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ANALISIS KECELAKAAN LALU LINTAS DI KOTA SEMARANG MENGGUNAKAN MODEL LOG LINIER Wilandari, Yuciana; Sugito, Sugito; Silvia, Candra
MEDIA STATISTIKA Vol 9, No 1 (2016): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Traffic accident is an event in the unanticipated and unintended involve vehicles with or without other road users, resulting in losses and/or loss of property. According Polrestabes Semarang number of traffic accidents decreased in 2014 compared to 2013, but the figure is still considered high. Therefore we need an analysis of traffic accident cases, in this case using a log linear models. Log linear models used to analyze the relationship between the response variables that are categories that make up the contingency table and determine which variables are likely to cause depedensi. In this study, the variable used is the severity of the victim, the type of accident, the role of the victim, the victim vehicle type, time of the accident and the age of the victim. The results indicate that the variables that affect the model is the severity of the victim, the type of accident, the role of the victim, the type of vehicle the victim, time of the accident, the age of the victim, the role of the victim * type of vehicle the victim, the type of accident * the role of the victim, the type of vehicle the victim * age of the victim, the type of accident * type of vehicle the victim, the severity of the victim * type of accident, type of accident * age of the victim. So that raises the most variable attachment is a type of accident.Â Keywords : Traffic Accident, Log Linear Model

DISTRIBUSI INVERS GAMMA PADA INFERENSI BAYESIAN Sugito, Sugito; Ispriyanti, Dwi
MEDIA STATISTIKA Vol 3, No 2 (2010): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

One of the methods which can be used in statistical inferencesÂ is Bayesian inference. It is combine sample distribution and prior distribution, that can be resulted posterior distribution. In this article, sample distribution use univariate normal distribution. If prior distribution for variance with known mean is gamma inverse distribution, then posterior distribution is formed gamma inverse distribution. If Prior distribution use non-informative prior, then have the posterior distribution, by theÂ marginal distribution of mean and varian. Also posterior distribution formed by gamma inverse distribution. Â Keywords: Gamma Inverse Distribution, Posterior Distribution, Non-Informatif Prior

MODEL ANTREAN NORMAL DAN TRIANGULAR (Studi Kasus : Gerbang Tol Tembalang Semarang) Sugito, Sugito
MEDIA STATISTIKA Vol 10, No 2 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The growing number of vehicle in each year resulting an inevitable congestion, one of them is jamming vehicle transaction in Tembalang toll gate. This condition can cause dissatisfaction to the toll road users in obtaining services. It is need to be specified the appropriate queue system model to the conditions of service in Tembalang toll gate. So it can be determined the number of booth service is working optimally. Based on the data analysis obtained from the Arena software, the queue system model that can describe the conditions of service at Tembalang toll gates with data total- time, time-total, and time-time the direction of Srondol-Jatingaleh at the regular toll booth is (Norm/G/2):(GD/âˆž/âˆž), (G/Norm/2): (GD/âˆž/âˆž), (G/G/2): (GD/âˆž/âˆž) and at the automatic toll booth is (G/Tria/3): (GD/âˆž/âˆž), (Tria/G/3): (GD/âˆž/âˆž), (G/G/3): (GD/âˆž/âˆž) while with the direction of Jatingaleh-Srondol at the regular toll booth is (Norm/G/3): (GD/âˆž/âˆž), (G/Norm/3): (GD/âˆž/âˆž), (G/G/3): (GD/âˆž/âˆž) and (G/Tria/2): (GD/âˆž/âˆž),Â (Tria/G/2): (GD/âˆž/âˆž), (G/G/2): (GD/âˆž/âˆž) at automatic toll booth.

