sectional study, and the number of samples were 45 pregnant women. The result of the research show that the anemia prevalence was 22.2%. Consumption of animal foods as a source of iron was still low (60.3 g) it might for 68.8% of the samples had inadequate iron. Intake of vitamin C as a enhancer of iron bioavailability was 27.0 mg. This study has shown that intake of heme iron (6.9 mg) was lower than the non-heme iron (10.4 mg). Most of sample on group anemia and non anemia has %RDA of energy and protein as a deficit level of heavy and then %RDA of vitamin A, vitamin C, folic acid, and iron as a deficit. Results test correlation show there is no relation between %RDA of protein and iron with levels of hemoglobin (p>0.05)
Keyword: