Judul: Klasifikasi Data Titik Api di Bengkalis Riau Menggunakan Algoritme Pohon Keputusan Berbasis Spatial Entropy
Abstrak: Forest fire can be monitored using satellite by detecting hotspots as fire indicators at certain times and locations. The purpose of this research is to develop a decision tree for predicting hotspot occurences in Bengkalis district, Riau province Indonesia using the spatial entropy-based decision tree algorithm. The data used in this research are forest fire data of Bengkalis area. The data include city centre, river, road, income source, land cover, population, precipitation, school, temperature, and wind speed. This research, using the 5-fold cross validation, yields five decision trees with the average accuracy of 52.05% and 89.04% on the testing set and the training set respectively.The best accuracy of decision tree is 56% on the testing set that has 560 nodes with the land cover layer as the root node. From the decision tree, as 255 rules for classifying hotspot occurences are obtained. There are 20 objects in the testing set that cannot be classified by the decision tree with the highest accuracy on the testing set.
Keyword: spatial entropy, spatial decision tree, hotspot, forest fire, bengkalis

Judul: Klasifikasi Titik Api di Bengkalis Riau Menggunakan Algoritme ID3 Spasial yang Diperluas
Abstrak: Forest fire in Riau Province including Bengkalis district, are frequently occurred every year. Hotspot is an indicator for forest fire events. Hotspots monitoring by the NOAA satellite is one of the efforts to prevent forest fires. Hotspot data are spatial data. In order to analyze the data, spatial algorithms are required. The extended spatial ID3 algorithm is a spatial classification algorithm for creating a spatial decision tree from spatial datasets. This research applied the extended spatial ID3 algorithm to the forest fires data in Bengkalis district, Riau. The data include hotspots and non-hotspots, weather data, socio-economic data, and geographical characteristics of the study area. The result of this research is a decision tree with income source layer as the root node. As many as 137 rules were generated to the tree. The accuracy of the tree is 75.66% and 41.38% respectively on the forest fires dataset in Bengkalis district and Rokan Hilir district Riau.
Keyword: spatial decision tree, ID3, hotspots, forest fires

Judul: Characterizations of low alloy steel sae 4422  plated with chromic acid (Cro3)
Abstrak: Characterizations of low alloy steel SAE 4422 plated with chromic acid (CrOrO3) was use Optical Microscopy (OM), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), RD),Energy Dispersive Analysis of X-Ray (EDAX), Hardness Test and Roughness Test. Microstructures analysis exhibits cracks and grain boundaries microcracks as a characteristics of chrome metal found at plating metal. Perlite and Ferrite as grains of steel found at base metal with grain boundaries around it. Phase analysis of plating metal appropriate to chrome metal with lattice constant (a) is 2.559 Å and phase analysis of base metal appropriate to iron ferrite with lattice constant (a) is 3.318 Å. Both plating and base metal have cubic system. Chemical analysis of plating metal at surface section exhibits that cracks area have highest value of carbon element compare with grains and grains boundaries area. While chemical analysis of base metal at cross section exhibits that perlite have highest value of carbon element compare with ferrite and grain boundaries. The hardness value of plating metal at surface section and cross section are 753 and 637 VHN. While, the hardness value of base metal and interface area at cross section are 205 and 373 VHN. The roughness value at measurement points of chrome surface for as received sample are 0.445 μm. Observation used Optical Microscopy and Scanning Electron Microscopy exhibits surface irregularities combine to form surface texture of plating metal at surface section.
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