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All Journal Jurnal Ilmu Lingkungan SIGMA EPSILON - Majalah Ilmiah Teknologi Keselamatan Nuklir Jurnal Teknik Lingkungan Jurnal Gaussian Diponegoro Journal of Accounting Jurnal Pendidikan Ekonomi (JUPE) Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Online Mahasiswa (JOM) Bidang Pertanian JURNAL AKUNTANSI UNIVERSITAS JEMBER Wahana Teknik Sipil: Jurnal Pengembangan Teknik Sipil BISE: Jurnal Pendidikan Bisnis dan Ekonomi INKUIRI : Jurnal Pendidikan IPA Reviews in Civil Engineering Seminar Nasional Lahan Suboptimal Aksara: Jurnal Ilmu Pendidikan Nonformal Agroekotek View Jurnal Pengabdian Masyarakat Multidisiplin Inobis: Jurnal Inovasi Bisnis dan Manajemen Indonesia Journal of Marine and Coastal Science Jurnal Teknik Sipil Terapan JURNAL UMBANUA Jurnal Pengabdian pada Masyarakat Jurnal Bisnis Event Prosiding Seminar Nasional Unimus

Sudarno Sudarno

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Author-ID : 387715

Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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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

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

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

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

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

KAJIAN SIX SIGMA DALAM PENGENDALIAN KUALITAS PADA BAGIAN PENGECEKAN PRODUK DVD PLAYERS PT X Nailatis Shofia; Mustafid Mustafid; Sudarno Sudarno
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Increasingly rapid development period, many industry sectors are growing and developing in Indonesia. Quality basic consumer decision factor in selecting goods and services. In the process of checking the audio end section 8 types of defects found on the product DVD players. Damage that occurs due to several factors, including factors human, material factors, and factors machines. If the quality of a company is said to have good production systems with process control. Six Sigma method is a method that can be used for analysis of the defect rate to approach zero defect products. The procedures used for quality improvement towards the target that the concept of Six Sigma DMAIC. This study aims to apply Six Sigma methods in quality control by conducting case studies to improve product quality DVD player at the end of the audio process. The results obtained in this study is on the whole production process mengkasilkan DPMO value of 5487 with sigma quality level of 4.04 means that the product of one million DVD players there are 5487 units of product that does not fit in production. Keywords : Quality, Statistical Quality Control, Six Sigma

PERBANDINGAN METODE RUNTUN WAKTU FUZZY-CHEN DAN FUZZY-MARKOV CHAIN UNTUK MERAMALKAN DATA INFLASI DI INDONESIA Lintang Afdianti Nurkhasanah; Suparti Suparti; Sudarno Sudarno
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Inflation data are financial time series data which often violate assumption if it is modeled with ARIMA Box-Jenkins classic method. Therefore, to forecast inflation data are used forecast method which has not requirement classic assumptions, like as fuzzy time series method. Fuzzy time series is a method of predicting data that use principles of fuzzy as basis. Many researches has been developed about this method, such as fuzzy time series developed by Chen (1996) and fuzzy time series-Markov chain developed by Tsaur (2012). In this case, both methods are used to predict inflation data in Indonesia. Result of predicting from both methods are compared with MSE value to in sample data. Method of fuzzy time series-Chen get MSE value 0,656, whereas method of fuzzy time series-Markov chain get MSE value 0,216. Because of this reason, method of fuzzy time series-Markov chain get smallest MSE value. So, this method as the best method. Furthermore, to evaluate the best of predicting model used MAPE value to out sample data. The MAPE value in method of fuzzy time series-Markov chain is 6,610%. As conclusion, model of fuzzy time series Markov chain have best performance.Keywords : fuzzy time series, Markov chain , MSE, MAPE.

KAJIAN AVAILABILITAS PADA SISTEM KOMPONEN SERI Avida Nugraheni C.; Sudarno Sudarno; Triastuti Wuryandari
Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Availability is a measure of system performance and measures the combined effect of reliability, maintenance and logistic support on the operational effectiveness of the system. Availability of series system is derived from inherent availability of system that takes effect from mean time to failure (MTTF) and mean time to repair (MTTR). Given observed time data of microcontroller consists of processor core, memory and programmable I/O peripheral in series, is measured its system availability. By simple linier regression method, the parameter estimation is determined after data distribution known, for the mean time. Processor core has Weibull distribution for failure time data with , and as regression model while repair time data is lognormal distribution with , and regression model is . Memory has exponential failure time data with and as regression model while normal repair time data has dan and regression model is . Failure time data distribution of programmable I/O peripherals is Weibull with , and regression model while lognormal repair time data has , and regression model is . Due to MTTF is 11364.57 hours and MTTR is 41.59 hours, processor core’s availability is 99.64%. Availability of memory is 99.87% from MTTF is 20000 hours and MTTR is 27 hours. Programmable I/O peripheral has 18773.41 hours as MTTF and MTTR is 38.67 hours that deliver availability 99.79%. The series system availability is 99.30% means the probability of system is in the state of functioning at given time is 99.30%.

