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All Journal PROSIDING SEMINAR NASIONAL Media Statistika SAINS DAN MATEMATIKA Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang E-Dimas: Jurnal Pengabdian kepada Masyarakat Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) EKO-REGIONAL JURNAL PENGEMBANGAN EKONOMI WILAYAH

Abdul Hoyyi

Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

Author-ID : 3131506

Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Social Sciences Other

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ANALISIS SISTEM ANTRIAN PADA LAYANAN PENGURUSAN PASPOR DI KANTOR IMIGRASI KELAS I SEMARANG Purina Pakurnia Artiguna; Sugito Sugito; Abdul Hoyyi
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Queue is something that can not be separated in everyday life. Almost all services will form a queue, including passport treatment services at the Immigration Office Class I Semarang.To solve the problems associated with the queue, queuing system model needs to be determined in accordance with the conditions and characteristics queue of the service facility at the Immigration Office Class I Semarang appropriately. So it can be known the measure of system performance to create an effective and efficient service. Based on the data analysis of the six (6) counters work, obtained queuing system model that occurs at the Immigration Office Class I Semarang is, (M/M/2) queuing model for Passports Taking Counter and Customer Service Counter, queuing model for file transfer counter and payment transfer counter, and queuing model for photos counter and interview counter. The effectiveness of the applicant’s passport service process can be determined by calculating the average number of applicants in the system and queue, calculates the average time spent in the system and queue, and calculates the probability of a server that is not serving an applicant. Keywords : Queuing system model, Passport’s services, Size of system performanceANALISIS SISTEM ANTRIAN PADA LAYANAN PENGURUSAN PASPOR DI KANTOR IMIGRASI KELAS I SEMARANG

FAKTOR-FAKTOR YANG MEMPENGARUHI KRIMINALITAS DI KABUPATEN BATANG TAHUN 2013 DENGAN ANALISIS JALUR Dermawanti Dermawanti; Abdul Hoyyi; Agus Rusgiyono
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Crime or criminality in Indonesia is rampant both in print or television can be seen almost every day news about crime. Basically, each individual will be influenced by several factors, both internal and external causes a person to commit a criminal act, including population, education, morality, poverty, and unemployment. In this case will be studied in a statistical analysis that can detect the magnitude of these factors, either directly or indirectly to the level of criminality. One of the statistical analysis that can be used to analyze the causal relationship of the variables is the path analysis (path analysis) which is a direct development of multiple regression form with the aim to provide estimates of the level of interest (magnitude) and significance (significance) in a hypothetical causal link set variable. In this study showed that the factor that has the greatest positive effect on crime is unemployment factor of 0.395 with immediate effect. A factor which has the second largest positive effect of education is a factor of 0.222 to the direct effects and the indirect effect of 0.0818. Meanwhile, a factor that has a positive influence smallest is the moral factor to the effect of 0.180.Keywords : Criminality, Path Analysis

METODE PERAMALAN DENGAN MENGGUNAKAN MODEL VOLATILITAS ASYMMETRIC POWER ARCH (APARCH) Cindy Wahyu Elvitra; Budi Warsito; Abdul Hoyyi
Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Exchange rate can be defined as a ratio the value of currency. The exchange rate shows a currency price, if it exchanged with another currency. Exchange rates of a currency fluctuate all the time. Rise and fall exchange rates of a currency in the money market shows the magnitude of volatility occurred in a country currency to other's. To estimate the volatility behavior of the data gave rise to volatility clustering or heteroscedasticity problems, can’t be modeled using ARMA model and asymmetric effects that can‘t be modeled by ARCH or GARCH, can be modeled by Asymmetric Power ARCH (APARCH). In determining the estimated parameter values of APARCH model, used the maximum likelihood method, followed by using the iteration method is Berndt, Hall, Hall and Hausman (BHHH). The APARCH model used to the data return of exchange rate against dollar is APARCH(2,1) or in the form as follows : = 0,00000268 + 0,830902 + 0,130516 + 0,074784 + 0,151157