ESTIMASI PARAMETER DISTRIBUSI WEIBULL DUA PARAMETER MENGGUNAKAN METODE BAYES Hazhiah, Indria Tsani; Sugito, Sugito; Rahmawati, Rita
MEDIA STATISTIKA Vol 5, No 1 (2012): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Interval estimation of a parameter is one part of statistical inference. One of the methods that used is the Bayes method. A Bayesian method is combine prior distribution and distribution of samples, so that the posterior distribution can be obtained. Interval estimation using a method Bayes called credibel interval estimation. In this thesis, the distribution of the sample is used a two-parameter Weibull distribution scale-shape-version of survival distribution (reliability). Data that used are data that is not censored data type and data type II censored if prior distribution using non-informative which of the produce distribution the resulting posterior distribution is gamma distribution. Parameters of the sample distribution that to find out is a parameter that Â by the parameter c (shape parameter) known while the parameter b (scale parameter) had unknown. Keywords: Bayes Method, Two-Parameters Weibull Distribution , Gamma Distribution, The Estimated Credible Interval.

ANALISIS SISTEM ANTRIAN KERETA API DI STASIUN BESAR CIREBON DAN STASIUN CIREBON PRUJAKAN Sugito, Sugito; Fauzia, Marissa
MEDIA STATISTIKA Vol 2, No 2 (2009): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Queue system is a group of customer, service, and some rules to regulate arrival customers. Queue happened if a customers which need a serve more than service capacity. Phenomenon queue will find easily in public facility. One of is trainÂ queue at Cirebon Main Train StationÂ and Cirebon Prujakan Train Station. Queue happened from train awaiting to be ridden away and from train which would to go to station, so that makes sometimes inappropriate arrival and departure the train of schedule resulting cumulative of train passenger candidate. To analyseÂ problems of train queue happened in station Cirebon can be applied the application of the queue theory. The steps must to do is by to create the examination where the queue happened. Based on those analysis can be known queue model and performance measure of queue system. And from data analysis can get two best kind of model for service system at Cirebon Main Train Station, that is (M/M/1):(GD/âˆž/âˆž) and (G/G/3):(GD/âˆž/âˆž). And two model service system at Cirebon Prujakan Train station, that is (M/G/2):(GD/âˆž/âˆž) and (M/G/1):(GD/âˆž/âˆž). Â Keywords : Queue System, The Cirebon Station, Queue Model

PROSES ANTRIAN DENGAN KEDATANGAN BERDISTRIBUSI POISSON DAN POLA PELAYANAN BERDISTRIBUSI GENERAL Sugito, Sugito; Hoyyi, Abdul
MEDIA STATISTIKA Vol 6, No 1 (2013): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In the queuing process,Â Â the distribution testing is performed to obtain the distribution of arrival and service distributions. Customer arrival distribution is obtained based on the number of arrivals or inter-arrival time. Service distribution is obtained based on the number of arrivals or inter-arrival time. In this paper we will discuss the process in queuing with the arrival of the Poisson distribution and the general pattern of service distribution Â Keywords : Queuing,Â Arrival Distribution, Service Distribution

DISTRIBUSI POISSON DAN DISTRIBUSI EKSPONENSIAL DALAM PROSES STOKASTIK Sugito, Sugito; Mukid, Moch Abdul
MEDIA STATISTIKA Vol 4, No 2 (2011): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In the queueing system, the processes usually come from a Poisson process. In this system should be obtained an arrival distribution and a service distribution. This paper studies about the form of the number of arrival distribution, the number of service distribution, the interarrival distribution and the service time distribution. Futhermore it talks about the relation of them to a Poisson distribution andÂ an exponential distribution. Â Keywords: Poisson Process, Poisson Distribution, Eksponential Distribution

MODEL EKSPONENSIAL GANDA PADA PROSES STOKASTIK (STUDI KASUS DI STASIUN PURWOSARI) Sugito, Sugito; Wilandari, Yuciana
MEDIA STATISTIKA Vol 8, No 1 (2015): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In general, mathematical modeling is divided into two, namely the model of deterministic and stochastic models. On stochastic modeling involves several processes among them are the Poisson process, the process of Bernoulli, Gaussian processes, the process of renewal and other processes. Specifically for the Poisson process often found in modeling queuing theory. At Poisson process there are four kinds of sub model that can be formed that is Double Poisson models, Exponential Poisson models, Poisson Exponential model, and Double Exponential models. In this paper will discuss the Double Exponential model in stochastic processes , specifically for the Poisson process. Analysis was performed on the data arrival time and service time. The model is a model (M / M / c) : ( GD / ~, ~) which is a double exponential model in stochastic processes.Â Keywords: Double Exponential, Poisson Process, Stochastic Process

