MODEL REGRESI PROBIT DATA PANEL PADA INDEKS PEMBANGUNAN MANUSIA KABUPATEN/KOTA DI PROVINSI SULAWESI SELATAN

Abstrak. Salah satu model regresi yang dapat digunakan pada data peubah terikat kualitatif adalah regresi model probit. Pada penelitian ini, pemodelan probit menggunakan data panel yaitu data pengamatan unit dilakukan pada beberapa waktu. Pendek estimasi parameter Maximum Likelihood Estimation penelitian ini merupakan data sekunder dari BPS Provinsi Sulawesi Selatan. Peubah t adalah data kategori IPM di Provinsi Sulawesi Selatan tahun 2013 tinggi dan nilai 0 menunjukkan kategori IPM sedang. Sedangkan peubah bebasnya adalah angka harapan hidup, rata rata lama sekolah, persentase penduduk miskin, dan laju pertumbuhan PDRB. Peubah bebas yang berpengaruh signifikan terhadap kategori IPM di Provinsi Sulawesi Selatan adalah rata rata-rata lama sekolah, maka probabilitas kabu tinggi semakin besa

ANALISIS CLUSTER PENDEKATAN METODE HIERARCHICAL CLUSTERING TERHADAP PERTUMBUHAN EKONOMI DI PROVINSI SULAWESI SELATAN

Analisis cluster digunakan untuk mencari bagaimana tingkat kemiripan atau kesamaan karakteristik setiap objeknya yang berada didalam masing-masing pengelompokkan yang sudah terbentuk, oleh karena itu tujuan dari penelitian ini untuk mengetahui bagaimana penningkaatan pada pertumbuhan ekonomi di Sulawesi Selatan menggunakan analisis cluster dengan salah satu metodenya yaitu hierarki (Hierarchical). Hasil penelitian tersebut, objek dikelompokkan menjadi 3 cluster dari 24 sektor wilayah kabupaten/kota Provinsi Sulawesi Selatan berdasarkan, penentuan metode hierarchical clustering yakni diantara average linkage methods, ward’s methods, dan centroid methods menunjukkan hasil rasio simpangan baku terbaik pada metode wards’s karena memiliki nilai rasio terkecil yaitu 0,5052. Kata Kunci : Analisis Cluster, Hierarchical Clustering, Pertumbuhan Ekonom

Survival analysis in dengue hemorrhagic fever using Cox proportional hazard model

Survival analysis is a statistical procedure used to analyze the distribution of time to event data. Dengue hemorrhagic fever data has characteristics that suitable for survival analysis. This study presents a survival analysis to identify the correlation between the times of event of dengue hemorrhagic fever with the measured independent variables by using Cox proportional hazard model. The hazard ratio for platelets obtained that the recovery rate of the patients of dengue hemorrhagic fever with below normal platelet is 2.625 times to the normal platelet count. The result indicated that patients with below normal platelet counts would need a long time to recovery compared than patients with normal platelet counts

Performa Restricted Maximum Likelihood and Maximum Likelihood Estimators on Small Area Estimation

In this paper, it was studied performance of maximum likelihood and restricted maximum likelihood method to estimate random factor on small area estimation. To evaluate of their performances, it was used mean square error as criteria. Based on data simulation, it was found that mean square error of restricted maximum likelihood estimator smaller than ML. Therefore, it could be concluded that restricted maximum likelihood method is better than maximum likelihood. Hereafter, it was applied those methods to human development index in South Sulawesi. The result of study showed that restricted maximum likelihood method is also better than Ordinary Least Square or maximum likelihood. The results of the study on human development index data in South Sulawesi Province; Gross Regional Domestic Product is one of the components that significantly affect the human development index

Fuzzy c-means and gath-geva methods in clustering districts based on human development index (hdi) in south sulawesi

District grouping in South Sulawesi based on the Human Development Index (HDI) indicators needs to be done as a material for planning and evaluating the targets of government work programs. This grouping is based on dominant indicators of the high and low HDI. The value of the HDI indicator needs to be considered so that the achievement of each indicator is known. Statistical analysis that can be used to group districts that have similarities is cluster analysis. The method that is currently developing is fuzzy clustering analysis, which classifies objects using certain membership degrees. Fuzzy clustering algorithm that can be used is Fuzzy C-means (FCM). Another method of fuzzy clustering analysis developed further is Gath Geva (GG), which is able to detect groups with different forms. In this study, the fuzzy clustering process on the FCM and GG methods with the same parameters and shows that the GG method is better than the FCM method. This conclusion is based on a total of 1000 iterations. The GG method gives an objective function value smaller than FCM, besides it gives a fasterconferencin

Cox Proportional Hazard Regression Analysis of Dengue Hemorrhagic Fever

Survival analysis is a statistical procedure used to analyze data in the form of time of the incident until an event occurs. The purpose of the survival analysis is to estimate the probability of survival, recurrence, death or other events until a certain period of time. .In this case, one of the regression method that can be used Cox Proportional Hazard (Cox PH) regression. Data used in this research is data of 70 patients Dengue Hemorrhagic Fever (DHF) in Makassar City Hospital. The results of analysis indicated that the factor that most affect the rate of healing DHF patients is platelet factor. The rate of recovery of patients with DHF with platelet counts below normal is 2,625 times the normal platelet count. Therefore, patients with dengue disease who have lower platelet counts tend to have a longer recovery rate than patients who have normal platelet counts

Spatial EBLUP dalam Pendugaan Area Kecil

Empirical Best Linear Unbiased Prediction (EBLUP) merupakan salah satu metode dalam pendugaan area kecil. Asumsi yang digunakan dalam EBLUP adalah bahwa pengaruh acak galat area saling bebas. Namun dalam beberapa kasus, asumsi ini sering dilanggar. Penyebabnya adalah keragaman suatu area dipengaruhi area sekitarnya, sehingga pengaruh spasial dapat dimasukkan ke dalam pengaruh acak. Akibat pelanggaran ini menyebabkan penduga EBLUP menjadi bias dan memiliki ragam yang besar. Solusi untuk mengatasi hal tersebut adalah dengan memasukkan informasi pengaruh spasial ke dalam model. Pendugaan area kecil yang memperhatikan pengaruh acak spasial area dikenal dengan istilah penduga Spatial Empirical Best Linear Unbiased Prediction (SEBLUP). Penduga SEBLUP memberikan pendugaan yang lebih baik dibandingkan dengan penduga EBLUP dengan membandingkan nilai ARRMSE dari masing-masing metode pendugaan