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PENENTUAN MODEL DAN UKURAN KINERJA PROSES ANTRIAN PADA UNIT PELAYANAN TEKNIK DINAS PUSKESMAS LIMBANGAN KABUPATEN KENDAL Fatkhan Arissetya; Sugito Sugito; Sudarno Sudarno
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (335.937 KB) | DOI: 10.14710/j.gauss.v3i3.6447

Abstract

The UPTD (Unit Pelayanan Teknik Dinas) of Local Government Clinic of Limbangan in Kendal Regency is the only health-service in Limbangan Sub-district although there is another health-service such as doctors and midwifes. Since there are many people coming to the Local Clinic of Limbangan, it causes quite long queue. Therefore, it is needed to analyze the queuing model to finding out the system of the activity measure, so it can be concluded the queuing description and the service. If the distributrion of the arrival or the service is poisson or exponential, so the model is Markovial (M). However, if the distribution is not poisson or exponential, so the model is General (G). The queuing model of outpatients includes Regristrtion-Counter (M/G/1):(GD/∞/∞) , Medical Service (M/M/3):(GD/∞/∞)  and Medicine-Counter (M/G/1):(GD/∞/∞). Meanwhile, the queuing model of hospitalized patients covers Hospitalized Rooms (M/M/16):(GD/∞/∞) and Payment Counter (M/G/1):(GD/∞/∞). It has been found out the best queue from the analysis in UPTD Local Government Clinic of Limbangan that is registration counter because the service time is quick and there are few queuing patients, so it won’t be hoarding
KETEPATAN KLASIFIKASI STATUS KERJA DI KOTA TEGAL MENGGUNAKAN ALGORITMA C4.5 DAN FUZZY K-NEAREST NEIGHBOR IN EVERY CLASS (FK-NNC) Atika Elsadining Tyas; Dwi Ispriyanti; Sudarno Sudarno
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (379.616 KB) | DOI: 10.14710/j.gauss.v4i4.10127

Abstract

Unemployment is a very crucial problem that always deal a developing country and affected a national foundation. It used two methods for classifying a employment status on productive society in Tegal City on August 2014, the methods are C4.5 Algorithm and Fuzzy K-Nearest Neighbor in every Class (FK-NNC). C4.5 Algorithm is a way of classifying methods from data mining that use to construct a decision tree. FK-NNC is another classification technique that predict using the amount of closest neighbor of K in every class from a testing data. The predictor variables that used on classifying an employment status are neighborhood status, sex, age, marriage status, education, and a work training. To evaluate the result of classification use APER calculation. Based on this analysis, classification of employment status using C4.5 Algorithm obtained APER = 28,3784% and 71,6216% of accuracy, while FK-NNC methods obtained APER = 21,62% and 78,38% of accuracy. So, it can be concluded that FK-NNC is better than C4.5 Algorithm. Keywords: Classification, C4.5 Algorithm, Fuzzy K-Nearest Neighbor in every Class ­(FK-NNC), APER
ANALISIS JALUR TERHADAP FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS PRESTASI KUMULATIF (IPK) MAHASISWA STATISTIKA UNDIP Malik Hakam; Sudarno Sudarno; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (414.358 KB) | DOI: 10.14710/j.gauss.v4i1.8146

Abstract

Education is a priority thing everyone today. Education is implemented in learning, by learning humans can develop all the potential there is in him. Learning is always related to the achievement of learning, because learning is a process while learning achievement is the result of the learning process. In the course of learning achievement levels measured by GPA (Grade Point Average). Factors that influence GPA among allowance, age, value of the UN Senior High School, many organizations, the internet long, long time to learn. Path analysis is the development of multiple regression which the independent variables affect the dependent variable not only directly but also indirectly affect. Based on the results of the discussion of the factors that affect the GPA is concluded that the allowance has indirect effect of   -0,211, age has  direct effect of age at 0,1901, the UN has direct effect of 0,258, many organizations have a direct effect of -0,3582 and has indirect effect of -0,132, the  internet long direct effect of -0,2376 and has indirect effect of -0,038, long learning has a direct effect of 0,2344. Keywords: Education, GPA, Path analysis, Direct effect, Indirect effect
ANALISIS JALUR TERHADAP FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS PRESTASI KUMULATIF (IPK) MAHASISWA STATISTIKA UNDIP Malik Hakam; Sudarno Sudarno; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v4i2.8581

