Judul: Penggunaan Adaptive Neuro Fuzzy Inference System untuk Pembentukan Data Fuzzy dalam Association Rules Mining
Abstrak: Forest fires are susceptible happened in Indonesia. Some of the factors that influence their occurrences are weather and climate. Both of them will cause the increase or decrease of the number of hotspots. Previous studies have succeed to provide the relation between the fuzzy data of climatology and number of hotspots using Association Rules Mining (ARM) with membership functions for the attributes are determined by the expert. However, the results have some rules with low percentage of support and confidence and few rules are not in accordance with the expert knowledge. It could be caused by the membership functions provided by the experts are not optimal. In this study, the method used is Adaptive Neuro Fuzzy Inference System to generate membership functions that are used in the formation of data fuzzy. Then, the data is processed with association rules mining that produce rules with better support and confidence percentage than the previous work. It is also able to manage to create new rules that comply with the expert knowledge
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Judul: Fuzzy Association Rules Mining pada Data Klimatologi dan Jumlah Hotspot di Kalimantan Tengah dan Kalimantan Selatan
Abstrak: The occurrence of forest fires was influenced by many factors of weather and climate such as temperature, rainfall, solar radiation, humidity, air stability, speed and direction of wind. Rainfall, relative humidity and temperature were the main factors on the moisture of fuel control. Wind and solar radiation were important factors on drying fuels. It was influenced on change in fuel temperature also temperature and relative humidity in the air. This research was aimed to extract or “mine” knowledge from climatology and number of hotspots data in Central Kalimantan and South Kalimantan by 2001 until 2004. It is using Association Rules Mining method with apriori algorithm to see the relation between the number of hotspots and climatology data. Also fuzzy logic was used to solve an uncertainty and the numerical data. The result of this research was presented in the rules. The rules show relation between climatology and the number hotspots data. In rainy season (November-June) few hotspots were shown. This was influenced by mild temperature, mild solar radiation, mild air pressure, high relative humidity and low wind speed. However in dry season the occurence of forest fires was high in each year. The peak of forest fires occurred in August and September. It was influenced by mild temperatures, low rainfall, low solar radiation, mild air pressure, mild relative humidity, low and mild wind speed
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Judul: Enrichment of organic selenium, inorganic selenium and  vitamin E in quail products through its supplementation in the diet and its potency  of quail eggs as an ingredient in selenium-rich egg juice
Abstrak: This study was aimed to achieve an optimum level of combine organic selenium, inorganic selenium and vitamin E in obtaining the best production and reproduction as well as the highest level of selenium in quail eggs. This study was conducted from January to August 2008. Numbers of observed quails were 720 (360 females and 360 males). The treatments were applied when the quails were six weeks old. Nine treatment diets were: To (commercial diet), T1(0.46 ppm inorganic Se + 43.50 ppm vitamin E), T2 (0.46 ppm inorganic Se + 87.00 ppm vitamin E), T3 (0.92 ppm inorganic Se + 43.50 ppm vitamin E), T4 (0.92 ppm inorganic Se +87.00 ppm vitamin E), T5 (0.46 ppm organic Se + 43.50 ppm vitamin E), T6 (0.46 ppm organic Se + 87.00 ppm vitamin E), T7(0.92 ppm organic Se + 43.50 vitamin E) and T8(0.92 ppm organic Se + 87.00 ppm vitamin E).
Keyword: egg yolk, glutathione peroxidase ( GSH-Px), hedonic test, rank test