Judul: Performance of logistic regression model for predicting deforestation, case study: cikepuh wildlife reserve and cibanteng natural reserve
Abstrak: Cikepuh Wildlife Reserve and Cibanteng Natural Reserve, since both conservation area was established in 1973 and 1925 have been facing complex problem caused by land use changed, deforestation, illegal hunting, forest fire, and so on. Deforestation itself is a complex socio-economic, cultural, and political event. This thesis focused on what factors affect the rate of deforestation by considering some common driving forces of deforestation and using logistic regression for predicting deforestation. It is clearly important to know where deforestation is likely to occur. The objectives of the thesis are to quantify the contribution of each deforestation driving factor such as distance from center of dweller, aspect, slope, distance from shore line, distance from existing road, and elevation, and to elaborate spatial projection of future trends of deforestation based on possibility of deforestation as the result of logistic regression equation. The methodology is using Stacking Method from CI (Conservation International) CABS (Center for Biodiversity Applied Science) and developed together with WCS IP (Wildlife Conservation Society – Indonesia Program). Two image with different dates or one period was stacked and analyzed by visualization from both images. Signature area was extracted from the stacked-images by using shapefile polygon for forest to forest class, forest to non forest class, non to non forest class, water, cloud and shadow. Signature area should be represented certain spectral characteristic, so for obtaining number of class as many as possible, it could use 16 bit data type indeed 8 bits. Classification method is supervised classification that was done by CART ERDAS Imagine plug in tool and See5, a stand alone decision-tree based classification program. The result of classification is thematic raster image with forest change attribute. Analysis was done in one attribute table of polygon vector cell (PVC), that is created by using Edit Tool Vector Grid, an extension from ArcView 3.3. All attribute of independent variables fill the squared-shaped polygon as called PVC, and the result probability of logistic regression as the result of the calculation as well. Independent variable is divided to two binary category 0 and 1. 1 is a parameter that tends to occur deforestation such as less 1 km distance from road. 0 is stable condition that there is no change from forest to non forest. The result of possibility deforestation occurrence is if the road distance less than 1 km, tends to deforested occurrence 3 times compare the distance greater or equal 1 km. The smallest possibility of deforestation occurrence was contributed by predictor distance 1 km from river, and almost has no effect to deforested occurrence. Regression logistic equation in this thesis can predict deforestation significantly, although some processes of polygon vector cell could not accommodated to assign data from attribute of independent variables to polygon vector cell exactly. Regression logistic model could predict deforestation better if distribution of independent variables that are assumed to tend to deforestation occurrence distribute evenly entire the study area.
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Judul: Identifikasi Faktor Penyebab Deforestasi dan Reforestasi Ditinjau dari Aspek Sosial Ekonomi (Kasus di KPH Kuningan, Perum Perhutani Unit III Jawa Barat dan Banten)
Abstrak: Deforestation is conversion of forest into other land use/land cover due to forest exploitation, agricultural expansion, settlement development or other activities. Deforestation resulted in wildlife habitat loss and forest cover decline. Meanwhile reforestation is recovery of forest area resulted from natural regeneration or planted. Deforestation and reforestation merely is not happening in the forest or protected forest conservation, but also occur in production forests. Production forests located in Java Island is managed by Perum Perhutani. According Ichsan (2006), in general, the existence of forest is surrounded by villages with social conditions, economic classified as poor. Ownership of land by the community is very narrow, having low technological capabilities, scarcity of capital as well as limited access to public services. These conditions have made the villagers who are living around the forest are difficult to rise from poverty. Moreover revenue contribution of forest land is not optimal for for the community This study aims to determine level of deforestation and reforestation (of natural forests and forest plantations) in KPH Kuningan and identify its socioeconomic factors associated with deforestation and reforestation. The results of this research may be contributed to formulation of programs to reduce deforestation and increase reforestation of Perum Perhutani. This research was conducted in KPH Kuningan start of the month from June to December 2009. The tools used in this study is a set of computers equipped with software Arc View GIS 3.2, ERDAS Imagine 9.1, SPSS 15.0, and Microsoft Office Excel 2007; Global Positioning System (GPS), voice recorder, digital camera; questionnaire (Forest Village Community Forest Village Community Institution); and stationery. The materials used are Landsat 7 ETM (March 2002) and 5 TM (March 2009) path/row 121/65, RBI Indonesia map scale 1: 25.000, the potential of the village in 2006, statistics of Registration Forest Village Community Institution to KPH Kuningan In May 2009, and Recapitulation Results Vulnerability Identification Zone (Red/Green Area Zone) during July- December 2008 KPH Kuningan. In the period 2002-2009, deforestation occurred in Kuningan District of about 16.305,93 ha from total forest area of 29.618,19 ha. There were two villages taken as sample area namely, Sukarapih village with deforestation of - 4.20 ha/year, and Segong Village with reforestation of about 6.77 ha/year. Based on statistical analysis using logistic regression models, it was found that socioeconomic factors have gave significantly affect to deforestation were revenues, forest disturbance, and knowledge about the existence of state forestry logging. While socioeconomic factors significantly affect reforestation was participation in the reforestation of state forestry activities.
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Judul: Trichomonas Gallinae Penyebab Trichomonosis Pada Unggas
Abstrak: Trichomonas gallinae adalah protozoa yang bergerak aktof dengan keempat flagella yang mempunyai layar dan pada salah satu sisinya terdapat membran seperti sirip ikan yang berombak. Spesies dari genus Trichomonas ini mempunyai arti penting pada unggas, karena dapat menyebabkan infeksi pada alat pencernaan bagian atas.
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