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Journal : Jurnal Gaussian

ANALISIS INDEKS HARGA SAHAM GABUNGAN (IHSG) DENGAN MENGGUNAKAN MODEL REGRESI KERNEL Puspitasari, Icha; Suparti, Suparti; Wilandari, Yuciana
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

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.
PEMODELAN TINGKAT PENGANGGURAN TERBUKA DI JAWA TENGAH MENGGUNAKAN REGRESI SPLINE Utama, Seta Satria; Suparti, Suparti; Rahmawati, Rita
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

Unemployment is one of the employment problems facing Indonesia. Central Java Province is one of the provinces with a high enough unemployment. The main indicators used to measure the unemployment rate in the labor force that is unemployed. Based on research Arianie (2012) labor force participation rate significantly affect the unemployment rate and based on research Sari (2012) the gross enrollment ratio significantly affects the rate of open unemployment. Therefore, in this study using the two predictor variables with the labor force participation rate as X1 and gross enrollment rate as X2. This study aimed to explore the model of open unemployment rate in the Province of Central Java. The method used is the method of spline regression. Spline regression has the ability to adapt more effectively to the data patterns up or down dramatically with the help of dots knots. Determination of the optimal point knots are very influential in determining the best spline models. The best spline models are models that have a minimum GCV (Generalized Cross Validation) Value. Best spline models for the analysis of the data rate of unemployment in Central Java Province is the spline regression model when order X1 is 2 and order X2 is 4 and large number of knots in the X1 is 1 knot at the point 68.02394 and X2 is 3 knots at the point 82.13, 87.19, and 87.65 with GCV value of 1.732746. Keywords: Rate of  Open Unemployment, Spline Regression, GCV
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): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

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.
PERBANDINGAN METODE REGRESI LOGISTIK BINER DAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) PADA PEMINATAN JURUSAN SMA (Studi Kasus SMA Negeri 2 Semarang) Binadari, Ratih; Wilandari, Yuciana; Suparti, Suparti
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

Major specialization at High School is aimed to gives opened opportunity for students to choose subject that are interest and develop their potential in accordance with the abilities, interests, talents, and personality. Major specialization at High school is influenced by some factors. To detect those factors, used biner logistic regression method and Multivariate Adaptive Regression Spline (MARS). Biner Logistic Regression is method that describes relationship between dependent variable and some independent variable, with independent variable has been coded 1 as representing the presence of the characteristic, and 0 as representing the absence of the characteristic. MARS is multivariate nonparametric regression method that development of Recursive Partitioning Regression (RPR) method and Spline method for high dimensional data that produces accurate prediction and continuous models on knots. Both of the methods are compared to know the best method used in research. From the result of analysis using biner logistic regression method and MARS, concluded that major specialization has been influenced by mathematic score, science score and relationship between students and friends. From proportion test, concluded classification that formed by regression logistic is as good as by MARS. Keywords : Major specialization at High School, Biner Logistic Regression, Mutlivariate Adaptive Regression Spline (MARS), Clasification
ANALISIS PENGENDALIAN KUALITAS MENGGUNAKAN DIAGRAM KENDALI DEMERIT (Studi Kasus Produksi Air Minum Dalam Kemasan 240 ml di PT TIW) Ramadhani, Gita Suci; Wilandari, Yuciana; Suparti, Suparti
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

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.
KAJIAN RELIABILITAS DAN AVAILABILITAS PADA SISTEM KOMPONEN PARALEL Pradewi, Riana Ayu Andam; Sudarno, Sudarno; Suparti, Suparti
Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

Reliability and availability are a measure of item or system performance. System reliability and system availability obtained from the calculation of reliability and availability of the components in the system. Reliability of components in the system are affected by the time to failure (TTF). While the availability of components in the system are affected by the mean time to failure (MTTF) and mean time to repair (MTTR). Given observed time data of lifting machines consists of trolley drive and hoist in parallel, is measured its system availability. Parameter values determined using simple linear regression and maximum likelihood estimation. Furthermore observation time test data distributions in the Kolmogorov-Smirnov test. Trolley drive has exponential distribution for failure time data with  while repair time data is normal distribution with  and . Hoist has weibull failure time data with  and  while lognormal repair time data has  and . The higer value of ti,system reliability value will be close to 0 and the engine can survive until the specified time. Due to MTTF is 4000 hours and MTTR is 45,70 hours, trolley drive’s availability is 98,87%. Availability of hoist is 98,84% from MTTF is 5821,61 hours and MTTR is 67,80 hours. The parallel system availability is 99,986% means the probability of system is in the state of functioning at given time is 99,986%.
PROYEKSI DATA PRODUK DOMESTIK BRUTO (PDB) DAN FOREIGN DIRECT INVESTMENT (FDI) MENGGUNAKAN VECTOR AUTOREGRESSIVE (VAR) Satria, Indra; Yasin, Hasbi; Suparti, Suparti
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

