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Journal : Jurnal Gaussian

PEMODELAN REGRESI ZERO-INFLATED NEGATIVE BINOMIAL (ZINB) UNTUK DATA RESPON DISKRIT DENGAN EXCESS ZEROS Ariawan, Bayu; Suparti, Suparti; Sudarno, Sudarno
Jurnal Gaussian Vol 1, No 1 (2012): Wisuda Periode Oktober 2012
Publisher : Jurusan Statistika UNDIP

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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.
PERBANDINGAN MODEL REGRESI BINOMIAL NEGATIF DENGAN MODEL GEOGRAPHICALLY WEIGHTED POISSON REGRESSION (GWPR) (Studi kasus : Angka Kematian Ibu di Provinsi Jawa Timur Tahun 2011) Suparti, Suparti; Ispriyanti, Dwi
Jurnal Gaussian Vol 2, No 3 (2013): Wisuda Periode Agustus 2013
Publisher : Jurusan Statistika UNDIP

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Maternal mortality rate is one of the crucial problems of death in Indonesia. Maternal deaths in East Java province is likely to increase so that the role of data and information are very important. Negative Binomial Regression is a model that can be used to address the problem overdispersion. While the method of spatial attention factor for type discrete data is Geographically Weighted Poisson Regression Model (GWPR). This study was conducted on the comparison between the Negative Binomial Regression and GWPR to discuss the factors that influence maternal mortality rate in the province of East Java. Indicators that affect maternal mortality include maternal health services. Maternal health services such as antenatal care, obstetric complications treated, Aid deliveries by skilled health care child birth, and neonatal health care services handled neonatal complications. The results of testing the suitability of model shows that there is no influence of spatial factors on maternal mortality rate in the province of East Java. Based on Negative Binomial Regression derived variable number of puerperal women who received vitamin A significantly affect maternal mortality rate, while for GWPR is divided into six clusters districts/cities by same significant variables. From the comparison value of AIC was found that GWPR better to analyzing Maternal mortality in East Java because it has the smallest value of AIC
REGRESI SPLINE SEBAGAI ALTERNATIF DALAM PEMODELAN KURS RUPIAH TERHADAP DOLAR AMERIKA SERIKAT Katijaya, Sulton Syafii; Suparti, Suparti; Sudarno, Sudarno
Jurnal Gaussian Vol 2, No 3 (2013): Wisuda Periode Agustus 2013
Publisher : Jurusan Statistika UNDIP

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Exchange rate is the ratio of value or price of the currency between two countries. Many factors are thought to affect change in the inflation rate, the activity balance of payments, interest rate differentials, the relative level of income, government control and expectations. Therefore the method that can be used to analyze the exchange rate is needed such as the classical time series analysis (parametric). However the fluctuated data rate doesn’t occupy the assumption of stationarity often. Another alternative for this study is the spline regression. Spline is a nonparametric regression that doesn’t hold any assumption of regression curves. Spline regression has high flexibility and ability to estimate the data behavior which is likely to be different at every point of the interval, with the help of knots. The best model depends on the determination of the optimal point knots, that is has a minimum value of Generalized Cross Validation (GCV). Using data daily exchange rate of the rupiah against the dollar in the period of January 2, 2012 until October 15, 2012, the best spline model in this study is when using 2 to 3 order of approaching knots point, those points are 9512, 9517 and 9522 with the GCV = 1036.38.
