Rukun Santoso
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Published : 10 Documents
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GRAFIK PENGENDALI NON PARAMETRIK EMPIRIK Santoso, Rukun
MEDIA STATISTIKA Vol 1, No 2 (2008): Media Statistika
Publisher : Jurusan Statistika FSM Undip

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Abstract

Shewhart control chart is constructed base on the normality assumption of process.  If the normality is fail then the empirical control chart can be an alternative solution. This means that the control chart is constructed base on empirical density estimator. In this paper the density function is estimated by kernel method.  The optimal bandwidth is selected by leave one out Cross Validation method. The result of empirical control chart will be compared to ordinary Shewhart chart.   Key words : Control chart, Kernel, Cross Validation
TERAPAN FUNGSI DENSITAS EMPIRIK DENGAN PENDEKATAN DERET FOURIER UNTUK ESTIMASI DIAGRAM PENGENDALI KUALITAS Santoso, Rukun
MATEMATIKA Vol 10, No 3 (2007): JURNAL MATEMATIKA
Publisher : MATEMATIKA

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Abstract

Any continues function on the Hilbert space L2[-p,p] can be represented as Fourier series. By this fact, a density function can be estimated by Fourier series as estimator of continues function on L2[-p,p]. Further, this function estimator will be used to derive process parameters that needed on the control quality chart design  
MODEL ASURANSI KENDARAAN BERMOTOR MENGGUNAKAN DISTRIBUSI MIXED POISSON Diningrum, Tina; Wilandari, Yuciana; Santoso, Rukun
Jurnal Gaussian Vol 1, No 1 (2012): Wisuda Periode Oktober 2012
Publisher : Jurusan Statistika UNDIP

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Abstract

Motor vehicle insurance is a form of protection of motor vehicles owned by the insured. One of the activities in insurance companies is claim. Claim is risk of loss claim is paid by the insurance company to the insured. Analysis of motor vehicle insurance claims typically uses poisson distribution approach. Nevertheless in many cases of motor vehicle insurance claim, the value of variance greater than the mean value. In this case overdispersed has been going on the assumption poisson distribution. If the poisson distribution continued to be used when going overdispersed, so the poisson distribution is inefficient because it affects the error standard. To solve the problem can be used mixed Poisson distribution.  This final project used two mixed Poisson distribution which is a mixture of gamma poison known as negative binomial distribution and poisson-exponential mixture known as a geometric distribution. Carried out on the data motor vehicle claim in PT. Jasa Asuransi Indonesia, Semarang branch year 2010 to 2011 it is estimated that of the 100 vehicle type Car policyholders aged <1 year will be 2 claims per year.
ANALISIS GRAFIK PENGENDALI NONPARAMETRIK DENGAN ESTIMASI FUNGSI DENSITAS KERNEL PADA KASUS WAKTU PELOROTAN BATIK TULIS Hayati, Hana; Santoso, Rukun; Rusgiyono, Agus
Jurnal Gaussian Vol 3, No 1 (2014): Wisuda Periode Januari 2014
Publisher : Jurusan Statistika UNDIP

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Abstract

The quality of the product becomes one of the basic factors in the decisions of consumers in selecting products. A companny needs a quality control for keeping the consistency of product quality. One of statistic tools which can be used in quality control is a control chart. If  the obtained data do not have  a specific distribution assumption, it is needs to use nonparametric control chart as the solution. One of ways to describe the nonparametric control chart is a kernel density estimation. The most important point in the kernel density estimation is optimal bandwidth selection and one of the method that can be used is Least Squares Cross Validation. In this case, will be described a nonparametric control chart to data of vanishing candle at batik in Pekalongan using Rectangular, Triangular, Biweight and Epanechnikov kernel density estimation. Based on the data processing using R.2.14, the result was obtained that from the four kernel estimatios which were used, the obtained control chart by the Rectangular kernel density estimation which have the largest value of variance. It shows that the control chart by the Rectangular kernel density estimation is the widest control chart. While, the obtained control chart by the Epanechnikov kernel density estimation which have the smallest value of variance. It shows that the control chart by the Epanechnikov kernel density estimation is the narrowest control chart
KOMPUTASI METODE SAW DAN TOPSIS MENGGUNAKAN GUI MATLAB UNTUK PEMILIHAN JENIS OBJEK WISATA TERBAIK (Studi Kasus : Pesona Wisata Jawa Tengah) Sari, Rima Nurlita; Santoso, Rukun; Yasin, Hasbi
Jurnal Gaussian Vol 5, No 2 (2016): Wisuda periode April 2016
Publisher : Departemen Statistika FSM Undip

