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All Journal PROSIDING SEMINAR NASIONAL JPK (Jurnal Pendidikan Khusus) Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang Pedagogi : Jurnal Penelitian Pendidikan Majalah Kulit, Karet, dan Plastik Bioeksperimen: Jurnal Penelitian Biologi Journal of English Education, Linguistic and Literature JURNAL PENA EDUKASI Academy of Education Journal Social, Humanities, and Educational Studies (SHEs): Conference Series Jurnal Teknodik Indonesian Journal of Instructional Media and Model Proceeding Biology Education Conference

Suparti Suparti

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Author-ID : 475542

Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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PEMODELAN DATA INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN REGRESI PENALIZED SPLINE Novia Agustina; Suparti Suparti; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Indonesia Composite Index (IHSG) is an indicator of stock price changes in Indonesia Stock Exchange. IHSG is time series data that can be modeled with parametric models. But there are some assumptions for parametric model, while the fluctuated IHSG data usually doesn’t occupy these assumptions. Another alternative for this study is nonparametric regression. Penalized spline regression is one of nonparametric regression method that can be used. The optimal penalized spline models depends on the determination of the optimal smoothing parameter λ and the optimal number of knots, that has a minimum value of Generalized Cross Validation (GCV). The best model in this study is penalized spline degree 1 (linear) with 1 knot, that is 5120,625, smoothing parameter λ value is 41590, and GCV value is 1567,203. R2 value for in sample data is 83,2694% and R2 value for out sample data is 96,4976% show that the model have a very good performance. MAPE values for in sample data is 0,5983% and MAPE values for out sample data is 0,4974%. Because the value of MAPE in sample and out sample is less than 10%, it means that the performance of the model and forecasting are very accurate. Keywords: Indonesia Composite Index, Nonparametric Regression, Penalized Spline Regression, GCV, MAPE

PERHITUNGAN PEMBIAYAAN DANA PENSIUN DENGAN METODE ATTAINED AGE NORMAL DAN PROJECTED UNIT CREDIT (STUDI KASUS : PT. TASPEN (PERSERO) KANTOR CABANG UTAMA SEMARANG) Musandingmi Elok Nurul Islam; Yuciana Wilandari; Suparti Suparti
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Welfare in the future is something that all people dreamed, including goverment employees. As a government's concern for welfare in the future for the goverment employees so the government give pension program. The pension program will give pension benefit to the goverment employees on their retirement age. Pension funding requires actuarial computation which normal cost and actuarial liability. Actuarial computation is divided into two major parts, Accrued Benefit Cost Method and Projected Benefit Cost Method. One of Accrued Benefit Cost Method example is Projected Unit Credit and for the Projected Benefit cost one of the method is Attained Age Normal. This research uses secondary data from PT. TASPEN (Persero) KCU Semarang. Computation result shows on the both second normal cost the method tends to increase each year. Projected Unit Credit Method exhibits substansial increment, meanwhile on Attained Age Nornal Method the increment is relatively slow. The amount of both second actuarial liability method will always increase each year, by using Attained Age Normal Cost produces bigger actuarial liability than Projected Unit Credit Method. Projected Unit Credit Method give final normal cost less than Attained Age Nornal Method. Keywords: Pension, Normal Cost, Actuarial liability, Attained Age Normal, Projected Unit Credit.

PEMILIHAN PENGRAJIN TERBAIK DENGAN METODE ELECTRE DAN TOPSIS MENGGUNAKAN GUI MATLAB (STUDI KASUS : PT. Asaputex Jaya, Tegal) Hafii Risalam; Rita Rahmawati; Suparti Suparti
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Company is technical unity that aims to produce goods services. One of determinants of succesful company is its human resources or known as employees. PT. Asaputex Jaya is one of company that enganged in the manufacture of sarong. Poor quality of human resources, especially on the production is still an obstacle for PT. Asaputex Jaya. Therefore selection of the best craftsmen need to be done so that production process doesn’t meet any probelms. This research was conducted to determine top craftsmen in sarong production on PT. Asaputex Jaya, and also used for PT. Asaputex Jaya’s human resources management interests. ELECTRE is based on rankings concept through pair comparison between alternatives on the suitable criteria. While TOPSIS can determine the value of preference for each alternative, the concept is simple and easy to understand. There are 8 criteria in the selection of top craftsmen: design, fabrics assembly, merger with filler material, manufacture of sarong, punctuality, statutes of size, tailoring results, and neatness or stitching cleanliness. Through the TOPSIS method selected 10 top craftsmen: 5th, 14th, 15th, 9th, 3rd, 13th,6th, 20th, 18th, and 10th , which then only one top craftsman will be chosen using the ELECTRE method. This study also produced a GUI Matlab programming application that can help users in performing data processing using TOPSIS and ELCTRE to select the best craftsmen on PT. Asaputex Jaya Keyword: SDM, TOPSIS, ELECTRE, GUI Matlab, top craftsmen