ANALISIS PENGARUH KUALITAS LAYANAN DAN KUALITAS PRODUK TERHADAP LOYALITAS PELANGGAN PADA ONLINE SHOP MENGGUNAKAN STRUCTURAL EQUATION MODELING Fitriyana, Fina; Mustafid, Mustafid; Suparti, Suparti
Jurnal Gaussian Vol 2, No 2 (2013): Wisuda Periode April 2013
Publisher : Jurusan Statistika UNDIP

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Semakin meningkatnya jumlah pengguna internet membawa dampak yang besar bagi dunia bisnis dengan berbelanja lewat internet sebagai lifestyle. Fenomena ini membuat para pebisnis mulai beralih dari pemasaran tradisional ke pemasaran modern seperti membuka toko online lewat website maupun social media. Penelitian ini bertujuan menganalisa pengaruh kualitas layanan dan kualitas produk terhadap loyalitas pelanggan  pada  online shop. Model yang dipakai adalah model e-SERVQUAL dan metode analisisnya menggunakan structural equation modeling (SEM). Hasil dari penelitian ini menunjukkan adanya hubungan antara kualitas layanan dan kualitas produk terhadap loyalitas pelanggan pada online shop. Variabel indikator daya tanggap memiliki pengaruh yang paling besar terhadap variabel kualitas layanan pada online shop. Sedangkan, variabel indikator daya tahan memiliki pengaruh yang paling besar terhadap variabel kualitas produk pada online shop.
ANALISIS ANTREAN BUS KOTA DI TERMINAL INDUK PURABAYA SURABAYA Priyambodo, Richy; Sugito, Sugito; Suparti, Suparti
Jurnal Gaussian Vol 1, No 1 (2012): Wisuda Periode Oktober 2012
Publisher : Jurusan Statistika UNDIP

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Transportation is an important factor to grow the economy of a region. This is because the more smoothly transport then the faster the economy growth of a region. For that, Purabaya bus station always try to provide optimum service to avoid long queue. Queue process is a process of the coming of a customer to a service facility, then waiting in line (queue) when the officers busy, and leaving the place after getting the service. If the queue at Purabaya bus station is pretty much, it will reduce the amount of revenue generated by the transport service provider. Therefore, we need a model of the queue to optimize service to customers in Purabaya bus station. From the analysis, the best queuing models obtained on the service system in Purabaya bus station is (M/G/c): (GD/∞/∞) to service system at the postal arrival with 5 counters, service system for each bus line in passenger service post is (M/G/1): (GD/∞/∞), and (G/G/2): (GD/∞/∞) to service system at the postal departure.
ANALISIS INDEKS HARGA SAHAM GABUNGAN (IHSG) DENGAN MENGGUNAKAN MODEL REGRESI KERNEL Puspitasari, Icha; Suparti, Suparti; Wilandari, Yuciana
Jurnal Gaussian Vol 1, No 1 (2012): Wisuda Periode Oktober 2012
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Saham merupakaninvestasi yang banyak dipilih para investor, salah satu indikator yang menunjukkan pergerakan harga saham adalah Indeks Harga Saham Gabungan (IHSG). IHSG merupakan data runtun waktu sehingga untuk menganalisisnya dapat menggunakan metode runtun waktu klasik. Namun dengan metode tersebut banyak asumsi yang harus dipenuhi, sehingga diperlukan metode alternatif salah satunya metode regresi nonparametrik karena dalam model regresi nonparametrik tidak ada asumsi khusus sehingga model ini merupakan metode alternatif yang dapat digunakan dalam analisis IHSG. Dalam makalah ini dibandingkan nilai MSE yang dihasilkan dari analisis runtun waktu klasik, regresi parametrik linier sederhana dan regresi nonparametrik kernel. Data IHSG yang digunakan adalah  periode minggu pertama Januari 2011 sampai dengan minggu ke empat Februari 2012. Data tersebut merupakan data closing price saham mingguan pada periode perdagangan terakhir. Hasil perbandingan nilai MSE dari dataIHSG yang sering fluktuatif pada tiga analisis didapatkan nilai MSE terkecil adalah pada analisis menggunakan regresi nonparametrik kernel dengan fungsi triangle dan badwidth h sebesar 58.2 dengan nilai MSE = 6987.787. Model terbaik tersebut dapat digunakan untuk memprediksikan nilai IHSG selanjutnya.
