Peramalan Data Runtun Waktu menggunakan Model Hybrid Time Series Regression – Autoregressive Integrated Moving Average

Forecasting is a method used to estimate or predict a value in the future using data from the past. With the development of methods in time series data analysis, a hybrid method was developed in which a combination of several models was carried out in order to produce a more accurate forecast. The purpose of this study was to determine whether the TSR-ARIMA hybrid method has a better level of accuracy than the individual TSR method so that more accurate forecasting results are obtained. The data in this study are monthly data on the number of passengers on American airlines for the period January 1949 to December 1960. Based on the analysis, the TSR-ARIMA hybrid method produces a MAPE of 3,061% and the TSR method produces an MAPE of 7,902%.

Perbandingan Metode Bootstrap, Jacknife Jiang Dan Area Specific Jacknife Pada Pendugaan Mean Square Error Model Beta-Bernoulli

Small area estimation is defined as a statistical technique for estimating the parameters of a subpopulation with a small sample size. One method of estimating small area parameters is the Empirical Bayes (EB) method. The accuracy of the Empirical Bayes (EB) estimator can be measured by evaluating the Mean Squared Error (MSE). In this study, 3 methods to determine MSE in the EB estimator of the Beta-Bernoulli model will be compared, namely the Bootstrap, Jackknife Jiang and Area-specific Jackknife methods. The study is carried out theoretically and empirically through simulation with R-studio software version 1.2.5033. The simulation results in a number of areas and pairs of prior distribution parameter values, namely Beta, show the effect of sample size and parameter value pairs on the Mean Square Error (MSE) value. The larger the number of areas and the smaller the initial 𝛽, the smaller the MSE value. The area-specific Jackknife method produces the smallest MSE in the number of areas 100 and the Beta parameter value 0.1.

Perbaikan Citra Menggunakan Metode Contrast Stretching

Contrasting images that are not good because they are too bright or too dark cannot provide good information. Therefore, a method is needed to improve the image quality, so that the information in the image can be conveyed properly. Contrast stretching is one of the methods for improving image quality. With this method is expected to produce a new image that is better. The purpose of this research is to apply contrast stretching method to an application or software that can be used to improve image quality. Data used in this study in the form of grayscale image data and RGB imagery (true color), with the format . BMP or .JPG, while the application development uses the Matlab programming language.The results of the study, contrast stretching method can be used to repair image that affects bad or poor image quality such as too bright / dark image, less sharp image, blurry, and so on. Contrast stretching method can also be used to improve image enhancement by leveling the histogram that was collected in an area, so that the information contained in the image is more clearly visible compared to the original image.

Hubungan Antara Kelembaban Relatif Dengan Beberapa Variabel Iklim Dengan Pendekatan Korelasi Pearson di Samudera Hindia

The earth's climate is constantly changing, it's just that climate change in the past took place naturally. But until now, climate change has been very closely related to human activity, so the nature of the event has become faster and more drastic. Relative humidity is a parameter that can affect climate change in Indonesia, especially in Aceh Province. Aceh province is one of the provinces located on the island of Sumatra and directly facing the Indian Ocean. Thus, Aceh Province has a considerable impact on climate change. Changes in relative humidity will lead to changes in climate elements. There are several climate elements including air temperature, rainfall, sea surface temperature, wind speed, solar radiation, and dynamic altitude. One of the methods used to look at the relationship of each climate element is the Correlation method. The purpose of this study is to find out the relationship of each variable of the climate elements. The results showed that the relationship between variables X1 (air temperature) and X3 (sea surface temperature) had the highest closeness relationship with a positive correlation value of 0.77. The lowest closeness relationships are variables X2 (rainfall) and X4 (wind speed) with a negative weak correlation value of -0.01.

Penerapan Model Geographically Dan Temporally Weighted Regression Pada Kecelakaan Lalu Lintas

Geographically and temporally weighted regression (GTWR) is a model that is used to deal with instability in data both spatially and temporally and to produce local parameters. In this paper, The GTWR model is used to analyze the factors that are thought to significantly influence the number of traffic accidents in Mempawah Regency. The data used in this study came from 8 districts with the variables used were the number of traffic accidents, the number of population (gender ratio, length of damaged road conditions, and percentage of adolescence. The parameter estimation of the GTWR model was obtained using the weighted least square (WLS) method. The optimal bandwidth selection uses the Cross-Validation (CV) method and the weighting used is the Fixed bisquare function. The results of the analysis show that using the GTWR model, it was found that only the population size variable significantly affected the number of traffic accidents in all locations in Mempawah Regency from 2015 to 2018. The GTWR model was known to be better than the multiple regression model because it produced smaller AIC and RSS values and a larger R-square value.

