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Jurnal Gaussian

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Published by Universitas Diponegoro

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Jurnal Gaussian terbit 4 (empat) kali dalam setahun setiap kali periode wisuda. Jurnal ini memuat tulisan ilmiah tentang hasil-hasil penelitian, kajian ilmiah, analisis dan pemecahan permasalahan yang berkaitan dengan Statistika yang berasal dari skripsi mahasiswa S1 Departemen Statistika FSM UNDIP.

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Articles 693 Documents

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PERAMALAN HARGA SAHAM DENGAN METODE EXPONENTIAL SMOOTH TRANSITION AUTOREGRESSIVE (ESTAR) (Studi Kasus pada Harga Saham Mingguan PT United Tractors) Rahmayani, Dwi; Ispriyanti, Dwi; Mukid, Moch. Abdul
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The stock price data series of PT United Tractors in the period of December 1th 2008 to December 29th 2014 is fluctuative. To model data nonlinear time series one method that can be used is Smooth Transition Autoregressive (STAR), if the function of an exponential transition then a method that can be used is Exponential Smooth Transition Autoregressive (ESTAR). In modelling ESTAR determined transition variable ( of transition function ). Of the research result obtained model ESTAR (1,1). With significance level of 5% obtainedthe value of the stock price data for pt united tractors in the next four to the original. It was also strengthened by Mean Absolute Percentage Error (MAPE) 0,768233 % are relatively small. Keywords : Autoregressive,time series, nonlinearity, ESTAR, MAPEThe stock price data series of PT United Tractors in the period of December 1th 2008 to December 29th 2014 is fluctuative. To model data nonlinear time series one method that can be used is Smooth Transition Autoregressive (STAR), if the function of an exponential transition then a method that can be used is Exponential Smooth Transition Autoregressive (ESTAR). In modelling ESTAR determined transition variable ( of transition function ). Of the research result obtained model ESTAR (1,1). With significance level of 5% obtainedthe value of the stock price data for pt united tractors in the next four to the original. It was also strengthened by Mean Absolute Percentage Error (MAPE) 0,768233 % are relatively small. Keywords : Autoregressive,time series, nonlinearity, ESTAR, MAPE

PEMODELAN REGRESI SPLINE TRUNCATED UNTUK DATA LONGITUDINAL ( Studi Kasus : Harga Saham Bulanan pada Kelompok Saham Perbankan Periode Januari 2009 – Desember 2015 ) Khoirunnisa Nur Fadhilah; Suparti Suparti; Tarno Tarno
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

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

ANALISIS ANTRIAN PASIEN INSTALASI RAWAT JALAN RSUP Dr. KARIADI BAGIAN POLIKLINIK, LABORATORIUM, DAN APOTEK Rany Wahyuningtias; Dwi Ispriyanti; Sugito Sugito
Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

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. Patient’s line at RSUP DR. Kariadi is a lot enough then it will making the service from the hospital isn’t optimal as a result. Hence, it needed a queue model to optimize the service to patient. From the result of the analysis in RSUP Dr. Kariadi it gives the best queue models is in polyclinic area second floor, laboratory, and pharmacy.

PEMODELAN INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN REGRESI SPLINE MULTIVARIABEL Ihdayani Banun Afa; Suparti Suparti; Rita Rahmawati
Jurnal Gaussian Vol 7, No 3 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

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

OPTIMALISASI PARAMETER TEKNIK PENGELASAN FLUX CORED ARC WELDING (FCAW) MENGGUNAKAN METODE TAGUCHI MULTIRESPON PCR-TOPSIS Kusumawardani, Meilia; Mustafid, Mustafid; Yasin, Hasbi
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Multi response optimization case has encountered in industrial. Multirespon Taguchi TOPSIS PCR method is used to determine the optimal combination of factors/level and calculate the optimum performance for each response. Purpose of Taguchi method is to reduce the variability, and theory Process Capability Ratio (PCR) shows the process situation in which the parts produced are good or defective. Then Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to determine the optimal combination multi response case. The case study using the technique of Flux Cored Arc Welding welding (FCAW) using characteristic larger is better. Performance optimal conditions for factor Welding current at 280 ampere and factor Electrode stickout at 21 mm. Then optimal performance conditions for each responses are hardness=481.145 and deposition rate=3.813. These results have a higher value when compared with the initial conditions. So the case results meet the characteristics of larger is better. Keywords : Taguchi Method, PCR, TOPSIS, FCAW

PENENTUAN FAKTOR-FAKTOR YANG MEMPENGARUHI INTENSITAS CURAH HUJAN DENGAN ANALISIS DISKRIMINAN GANDA DAN REGRESI LOGISTIK MULTINOMIAL (Studi Kasus: Data Curah Hujan Kota Semarang dari Stasiun Meteorologi Maritim Tanjung Emas Periode Oktober 2018 – Maret 2019) Shella Faiz Rohmana; Agus Rusgiyono; Sugito Sugito
Jurnal Gaussian Vol 8, No 3 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Meteorologist develop rainfall forecasting methods to obtain better and more accurate rainfall information. One of them is the research of grid data and the method of grouping rainfall. According to BMKG, rainfall is classified into light, medium, and heavy rain. This study aims to determine the factors that influencing rainfall grouping using multiple discriminant analysis with a stepwise selection method. This study uses the daily climate data of Semarang City for period of October 2018 to March 2019. Based on its partial F value, the wind speed variable is eliminated so the significant variable on rainfall grouping are air temperature, air humidity, and wind direction. This analysis produces discriminant scores obtained from linear combinations between discriminant weights and observation values of significant independent variable. The classification procedure is based on the discriminant score each observations compared to cutting score resulted in classification accuracy of 62.89%. Multinomial logistic regression analysis is used to determine the effect of independent variables on rainfall intensity using the odds ratio. This analysis produces an estimate of the conditional probability of each group using significant independent variables are air temperature, air humidity, wind speed, and wind direction. The classification procedure is based on the largest conditional probability value between rainfall groups resulted in classification accuracy of 69.80%. Keywords: multiple discriminant analysis, multinomial logistic regresion, classification accuracy, rainfall

