59 research outputs found
Pengetahuan Lokal Masyarakat Adat Kasepuhan: Adaptasi, Konflik dan Dinamika Sosio-Ekologis
Masyarakat Kasepuhan merupakan masyarakat adat Sunda yang hidup di sekitar Taman Nasional Gunung Halimun - Salak (TNGHS). Masyarakat adat ini mempunyai kekhasan dalam mengatur kehidupan warganya dalam berelasi dengan alam. Melalui konsep pancer pangawinan masyarakat mensandarkan kehidupannya pada keterikatan atas tanah. Permasalahannya sekarang adalah sejak diterbitkannya kebijakan perluasan Taman Nasional melalui SK Menteri Kehutanan Nomor 175/Kpts-II/2003, tanah yang dulu dikuasai oleh masyarakat berubah status menjadi tanah Taman Nasional. Perubahan status tanah tersebut menyebabkan hilangnya akses masyarakat terhadap tanah. Kondisi ini menempatkan masyarakat pada kondisi konflik dengan Pengelola TNGHS. Metode penelitian ini adalah kualitatif dengan paradigma konstruktivisme (Denzin, 2000). Teknik pengumpulan data melalui indepth interview, observasi partisipan, dan Focus Group Discussion (FGD). Hasil dan temuan penelitian menunjukkan adanya pengetahuan lokal masyarakat Kasepuhan dalam hal mengatur kelestarian lingkungan dan bagaimana lingkungan tersebut dapat memberi manfaat untuk kehidupan masyarakat. Misalkan dengan adanya konsep Ibu Bumi, Bapak Langit dan Guru Mangsa, Leuit dan Wewengkon Hutan. Pengetahuan ini telah dikembangkan secara turun temurun dan mengatur relasi masyarakat dengan alam (hutan). Namun pertarungan pengetahuan masyarakat lokal dan pengelola TNGHS telah menyebabkan teralienasinya pengetahuan lokal tersebut. Dengan mengacu pada konsep Escobar (1999), maka dapat disimpulkan bahwa pengetahuan lokal dalam mengelola sumber daya alam dapat dipandang sebagai rezim alam organik, dimana sejak diberlakukannya SK Menteri Kehutanan tentang perluasan TNGHS, masyarakat lokal dengan alam organiknya sedang berhadapan dengan pengelola TNGHS selaku rezim alam negara yang dalam prakteknya bertumpu pada pengetahuan kapitalis dan tekno, dalam memperjuangkan hak akses atas tanah
Penerapan Metode Empirical Best Linear Unbiased Prediction (Eblup) Pada Model Penduga Area Kecil Dalam Pendugaan Pengeluaran Per Kapita Di Kabupaten Brebes
The coming of a policy about regional autonomy makes district government's choices of strategy and policy become crucial and important for it's district's development and prosperity. Indicator that can states this district development is Human Development Index (HDI). One of dimension that being used to predict the value of HDI is the dimensions of decent living, which can be shown from expenditure per capita. Should the samples of expenditure per capita are less than needed, it can cause difficulty to analyze the value of HDI on next level, which is sub-districal HDI. Direct estimaton only will not give enough validity for the results which can cause the increasing value for it's variance. Another method that can be used is small area estimation (SAE) with Empirical Best Linear Unbiased Prediction (EBLUP) method. This estimation uses the information from it's surrounding areas that correlates with the subject's parametrics. The evaluation for the results is done by comparing the value of Relative Root Mean Square Error (RRMSE) from a direct estimation with the RRMSE from an indirect estimation, which is the EBLUP method. Results from EBLUP estimation is better with average of RRMSE of 7,219% than direct estimation's average of RRMSE with 9,361%
Perbandingan Model Gwr Dengan Fixed Dan Adaptive Bandwidth Untuk Persentase Penduduk Miskin Di Jawa Tengah
Regression analysis is statistical method for modeling the dependency relationship that might exist among the dependent variable with independent variable. Geographically Weighted Regression (GWR) is an expansion of linier regression model where each of the parameters from every observation sites is counted, so each sites have local regression parameter. Weighted Least Square (WLS) model is applied to estimate the parameter of GWR model. GWR method differentiates bandwidth kernel into two, fixed bandwidth kernel and adaptive bandwidth kernel. Fixed kernel has the same bandwidth in each observation location, meanwhile adaptive kernel has different bandwidth value in each observation location. Cross Validation (CV) is used to choose the most optimum bandwidth. The application of GWR model to show the percentage of poor population at district and city of Central Java shows that GWR model is significantly different in each location towards global regression model, also the estimated model will also give different result between one location and another. Based on Akaike Information Criterion (AIC) value between global regression models with GWR, it is know that GWR model with fixed exponentially weighted kernel is the best model to use to analyze the percentage poor population at district and city of Central Java because of it has the smallest AIC value
Analisis Faktor-faktor Yang Mempengaruhi Gizi Buruk Balita Di Jawa Tengah Dengan Metode Spatial Durbin Model
Severe malnutrition is a state of nutritional deficiencies at a severe level, where the nutritional status is far below the standard. Anyone can suffer from severe malnutrition, especially infants and children who are in the growth period. Central Java Province is one of many provinces in Indonesia where the cases of severe malnourished children under five years are high enough. It is noted that Central Java Province is one of 10 provinces in Indonesia with the highest rate of severe malnutrition cases for 6 years (2005-2010). Using data from year 2011, the result of the Moran's I test states that there are spatial dependencies on severe malnutrition's rate of children under five years and some of its influential factors on Central Java Province. Therefore, Spatial Durbin Model (SDM) method is used in this experiment. Variables which significantly affect severe malnutrition on Central Java Province through SDM method are : the numbers of infants with low birth weight ( ), the numbers of houses with good health status ( ), and the numbers of households with access to source of clean water ( ). SDM model obtains value of as much as 70.3% with AIC and MSE respectively 476.32 and 35280.11, results better than Ordinary Least Square (OLS) which produce as much as 41.5% with AIC 490.52 and MSE 60653.69
