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: Sistem Pakar untuk Identifikasi Shorea Menggunakan Algoritme Voting Feature Interval 5
Abstrak: Shorea is a kind of meranti species that have high value. Shorea is a genus name with 194 species and belong to the Dipterocarpaceae family. Shorea has a considerable number of benefits. It is the most important timber source. Shorea can be used to produce varnish, paint and other chemical materials. One kind of Shorea is better known as tengkawang and can produce a high price oil that can be used to make cosmetics and food. The morphological similarity of Shorea makes it difficult to distinguish one Shorea to another. The identification is usually done by experts. Unfortunately, there is limited time and resource of experts to identify. Expert system is a computer system that emulates the decision making ability of human expert. This research aims to develop an expert system to identify Shorea based on morphological characteristics of Shorea. The expert system being built uses Voting Feature Intervals 5 (VFI5) algorithm to identify Shorea. The acquistion of data is done with expert to examine Shorea morphological characteristics. The acquisition is generating identification of determination key as comparison to VFI5 algoritm. The identification using VFI5 algorithm produced 99% average accuracy, and identification of Shorea performed by an expert produced 90% accuracy.
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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)
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