Gross Domestic Product (GDP) and Foreign Direct Investment (FDI) is an economic instrument that has an attachment and often used for economic development of a country. To predict these two variables there are several methods that can be used, one of which is a method of Vector Autoregressive (VAR). VAR method has some assumptions that the data to be foreseen must have an attachment, stationary in the mean and variance and the resulting error must meet the test of independence and normal distribution. In the early stages of identification done by considering the value of AIC as a determinant of the optimal lag value, which in this case lag 4 who came out as the optimal lag. Granger causality test as an attachment test between variable and Augmented Dickey Fuller test (ADF) as a stationary test. In the parameter estimation phase used Ordinary Least Square method (OLS) to determine the values of the parameters to be used as a model. After getting the model it is necessary to do verification on condition that the residuals must comply with the independence test and multivariate normal test. With a second fulfillment verification test is carried out projections for the next 5 years with a value of R-Square 64% to GDP and 48% for the variable FDI Keywords: FDI, GDP, VAR, causality, independency, multivariate normal, R-Square
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): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

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.
PEMODELAN REGRESI SPLINE TRUNCATED UNTUK DATA LONGITUDINAL ( Studi Kasus : Harga Saham Bulanan pada Kelompok Saham Perbankan Periode Januari 2009 – Desember 2015 ) Fadhilah, Khoirunnisa Nur; Suparti, Suparti; Tarno, Tarno
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

Stocks are securities that can be bought and sold by individuals or institutions as a sign of ownership of any person nor bussines entity within a company. From the value of market capitalization, the stock is divided into 3 groups: large capitalization (big-cap), medium capitalization (mid-cap), and small capitalization (small-cap). The stocks has been fluctuated up and down because of several factors, one of them is inflation. Longitudinal data are observations made of n subjects that mutually independent with each subject which observed repeatedly in different period of time mutually dependent. Modelling longitudinal data of stock prices do with truncated spline nonparametric regression approach. The best model of spline depends on the determination of the optimal knot points which has minimum value of Generalized Cross Validation (GCV). The best of truncated spline regression is spline order 2 with 3 knot points for each of the subjects on longitudinal data. By using the model, the value of MAPE for each subject is 29,93% for PT Bank Mandiri (Persero) Tbk., 16,67% for PT Bank Bukopin Tbk., and 12,99% for PT Bank Bumi Arta Tbk.. Keywords: stocks, longitudinal data, truncated spline, GCV
PEMODELAN INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN REGRESI SPLINE MULTIVARIABEL Afa, Ihdayani Banun; Suparti, Suparti; Rahmawati, Rita
Jurnal Gaussian Vol 7, No 3 (2018): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