PENGELOMPOKAN KABUPATEN/KOTA DI PROVINSI JAWA TENGAH BERDASARKAN ANGKA PARTISIPASI PENDIDIKAN JENJANG SMA/MA/PAKET C DENGAN FUZZY SUBTRACTIVE CLUSTERING Onny Kartika Hitasari; Diah Safitri; Suparti Suparti
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Education is one aspect of nation building is very important to realize the human resource development and national character. Awareness of the importance of education can be seen through education enrollment rates. This study aims to classify the enrollment rates in the district / city Central Java. The data used is the Gross Enrollment Rate (GER), Net Enrollment Rate (NER) and School Enrollment Rate (SER) at the district / city in Central Java Province in 2013. The grouping method used in this study is Fuzzy Subtractive Clustering. The results showed that the best cluster grouping enrollment rates in Central Java Province which consists of 4 clusters with value of cluster variant is 0.00749 and radii between 0.35 to 0.50. Keywords: education participation rate, GER, NER, SER, Fuzzy Subtractive Clustering

KAJIAN MODEL INFLASI TAHUNAN KOTA SIBOLGA DENGAN ARIMA DAN PENDEKATAN REGRESI POLINOMIAL PADA ANALISIS MULTIRESOLUSI WAVELET Ebeit Devita Simatupang; Suparti Suparti; Rita Rahmawati
Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Inflation rate is one of the fundamental economic indicators of a country. Therefore, prediction of inflation rate become important thing in taking monetary to maintain economy stability. In studying inflation model, commonly used method of parametric ARIMA Box-Jenkins which requires data is stationer and residual is white noise. However, data inflation which is fluctuates often does not meet parametric assumptions. In this study, it is proposed to use wavelet Multiresolution Analysis (MRA) as alternative method. The transformation from wavelet capable in representing time and frequencies simultaneously so that it can be used to analyze nonstasioner data. One of wavelet transformation form is discrete wavelet transformation (DWT) which expresses sized data N as for positive integer j. DWT analyses supported by MRA that divides data X become detail component ( ) and smoothing component ( ) to gain of estimating result. The best of MRA estimation will be approached by polynomial regression. The model of regression is formed by summing influence each variable predictor which raised increasingly to k-degress. By using yoy inflation data of Sibolga City in July 2008-October 2013 period, obtain the best parametric model ARIMA (0,1,[12]) with MSE=1,15411 and the best model of polynomial regression approached 13-degress at MRA that use la18 filter in resolution level which has MSE=1,238816. Both models are used to forecast yoy inflation of Sibolga City in 2014.

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.

PEMODELAN NEURO-GARCH PADA RETURN NILAI TUKAR RUPIAH TERHADAP DOLLAR AMERIKA Umi Sulistyorini Adi; Budi Warsito; Suparti Suparti
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Exchange rate can be defined as the value of a currency against other currencies. Exchange rates always fluctuate all the time. Very high fluctuations and unconstant becoming problem in forecasting where the data changed extremely. Most of economic data have heteroskedasticity characteristic analyzed using (Generalized Autoregressive Conditional Heteroskedasticity) GARCH models. Another model that commonly used as an alternative is Artificial Neural Network (ANN). However, both models have weaknesses. ARIMA models are linear, but the residual probably still contains non-linear relationship, while the ANN model used to non-linear relationship there is difficulty in determining the input. In this research combination of the two models is Neuro-GARCH model, with GARCH model used as input of ANN model. The purpose of this study was determined the best variance model Neuro-GARCH of return exchange rates rupiah against US dollar. The data used is daily return value of the rupiah (IDR) against the US dollar (USD) from August 27th, 2012 to March 31st, 2016. In this research, the mean model obtained is MA (1) and varian model is GARCH (1,1). The best model is Neuro-GARCH (2-10-1) which MSE smaller than the GARCH (1,1). Keywords: exchange rate, return, GARCH, Neuro-GARCH.

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.