KAJIAN DATA KETAHANAN HIDUP TERSENSOR TIPE I BERDISTRIBUSI EKSPONENSIAL DAN SIX SIGMA Murti, Victoria Dwi; Sudarno, Sudarno; Suparti, Suparti
Jurnal Gaussian Vol 1, No 1 (2012): Wisuda Periode Oktober 2012
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Analisis data tahan hidup biasanya digunakan untuk mengetahui ketahanan hidup suatu produk dalam bidang industri. Data waktu hidup dapat berupa data tersensor tipe I, tipe II dan tipe III. Dalam penelitian ini digunakan data tersensor tipe I yang merupakan suatu data waktu kematian atau kegagalan dimana semua unit uji n masuk pada waktu yang sama dan percobaan dihentikan sampai waktu tertentu. Salah satu distribusi yang dapat digunakan untuk menggambarkan waktu hidup adalah distribusi eksponensial dengan parameter l. Parameter l diestimasi dengan menggunakan metode Maximum Likelihood Estimation (MLE). Untuk mengetahui hubungan linear data kegagalan dengan intensitas kegagalan produk digunakan regresi linier. Selain itu, untuk memperkecil tingkat kegagalan yaitu dengan memprediksi kegagalannya menggunakan tingkat sigma. Nilai tingkat sigma bisa didapatkan dari DPMO (Defect Per Million Opportunity) yang berhubungan dengan MTTF (Mean Time To Failure) atau fungsi Reliabilitas. Jika nilai DPMO semakin kecil maka nilai tingkat sigma semakin besar.
ANALISIS DATA RUNTUN WAKTU MENGGUNAKAN METODE WAVELET THRESHOLDING Wibowo, Yudi Ari; Suparti, Suparti; Tarno, Tarno
Jurnal Gaussian Vol 1, No 1 (2012): Wisuda Periode Oktober 2012
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Latterly, wavelet is used in various application of statistics. Wavelet is a method without parameter which used in signal analysis, data compression, and time series analysis. Wavelet thresholding is a method which reconstructing the largest number of wavelet coefficients. Only the coefficients are greater than a specified value which taken and the rest coefficients are ignored, because considered null. Certain value is called the threshold value. The level of smoothness estimation are determined by some factor such as wavelet functions, the type of thresholding functions, level of resolutions and threshold parameters. But most dominant factor is threshold parameter. Because that was required to select the optimal threshold value. At the simulation study was analyzing of the stasioner, nonstasioner and nonlinier data. Wavelet thresholding method gives the value of Mean Square Error (MSE) which is smaller than the ARIMA. Wavelet thresholding is considered quite so well in the analysis of time series data.
PENGONTROLAN KUALITAS PRODUK MENGGUNAKAN METODE DIAGRAM KONTROL MULTIVARIAT np (Mnp) DALAM USAHA PENINGKATAN KUALITAS (Studi Kasus di PT Coca-Cola Amatil Indonesia (CCAI) Semarang) Primastuti, Nonik Brilliana; Sudarno, Sudarno; Suparti, Suparti
Jurnal Gaussian Vol 3, No 1 (2014): Wisuda Periode Januari 2014
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The industrial revolution was mark the beginning of the rise of industrial in the world. Moreover, in this globalization era, a lot of industry popping up especially those industries in Indonesia with many of those industries would emerge also thight competition. Each company must be trying to superior to that of its products so that each company will always improve the quality of their products in various ways so that the product can deportment in the market. One way of improving the quality of by doing quality control on each of its products. There are many method of conducting control quality. One method used is multivariate np chart. Multivariate np chart usually used for nonconforming units. Based on the results of this research, it is found that the production process in phase I namely from January to February in a state of controlled so that the parameters in the production process phase I can be used in the production process phase II, while to the process of the production phase II there are several observations that are out-of-control so that the production phase II in a state of uncontrolled.
