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Media Statistika

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Published by Universitas Diponegoro

ISSN : - EISSN : 24770647 DOI : -

Core Subject : Science,

Decision Sciences, Operations Research & Management

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Articles 271 Documents

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PENELUSURAN KERAGAMAN DALAM BLOK PADA RANCANGAN ACAK KELOMPOK DENGAN INTERGRADIEN Rahmawati, Rita
MEDIA STATISTIKA Vol 1, No 2 (2008): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Dalam Rancangan Acak Kelompok Lengkap (RAKL), asumsi terpenting adalah unit percobaan dalam blok harus bersifat homogen. Asumsi ini sulit dipenuhi jika ukuran blok terlalu besar. Penelitian ini bertujuan untuk menelusuri keragaman yang ada dalam blok dengan memasukkan unsur arah keragaman (baris atau kolom dalam blok) yang mungkin ada, sehingga analisis ragam yang kemudian dihasilkan akan memberikan keragaman galat yang lebih kecil. Penelusuran keragaman dengan cara ini disebut analisis Intergradien. Dalam penelitian ini digunakan data jumlah anakan produktif/rumpun yang diperoleh dari Balai Tanaman Padi Sukamandi dalam Penelitian Interaksi antara Genotipe dengan Lingkungan Galur Harapan Padi Sawah pada Agroklimat Utama. Hasil dari penelitian ini, juga dengan data simulasi, memberi kesimpulan bahwa analisis Intergradien dalam RAKL menghasilkan kuadrat tengah galat (KTG) yang lebih kecil daripada RAKL biasa. Tetapi karena unsur baris dan arah keragaman pada data jumlah anakan produktif/rumpun tidak berpengaruh nyata pada alpha 5%, maka digunakan RAKL biasa untuk menentukan varietas terbaik. Dengan RAKL, didapatkan IR71031 memiliki jumlah anakan produktif/rumpun yang paling besar.

ESTIMASI MODEL UNTUK DATA DEPENDEN DENGAN METODE CROSS VALIDATION Tarno, Tarno
MEDIA STATISTIKA Vol 1, No 2 (2008): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

This paper discuss about application of cross-validation method for modeling of dependent data. One of the data that categorized into dependent data is a time series. To construct the mathematical model for a time series data, we must have at least 50 series. In practices we often have some problem as long as we collect the time series data. So we donâ€™t get ideal data related to number of sample. To solve this problem, we can generate observation data. There are several methods that can be used to generate data such as cross-validation and bootstrap. Application of cross-validation method to generate time series data canâ€™t be done randomly, but we must generate the data based on balanced incomplete block design. The basic principle of cross-validation method is the data divided into two parts those are construction data and validation data. Construction data are drawn from observation data based on moving block and then we construct the model with Box-Jenkins method and verify the model with validation data. Do this process for different blocks as replication samples of cross-validation method, such that we can construct the best model that minimized loss function for prediction errors. Â Key words: time series data, estimate model, cross-validation

MODEL PREDIKSI CURAH HUJAN DENGAN PENDEKATAN REGRESI PROSES GAUSSIAN (Studi Kasus di Kabupaten Grobogan) Mukid, Moch. Abdul; Sugito, Sugito
MEDIA STATISTIKA Vol 6, No 2 (2013): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Forecasting method of rainfall has developed rapidly, ranging from the deterministic approach to the stochastic one. Deterministic approach is done through an analysis based on physical laws expressed in mathematical form, which identify the relationships between rainfall and temperature, air pressure, humidity and the intensity of solar radiation. Similarly, there are some stochastic models for the prediction of rainfall that have been commonly used, for instances, the model Autoregressive Integrated Moving Average (ARIMA), Fourier analysis and Kalman filter analysis. Some researchers about climate and weather have also developed a predictive model of rainfall based on nonparametric models, especially models based on artificial neural networks. Above models are based on classical statistical approach where the estimation and inference of model parameters only pay attention to the information obtained from the sample and ignore the initial information (prior) of parameter model. In this research, prediction model with Gaussian process regression approach is used for predicting the monthly rainfall. Gaussian process regression uses a stochastic approach by assuming that the amount of rainfall is random. Based on the value of Root Mean Square Error Prediction (RMSEP), the best covariance function that can be used for prediction is Quadratic Exponential ARD (Automatic Relevance Determination) with RMSEP value 123,63. The highest prediction of the monthly rainfall is in January 2014Â reached into 336,5 mm andÂ the lowest in August 2014 with 36,94 mm. Â Key Words: Gaussian Procces Regression, Covariance Function, Rainfall Prediction