ANALISIS PENGENDALIAN KUALITAS MENGGUNAKAN DIAGRAM KENDALI DEMERIT (Studi Kasus Produksi Air Minum Dalam Kemasan 240 ml di PT TIW) Gita Suci Ramadhani; Yuciana Wilandari; Suparti Suparti
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The efforts to maintain and improve the quality of the resulting product with statistical process control. Demerit control chart is a control chart in which the defect type is categorized into several classes according to the level of disability interests. Types of defects in the production processes of bottled water 240 ml in PT TIW divided into critical defects, major defects and minor defects. Based on the results of the analysis that has been done shows that the production process has been controlled statistically using demerit control charts on the third iteration for each line 1 and line 2. Capability of production processes in line 1 and line 2 shows that although the production process has been controlled statistics, but the process still produces a product that is not in accordance with specifications. But in the end all defective products are produced, will be immediately discarded and will not be marketed or sold to the consumer. This is done for the commitment PT TIW who always maintain the best quality products. Based on pareto chart for this type of defect on line 1 and line 2, it is known that 20% of the total types of defects, obtained two types of defects which constitute 80% of disability of the entire production process. The defect type is slanted lid and reject filler. The factors that cause this type of defect are slanted lid and reject filler among others, there is a worn machine components and uncorrect machine settings, the operator has not been retrained and lack of focus so not accordance with the procedure in the work, the composition of the materials is uncorrect, and methods or procedures are less well executed.

PERAMALAN TINGGI GELOMBANG BERDASARKAN KECEPATAN ANGIN DI PERAIRAN PESISIR SEMARANG MENGGUNAKAN MODEL FUNGSI TRANSFER (Studi Kasus Bulan Januari 2014 sampai dengan Desember 2014) Firda Megawati; Rita Rahmawati; Suparti Suparti
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Semarang coast is suitable to develop marine transport activities such as sailing because of its strategic location in the coastal region of Indonesia. The condition of sailing in Indonesia is said smoothly if wave height is in the normal range which is 1-2 meters. Therefore, there will be research to predict wave height in Semarang harbor by using transfer function. The data used is secondary data from BMKG of Semarang period January 2014 to December 2014 with the variable X as the average daily of wind speed and variable Y as average daily of wave height. Model that formed based on the input wind speed is ARIMA(2,1,0) while transfer function model that formed is b=0, s=0, and r=0 with noise model ARMA(1,1). The forecasting results for January 2015 show that the wave height tends to rise and the highest wave is on the third day with 0,9589 meters. Calculation accuracy of forecasting wave heights using transfer function model with MAPE produce a value of 18,7%. Keywords : Transfer Function, Wave Height, Wind Speed.

Co-Authors Abdul Hoyyi Agus Rusgiyono Ahmad Reza Aditya Akhmad Zaki Alan Prahutama Aminah Asngad Any Setyaningsih Bayu Ariawan Budi Warsito Bunga Maharani C Yuwono Sumasto Di Asih I Maruddani Diah Budiati Diah Safitri Dimas Kevin Natanael Dini Puspita Dwi Ampuni Agustina Dwi Ispriyanti Dyah Ayu Kusumaningrum Ebeit Devita Simatupang Elyas Darmawan Eni Dwi Lestariningsih Fajar Heru Setiawan Fina Fitriyana Firda Megawati Gita Suci Ramadhani Hafii Risalam Hanifa Eka Oktafiani Happy Suci Puspitasari Hasbi Yasin Icha Puspitasari Indah Puspaningrum Indra Satria Indra Satria Iwan Ali Sofwan Kartikaningtiyas Hanunggraheni Saputri Khoirunnisa Nur Fadhilah Lailly Rahmatika Lintang Afdianti Nurkhasanah M. Ali Ma'sum Martyanto Tedjo Moch. Abdul Mukid Muhammad Saibani Wiyanto Musandingmi Elok Nurul Islam Mustafid Mustafid Ndaru Dian Darmawanti Nonik Brilliana Primastuti Novia Agustina Onny Kartika Hitasari Rambat Rambat Ratih Binadari Ria Sutitis Rita Rahmawati Riyan Eko Putri Rizky Dwi Rahmawati Rukun Santoso Seta Satria Utama Shinta Karunia Permata Sari Singgih Subiyantoro Siti Anisah Siti Romlah Sri Budiasih Sudarno Sudarno Sugito Sugito Sulthon Masyhud Sulton Syafii Katijaya sunardi sunardi Swasnita Swasnita Tarno Tarno Testiana Deni Wijayatiningsih Tiani Wahyu Utami Triastuti Wuryandari Umi Sulistyorini Adi Vivi Meidina Amalia Wardani Ana Safitri Wasis Wicaksono Widari Widari Wulan Safitri Yossinta Intaniasari Yuciana Wilandari Yudi Ari Wibowo Yusuf Arifka Rahman

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