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Abstract

Multi-Attribute Decision Making (MADM) is a method of decision-making to establish the best alternative from a number of alternatives based on certain criteria. Some of the methods that can be used to solve MADM problems are Simple Additive Weighting (SAW) Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). SAW works by finding the sum of the weighted performance rating for each alternative in all criteria. While TOPSIS uses the principle that the alternative selected must have the shortest distance from the positive ideal solution and the farthest from the negative ideal solution. Both of these methods were applied in making the selection of the best tourist attractions in Central Java. There are 15 tourist attractions and 7 criteria: location, infrastructure, beauty, atmosphere, tourist interest, promotion, and cost. This primary research employed a questionnaire that passed the questionnaire testing, namely its validity and reliability test. The result of this study shows that the best type of tourism according to the government is temple tour. While water sports tourism is favored by tourism observers. As for college students, the preferred tourist destination is religious tourism. This study also produced a GUI Matlab programming application that can help users in performing data processing using SAW and TOPSIS to select the best attraction in Central Java. Keywords: MADM, SAW, TOPSIS, GUI, tourism
ANALISIS REGRESI NONPARAMETRIK KERNEL MENGGUNAKAN METODE JACKKNIFE SAMPEL TERHAPUS-1 DAN SAMPEL TERHAPUS-2 (Studi Kasus: Pemodelan Tingkat Inflasi Terhadap Nilai Tukar Rupiah di Indonesia Periode 2004-2016) Putri, Agum Prafindhani; Santoso, Rukun; Sugito, Sugito
Jurnal Gaussian Vol 6, No 1 (2017): Wisuda Periode Januari 2017
Publisher : Departemen Statistika FSM Undip

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Abstract

Exchange rate is a conversion between currencies of a country to another country. Inflation can be defined as the rise of good and service’s level of price continually. The fluctuation of exchange rate is related to inflation, because inflation is the reflection of changes in the price level which happens in market and led to changes in level of money demand and supply. From the data distribution pattern which doesn’t show linearity relation, therefore the right modeling needs to be done using non-parametrical regression. Kernel Function which is used in non-parametrical component is Gaussian with optimal choice of bandwidth using the delete-1 Jackknife sample and the delete-2 Jackknife sample in Cross Validation (CV) method. This research using monthly data, 100 in sample data which taken from September 2014 until December 2012, while the number of out sample data used is 40 which taken from January 2013 until April 2014. Based on the analysis which had been done, the best kernel non-parametrical regression is the model using the delete-2 Jackknife sample because it produced the smallest Mean Absolute Percentage Error (MAPE) therefore it had better model accuracy evaluation. Keyword : Exchange Value, Non-parametrical Regression, Kernel, Jackknife Method, Cross Validation (CV)
PERAMALAN OUTFLOW UANG KARTAL DI BANK INDONESIA WILAYAH JAWA TENGAH DENGAN METODE GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) Fina, Aukhal Maula; Tarno, Tarno; Santoso, Rukun
Jurnal Gaussian Vol 5, No 3 (2016): Wisuda periode Agustus 2016
Publisher : Departemen Statistika FSM Undip

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Abstract

Generalized Space Time Autoregressive (GSTAR) model is a method that has interrelation between time and location or called with space time data. This model is generalization of  Space Time Autoregressive (STAR) model where GSTAR more flexible for data with heterogeneous location characteristics. The purposes of this research are to get the best GSTAR model that will be used to forecast the outflow in the Bank Indonesia Office (BIO) Semarang, Solo, Purwokerto and Tegal. The best model obtained in this study is GSTAR (11) I(1) using the inverse distance weighting locations. This model has an average value of MAPE 35.732% and RMSE 440.52. The best model obtained explains that the outflow in BIO Semarang, Solo and Purwokerto are affected by two time lag before while for outflow in BIO Tegal is affected by two time lag befor and outflows in three other BIO. Keywords: GSTAR, Space Time, Outflow, Currency
KOMPUTASI METODE EXPONENTIALLY WEIGHTED MOVING AVERAGE UNTUK PENGENDALIAN KUALITAS PROSES PRODUKSIMENGGUNAKAN GUI MATLAB (STUDI KASUS : PT Djarum Kudus SKT Brak Megawon III) Antono, Iyan; Santoso, Rukun; Wilandari, Yuciana
Jurnal Gaussian Vol 5, No 4 (2016): Wisuda Periode Oktober 2016
Publisher : Departemen Statistika FSM Undip

