Judul: Spatial Outlier Detection Berdasarkan Poligon Desa Pada Data Pemilihan Walikota Bogor
Abstrak: Spatial outlier detection is a technique which is used in spatial data mining for detecting outlier based on spatial dimension. This research is used for examining some outlier data by using PILWALKOT (The Mayor Election) of Bogor in 2008. Outlier is a research that diverges from other research and it is caused a suspicion that comes from the distribution of difference data in the research. A county called outlier if it is include into outlier list in Naïve Algorithm. Naïve Algorithm is an algorithm which is used for detecting spatial order in Bogor county data which is based on special functions. This research also compares the result into 3 methods, by using statistic Z-Value approach, division class with Equal Interval and Natural Breaks classification method and Naïve algorithm. Naïve algorithm shows the result which is got by using Z-Value and classification method shows some equal result. By using Z-Value approach, the result which is got for the first (1st), second (2nd), and fourth (4th) candidate and it is used in three outlier regions while the third (3rd) and fifth (5th) is used in four outlier regions. In the division class using classification method, there is a presumption that Equal Interval method is better than it. It also happens in some results which are using Naïve algorithm where is had some equal results with two previous methods.
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Judul: Spatial Outlier Detection On Bogor City Regional Election Data Based On Polling Center.
Abstrak: Spatial outlier is a local instability (in values of non-spatial attributes) or a spatially referenced object whose non-spatial attributes are significantly different from the object surrounding it, even though the attributes may not significantly different from the entire population. Detecting spatial outlier is very useful in the application of geographic information system as well as in the spatial data base. This research focuses on the spatial outlier on Bogor City Regional Election Data in the 2008 election. Before starting the spatial outlier detection, the spatial outlier model was done visually by using an equal interval and natural breaks methods. This research uses the iterative ratio and iterative z-value algorithm. Both algorithms uses an iterative process. With this iterative process done by both algorithm, the falsity of a spatial outlier detection can be minimized. One example algorithm that potentially make a false detection is Moran scatterplot. For each iteration, there will be one detected spatial outlier. To determine a spatial outlier, a comparison function is used. On iterative ratio algorithm, a comparison function used is ratio function. On iterative z-value algorithm, a comparison function used is the gap function which is later normalized. A polling center’s data is said to be a spatial outlier if its value out of a comparison function exceeds the threshold. Threshold used in this research is 3, it means that number of spatial outlier detected is 2% - 5% from total data. Based on the research done, the result being detected as the spatial outlier use in iterative ratio and iterative z-value algorithm owns the difference in the detection amount. Iterative ratio and iterative z-value algorithm can also reduce a false detection which is done by Moran scatterplot. Keywords : spatial outlier, iterative z-value algorithm, iterative ratio algorithm.
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Judul: Essential Fatty Acid Requirements of Catfish (Clarias batrachus Linn.) for Broodstock Development
Abstrak: This experiment was conducted to determine essential fatty acid requirements of catfish (Clarias batrachus Linn.) for broodstock development. The basic diet supplied to the test fish had protein and fat content 46.51 - 48.29% and 5.8 - 5.96% respectively. The five test diets differed in the essential fatty acid (EFA) level. Diet A contained 0.21% (36-fatty acid and 0.03% S3-fatty acid; diet B 0.67% d6-fatty acid and 2.09%&3-fatty acid; diet C 2.24KU6-fatty acid and 0.07%&3-fatty acid; diet 0 1.85%(;36-fatty acid and 0.56% a3-fatty acid; diet E 0.26% a6 fatty acid and 1.68% d3-fatty acid. Most of US-fatty acid in diet B and D were 1$:3 (33, on the other hand those in diet E were 20:s c33 and 22:6 W3.
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