Lansium domesticum Corr. with vernacular name in Indonesian duku has been reported containing therapeutic bioactive compounds, and some of these compounds shown to be potent antitumor, anticancer, antimalaria, antimelanogenesis, antibacteria, and antimutagenic activities. This plant is commonly known as duku, kokosan and langsat by the local community in Indonesia. The morphological appearance of all varieties is nearly the same, and identifi cation of the varieties is very diffi cult for growers. Variation of DNA sequences of the ITS (Internal transcribed spacer) region can be used as a molecular character to determine the phylogenetic relationship of different varieties of L. domesticum. The aims of this study were to determine taxonomy status of duku, kokosan, and langsat, also phylogenetic relationship among varieties of L. domesticum based on ITS rDNA sequencing. DNA was isolated from leaves of plant and then amplifi ed using F1 and R1 primers. Nucleotide sequences were identifi ed using Sequence Scanner Software Programm version 1.0, nucleotide sequences from 18S, ITS1, 5.8S, ITS2 and 26S region, that has been mergered using EditSeq and SegMan in software Suite for Sequence Analysis DNASTAR Lasergene DM version 3.0.25. The results of study showed that DNA fragments ranging in size from 782-810 bp. Different pattern of DNA fragments indicated polymorphism among duku, kokosan, and langsat. Based on the results of the ITS rDNA sequencing and phylogenetic tree analysis. It was determined that Lansium and Aglaia are a separated genus with the similarity index value of 0.98. Duku, kokosan and langsat were divided into two cluster, namely cluster kokosan-langsat and cluster duku with the similarity index value of 0.996.

Research in the molecular field requires DNA with a high degree of purity. Local rice varieties of South Sumatra have different leaf texture so that in isolation process to obtain DNA with high purity level required the right method. This study aims to compare the quality and quantity of purity of local rice insulation of local rice varieties of South Sumatra with different methods of CTAB and Wizard Genomic DNA Purification System Kit from Promega. The research was conducted from

Analysis and identification of land use in coastal areas to study the coastal environment Sembilang National Park in South Sumatra using remote sensing system (Geographical Information System) has been conducted from June until November 2014. The objective to study the changes that occur in the coastal environment as well as to identify and estimate the area use change existing mangrove areas in Region I of the Section of Sembilang National Park Management, South Sumatra. Methods for the analysis and identification based on Landsat image data 8 in 2013 using ENVI 4.3 and Arc GIS 9.3 software as well as the conversion of ground check. The results showed the use of land in the mangrove areas in the region I of the Section of Sembilang National Park Management classified into 5 classes, namely mangrove, water area, mangrove shrubs, mainland mud, and ponds areas. The area of each class were observed in sequence as follows 8921.19 ha (41.69%) as mangrove area; 3934.3 ha (23.28%) as water areas; 3.608,52 ha (17.41%) as area of mangrove shrubs; 1.649,11 ha (9.05%) as mainland mud and settlement area; and 1.561,04 ha (8.57%) as the ponds area. The percentage of the class obtained as a result of the conversion of ground check, and it is based on the land use map data over the total area observed.

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Optimizing the facility location has a vital role in providing services to the community. This study aims to determine the Temporary Waste Disposal Site (TWDS) in Sako District, Palembang City. The distance data between each TWDS in Sako District is used to formulate the Set Covering model, consisting of the Set Covering Location Problem (SCLP) model and the p-Median Problem model. The classical approach is made by solving both models using Lingo 18.0 software. The Greedy Heuristic algorithm is used as the heuristic approach. Based on the results and discussion, Sako District consists of 4 Villages and 9 TWDS. The SCLP and p-Median Problem models with LINGO 18.0 software and the Greedy Heuristic algorithm show a difference. The study results suggest using the optimal solution resulting from the Greedy Heuristic algorithm because it can meet all requests in Sako District. Research shows that there are six optimal TWDS in Sako District. However, several locations are still not optimal, so it is recommended that there are an additional 14 new TWDS facilities in Sako District to serve all requests.

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