Abstract

Education is a priority thing everyone today. Education is implemented in learning, by learning humans can develop all the potential there is in him. Learning is always related to the achievement of learning, because learning is a process while learning achievement is the result of the learning process. In the course of learning achievement levels measured by GPA (Grade Point Average). Factors that influence GPA among allowance, age, value of the UN Senior High School, many organizations, the internet long, long time to learn. Path analysis is the development of multiple regression which the independent variables affect the dependent variable not only directly but also indirectly affect. Based on the results of the discussion of the factors that affect the GPA is concluded that the allowance has indirect effect of   -0,211, age has  direct effect of age at 0,1901, the UN has direct effect of 0,258, many organizations have a direct effect of -0,3582 and has indirect effect of -0,132, the  internet long direct effect of -0,2376 and has indirect effect of -0,038, long learning has a direct effect of 0,2344. Keywords: Education, GPA, Path analysis, Direct effect, Indirect effect
OPTIMALISASI PORTOFOLIO MENGGUNAKAN CAPITAL ASSET PRICING MODEL (CAPM) DAN MEAN VARIANCE EFFICIENT PORTFOLIO (MVEP) (Studi Kasus: Saham-Saham LQ45) Mardison Purba; Sudarno Sudarno; Moch. Abdul Mukid
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (573.138 KB) | DOI: 10.14710/j.gauss.v3i3.6483

Abstract

Investment is planting some funds to get profit. However, there is a positive relationship between risk and return that is High Risk High Return. So, the investor seeks to maximize expected return using portfolio optimization. The nature of the stock fluctuates over time, often times it poses a risk to lose money. In the science of finance, the fluctuations of stock returns is known as volatility. Then the stock volatility measurement uses Exponentially Weighted Moving Average (EWMA). Methods of Capital Assets Pricing Model (CAPM) is used for the selection of the best stocks of the nine sectors LQ45. Portfolios are formed of nine sectors were weighted using the Mean-Variance optimal Efficient Portfolio (MVEP). The weight placed on the largest fund shares at IMAS 25.12%, amounting to 19.53% BDMN, BWPT by 6.40%, 9.75% for INCO, SMCB by 7.72%, amounting to 9.37% INDF, BKSL for 2.27%, 16.87% and TLKM of MAPI by 2.98%. Based on analysis, volatility measurement of IMAS, TLKM and BDMN especially using EWMA. Risk measurement tool used for stock portfolio is Value at Risk (VaR) and Risk measurement tool used for stocks is Component Value at Risk (CVaR). With a confidence level of 95% and an investment of IDR 100.000.000 the loss investment using VaR for one day in the future is IDR 1.799.824. Meanwhile, if using CVaR then the maximum loss investment for the day ahead is IDR 1.523.000,73.
PEMILIHAN MODEL REGRESI LINIER MULTIVARIAT TERBAIK DENGAN KRITERIA MEAN SQUARE ERROR Aminuddin Aminuddin; Sudarno Sudarno; Sugito Sugito
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (913.495 KB) | DOI: 10.14710/j.gauss.v2i1.2125

Abstract

Regresi linier multivariat merupakan salah satu metode analisis regresi yang melibatkan lebih dari satu variabel respon, dengan model regresinya adalah . Penggunaan banyak variabel dalam analisis regresi linier multivariat dapat menjadi hal yang menyulitkan untuk menentukan besarnya pengaruh variabel prediktor terhadap variabel respon. Oleh karena itu, dilakukan penyeleksian variabel guna mendapatkan model regresi terbaik. Prosedur seleksi variabel dengan kriteria Mean Square Error (MSE) merupakan suatu metode untuk mendapatkan model terbaik dengan cara mencari model yang memiliki nilai MSE terkecil dari seluruh model yang mungkin
DIAGRAM KONTROL MULTIVARIAT BERDASARKAN JARAK CHI-KUADRAT UNTUK QUALITY CONTROL PRODUKSI DI PT ARA SHOES Galuh Ayu Prameshti; Sudarno Sudarno; Diah Safitri
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (391.259 KB) | DOI: 10.14710/j.gauss.v3i4.8079

Abstract

Shoes are demands required by everyone. As a time changing and increasing demand for shoes, so many competitor shoe factories produce the best shoes for the customer. PT Ara Shoes is a famous shoe factory that has been well known for six decades. To be able to make fairness quality competition shoe factory would have to ability to produce a high quality product. To improve quality and production process is the way to determine whether quality of production is already achieve the minimum standard quality needed by applying the minimum standard quality control system. Control charts based on chi-square distance is a diagram of the control that can be used for multivariate data attributes. Production processes at PT ARA Shoes is divided into 3 stages of the shoe production process, including the process of cutting, process of sewing and assembling process. The cases study examined in this observation is the production process of cutting from January 2012 - October 2013 total applying 22 observations. Based on the research that has been done it is concluded that the production process is not enough controlled in cutting and improvement needed to be done twice, by eliminating observations 4th and 5th.Keywords : shoes charts control, chi-square distance, PT ARA Shoes
PEMODELAN RETURN INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN THRESHOLD GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (TGARCH) Maidiah Dwi Naruri Saida; Sudarno Sudarno; Abdul Hoyyi
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.349 KB) | DOI: 10.14710/j.gauss.v5i3.14702

