Penelitian ini dilakukan untuk mengetahui ukuran ketepatan kuesioner yang mengukur tingkat partisipasi politik masyarakat Kota Padang dengan menggunakan uji validitas dan uji reliabilitas. Uji validitas dilakukan untuk mengetahui instrumen atau pertanyaan dalam kuesioner benar-benar mengukur apa yang hendak diukur. Uji reliabilitas adalah pengujian indeks yang menunjukkan sejauh mana kuesioner dapat dipercaya atau diandalkan. Teknik pengambilan contoh acak yang digunakan dalam penelitian ini adalah pengambilan contoh acak gerombol bertahap. Kemudian untuk mendapatkan hasil penelitian, untuk uji validitas digunakan korelasi product moment sedangkan untuk uji reliabilitas digunakan formula cronbach’s alpha (α). Penelitian ini menghasilkan nilai validitas untuk semua pernyataan yang digunakan dalam kuesioner menghasilkan nilai validitas lebih besar dari rtabel yang bernilai 0,210 dan berdasarkan uji reliabilitas diperoleh nilai cronbach’s alpha (α) sebesar 0,90. Nilai ini lebih besar dari 0,6. Hal ini berarti kuesioner yang digunakan sudah reliabel. Dengan demikian pada penelitian ini membuktikan bahwa kuesioner yang digunakan untuk mengukur tingkat partisipasi politik masyarakat Kota Padang sudah valid dan reliabelKata Kunci: validitas, reliabilitas, partisipasi politik

The characteristics of diurnal variation of precipitation in terms of amount (PA), frequency (PF), and intensity (PI) over Sumatra have been investigated using rain‐gauge data from 186 stations. Mean PA and PF show spatial variations significantly affected by the terrain elevation and stations' distance to the west coastline of Sumatra. A slightly larger PA and PF appear over the middle and western sections of the Barisan mountains, in which the mean PI is smaller in these regions. Most stations with large rainfall amount also have large rainfall frequencies, indicated by a strong correlation between PA and PF. The timing of the diurnal peak of PA, PF, and PI also has prominent regional characteristics. The cluster analysis reveals different grouping of stations with distinctive diurnal peaks. The prevailing afternoon and early‐evening peaks, that is, 1500–2000 LST, appear mostly over mountain ranges where amplitude of PA and PF tended to increase with elevation. Moreover, the amplitude of diurnal cycles tended to decrease as distance from the Sumatra's west coastline increases. On the western side of Barisan's mountain range, high amplitude of diurnal cycle prevails compared to the eastern side. We also found a strong relationship between rain event duration with diurnal cycle pattern. Generally, rain event with a long duration tended to have a peak occurring at a later time compared with those events of shorter duration. The diurnal variation of precipitation corresponds to the temporal evolution of the low‐level convergences and wind vectors, and cloud migration modulated by land‐sea breeze system.

This study aims to model factors affecting HDI (Human Development Index) in North Sumatra at 2015 using ridge regression method. We use ridge regression method because in the IPM data there is a multicolinearity problem. Ordinary least squares, as regression method commonly used in statistical modeling, cannot be applied in this case. This study makes the comparison between the use of OLS and the ridge regression method to the HDI data. This study proves that the ridge regression method produces better model and can solve the problem of multicolinearity case in data, while the OLS method can not. The significant factors that effecting the HDI at North Sumtera in 2015 are Total expenditure / capita / month ( 4 ) and Average school length ( 5 ). The indicator of the goodness of fit for the proposed model 81.81% which means that the model is good and could be accepted.

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The purposes of this paper is  to introduce the ability of the Bayesian quantile regression method in overcoming the problem of the nonnormal errors using asymmetric laplace distribution on simulation study. <strong>Method: </strong>We generate data and set distribution of error is asymmetric laplace distribution error, which is non normal data.  In this research, we solve the nonnormal problem using quantile regression method and Bayesian quantile regression method and then we compare. The approach of the quantile regression is to separate or divide the data into any quantiles, estimate the conditional quantile function and minimize absolute error that is asymmetrical. Bayesian regression method used the asymmetric laplace distribution in likelihood function. Markov Chain Monte Carlo method using Gibbs sampling algorithm is applied then to estimate the parameter in Bayesian regression method. Convergency and confidence interval of parameter estimated are also checked. <strong>Result: </strong>Bayesian quantile regression method results has more significance parameter and smaller confidence interval than quantile regression method. <strong>Conclusion: </strong>This study proves that Bayesian quantile regression method can produce acceptable parameter estimate for nonnormal error.

The new distribution is constructed by generating random variables from an exponential distribution with stabilizer constant. It is presented the convolution from this identically and independent new random variable by using analytical methods in the form of probability density function and cumulative distribution function. In addition, it is presented some properties of the exponential distribution with stabilizer constant and its convolution including mean, variance, moment generating function, characteristic function, skewness and kurtosis.

Abstrak. Portofolio merupakan kumpulan dari beberapa investasi saham. Portofolioterbaik adalah portofolio dengan mean return dan risiko saham yang terbaik. Salah satumetode dalam mengukur nilai risiko adalah dengan Value at Risk (VaR). VaR didenisikansebagai tingkat kerugian maksimal atau return minimal pada tingkat kepercayaanyang cukup tinggi untuk waktu tertentu. Jika seorang investor membentuk portofoliomaka berarti investor menentukan proporsi dana yang diinvestasikan pada masingmasingsaham. Investor menginvestasikan dana pada masing-masing saham dengan totalproporsi dana adalah 1. Permasalahan dalam menghitung proporsi dana dapat menggunakanmetode Pengganda Lagrange. Dari 33 saham Perbankan yang terdaftar padaBursa Efek Indonesia didapat komposisi portofolio yang terdiri dari Bank DanamonIndonesia Tbk, Bank Mandiri (Persero) Tbk dan Bank CIMB Niaga Tbk. Dari ketigasaham diperoleh proporsi investasi masing-masing dana yaitu 19,76% Bank DanamonIndonesia Tbk, 60,34% Bank Mandiri (Persero) Tbk dan 19,90% Bank CIMB Niaga Tbk.Dari portofolio yang terbentuk didapat nilai risiko yaitu 0,001345. Hal ini berarti risikodari portofolio yang terbentuk sangat kecil yaitu 0,13% sehingga aman bagi investordalam berinvestasi.Kata Kunci: Portofolio, Value at Risk, Pengganda Lagrange, Risiko