OPTIMASI VALUE AT RISK REKSA DANA MENGGUNAKAN METODE ROBUST EXPONENTIALLY WEIGHTED MOVING AVERAGE (ROBUST EWMA) DENGAN PROSEDUR VOLATILITY UPDATING HULL AND WHITE Khalida Hanum; Tarno Tarno; Sudarno Sudarno
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Risk measurement is important in making investments. One tool to measure risk is Value at Risk (VaR), which is the worst possible loss on a given time horizon under normal market conditions with a certain confidence level. The successful implementation of VaR depends on conditional volatility estimates of portfolio returns. Robust Exponentially Weighted Moving Average (robust EWMA) is one approach in forecasting the conditional volatility of asset returns. Robust EWMA is suitable for financial data analysis which is heteroscedastic and not normally distributed. The final VaR is calculated using historical simulation method with updated data return through volatility updating Hull and White procedure. In this research, robust EWMA is used for portfolio VaR calculation with case study of mutual funds shares BNI AM Dana Berkembang (BNI), Manulife Dana Saham Utama (MDSU) and Mega Asset Greater Infrastructure (MAGI). Validity testing of VaR was conducted based on Basel rule and Kupiec's proportion of failures (PF) test. The result of backtesting test shows that the obtained VaR are valid to predict the loss of the equity fund portfolio at both 95% and 99% confidence level.Keywords : mutual fund, Value at Risk, robust EWMA, volatility updating

PEMISAHAN DESA/KELURAHAN DI KABUPATEN SEMARANG MENURUT STATUS DAERAH MENGGUNAKAN ANALISIS DISKRIMINAN KUADRATIK KLASIK DAN DISKRIMINAN KUADRATIK ROBUST Afianti Sonya Kurniasari; Diah Safitri; Sudarno Sudarno
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Semarang Regency is one of 29 counties and 6 towns in Central Java province. In the district there are rural areas and urban areas. Discriminant analysis is a technique related to the separation of objects into different groups that have been set previously, thus, discriminant analysis can be used to separate village in Semarang Regency into urban or rural groups. Linear discriminant analysis assumes that the covariance matrix of the two groups are equal, If the assumption of equality covariance matrix is denied, function of quadratic discriminant can be used for classification. Classical estimation for the sample mean vector and sample covariance matrix is very sensitive to the presence of outliers in the observations and the functioning of the separation can be non-robust. Estimators that can be used to cope with data containing outliers are the Minimum Covariance Determinant. Robust discriminant analysis is obtained by replacing the mean and covariance matrix using the classic MCD estimator. After analysis is performed, obtained result the data of 2011 Village Potential contains outlier, so that the robust quadratic discriminant analysis more appropriate because it can provide precision the results of separation 89,79% while classical quadratic discriminant analysis give exactness of 87,23%.

APLIKASI FUZZY ANALYTICAL HIERARCHY PROCESS UNTUK MENENTUKAN PRIORITAS PELANGGAN BERKUNJUNG KE GALERI (Studi Kasus di Secondhand Semarang) Agung Santoso; Rita Rahmawati; Sudarno Sudarno
Jurnal Gaussian Vol 5, No 2 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Entrepreneur have an important role in the development of developing countries. Entrepreneurship has many responsibilities, one of them is in making decisions concerning organizational leadership, marketing and others. Making the right decisions to support advancement a company. Analytic Hierarchy Process (AHP) is a decision support models to find the order of priority of the various alternatives in solving a problem. Weakness contained in the AHP is subjectivity. The approach to the fuzzy concept can minimize these weaknesses. The use of function Triangular Fuzzy Number (TFN) on Fuzzy AHP can clarify uncertainties in the interval assessment scale. This study aims to identifies the priority of customers visiting the gallery case study in Secondhand Semarang. The data taken by distributing questionnaires to customers have ever visiting as respondents. The results showed criteria of Barang is a top of priority with the highest priority weight is 0,341. Criteria of Produk followed with 0,245 priority weight, then criteria of Suasana with 0,211 priority weight, and the last criteria of Lingkungan with 0,201 priority weight.

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

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