SEKITAR OPERATOR DAN MATRIKS LAX ( LAX PAIR ) UNTUK PERSAMAAN GELOMBANG AIR TIPE KdV

Operator dan Matriks Lax Pair merupakan operator dari sebuah persamaan diferensial parsial non linier yang dapat digunakan untuk merubah persamaan diferensial parsial dalam bentuk system persamaan diferensial biasa. Persamaan yang diperolehan akan memudahkan seseorang untuk mencari solusi dari persamaan diferensial tersebut. Dalam paper ini akan dibahas tentang penentuan operator Lax Pair dan Matriks Lax Pair dari sebuah sebuah persamaan gelombang air tipeKdV. Pencarian operator Lax Pair dimulai dengan menentukan bobot dari masing-masing suku menggunakan penskalaan invariant pada setiap variable persamaan dalam persamaan KdV yang diberikan. Selanjutnya, operator Lax Pair dibentuk berdasarkan asumsi dari bobot yang dihasilkan. Dengan menggunakan definisi operator Lax Pair maka operator yang dicari dapat ditemukan. Matriks Lax Pair dari persamaan KdV dapat dicari menggunakan konversi dari operator yang dihasilkan. Dengan menggunakan definisi matrik Lax Pair, dan melalui operasi aljabar biasa dapat dihasilkan matriks Lax Pair

SIMULASI PEMILIHAN METODE ANALISIS CLUSTER HIRARKI AGGLOMERATIVE TERBAIK ANTARA AVERAGE LINKAGE DAN WARD PADA DATA YANG MENGANDUNG MASALAH MULTIKOLINEARITAS

Multikolinearitas adalah hubungan linear yang ada di antara variabel independen, pada analisis klaster efek yang ditimbulkan oleh multikolinearitas berbeda, dikarenakan pada dasarnya multikolinearitas adalah bentuk pembobotan implisit. Analisis komponen utama dapat digunakan untuk mereduksi jumlah himpunan peubah yang banyak dan saling berkorelasi menjadi peubah-peubah baru yang tidak berkorelasi dengan mempertahankan sebanyak mungkin keragaman data tersebut, dengan menggunakan hasil analisis komponen utama dilakukan analisis klaster menggunakan metode average linkage dan Ward, yang kemudian akan dipilih metode terbaiknya berdasarkan nilai indeks Dunn dan indeks RS, didapat kesimpulan bahwa metode Ward adalah metode terbaik dibandingkan average linkage yang ditinjau berdasarkan indeks RS, sedangkan dengan menggunakan indeks Dunn didapatkan kesimpulan bahwa metode average linkage adalah metode terbaik dibandingkan Ward.

Desain dan Analisis Geometri Propellant Grain Configuration pada Roket Padat

This article examine mathematical model of propellant grain configuration to obtain the appropriate burning area in sonda rocket. Sonda roket is experimental rocket that created by Pustekroket LAPAN to support research on space sector with altitude as the target of assessment. Burning area for hollow grain, wagon wheel grain, star grain are analysed analytically through mathematical modelling. Than the results are compared by manual calculation using SolidWork. The results show that burning area of three types of grain did not show a significant difference between these two methods.

Pemodelan Regresi Nonparametrik Spline Linear Persentase Penduduk Miskin di Kalimantan

Poverty is a social problem faced in almost every country. Based on BPS data published in 2018, East Kalimantan Province has a population of poor people of 222.39 thousand people or around 6.06 percent. In March 2018, the number of poor people was 218.90 thousand people or about 6.03 percent, which means the number of poor people had increased by an absolute 3.49 thousand people, this caused the percentage of poor people to rise 0.03 percent. In this study identified factors that influence the percentage of poor population using a linear spline nonparametric regression model. The data used in this study are data from the Central Statistics Agency (BPS) in 5 provinces in Kalimantan. In the nonparametric linear spline regression method using the optimal knot point based on the smallest GCV value. The results obtained an R2 value of 74.48% which shows that the model formed is feasible to be used to model the data pattern and there are 5 variables that have a significant effect on the Percentage of Poor Population, namely Population Growth Rate, School Length Average, School Old School Expectancy Rate, Level Open Unemployment, Labor Force Participation Rate.