Judul: The Development of Spatio-Temporal Data Warehouse Forest Fire in Indonesia
Abstrak: Data warehouse is a repository of information collected from multiple sources, stored under a unified schema, and that usually resides at a single site. If there is a change in the data structure, such as data separation and data merging, the data warehouse should be modified to handle the changes in the existing structure. This research was done with the development of a data warehouse approach with aspects of spatio-temporal, by using spatial data, which expected to be able to handle any case related to structural changes in the data. Hotspot data was used in this research come from the Directorate of Forest Fire Control (DPKH) Ministry of Forestry, Republic of Indonesia that has been revised by Kurniawan (2011). The result of this study is a data warehouse that can provide valid information value of data aggregation and the number of hotspot in the whole country of Indonesia starting from provincial to district level. Information on the distribution of hotspot is displayed in the form of crosstab and with interesting graphic. The graphic is displayed in the form of bar graphs and pie plots.
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Judul: Forest Fire Spatio-Temporal Data Warehouse using GeoMondrian and GeoServer
Abstrak: Indonesia is a country that has tremendous wealth of forests in the world. But Indonesia's forests decreases each year by deforestation amounted to 1.87 million hectares (FAO 2007). One of the main causes of deforestation in Indonesia is forest fires. Catastrophic forest fires cause major problems and need complex ways to overcome. One form of forest fire prevention is monitoring hotspots using the National Oceanic and Atmospheric Administration (NOAA) satellites. This satellite imagery capturing the form of hotspots, which could indicate the existence of forest fires based on location and time. Data obtained from these satellites have particularly large amount, causing the accumulation of data hotspot. This can be overcome by the presence spatio-temporal data warehouse technology with Spatial Online Analytical Processing (SOLAP) applications. Spatio-temporal data warehouse capabilities in integrating data into a quick and comprehensive information to assist decision-making process in terms of controlling forest fires. This study developed a geographic information system that integrates data warehousing applications spatio-temporaly with Spatial On-Line Analytical Processing (SOLAP) application using the framework Geomondrian and Geoserver as a web map server. Pre-process data such as data extraction, data transformation and loading of data, performed before the data warehouse is built in accordance with the dimensional data model (the concept of design in building a data warehouse) and integrated with Geoserver that handles the presentation of data in map form. The system was developed to visualize data of forest fires in the form of pivot tables, graphs and maps spread of hotspots in a web-based environment, so the system can support decision-making in an effort to control forest fire in Indonesia.
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Judul: Karakteristik Carboxymethyl Chitosan Dengan Variasi Konsentrasi NaOH
Abstrak: Carboxymethyl chitosan is chitosan derivative product obtained from chemical modification. CMCh were made by alkalization process and carboxymethylation process. Factors that affect CMCh characteristics were excess sodium hydroxide in alkalization process, ratio between chitosan and monochloroacetic acid, and carboxymethylation temperature. The objectives of this research were to study the NaOH effect to CMCh characteristics, to learn process of making CMCh, to set the proper concentration of NaOH, and to analyze CMCh characteristics. CMCh yields were 110.72%-114.22%. CMCh pH value were 3.74-4.31. The optimum NaOH concentration to obtain the best CHCh was 10 M. Percentage of CMCh moisture content was 10.70%-11.42%. Ash content and nitrogen content of CMCh were 0.49%-0.50% and 4.52%-4.81%. CMCh viscousity was 8.25 cps. Percentage of CMCh solubility was 61.61%-91.50%. The different functional groups from chitosan which observed in CMCh were C=O group, CH group from alkene functional group, C−O group, and C−O−C group.
Keyword: solubility., functional group, CMCh characteristics, chitosan, carboxymethyl chitosan