The major challenges on the statistical analysis of microarray data are the limited availability of samples, large number of measured variables and the complexity of distribution of the data obtained (e.g., multimodal). These phenomena could be considered in Bayesian method, used Bayesian Mixture Model (BMM) methods and Bayesian Model Averaging (BMA) methods. Modeling of Bayesian Mixture Model Averaging (BMMA) for microarray data was developed based on these two studies. One of the most important stages in BMMA is determination of the number of mixture components in the data setting as the most appropriate BMMA models. This paper proposes an algorithm for determining the number of mixture components in BMMA for microarray data. The algorithm is developed based on the simulation data generated from a case study of Indonesian and it has been implemented on the outside Indonesian microarray data. The results have succed to demonstrate two step algorithms, called Preliminary Process and Smoothing Process Algorithms, to the Indonesian case microarray data with the accuracy rate of 99.3690% and 99.9094% for the outside Indonesian microarray data.

The Bayesian Model Averaging (BMA) required the validation step to determine the accuracy of BMA model. Kolmogorov-Smirnov (KS) and Continuous Ranked Probability Score (CRPS) are used to validate the BMA model. The absolute difference between the empirical cumulative distribution and the hypothesis cumulative distribution were the basic idea of these methods. The KS method uses the distance concept and CRPS method uses the area concept. The validation of BMA model on microarray data by KS and CRPS methods would be identified in this paper. The results have succeed to indentify the performance of KS and CRPS in the validation to BMA model on microarray data with an average value of KS=0.469 and CRPS=0.211 for n=10 and then the value of KS=0.403 and CRPS=0.11 for n=12.

<p>Hipertensi merupakan penyakit degeneratif yang memerlukan pengobatan yang berkesinambungan untuk meminimalkan terjadinya komplikasi. Pengobatan hipertensi dapat dilakukan dengan berbagai cara salah satunya dengan menggunakan obat herbal. Penggunaan  obat herbal sangat bergantung pada pengetahuan, sikap, dan peran perawat agar penggunaan obat herbal dapat digunakan secara tepat dan benar. Penelitian ini merupakan penelitian kuantitatif dengan pendekatan C<em>ross </em><em>S</em><em>ectional</em><em> </em>yang bertujuan untuk mengidentifikasi tiga faktor penggunaan obat herbal hipertensi di puskesmas Putri Ayu Jambi dengan sampel berjumlah 82 orang. Pengambilan sampel dilakukan secara <em>proporsional random sampling</em>. Analisis data dilakukan secara <em>univariat </em>dan <em>bivariate.</em>Dari hasil uji statistik univariat diketahui sebanyak 47 (57,3%) responden menggunakan obat herbal,  sebanyak 49 (59,8%) memiliki pengetahuan rendah, sebanyak 44 (53,7%) memiliki sikap yang negatif dan sebanyak  47 (62,2%) mengatakan peran perawat kurang baik. Berdasarkan hasil analisis <em>bivariat </em>menunjukkan ada hubungan yang bermakna antara pengetahuan (<em>P value </em>0,011), sikap <em>P value </em>0,003 dengan penggunaan obat herbal dan tidak ada hubungan yang bermakna antara peran perawat dengan penggunaan obat herbal hipertensi dengan <em>P value </em>0,132.  Penelitian ini menunjukkan bahwa pengetahuan dan sikap masyarakat memiliki kontribusi terhadap penggunaan obat herbal pada pasien hipertensi sedangkan peran perawat tidak memiliki makna secara signifikan terhadap penggunaan obat herbal pada pasien hipertensi.</p><p> </p><p>Kata kunci:  Hipertensi, Herbal, Obat</p>

ABSTRAK

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<p><em>Prediabetes merupakan awal perjalanan penyakit diabetes mellitus yang tidak terdetekssi sejak dini karena tidak menimbulkan tanda dan gejala.  Namun dapat dicegah dengan mengendalikan faktor resiko seperti usia, obesitas dan aktifitasn fisik. Penelitian ini bertujuan untuk mengetahui hubungan usia, obesitas dan aktivitas fisik dengan kejadian Prediabetes di Wilayah Kerja Puskesmas Simpang IV Sipin Kota Jambi. Penelitian ini merupakan penelitian kuantitatif dengan menggunakan desain penelitian cross sectional, populasi dalam penelitian ini adalah seluruh penduduk yang berusia 18-59 tahun di wilayah kerja Puskesmas Simpang IV Sipin Kota Jambi   dengan jumlah sample sebanyak 52 responden, cara pengambilan sample menggunakan Purposive Sampling. Berdasarkan penelitian diketahui bahwa sebagian besar responden mengalami prediabetes (59,6%), memiliki usia&lt;45 tahun (73,1%), mengalami obesitas dengan IMT≥25 (57,7%), dan memili aktivitas fisik ringan (46,2%) dan diketahui ada hubungan yang bermakna antara usia (0,008), obesitas (0,000), dan aktivitas fisik (0,006) dengan kejadian prediabetes.<strong> </strong>Dengan adanya penelitian ini diharapkan dapat dilakukannya program skrining prediabetes agar orang yang mengalami prediabetes tidak berlanjut menjadi DM.  </em></p><p><em>  </em></p><p><em>Prediabetes is the beginning of the course of diabetes mellitus which is not detected early because it does not cause signs and symptoms. But it can be prevented by controlling risk factors such as age, obesity and physical activity.</em><em> </em><em>This study aims to determine the relationship of age, obesity and physical activity with Pre-diabetes incidence in Puskesmas Simpang IV Sipin city of Jambi. This research is a quantitative study using cross sectional study design, population in this study is the entire population aged 18-59 years in Puskesmas Simpang IV Sipin Jambi with a random sample of 52 respondents, how sampling using purposive sampling. Based on the research showed that most respondents had prediabetes (59.6%), had aged &lt;45 years (73.1%), obese with IMT≥25 (57.7%), and elect the light physical activity (46 , 2%) and it is known there is a significant correlation between age (0,008), obesity (0,000) and physical activity (0.006) and the incidence of prediabetes. With this study are expected to do prediabetes screening program for people who have prediabetes do not continue to be a DM.</em><em></em></p>