Abstract

ARIMA model is one of modeling method that can be applied on time series data. It assumes that the variance of residual is constant. Time series data, particularly the return of composite stock price index, tend to change rapidly from time to time and also fluctuating, which cause heteroscedasticity where the variance of residual is not constant. Autoregressive Conditional Heteroscedasticity (ARCH) or Generalized Autoregressive Conditional Heteroscedasticity (GARCH) can be used to construct model of financial data with heteroscedasticity. Besides of having inconsistent variance, financial data usually shows phenomenon where the difference of the effect between positive error value and negative error value towards data volatility, called asymmetric effect. Therefore, one of the GARCH asymmetric models, Threshold Generalized Autoregressive Conditional Heteroscedasticity (TGARCH) is used in this research to solve heteroscedasticity and asymmetric effect in stock price index return. The data in this research is stock price index return from January 2nd, 2013 until October 30th, 2015. From the analysis, TGARCH models are obtained. ARIMA([3],0,[26])-TGARCH(1,1) is the best model because it has the smallest AIC value compared to other models. It produces the forecast value of stock price index return nearly the same with actual return value on the same day. Keywords: Return, Heteroscedasticity, Asimmetry effect, ARCH/GARCH, TGARCH.
PEMODELAN REGRESI ZERO-INFLATED NEGATIVE BINOMIAL (ZINB) UNTUK DATA RESPON DISKRIT DENGAN EXCESS ZEROS Bayu Ariawan; Suparti Suparti; Sudarno Sudarno
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (813.87 KB) | DOI: 10.14710/j.gauss.v1i1.573

Abstract

Zero-Inflated Negative Binomial (ZINB) regression is one of the methods used in troubleshooting overdispersion due to excessive zero values ​​in the response variable (excess zeros). ZINB regression model was based on the negative binomial distribution resulting from a mixture distribution between Poisson distribution  withis value of random variable which gamma distributed. ZINB regression parameter estimation can be performed by using Maximum Likelihood Estimation (MLE) method then is followed by the EM algorithm (Expectation maximization) procedure and Newton Rhapson. Test the suitability of the model simultaneously performed using Likelihood Ratio test and significance testing parameters individually performed with Wald test statistics. The model is applied to the case of car insurance obtained PT. Insurance of Sinar Mas Semarang Branch in 2010 in the form of data many policyholders filed claims to the PT. Sinar Mas Semarang Branch Insurance. Response variable is the number of claims submitted to the PT. Insurance of Sinar Mas Semarang Branch, while the predictor  variable is the age car and the type of coverage that consists of All Risk, Total Lost Only (TLO), and the joint between All Risk and Total Lost Only (TLO). From the analytical result obtained the conclution that the age of the car and the type of coverage affects number of claims filed by the policyholder to the PT. Insurance of Sinar Mas Semarang Branch in 2010.
MODEL REGRESI DATA PANEL SIMULTAN DENGAN VARIABEL INDEKS HARGA YANG DITERIMA DAN YANG DIBAYAR PETANI Bayyina Zidni Falah; Mustafid Mustafid; Sudarno Sudarno
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (556.54 KB) | DOI: 10.14710/j.gauss.v5i4.14718

