Judul: Sifat fisis mekanis papan partikel dari bulu domba, serbuk gergaji kayu sengon (Paraserianthes falcataria) dan plastik polyprophylene
Abstrak: Vool of Indonesian or local sheep had been used as particle board material, however not all of its physical and mechanical traits, especially its texture match the SNI (Standar Nasional Indonesia) and JIS (Japanese Industrial Standard). Paraserianthes falcataria (sengon) can be used as practice board materials, because it contain lignocellulose fiber.
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Judul: Sifat Fisis-Mekanis Papan Partikel dari Serbuk Bulu Domba, Serbuk Gergaji, dan Serutan Kayu Sengon (Paraserianthes falcataria)
Abstrak: Indonesian or local sheep is classified as a meat type. It is not classified as a wool type because the wool yielded are coarse, so it is not optimally used. Wool can be added in the making of particle board because of its strength, pressure resistance, good insulator, and sound absorption properties. Paraserianthes falcataria (Sengon) saw dust and wood shaving are wood processing waste which can be used as particle board because it contains lignocellulose fiber. This research was to find the best formulation of wool dust (chopped wool at the length of 2-3 mm), saw dust, wood shaving and adhesive concentration used (urea formaldehida). The experiment will be conducted as a factorial experiment with two factors. The factors are wool dust, sawdust, and wood shaving combination (0% :60% : 40% ; 10% : 50% : 40% ; 20% : 40% : 40% ; 30% : 30% : 40%) and adhesive concentration (16, 18, and 20%). The parameter scored are the density, moisture content, thickness swelling, water absorbing capacity, modulus of rupture, modulus of elasticity, internal bond and strength of screw holding power. Any significant differences data will be further analyzed with Polynomial Orthogonal. The result showed that wool dust significantly improved the water absorbing capacity, modulus of rupture, and modulus of elasticity. The urea formaldehida adhesive significantly improved the density and water absorbing capacity. The interaction of two factors significantly improved the thickness swelling, internal bond, and strength of screw holding power. The data from this research showed that the number of density between 0,69-0,78 g/cm3, moisture containt with mean 6,49%, thickness swelling between 32,36-83,9%, water absorbing capacity beetween 89,04-169,15%, modulus of rupture between 68,4- 121,8 kgf/cm2, modulus of elasticity between 671,84-1381,51 kgf/cm2, internal bond between 0,44-1,3 kgf/cm2, and strength of screw holding power between 6,0-22,3 kg. To find out the proportion of the product that suite the JIS A 5908 and SNI 03-2105, the distribution of the data was estabilished and the area under the normal curve (represent the proportion) was examined. From the stand point of density, moisture containt and modulus of rupture more than 95% of the product suited to the standards. However, from the stand point of thickness swelling, modulus of elasticity, internal bond, and strength of screw holding power none of the product suited to the standards.
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Judul: Indexing Spatio-Temporal Pada Data Hotspot
Abstrak: The spatial information of hotspot is always changing over time. The recording of these changes makes it necessary to add dimension of time (temporal) into database. The database which is capable to store spatial and temporal information is known as spatiotemporal database. This database is bigger than a normal database because it stores all versions of an object over time and not allowed data to be physically deleted. A large database size causes it’s search time increases. It makes an access structure is needed in spatiotemporal database. Indexing is one of the access structure applied in the spatiotemporal database that accelerates data searching process. Spatiotemporal indexing method consists of two parts namely spatial indexing which is based on geographical information, and temporal indexing which is based on data timing information. The process of hotspot data indexing will be done in this research by using R-Tree approach for spatial data and Change Temporal Index (CTI) for temporal data. R-Tree is a hierarchical, height-balanced external memory data structure for multidimensional object. The hierarchical of R-Tree based on list of administrative such as regency, provinces and island. Change Temporal Index makes indexed data based on temporal side like valid time. CTI keeps valid data in current database and previous data according to interval valid time in historical database. This research is expected to accelerate the retrieving process in spatiotemporal databases. Spatial indexing makes searching faster up to 70%, temporal indexing makes searching faster up to 35% and spatiotemporal indexing makes searching faster than without indexing up to 50%.
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