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Abstract

Control chart is one of tools for quality control of production.  control chart is one of tool that can be used to control the quality of production for variable data such as weight of product. However, there is a weakness of   control chart, which is sensitivless in detecting small shift of the mean process. Exponentially Weighted Moving Average (EWMA) control chart is one of the quality control tool that can improve the weakness of  control chart. EWMA control chart has a weight smoothing parameter (λ) which makes EWMA control chart more sensitive in detecting small shifts the process mean. Each production data will be weighted and past production data will be affected by present production data. EWMA control chart will be used to make a control chart by weight of cigarette data in Brak Megawon III PT Djarum Kudus. In this study, will be established to assist in the GUI Matlab computational EWMA methods chart controller to control the quality of production at PT Djarum Kudus.In this study showed that the most optimum weight refiner which is at a value of 0.6.Keyword : EWMA, Smoothing weight (λ), GUI, Weight of cigarette
RELIABILITAS DAN AVAILABILITAS SISTEM TIGA KOMPONEN TERSUSUN PARALEL BERSERI Sudarno, Sudarno; Santoso, Rukun; Anugraheni, Avida
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 6, No 2 (2018): Jurnal Statistika
Publisher : Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Muham

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Abstract

Reliability is the ability of a product or an item to maintain the required function of a specified period of time under given operating conditions. Availability is a measure of system performance and measures the combined effect of reliability, maintenance and logistic support on the operational effectivesness of the system. The system was formedby some components. This system could be broken, then it could not be operated. In order to system could operate again, it should be repaired. This system consist of three components, such that component-1 is a processor core, component-2 is interface input/output, and component-3 is memory. The system was arranged by parallel-seri.This paper use generation data. Data are failure time and repair time of components of system, respectively. Therefore, research variables are failure time and repair time of all component of system. The aim of this research is finding the mean time to failure and the mean time to repair components, reliability of system, and availability of system.The research result of reliability of system is 0.9998 while availability of system is 0.9987. These results could be concluded that system have best quality and high performing. Generally, if reliability value was higher then quality of system more perfect and if availability value was higher then perform of system was better.  Keywords : Reliability, availability, mean time to failure, mean time to repair.
ANALISIS DATA INFLASI INDONESIA MENGGUNAKAN METODE FOURIER DAN WAVELET MULTISCALE AUTOREGRESIVE Suparti, Suparti; Santoso, Rukun; Prahutama, Alan; Yasin, Hasbi; Devi, Alvita Rachma
Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) 2018: Tahun 2018
Publisher : Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika)

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Abstract

Analisis regresi merupakan metode statistika untuk mengetahui hubungan antara variabel prediktor dan variabel respon. Pendekatan regresi dapat dilakukan dengan  pendekatan parametrik dan nonparametrik. Pendekatan parametrik ketat dengan asumsi dan harus dipenuhi untuk mendapatkan model yang baik. Sementara pendekatan nonparametrik tidak ketat dengan asumsi karena metode tersebut didasarkan pada pendekatan kurva yang tidak diketahui bentuknya. Pendekatan nonparametrik dapat dilakukan dengan beberapa pendekatan diantaranya metode Fourier dan Wavelet. Metode Fourier merupakan metode yang didasarkan pada deret cosinus atau sinus. Metode Fourier sangat sesuai untuk data yang mengalami pola berulang atau stasioner. Sedangkan pada pemodelan wavelet tidak hanya terbatas pada data berulang atau stasioner saja, akan tetapi juga mampu memodelkan data yang tidak stasioner. Pada penelitian ini dimodelkan nilai Inflasi di Indonesia dari Januari 2007 sampai Agustus 2017.  Variabel responnya adalah nilai inflasi, sedangkan variabel prediktornya adalah waktu. Metode Fourier dengan K=100 menghasilkan MSE sebesar 0,846216 dan R2 sebesar 80,12%. Model Wavelet menggunakan Multiscale Autoregresive dengan filter Haar, J=4 dan Aj = 2  mempunyai MSE sebesar 0,312 dengan R2  sebesar  96,91%.  Pada model Fourier dengan K=100 diperlukan parameter sebanyak 102 buah sedangkan model wavelet dengan J=4 dan Aj = 2 hanya diperlukan parameter sebanyak 10 buah. Jadi model wavelet sangat efisien dengan kinerja yang lebih bagus dibandingkan dengan model Fourier. Kata Kunci: Inflasi, nonparametrik, Fourier, Wavelet, MSE