The Composite Stock Price Index (CSPI) is a composite index of all types of shares listed on the stock exchange and their movements indicate the conditions occurring in the stock market. CSPI movement is an important indicator for investors to determine whether they will sell, hold, or buy a stock. One of the factors that influence the movement of CSPI is Inflation (X1), Exchange Rate (X2) and SBI rate (X3). This study aims to obtain the best CSPI model using a multivariable nonparametric spline regression approach. The approach is done by nonparametric regression because the regression curve obtained does not show a certain relationship pattern. Spline is very dependent on the order and location of the knot point. The best spline model is the model that has the minimum MSE (Mean Square Error) value. In this study, the best spline regression model is when X1 is 4 order, X2 is 2 order and X3 is 2 order. The number of knots on X1 is 1 knot at 8.22, X2 is 2 knots at 13066.82 and 13781.75 While X3 is 2 knots at 6.6 and 6.67 with value of MSE equal to 6686.85.Keywords: Composite Stock Price Index, Multivariable Spline Regression, MSE
Co-Authors A. Sulaksono, A. Abdul Hoyyi Afa, Ihdayani Banun Agus Cahyono Agus Rusgiyono Agustina, Dwi Ampuni Ahmad Reza Aditya Akhmad Zaki Alan Prahutama Alanindra Saputra Alvita Rachma Devi Amanda Devi Paramitha, Amanda Devi Aminah Asngad Any Setyaningsih, Any Arief Rachman Hakim Asismarta Asismarta, Asismarta Azizah, Adilla Nur Bayu Ariawan Budi Warsito Bunga Maharani, Bunga C Yuwono Sumasto, C Yuwono Deden Aditya Nanda, Deden Aditya Destiyani, Eka Di Asih I Maruddani Diah Budiati Diah Safitri Dini Puspita Dwi Ispriyanti Dwi Wahyuningsih, Dwi Dyah Ayu Kusumaningrum Ebeit Devita Simatupang Elyas Darmawan Ernawati, Devi Ernik Yuliana Esti Pratiwi Fadilah, Eka Fajar Heru Setiawan, Fajar Heru Farah, Sania Anisa Farikhin Farikhin Femadiyanti, Siti Fadhilla Fina Fitriyana Firda Megawati, Firda Fitri Juniaty Simatupang, Fitri Juniaty Fitriyatno Fitriyatno Gita Suci Ramadhani Habibah, Immawati Ainun Hafii Risalam, Hafii Hamid, Lukman Hanifa Eka Oktafiani, Hanifa Eka Happy Suci Puspitasari Hasbi Yasin Icha Puspitasari Ikrima, Hanjar Indra Satria, Indra Iwan Ali Sofwan Izzudin Khalid, Izzudin Karimawati, Nurul Kartika, Aninda Ayu Kartikaningtiyas Hanunggraheni Saputri, Kartikaningtiyas Hanunggraheni Khoirunnisa Nur Fadhilah, Khoirunnisa Nur Khoirunnisa, Siti Intan Lailly Rahmatika, Lailly Lestariningsih, Eni Dwi Lina Agustina, Lina Lintang Afdianti Nurkhasanah, Lintang Afdianti Lismiyati Marfuah, Lismiyati Lulus Darwati, Lulus Ma'sum, M. Ali Maman Suryaman Moch. Abdul Mukid Mu'affa, Lamik Nabil Muhammad Taufan Muqorobin, Masculine Muhammad Musandingmi Elok Nurul Islam, Musandingmi Elok Nurul Mustafid Mustafid Mustofa, Achmad 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 Ramadhan, Setyoko Prismanu Rambat Rambat, Rambat Ratih Binadari, Ratih Renti Oktaria, Renti Ria Sutitis, Ria Riana Ayu Andam Pradewi Richy Priyambodo Rinjani, Silvia Nur Rita Rahmawati Riyan Eko Putri Rizani, Nurul Fitria Fitria Rukun Santoso Sa'adah, Alfi Faridatus Sadjati, Ida Malati Sadjati, Ida Malati Safitri, Wardani Ana Sanitoria Nadeak, Sanitoria Sari, Shinta Karunia Permata Seta Satria Utama Setiawan, Fuad Alfaridzi Setiawati, Teti Setya Ayu Rahmawati Siti Anisah Sofyan Anif Sri Budiasih, Sri Sri Sumiyati Sri Wahyuningrum Sudargo Sudargo, Sudargo Sudarno Sudarno Sugito Sugito Suhartini, Arianti Sulton Syafii Katijaya Sunardi Sunardi Surasmi, Wuwuh Asrining Swasnita Swasnita, Swasnita Syariati, Dian T. Mart, T. Tarno Tarno Tatik Widiharih Tedjo, Martyanto Testiana Deni Wijayatiningsih Tiani Wahyu Utami Triastuti Rahayu Triastuti Wuryandari Triyanto Triyanto Tyas Estiningrum Umi Sulistyorini Adi, Umi Sulistyorini Vera Handayani Victoria Dwi Murti Wasis Wicaksono Widari Widari, Widari Wulan Safitri, Wulan Yasir Sidiq Yon Haryono Yuciana Wilandari Yudi Ari Wibowo Yuningsih Yuningsih Yusuf Arifka Rahman, Yusuf Arifka Zia, Nabila Ghaida Zubaidah, Lailia