PEMODELAN DATA INFLASI INDONESIA PADA SEKTOR TRANSPORTASI, KOMUNIKASI, DAN JASA KEUANGAN MENGGUNAKAN METODE KERNEL DAN SPLINE Suparti, Suparti; Tarno, Tarno
MEDIA STATISTIKA Vol 8, No 2 (2015): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In this research, we study data modeling of Indonesian inflation in theÂ transportation, communication and financial services sector using the kernel and spline models. Determination of the optimal models based on the smallest of GCVÂ value and determination of the best model based on the smallest out sampels of Mean Square Error (MSE) value. By modeling the yoy (year on year) inflation data in Indonesia in the transportation, communication and financial services sector In January 2007 to January 2015, shows that the kernel modelÂ using Gaussian kernel function obtained optimal model with a bandwidthÂ 0.24 and the optimal spline model with order 5 andÂ 4 points knots. Based on out sampels dataÂ in February to August 2015, obtained out sampelsÂ MSE value of the spline model is smaller than the kernel model. So that the spline model is better than the kernel modelÂ to analyzeÂ the inflation dataÂ of transportation, communication and financial services sector.Keywords: Inflation, Transportation, Communication and Financial Services Sector, Kernel, Spline, GCV, MSE.

ANALISIS KLASTER UNTUK SEGMENTASI PEMIRSA PROGRAM BERITA SORE STASIUN TV SWASTA Rosiatun, Aan; Widiharih, Tatik; Safitri, Diah
MEDIA STATISTIKA Vol 3, No 2 (2010): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

A procedure market segmentation is designing the market segmentation use the method of cluster k-means analyze which applied in process designing the market evening news audiences onÂ tv chanels. The process of grouping audiences into each segment whichÂ formed, based on likeness of characteristic owned and it formed 3 market segment evening news audiences, that is audiences group who give low evaluation, audiences group who give enough evaluation, and audiences group who give high evaluation. Result from the market segmentation with case study at Pangkah district Tegal regency got first cluster is 25.2 %, second cluster is 46 %, and third cluster is 28.8 %. Marketing strategy can target be old > 20 years because it has members total of cluster is biggest. The result can be used by a television company to determine marketing strategy. Â Keywords: Characteristic, Market Segmentation, Cluster K-Means Analysis

HAZARD PROPORTIONAL REGRESSION STUDY TO DETERMINE STROKE RISK FACTORS USING BRESLOW METHOD Sudarno Sudarno; Eri Setiani
MEDIA STATISTIKA Vol 12, No 2 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Cox proportional hazard regression is a regression model that is often used in survival analysis. Survival analysis is phrase used to describe analysis of data in the form of times from a well-defined time origin until occurrence of some particular be death. In analysis survival sometimes ties are found, namely there are two or more individual that have together event. The objectives of this research are applied Cox proportional hazard regression on ties event using Breslow methodand determine factors that affect survival of stroke patients in Tugurejo Hospital Semarang. The response variable is length of stay at hospital, and the predictors are gender, age, type of stroke, history of hypertension, systolic blood pressure, diastolic blood pressure, blood sugar levels, and body mass index. The factors cause stroke disease by significant are type of stroke, history of hypertension, systolic blood pressure, diastolic blood pressure, and blood sugar level. By the survivorship function that the patients have been looked after at hospital greater than 20 days, they have probability of healthy be little even go to death. A person in order to be healthy must notice and prevent some factors cause disease.