PENENTUAN MODEL ANTRIAN BUS ANTAR KOTA DI TERMINAL MANGKANG Ispriyanti, Dwi; Sugito, Sugito
MEDIA STATISTIKA Vol 5, No 2 (2012): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In daily activities, we often face in a situation of queueing. The Queue is dull. Most people have experienced in a queue situation or a waiting situation. It Â is Â a part of the state that occurs in a series of operations that are random in a service facility. The Queue can be found easily in a human life, for example bus queue in Terminal Mangkang. It means that a bus wait to be dispatched and from the bus that will go to the service station. Therefore make an arrival and departure of buses not on schedule which resulted in the accumulation of customers in the terminal. To analyze the extent of the effectiveness of terminal Mangkang particularly inter-city terminal Queue theory it is used in the service system in the terminal. Â Keywords: Queue, Terminal Mangkang Â

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

Co-Authors Abdul Hoyyi Abu Suud, Abu ADIN ARIYANTI DEWI Agum Prafindhani Putri, Agum Prafindhani Agung, Yosep Roro Agus Rusgiyono Ainiyah, Luluk Qurrotul Alan Prahutama Alan Prahutama AlFath, Ayatullah Muhammadin Allsabah, M. Akbar Husein AllSabah, Muhammad Akbar Husein Anggraini, Anggun Nur Anisa Alfiani Rahayu Arham Arham, Arham Arif Widagdo Ayu Nurdiana, Fitria Bastian, Antoni Bilalodin Bilalodin Budi Warsito Burstiando, Rizki Candra Silvia, Candra Caprityan, Revin Dewi Novitasari Di Asih I Maruddani Dwi Ispriyanti Dwi Rohmadiani, Linda Erma Kusumawardani Erwin Erwin Fadrial Karmil Fahra Pracendi Astrelita, Fahra Pracendi Firdaus, Mokhamad Hartono Hartono Hasbi Yasin Hati Wau, Kerinus Hermawanto, Ifan Indah Nurhayati Indra Permana Jati Indria Tsani Hazhiah Ipung Permadi Irnani, Christina Krismayasari, Damiyana Kurniawati, Galuh Nurvinda Luksmana, Roby Lutfia Septiningrum, Lutfia Made S, Desak Makmur, Ali Marissa Fauzia Marlina, Amalia Dwi Merlia Yustiti Moch Abdul Mukid Moch. Abdul Mukid Muhammad Al Kholif Muhammad Zulhilmi Nastiti, Wahyuningsih Nazaruddin A. Wahid Nia Puspita Sari Nisa, Mukrimatun Novia Rahmawati NURLIANA NURLIANA Oesman, Nastiti Maharani Pratama, Budiman Agung Puji Rahayu Puji Yanti Fauziah Pujiono Pujiono Pungut, Pungut Purwanto A T, Purwanto A Putra, Rendhitya Prima Rachim, Febyani Ratnawati, Rhenny Razali Daud Richy Priyambodo Rita Rahmawati Roslizawaty Roslizawaty, Roslizawaty Rukun Santoso Samadi Samadi Sanitoria Nadeak, Sanitoria Santi, Fitta Ummaya Saputri, Ani Funtika Sehah Sehah Sinta Maulida Hapsari, Sinta Maulida Siti Julaeha, Siti Siti Komariyah Sitomurang, Rosalina Aprilda Slamet Junaidi Sofia Naning Hertiana Subandowo, Marianus Sudarno Sudarno Sukanianto, Eko Adyan Suparti Suparti Susilowati Susilowati Sutismawati Sirait, Lincaria Switarto, Bambang Syafruddin Syafruddin Tarno Tarno Tika Nur Resa Utami, Tika Nur Resa Triastuti Wuryandari Tristanti Tristanti Tristiana, Dwi Sari Wahyuni, Sigma Wati, Dewi Ayu Trisno Wihantoro Wihantoro Yuciana Wilandari Yulia Agnis Sutarno Yulingga Nanda Hanief Yusak Maryunianta Zainuddin Zainuddin Zaroh Irayani

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