Judul: Spatio-Temporal Clustering Hotspot di Sumatera Selatan Tahun 2002-2003 Menggunakan Algoritme ST-DBSCAN dan Bahasa Pemrograman R
Abstrak: Forest fire is a serious problem in Indonesia. One indicator of forest fire possibility can be seen through the occurence of hotspots. Hotspot dataset is large spatial data because it is recorded continuously. ST-DBSCAN an algorithm that can process spatial and temporal data. This study implement ST-DBSCAN algorithm with R language programming. R is software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software. Clustering is performed on hotspots dataset in South Sumatra in the period 2002-2003. By using the spatial distance parameter (Eps1) = 0.2, the temporal distance parameters (Eps2) = 7 and a minimum cluster members (MinPts) = 7 resulted in 41 clusters with 712 noises.
Keyword: ST-DBSCAN, spatio-temporal, hotspot, R, forest fire

Judul: Spatio-temporal Clustering Hotspot di Sumatera Selatan Tahun 2002-2003 Menggunakan Algoritme ST-DBSCAN dan Bahasa Pemrograman Python
Abstrak: These last few years the issues of forest fire in Sumatera increase dramatically, attracting international attention. Hotspot data which are monitored using satellites can be used as an indicator of the occurrence of fire on the Earth's surface. One approach to analyze hotspot dataset is spatio-temporal clustering which can recognize patterns of hotspot event based on space and time. This study applies ST-DBSCAN clustering using hotspot data in South Sumatera 2002-2003. As multi-paradigm programming language, Python is chosen so that STDBSCAN algorithm can work fast. By using spatial distance (Eps1) 22 km, temporal distance (Eps2) 7 days, and density of cluster (MinPts) 7, 41 clusters were found to have many stationary patterns in Musi Banyu Asin. The average ST-DBSCAN execution runtime using Python was 4.934 seconds
Keyword: ST-DBSCAN, spatio-temporal clustering, Python, forest fire

Judul: In Vitro Release of Ibuprofen from Microcapsules Coated Polyblend of Poly(lactic acid) and Poly(ε-caprolactone)
Abstrak: Ibuprofen is an anti-inflammatory drug that has a short biological half-life and imposes adverse gastrointestinal reaction. Microencapsulation could be used to minimize its disadvantages. In this experiment, microencapsulation of ibuprofen was done by emulsification method. Coating material which was used were polyblend of poly(lactic acid) and poly(ε-caprolactone) which are biodegradable and biocompatible. Polyvinylalcohol was used as an emulsifier at concentrations of 1.5%. The microencapsulation was carried out with various quantities of ibuprofen. The increase in quantities of ibuprofen would improve encapsulation efficiency. Encapsulation of ibuprofen showed an efficiency of more than 71% with the highest score of 84.13% in microcapsule with ratio of polyblend-ibuprofen 5:1.5. The dissolution test results in basic medium showed that the encapsulation efficiencies affected ibuprofen release from the microcapsule. Microcapsules with the higest encapsulation efficiency released ibuprofen ranged from 26.71 to 28.78% for 6 hours. Kinetic of ibuprofen release followed first order kinetic model. The microcapsules particle sizes ranged from 38 to 250 μm.
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