Six Sigma Untuk Analisis Kepuasan Pelanggan Terhadap Persepsi Kualitas Provider Kartu Gsm Prabayar
The company is currently competing industry in offering a good product in the form of goods or services in order to attract consumers. Competition industrial companies also occur in companies engaged in the telecommunications sector that influence the cellular telecommunications services company. In 2000 PT Indosat and PT Telkomsel was licensed as an operator National GSM 1800 as mandated by the Telecommunications Act No. 36/1999. In recent years, the Provider of Indosat and Telkomsel occupied the top two in terms of number of customers and the profit generated. This study aimed to analyze the level of customer satisfaction on the perception of the quality of the GSM prepaid card provider used by using six sigma method that becomes an approach to reduce the variability of the process through the use of statistical tools. In this study, the overall process is in a state that has not been well despite being in the category of satisfied but do not meet the targets used. DPMO results obtained from the Provider Indosat and Telkomsel to dimensions of technical quality and functional quality with a target of 8 each is 189718,8; 180625; 102343,8; 105250 with the sigma level 2,37; 2,41; 2,76 and 2,32. As for the dimensions of technical quality and functional quality with the target 9 on each Provider DPMO results obtained for 279750; 271666,7; 202083,3; 204666,7 with sigma level 2,08; 2,41; 2,33 and 2,32. These results are still far from the expected target is 3,4 DPMO and 6-sigma
Analisis Faktor-faktor Produksi Perikanan Tangkap Perairan Umum Daratan Di Jawa Tengah Menggunakan Regresi Berganda Dan Model Durbin Spasial
Indonesia's inland openwater is the second largest in Asia after China. It's estimated Indonesia's inland openwater capture fisheries potential reached 3.034.934 tons per year. Central Java is one of the provinces that have great potential in the field of fisheries. In this study will be discussed about the factors suspected to affect inland openwater capture fisheries production. The method used are multiple regression analysis with maximum likelihood estimation and spatial durbin models. Spatial durbin models is the development of linear regression which location factors are also considered. The results of spatial dependences shows there is spatial dependence in the inland openwater capture fisheries production variable, fisheries establishments variables and the number of boats variable. So spatial durbin models can be used for analysis. In spatial durbin models, variables that significantly influence inland openwater capture fisheries production is the number of fishing gear, the number of boats, and the number of fishing trip with coefficient of determination (R2) of 0,9054. While in the multiple regression analysis showed that the only number of fishing trip variable that significantly, where the value of the coefficient of determination (R2) is 0,857. Thus better spatial durbin models used to analyze inland openwater capture fisheries production, in addition more significant variables also have the coefficient of determination (R2) that is greater than the multiple regression analysis
Pengendalian Kualitas Data Atribut Multivariat Dengan Mahalanobis Distance Dan T2 Hotelling (Studi Kasus PT Metec Semarang)
Vending machine is a machine used to sell the product automatically without any operator. Data vending machine products are classifiable in the attribute data for the category of disabled and not disabled. To maintain consistency of product quality and in accordance with market needs, it is necessary to do quality control on the activity undertaken. In the production process, to monitor the quality of service can be used multivariate control charts. Diagram control is often used is the Mahalanobis Distance and T2 Hotelling. The study was conducted on the data of defects in the production of vending machines in September 2013 to April 2015. Results showed that in the control diagram Mahalanobis Distance acquired upper limit value is 15.615 the control diagram is known there are two observations that are outside the control limits. While the T2 Hotelling control chart obtained upper limit value is 36.12 and all observations are within control limits. The production process has been good vending machine, known from the process capability of Cp value of 1.1503
Perbandingan Metode Klasifikasi Naïve Bayes Dan K-nearest Neighbor Pada Analisis Data Status Kerja Di Kabupaten Demak Tahun 2012
Large population in Indonesia is closely related to the working status of the population which is unemployed or employed. It can lead to the high unemployment when the avaliable jobs arent balance with the population. Used two methods to perform the classification of employment status on the number of residents in the labor force in Demak for 2012 which is Naïve Bayes and K-Nearest Neighbor. Naïve Bayes is a classification method based on a simple probability calculation, while the K-Nearest Neighbor is a classification method based on the calculation of proximity. Variables used in determining whether a person\u27s employment status is idle or not are gender, status in the household, marital status, education, and age. Employment status of the data processing methods of Naïve Bayes with the accuracy obtained is equal to 94.09% and the K-Nearest Neighbor method obtained is equal to 96.06% accuracy. To evaluate the results of the classification used calculations Press\u27s Q and APER. Based on the analysis, the Press\u27s Q values obtained indicate that both methods are already well in the classification of employment status data in Demak. Based on the calculation of APER, the classification of data in the employment status of Demak using the K-Nearest Neighbor method has an error rate smaller than the Naïve Bayes method. From this analysis it can be concluded that the K-Nearest Neighbor method works better compared with the Naïve Bayes for employment status data in the case of Demak for 2012
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