Abstract

Interdependent relationship (simultaneity) between endogenous variables, that’s Farmers Recieved and Paid Price Index, can’t be modeled in a single equation, but there are two equations in a system of simultaneous equations. Each of these equations can’t be estimated separately without entering information from other equations. The purpose of this research is modelling panel data regression simultaneously. The method that’s used is Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM) with estimation technique is Two Stages Least Square (2SLS). The modelling is done by a panel data consisting of 32 provinces in 2013, 2014, and 2015. Based on the results of the Chow test, Hausman test, F statistic, and the value of R2, the result is that REM is the most suitable model to model the simultaneity of the panel data. REM has different intercepts in each province. F statistic value for the first equation of 152,658 with a significance of 0.000, and R2 value of 83,2%. For the second equation, statistics F value of 44396,16 with siginifikansi 0,000, and R2 value of 99.9%. From the results of this modelling, the model that’s created can express the interdependent relationship between endogenous variables as well the diversity of variables between provinces.Keywords:      Panel data, CEM, FEM, REM, Farmers Recieved Price Index,Farmers Paid Price Index
Co-Authors Abdul Hoyyi Achmad Tavip Junaedi Ade Lenty Hoya Adimulya Nurrahman Aditya Eka Laksana Adiwirman Adiwirman Afianti Sonya Kurniasari Agung Santoso Agus Sudrajat Ahmad Reza Aditya Ajeng Arum Sari Alan Prahutama Aldila Khairina Sissandhy Alfita Rakhmayani Amin Nursudi Aminuddin Aminuddin Anak Agung Istri Sri Wiadnyani Angga Saputra Desti Anik Waryanti Anissa Pangastuti Anya Amabell Syukuri Arifah Wulansari Ariffandita Nuri Muttaqin Ashri Febrina Rahmasari Atika Elsadining Tyas Avida Anugraheni Avida Nugraheni C. Ayu Ambarsari bagus aji Bambang Wasito Adi Bayu Ariawan Bayyina Zidni Falah Boedi Setya Rahardja Budi Warsito Chiarakania Chaniago Cut Nur Aisyah Darari Rahma Lalita Dedy Haryanto Despriyanti Despriyanti diah novitasari Diah Safitri Dian Ika Pratiwi Dita Oktavia Ningrum Dwi Ispriyansti Dwi Ispriyanti Dwi Safrudin Dwi Siwi Handayani Eka Triakuntini Endang Dewi Masithah Endro Sutrisno Erna Puspitasari evelyn wijaya Farid Abdu Salam Fathimatuzzahra Syahrozad Nuroqi Fatkhan Arissetya Febriane Paulina Makalew Feri Setyowibowo Fifi Puspita Fuad Muhammad Galih Maraseta W H Prasaja Galuh Ayu Prameshti Gusti Rusmayadi Harini Harini Hasbi Yasin Hasmuri Hasmuri Huriyah Huriyah Ibnu Athoillah Irawan Wisnu Wardhana Johan Adi Wicaksana Joko Purnomo Julidian Julidian Julius E. Tenda Junaidi Junaidi Khalida Hanum Khersna Bayu Sangka Khresna Bayu Sangka Kikis Dinar Yuliesti Kristiani Kristiani Kussigit Santosa Lintang Afdianti Nurkhasanah Lulut Fadhilah Lundu Bontor Sihite Luthfi Rachma Dita M. Husni Arifin Maidiah Dwi Naruri Saida Malik Hakam Maluw, Fandel Mamuroh Mamuroh Mardison Purba Mario Moningka Martha Ng Mintasih Indriayu Mintasih Indriayu Moch. Abdul Mukid Mohammad Al Hazmi Mohammad Rama Fadillah Soeroso Muhammad Amin Muhammad Fachri Maulana Mustafid Mustafid Nailatis Shofia Nany Yuliastuti Nesvi Intan Oktajayanti Nonik Brilliana Primastuti Nourma Yulia Nova Yanti Gultom Novi Melawati Nur Aeniatus Solekakh Nur Musrifah Rohmaningsih Pradana Sahid Akbar Pranata Anggakara Priska Rialita Hardani Putu Handoko Murti Putu Jaya Permana Qomaruddin, Mochammad Ramdhan Febrianto Rangkang, Jeanely Retza Bahtiar Anugrah Ridha Ramandhani Ririn Khoiriyah Rita Rahmawati Rizka Asri Brilliani Rizky Ade Putranto Rukun Santoso Rumbayan, Rilya S. Suripin Salman Alfarisy Totalia Sandy Kristiara Sarwanto Sarwanto Satrio Adi Wibowo Sekar Niken Kartika Sheny Nurul Aini Shofiyatul Afidah Sholikhah Septiarti Khusnul Wardatus SITI NURLATIFAH Slamet Effendy Yusuf Sudenroy Mentang Sugito Sugito Suhardjo Suhardjo Sukrismiati Sukrismiati Sulton Syafii Katijaya Sunarto Sunarto Suparti Suparti Supriyanto Supriyanto Sutrisno Anggoro Syanne Pangemanan Tampanatu P. F. Sompie Tarina Rahmayani Tarno Tarno Tatik Widiharih Taufan Fahmi Taufik Dani Testian Yushli Ana Tiani Wahyu Utami Titin Nurfiatin Tri Retnaning Nur Amanah Triastuti Wuryandari Veronika Ellyana Vica Nurani Wahyu Nugraha Widha Sunarno WINARTI WINARTI Winda Rosiana Pratiwi Wulan Merdeka Sari Yanuar Luqman Yovina Mulyadi Yuciana Wilandari