MODEL REGRESI COX PROPORSIONAL HAZARD PADA DATA KETAHANAN HIDUP Hanni, Tuan; Wuryandari, Triastuti
MEDIA STATISTIKA Vol 6, No 1 (2013): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

A lot of events occured in daily life are connected with survival time, for example a time interval that measure the failure of a product, time duration which is needed to recover from disease, the back pain recurred after treatment. Data about survival time duration of an event is called survival data. Survival data can not be observed completely that is called as sensored data. Cox proportional hazard model is employed to analyze and determine the survival rate from cencored data affected one or more explanatory variables. This model assummed that the hazard rate of group is proportional to the hazard rate of another group. In the paper, wants to the factor that affect the survival of patient with cervical cancer. From the result of data processing that affect are age and stadum with cox proportionl hazard model isÂ hi(t) = exp(-1.848U1i â€“ 1.584U2i â€“ 3.255S2i - 2.108S3i ) h0(t) Â Keywords : Cox Proportional Hazard, Survival Rate, Hazard Rate, Cervical Cancer

MODEL CURAH HUJAN EKSTREM DI KOTA SEMARANG MENGGUNAKAN ESTIMASI MOMENT PROBABILITAS TERBOBOTI Rusgiyono, Agus; Wuryandari, Triastuti; Rahmawati, Annisa
MEDIA STATISTIKA Vol 8, No 1 (2015): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The methods is used to analyze extreme rainfall is the Extreme Value Theory (EVT). One of the approaches of EVT is the Block Maxima (BM) which it follows the distribution of Generalized Extreme Value (GEV). In this study, the dasarian rainfall data of 1990-2013 in the Semarang City is divided based on block monthly and examined in October, November, December, January, February, March and April. The resulted blocks are 24 with 3 observations each block. Parameter shape, location and scale are estimated Â Probability Weight Moments (PWM) methodes The result of this study are January has the greatest occurrence chance of extreme value, estimated of parameter shape 0,3840564, location 138,8152989 and scale 68,6067117. In addition, the alleged maximum value of dasarian rainfall obtained in a period of 2, 3, 4, 5 and 6 years are 243,45753 mm, 308,23559 mm, 357,26996 mm, 397,96557 mm and 433,28889 mm respectively.Â Keywords: Rainfall, Extreme Value Theory, Block Maxima, Generalized Extreme Value, Probability Weight Moments

PELUANG ALUMNI PENDIDIKAN MATEMATIKA FKIP UMB DALAM MENDAPATKAN PEKERJAAN DENGAN MENGGUNAKAN ANALISIS REGRESI LOGISTIK Mahyudi Mahyudi
MEDIA STATISTIKA Vol 10, No 2 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Graduation or college graduation become the most exciting moment for a student. In addition to successfully get a degree, they are also eager to enter the workforce. But sometimes the spirit was lost in the middle of the road. Many fresh graduates complain of difficult to get a job at this time. Every year the number of graduates to grow while jobs are not directly proportional to the increase in the number of graduates. The study analyzed what are the chances of graduates Mathematics Education FKIP Muhammadiyah University of Bengkulu in getting a job. Samples taken as many as 78 graduates between September 2015 to April 2016. The factors considered were gender, age, GPA, national origin, jobs for college and the work areas as desired. Analysis of survey data using ordinal logistic regression analysis. The results showed that the dominant factors that affect the length of the graduates in getting a job is GPA, work experience in college and the desired field of work.

IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN Mukid, Moch. Abdul; Sugito, Sugito
MEDIA STATISTIKA Vol 4, No 1 (2011): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

This paper studies the implementation of Markov Chain Monte Carlo on estimating the hyperparameter of Gaussian process. Metropolish-Hasting (MH) algorithm is used to generate the random samples from the posterior distribution that can not be generated by a direct simulation method. This algorithm require only a proposal distribution for generating a candidate point. In this paper uniform distribution is choosen as the proposal distribution. Â Keywords: Markov Chain Monte Carlo, Gaussian Process, Metropolis-Hasting Algorithm

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