AbstrakKontrol glukosa darah dapat dilakukan dengan terapi farmakologi dan tanaman berkhasiat obat atau herbal. Obat herbal yang mempunyai efek hipoglikemik salah satunya adalah biji mahoni yang berfungsi sebagai astrigen menghambat asupan glukosa dan laju peningkatan glukosa darah. Penelitian ini bertujuan untuk mengetahui pengaruh biji mahoni terhadap kadar glukosa darah pada penderita diabetes melitus tipe II, dengan desain penelitian adalah quasi eksperimental ''Pre and Post-Test Control Group Design'', pada desain ini responden penelitian dibagi menjadi dua kelompok. 34 responden kelompok intervensi, dan 34 responden kelompok kontrol sebagai pembanding. Pengumpulan data dilakukan dengan pemeriksaan kadar glukosa darah pre dan post perlakuan, lembar observasi dan hasil penelitian dianalisis secara univariat dan bivariat dengan menggunakan uji Wilcoxon.Hasil penelitian menunjukkan sebanyak (100%) responden sebelum dilakukan intervensi dan pemberian glibenklamide dengan kadar glukosa darah > 200 mg/dl. Sebanyak (85,3%) responden sesudah intervensi dengan nilai kadar glukosa darah 90-199 mg/dl. Dari analisis bivariat terdapat pengaruh biji mahoni terhadap kadar glukosa darah dengan nilai pvalue = 0,000 (p<0,05). Biji mahoni lebih berpotensi menurunkan kadar glukosa darah dibandingkan dengan glimepiride dengan beda rerata median 17,5 mg/dl. '', in Kata Kunci: Biji Mahoni, Glukosa Darah, Diabetes Melitus Tipe II Abstract Glycemic control can be performed by pharmacological therapy and herbs medicine. One of herbs medicine have a hypoglycemic effect which is mahogany seeds that serves as astrigentinhibiting glucose intake and the rate of increase in blood glucose. This study aims to determine the effect of mahogany seeds on blood glucose levels in people with type II diabetes mellitus, Designof this research is quasi-experimental '' Pre and Post Test Control Group Design

Abstract. Bayesian statistics proposes an approach that is very flexible in the number of samples and distribution of data. Bayesian Mixture Model (BMM) is a Bayesian approach for multimodal models. Diabetes Mellitus (DM) is more commonly known in the Indonesian community as sweet pee. This disease is one type of chronic non-communicable diseases but it is very dangerous to humans because of the effects of other diseases complications caused. WHO reports in 2013 showed DM disease was ranked 6th in the world as the leading causes of human death. In Indonesia, DM disease continues to increase over time. These research would be studied patterns and would be built the BMM models of the DM data through simulation studies where the simulation data built on cases of blood sugar levels of DM patients in RSUD Saiful Anwar Malang. The results have been successfully demonstrated pattern of distribution of the DM data which has a normal mixture distribution. The BMM models have succeed to accommodate the real condition of the DM data based on the data driven concept. IntroductionWhen a set of real data observed have a very small amount and a multimodal distribution then it is necessary need specially handling. The Bayesian statistics proposes an approach that is very flexible in the number of samples and distribution of data. These approach is based directly on the posterior distribution of the data. Therefore Bayesian approach can accommodate the real condition of the data based on the data driven concept and [5]). Bayesian Mixture Model (BMM) is one model that uses a Bayesian approach for multimodal models and its parameter models is seen as random variables in the model parameter space [6].Various studies have previously been carried out by BMM modeling. The modeling of BMM for the DM data in Surabaya is the research that has been done by [7] and the research of [8] has been conducted for the DM data in Malang by BMMA modeling. Some of the BMM research in the other field, among others [9] and [10]. Modeling of cases is very important in order to know the exact model and can be used for decision making in accordance with the cases observed [11].