PEMODELAN REGRESI ROBUST S-ESTIMATOR UNTUK PENANGANAN PENCILAN MENGGUNAKAN GUI MATLAB (Studi Kasus : Faktor-Faktor yang Mempengaruhi Produksi Ikan Tangkap di Jawa Tengah) Dhea Kurnia Mubyarjati; Abdul Hoyyi; Hasbi Yasin
Jurnal Gaussian Vol 8, No 1 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Multiple Linear Regression can be solved by using the Ordinary Least Squares (OLS). Some classic assumptions must be fulfilled namely normality, homoskedasticity, non-multicollinearity, and non-autocorrelation. However, violations of assumptions can occur due to outliers so the estimator obtained is biased and inefficient. In statistics, robust regression is one of method can be used to deal with outliers. Robust regression has several estimators, one of them is Scale estimator (S-estimator) used in this research. Case for this reasearch is fish production per district / city in Central Java in 2015-2016 which is influenced by the number of fishermen, number of vessels, number of trips, number of fishing units, and number of households / fishing companies. Approximate estimation with the Ordinary Least Squares occur in violation of the assumptions of normality, autocorrelation and homoskedasticity this occurs because there are outliers. Based on the t- test at 5% significance level can be concluded that several predictor variables there are the number of fishermen, the number of ships, the number of trips and the number of fishing units have a significant effect on the variables of fish production. The influence value of predictor variables to fish production is 88,006% and MSE value is 7109,519. GUI Matlab is program for robust regression for S-estimator to make it easier for users to do calculations. Keywords: Ordinary Least Squares (OLS), Outliers, Robust Regression, Fish Production, GUI Matlab.

PEMODELAN METODE BROWN’S DOUBLE EXPONENTIAL SMOOTHING (B-DES) DAN BROWN’S WEIGHTED EXPONENTIAL MOVING AVERAGE (B-WEMA) MENGGUNAKAN OPTIMASI LEVENBERG-MARQUARDT PADA JUMLAH WISATAWAN DI JAWA TENGAH Dilla Retno Deswita; Abdul Hoyyi; Tatik Widiharih
Jurnal Gaussian Vol 9, No 3 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v9i3.27956

The tourism sector is one of the national development priority sectors because it contributes to foreign exchange earnings, the development of business areas, and the absorption of investment and labor. In 2018 the tourism sector will become the second largest foreign exchange earner after oil palm. Foreign exchange contributed by the tourism sector in 2018 was US $ 19.29 billion, an increase of 15.4%. The increase in contributions was driven by an increase in the number of foreign tourist arrivals by 12.58%, domestic tourists by 12.37%, and from investment. Therefore it is necessary to study the forecasting of the number of tourists after seeing the great potential generated from the tourism sector. The data forecast is data on the number of tourists in Central Java, both foreign and domestic data. Both data shows the tendency of an upward trend pattern. So that both data can be analyzed using B-DESmethods (Brown's Double Exponential Smoothing) and B-WEMA (Brown's Weighted Exponential Moving Average)that are optimized with LM (Levenberg-Marquardt). Both methods are able to analyze trend patterned data without assumptions making it easier in the analysis process. In addition, the two methods in previous studies were able to produce a small forecasting accuracy. The MAPE (Mean Absolute Percentage Error) value out sample is used to compare the forecasting results of the two methods. The results of the implementation of LM optimization on the data of the number of domestic tourists obtained the optimal parameter value of the B-DES method is 0.21944386 with MAPE out sample 16.26516% and B-WEMA method is 0.219441 with MAPE out sample 16.26515%. While the data on the number of foreign tourists obtained the optimal parameter value of the B-DES method was 0.26213368 with the MAPE out of the sample 23.61278% and the B-WEMA method was 0.26213367 with the MAPE out the sample 23.61278%. This means that both methods have a good level of forecasting accuracy in the data on the number of domestic tourists and an adequate level of accuracy in the data on the number of foreign tourists. Keywords : B-DES, B-WEMA, Levenberg-Marquardt, Tourists in Central Java

PERAMALAN LAJU INFLASI, SUKU BUNGA INDONESIA DAN INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN METODE VECTOR AUTOREGRESSIVE (VAR) Priska Rialita Hardani; Abdul Hoyyi; Sudarno Sudarno
Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Inflation, Bi Rate (SBI) and the composite stock price index (IHSG) is an economic instrument and often seen as divorce progression of the economic progress of a country. Inflation, Bi Rate and IHSG is a multivariate time series that show activity for a certain period. One method to analyze multivariate time series is Vector Autoregressive (VAR). VAR method is a simultaneous equation model has several endogeneous variables. This research uses secondary data of inflation, SBI and IHSG on period January to June 2016. The VAR model acquired is a model VAR(4), with parameters estimated using the Ordinary Least Square (OLS). The selection model VAR(4) is based on the smallest value of AIC 4,255482 with value of MAPE is 47,11%. Keywords: Inflation, SBI, IHSG, Time Series Multivariate, Forecasting, Vector Autoregressive (VAR).