ANALISIS PAJAK KENDARAAN BERMOTOR MENGGUNAKAN MODEL MULTISCALE AUTOREGRESSIVE DENGAN MAXIMAL OVERLAP DISCRETE WAVELET TRANSFORM (Studi Kasus di UP3AD Kab.Temanggung) Wahyuningrum, Sri; Suparti, Suparti; Mukid, Moch. Abdul
Jurnal Gaussian Vol 3, No 1 (2014): Wisuda Periode Januari 2014
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Time series analysis is applied in many fields, one of them is in the economic field. In this paper will consider analysis of the time series on data income taxes motor vehicles UP3AD Kab.Temanggung using Maximal Overlap Wavelet Transform Discrete (MODWT). Data time series decomposed using wavelet transform, namely MODWT with filter Haar and D4. From this transformation wavelet coefficients and scales coefficients are used for the modeling of time series. Modeling is done using the Multiscale Autoregressive (MAR) forecasting to get period ahead. Results of analysis showed that the model MAR with filter D4 is better than on the model MAR with filter Haar.
Co-Authors A. Sulaksono, A. Abdul Hoyyi Afa, Ihdayani Banun Agus Cahyono Agus Rusgiyono Agustina, Dwi Ampuni Ahmad Reza Aditya Akhmad Zaki Alan Prahutama Alvita Rachma Devi Amanda Devi Paramitha, Amanda Devi Aminah Asngad Any Setyaningsih, Any Arief Rachman Hakim Asismarta Asismarta, Asismarta Bayu Ariawan Budi Warsito Bunga Maharani, Bunga C Yuwono Sumasto, C Yuwono Deden Aditya Nanda, Deden Aditya Di Asih I Maruddani Diah Budiati Diah Safitri Dini Puspita Dwi Ispriyanti Ebeit Devita Simatupang Elyas Darmawan Ernawati, Devi Ernik Yuliana Esti Pratiwi Fajar Heru Setiawan, Fajar Heru Fina Fitriyana Firda Megawati, Firda Fitri Juniaty Simatupang, Fitri Juniaty Fitriyatno Fitriyatno Gita Suci Ramadhani Hafii Risalam, Hafii Hanifa Eka Oktafiani, Hanifa Eka Happy Suci Puspitasari Hasbi Yasin Icha Puspitasari Indah Puspaningrum Indra Satria, Indra Iwan Ali Sofwan Izzudin Khalid, Izzudin Karimawati, Nurul Kartika, Aninda Ayu Kartikaningtiyas Hanunggraheni Saputri, Kartikaningtiyas Hanunggraheni Khoirunnisa Nur Fadhilah, Khoirunnisa Nur Lailly Rahmatika, Lailly Lestariningsih, Eni Dwi Lina Agustina, Lina Lintang Afdianti Nurkhasanah, Lintang Afdianti Lismiyati Marfuah, Lismiyati Lulus Darwati, Lulus Maman Suryaman Moch. Abdul Mukid Muhammad Taufan Musandingmi Elok Nurul Islam, Musandingmi Elok Nurul Mustafid Mustafid Natanael, Dimas Kevin Ndaru Dian Darmawanti Nonik Brilliana Primastuti Novia Agustina, Novia Onny Kartika Hitasari, Onny Kartika Paula Meilina Dwi Hapsari Putri Agustina Rahmawati, Resti Rahmawati, Rizky Dwi Rambat Rambat, Rambat Ratih Binadari, Ratih Ria Sutitis, Ria Riana Ayu Andam Pradewi Richy Priyambodo Rita Rahmawati Riyan Eko Putri Rukun Santoso Sadjati, Ida Malati Sanitoria Nadeak, Sanitoria Seta Satria Utama Siti Anisah Sofyan Anif Sri Budiasih, Sri Sri Sumiyati Sri Wahyuningrum Sudarno Sudarno Sugito Sugito Sulton Syafii Katijaya Sunardi Sunardi Swasnita Swasnita, Swasnita T. Mart, T. Tarno Tarno Testiana Deni Wijayatiningsih Tiani Wahyu Utami Triastuti Rahayu Triastuti Wuryandari Triyanto Triyanto Tyas Estiningrum Umi Sulistyorini Adi, Umi Sulistyorini Victoria Dwi Murti Wasis Wicaksono Widari Widari, Widari Wulan Safitri, Wulan Yon Haryono Yuciana Wilandari Yudi Ari Wibowo Yusuf Arifka Rahman, Yusuf Arifka Zubaidah, Lailia