Judul: Visualisasi Data Spasial di MonetDB Menggunakan OpenJUMP
Abstrak: There are currently the most used data model is relational. This model a database as a set of data that is stored in structural rows and columns. Besides the popullarity, the relational data model is lacking in the implementation of data is large and has a high complexity. Different of the relational model, MonetDB using a column store method to divide the data into sections binary tables . This method is only necessary to call the data, resulting method is faster. Anggi ( 2013 ) have tested the MonetDB as a spatial and non spatial data storage, but not yet visualize data from MonetDB. This result successfully visualize spatial data using a simple query “like” and “and” the average time 1 second , while the complex spatial queries using “joins”, “constains” and “Intersect” with average time more than 20 minutes. So it looks that MonetDB also can process spatial data simple and complex . But in the process of complex spatial data visualization that require run-time is relatively long .
Keyword: visualize, OpenJUMP, MonetDB, spatial data

Judul: Sinkronisasi antara Visualisasi Peta dan Query OLAP pada Spatial Data Warehouse Kebakaran Hutan di Indonesia
Abstrak: This research is a continuation from the previous research concerning data warehouse and spatial OLAP forest fire in Indonesia based on web using framework GeoMondrian and Geoserver. In the previous research, OLAP analysis process and hotspot location visualization are performed separately. In this research, the synchronization between OLAP analysis process and hotspot location visualization uses Spatialytics framework. This synchronization can be done because GeoMondrian and OpenLayers are embedded on Spatialytics, therefore OLAP analysis process and hotspot location visualization can be done by using just one query, that is MDX. This research develops a system which uses Spatialytics framework, PostGIS as spatial database, and GeoMondrian as spatial OLAP server. The system uses snowflake scheme with one table of fact and three dimensions consisting of the time dimension, the satelite dimension, and the location dimension. The System is built with threetier architecture consisting of the bottom layer, middle layer, and the top layer. The advantage of this system compared to the previous one is that this system takes only one input query, which is MDX to do OLAP analysis and show hotspot location. OLAP operations such as roll up, drill down, and slicing has been implemented in this system whilst dicing has not been implement because of Spatialytics limitation. For further research, system can be developed that is capable of dicing operation, data modification, such as insert, delete and update, without changing any scheme or structure.
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Judul: Penentuan pH dan suhu optimum aktivitas kitinase Bacillus cereus I.5 dan pengujian kitinase dalam mendegradasi eksoskeleton kutu bertepung putih (Ferrisia virgata Cockerell)
Abstrak: Bacillus cereus I.5 is one of chitinolytic bacteria isolated from chilli rhizosphere. The chitinase could be apply as a biocontrol of plant pest. One method to precipitate enzyme by using ammonium sulphate. It could increase specific activity enzyme. This research was conducted to determine optimum pH and temperature of chitinase activity of Bacillus cereus I.5 and tested its ability to degrade chitin exoskeleton of Ferrisia virgata Cockerell, one of Jatropha’s pest. Enzyme activity was obtained at the 10% ammonium sulphate saturation level, which is 20 times higher compared to crude enzyme. Specific enzyme activity increased from 0,039 U/mg of crude extract to 0,778 U/mg after ammonium sulphate precipitation. Chitinase of B. cereus i.5 showed highest activity at pH 7,0 and 55 °C although the enzyme also showed its activity at pH 5,0-9,0 and temperature 26-≤55 oC. Application of crude chitinase and the enzyme after ammonium sulphate precipitation on degrading of chitin Ferrisia virgata showed it worked better if incubated firstly at its optimum temperature.
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