ANALISIS EKUITAS MEREK SEPEDA MOTOR HONDA TERHADAP KEPUTUSAN PEMBELIAN DAN PERILAKU PASCA BELI MENGGUNAKAN STRUCTURAL EQUATION MODELLING (SEM) Herwindhito Dwi Putranto; Abdul Hoyyi; Moch. Abdul Mukid
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Research on the implementation of Structural Equation Modelingto analyze the Honda brand equityon purchase decision and post-purchase behavior is based on the strength of the brand equityas a market leader Honda motorcycles in Indonesia for many years. The problem saddressed in this study is how the relationship between brand equity Honda motorcycle on purchase decision and post purchase behavior of consumers. In this study developed six variables consisting of 4 exogenous variables, namely brand awareness, brand response, the impression of quality and product loyalty, to measure brand equityas well as two endogenous variables, ie, purchase decision and post-purchase behavior. The study involved 200 students of the University of Diponegoro as respondents using purposive sampling technique.Structura lequation modeling research is Behavioral Post Buy=Purchasing Decisions + error. From the Goodness of Fittest results, structural equation modelin this study can be used with a value of 70,237 and the Chi-Square probability AGF I1000 and 0951. Brand awareness of 10.1% influence on purchasing decisions and 10% of the post-purchase behavior and is avariable that gives the effect of CR 1477-value ≤2.58. Responses highest brandin fluenceis equal to 32.7% against 32.4% purchase decision and post-purchase behavior. Thusit was concluded that brand awareness does not affect the purchase decision, while there sponse the brand, the impression of quality and product loyalty influence purchasing decisions. Purchasing decisions also provide a positive influence on post-purchase decisions.

PENGELOMPOKAN PROVINSI DI INDONESIA BERDASARKAN KARAKTERISTIK KESEJAHTERAAN RAKYAT MENGGUNAKAN METODE K-MEANS CLUSTER Fitra Ramdhani; Abdul Hoyyi; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Welfare have a relative explanation, dynamic, and quantitative. Quantitative formulation of welfare is never final because it will continue to evolve along with the development needs of human life. In 2011, the National Team for the Acceleration of Poverty Reduction (NTAPR) made priority sector that can serve as a benchmark the welfare in a region. From the priority sector will be made cluster or group which contains all 33 provinces based on the level of public welfare in the region uses data in 2012 were sourced from the Central Statistics Agency (CSA). The method that can be used to group the 33 provinces is K-Means Cluster method with number cluster as many as two, three, four, and five clusters. K-Means Cluster method is one of cluster analysis method who can partition the data into one or more clusters, so that the data with the same characteristics are grouped into the same cluster and data with different characteristics grouped into other clusters. To know the most optimal of the number of clusters we use Davies-Bouldin Index (DBI). We concluded that the optimal number of cluster is three with details the province in the first clusters have superiority in four sectors like net enrollment rate of primary school, net enrollment rate of junior high school, IMR (Infant Mortality Rate), and access to electricity. The province in the second clusters have superiority in one sector, that is open unemployment rate. The province in the third clusters have superiority in all sectors. Keywords: Welfare, NTAPR Priority Sector, K-Means Cluster Method, Davies-.Bouldin Index (DBI)

PEMODELAN TRANSFORMASI FAST-FOURIER PADA VALUASI OBLIGASI KORPORASI (Studi Kasus: PT. Bank Danamon Tbk, PT. Bank CIMB Niaga Tbk, dan PT. Bank UOB Indonesia Tbk) Ubudia Hiliaily Chairunnnisa; Abdul Hoyyi; Hasbi Yasin
Jurnal Gaussian Vol 10, No 1 (2021): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v10i1.30937

The basic assumption that is often used in bond valuations is the assumption on the Black-Scholes model. The practical assumption of the Black-Scholes model is the return of assets with normal distribution, but in reality there are many conditions where the return of assets of a company is not normally distributed and causing improperly developed bond valuation modeling. The Fast-Fourier Transform model (FFT) was developed as a solution to this problem. The Fast-Fourier Transformation Model is a Fourier transformation technique with high accuracy and is more effective because it uses characteristic functions. In this research, a modeling will be carried out to calculate bond valuations designed to take advantage of the computational power of the FFT. The characteristic function used is the Variance Gamma, which has the advantage of being able to capture data return behavior that is not normally distributed. The data used in this study are Sustainable Bonds I of Bank Danamon Phase I Year 2019 Series B, Sustainable Bonds II of Bank CIMB Niaga II Phase IV Year 2018 Series C, Sustainable Subordinated Bonds II of Bank UOB Indonesia Phase II 2019. The results obtained are FFT model using the Variance Gamma characteristic function gives more precise results for the return of assets with not normal distribution. Keywords: Bonds, Bond Valuation, Black-Scholes, Fast-Fourier Transform, Variance Gamma