PERAMALAN INDEKS HARGA KONSUMEN MENGGUNAKAN MODEL INTERVENSI FUNGSI STEP Dita Ruliana; Sugito Sugito; Dwi Ispriyanti
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Intervention model is a model for time series data in which practically there is an extreme fluctuation, whether it’s anupward or downward fluctuation. Consumer price index is one of economic data which plot has a fluctuation, the data that will being used for analyze is consumer price index of Indonesia in January 2009 until March 2015, on data detectable downward fluctuation significantly on January 2014 (T=61). Intervention in data was occurred in long time period (T=61 until T=75), so the model of intervention’s assumption is step function. Based on the result and analysis, the obtaining best model of intervention is ARIMA (2,1,3) with intervention order b=0 s=15 and r=0 which later on being used for predicting Indonesian consumer price index in six periods ahead. Keywords : consumer price index, stationery, ARIMA, step function intervention analysis, forecasting

PENENTUAN CADANGAN DISESUAIKAN DENGAN METODE ILLINOIS PADA ASURANSI JIWA ENDOWMEN SEMIKONTINU Marlia Aide Revani; Yuciana Wilandari; Dwi Ispriyanti
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Semicontinuous endowment insurance is a kind of insurance with a periodic premium payments which gives two benefits, payment of death benefit at the moment of death if the insured dies during a certain period of years or payment of living benefit if the insured survives to the end of the period. The insurer’s obligation of insured’s premium payments, provides net level premium reserves for benefit payment in the future. The insurer needs expenses for it’s operate and in fact, the first year expenses usually exceed the loading. This means that an insurance company have to find funds to cover the first year expenses. The funds can be obtained by modified reserve system. To get information of modified reserve value for semicontinuous life insurance, the study of determination of modified reserve value using Illinois method has been done. The full net level reserves are lesser than the reserves under the Illinois method before the end of min(n, 20) years and both of these reserves will be equal at the the end of min(n, 20) years, with n is premium period.

KLASIFIKASI CALON PENDONOR DARAH MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER (Studi Kasus : Calon Pendonor Darah di Kota Semarang) Dhimas Bayususetyo; Rukun Santoso; Tarno Tarno
Jurnal Gaussian Vol 6, No 2 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Classification is the process of finding a model or function that describes and distinguishes data classes or concepts, for the purpose of being able to use the model to predict the class of objects whose class label is unknown. There are some methods that are included in the classification methods, one of them is Naïve Bayes. Naïve Bayes is a prediction technique that based simple probabilistic are based on the application of Bayes theorem with strong independence assumption. On this study carried out correction to the Naïve Bayes method in calculating the conditional probability of each feature using two approaches, normal density function and cumulative distribution function approaches. These two approaches are used to classify prospective blood donors in Semarang City. The predictor variables used are hemoglobin level, upper blood pressure, lower blood pressure, and weight. The result of this study shows that both approaches have the same Matthews Correlation Coefficient (MCC) values, 0.8985841 or close to +1. It means that both approaches equally well doing classification.Keywords: Classification, Naïve Bayes, Normal Density Function, Cumulative Distribution Function, Blood Donors, Matthews Correlation Coefficient (MCC).

ANALISIS SISTEM ANTREAN PELAYANAN DI KANTOR PERTANAHAN KOTA SEMARANG Lenti Agustina Lianasari Tambunan; Sugito Sugito; Hasbi Yasin
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Kantor Pertanahan Kota Semarang in charge of the land with an area of 373.70 km2 coverage, every day crowded with visitors who want to take care of the land petition. However, the high number of applicants who must be served not proportional to the number of care facilities available to the applicant should enter the waiting list queue or experiencing situation. This situation occurs in almost all counters, namely Counter 1 Land Information, Counter 2 Registration, Counter 3 Payment, and Counter 4 Product Delivery. Therefore, the required analysis is based on the model line system in accordance with the conditions of service which can then be used to address the issue queue. Based on the analysis, the model system is the best line in counter 1 land information (M/M/1): (GD/∞/∞). Counter 2 registration which is divided into 7 sub-counters have a model (M/M/2): (GD/∞/∞) to sub counters 2A, 2B, 2C, 2E/F, 2G, 2H, and the model (M/M/4): (GD/∞/∞) to sub counter 2D. Counter 3 payment (M/M/2): (GD/∞/∞). Counter 4 is the product delivery (M/M/2): (GD/∞/∞).Keywords : Queuing system, Service, Arrivals

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Department of Statistic, Faculty of Science and Mathematics , Universitas Diponegoro Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro Gedung F lt.3 Tembalang Semarang 50275

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Kota semarang,

Jawa tengah

INDONESIA