PEMODELAN GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION (GWLR) DENGAN FUNGSI PEMBOBOT FIXED GAUSSIAN KERNEL DAN ADAPTIVE GAUSSIAN KERNEL (Studi Kasus : Laju Pertumbuhan Penduduk Provinsi Jawa Tengah) Desriwendi Desriwendi; Abdul Hoyyi; Triastuti Wuryandari
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The Population Growth Rate (PGR) that are not controlled will have a negative impact on the various social-economic problems such as increased poverty, crime, and so forth. Factors contributing to the population growth rate of uncontrolled allegedly various between Regency/City. Geographically Weighted Logistic Regression (GWLR) is a local form of the logistic regression where geographical factors considered. This study will analyze the factors that affect the population growth rate of Central Java Province using logistic regression and GWLR with a weighting function of Fixed Gaussian Kernel and Adaptive Gaussian Kernel. The results showed that GWLR model with a weighting function of Adaptive Gaussian Kernel better than logistic regression model and GWLR model with a weighting function of Fixed Gaussian Kernel because it has the smallest Akaike Information Criterion (AIC) value with the classification accuracy is 82.8 %.Keywords : PGR, Logistic Regression, Fixed Gaussian Kernel, Adaptive Gaussian Kernel, GWLR, AIC.

Co-Authors Abdurakhman Abdurakhman Afifah Alrizqi Agus Rusgiyono Agus Somantri Ahmat Dhani Riau Bahtiyar Alan Prahutama Alan Prahutama Alifah Zahlevi Allima Stefiana Insani Alvi Waldira Alwi Assegaf Amelia Crystine Anggit Ratnakusuma Anggita, Esta Dewi Anik Nurul Aini Annisa Intan Mayasari ANNISA RAHMAWATI Ari Fakhrus Sanny Arief Rachman Hakim Arya Huda Arrasyid Aulia Desy Deria Avia Enggar Tyasti Bella Cynthia Devi Besya Salsabilla Azani Arif Bisri Merluarini Bitoria Rosa Niashinta Budi Warsito Budi Warsito Candra Silvia Chyntia Arum Widyastusti Cindy Wahyu Elvitra Darwanto Darwanto Dea Manuella Widodo Deby Fakhriyana, Deby Dede Zumrohtuliyosi Deden Aditya Nanda, Deden Aditya Dedi Rosadi Dermawanti Dermawanti Desriwendi Desriwendi Dewi Erliana Dewi Setya Kusumawardani Dhea Kurnia Mubyarjati Di Asih I Maruddani Di Asih I Maruddani Di Asih I Maruddani Diah Safitri Diah Safitri Diah Wulandari Dilla Retno Deswita Dwi Ispriyanti DWI RAHMAWATI Emyria Natalia br Sembiring Endah Cahyaningrum Erna Musri Arlita Esti Pratiwi Faiqotul Himmah Fiki Farkhati Firda Dinny Islami Fitra Ramdhani Gayuh Kresnawati Hasbi Yasin Hasbi Yasin Henny Setyowati Herwindhito Dwi Putranto Ikha Rizky Ramadani Indri Puspitasari Irfan Afifi Isowedha Widya Dewi Issabella Marsasella Christy Jeffri Nelwin J. O. Siburian Juli Sekar Sari, Juli Sekar Kartikaningtiyas Hanunggraheni Saputri Khotimatus Sholihah Khusnul Umi Fatimah Kiki Febri Azriati Koko Arie Bowo Kristika Safitri Kumo Ratih Leni Pamularsih Maidiah Dwi Naruri Saida Malik Hakam Mega Fitria Andriyani Mega Fitria Andriyani Mia Anastasia Sinulingga Moch. Abdul Hoyyi Moch. Abdul Mukid Moch. Abdul Mukid MUHAMMAD HARIS Mustafid Mustafid Mustafid Mustafid Mutiara Ardin Rifkiani Nadya Kiki Aulia Nandang Fahmi Jalaludin Malik Novika Pratnyaningrum Nurissalma Alivia Putri Nurul Fauziah Ovie Auliya’atul Faizah Priska Rialita Hardani Purina Pakurnia Artiguna Rita Rachmawati Rita Rahmawati Rita Rahmawati Rizki Pradipto Widyantomo Rizky Oky Ari Satrio Rukun Santoso Saputri, Ani Funtika Saraswati, Mei Sita Shaumal Luqman Silvia Nur Rinjani SITI NURLATIFAH Sudarno Sudarno Sudarno Sudarno Sugito - Sugito Sugito Sugito Sugito Suparti Suparti Suparti Suparti Tarno Tarno Tarno Tarno Tatik Widiharih Tatik Widiharih Tatik Widiharih Titis Nur Utami Tresno Sayekti Nuryanto Triastuti Wuryandari Triastuti Wuryandari Trisnawati Gusnawita Berutu Ubudia Hiliaily Chairunnnisa Ulfah Sulistyowati Yosi Dhyas Monica Yuciana Wilandari Yuciana Wilandari Yudia Yustine Yunisa Ratna Resti Yustian Dwi Saputra

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