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All Journal Jurnal Matematika International Journal of Science and Engineering (IJSE) Media Statistika SAINS DAN MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Science and Technology E-Dimas: Jurnal Pengabdian kepada Masyarakat Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Jurnal Riset Teknologi Pencegahan Pencemaran Industri STATISTIKA

Hasbi Yasin

Department Of Statistics, Faculty Of Sciences And Mathematics, Diponegoro University

Author-ID : 422426

Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Identifikasi Faktor-Faktor Penyebab Kejadian Diare Di Kota Semarang Dengan Pendekatan Geographically Weighted Poisson Regression Yasin, Hasbi; Rusgiyono, Agus
JURNAL SAINS DAN MATEMATIKA Volume 21 Issue 3 Year 2013
Publisher : JURNAL SAINS DAN MATEMATIKA

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The percentage of people affected by diarrheal diseases are still quite high, reaching 5.2%. Therefore we need an effort to identify the factors that cause diarrhea efforts of the government in order to reduce morbidity of diarrhea optimally. Such efforts include reviewing of the factors causing the incidence of diarrhea by focusing on linkages between regions or spatial aspects. Spatial aspect is considered important to study because between regions must have different characteristics. One approach that can be used is a spatial model Geographically Weighted Poisson Regression (GWPR) which is a local form of the Poisson Regression. This research was conducted in Semarang city with the unit of observation is the 16 districts in Semarang city. The results showed that the locally influential variable is the number of protected drinking water facilities and the number of medical personnel available. This model has a level of accuracy of 84.33%.

ANALISIS FAKTOR-FAKTOR TINGKAT KEMISKINAN DI KABUPATEN WONOSOBO DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION Permana, Maulana Taufan; Yasin, Hasbi; Rusgiyono, Agus
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Poverty reduction is the main priority in development strategies in Indonesia, but during this computation is modeled as a function of the poor global regression. That is, the value of the regression coefficient applies to all geographic regions. In reality each region has different characteristics according to the geographical location, therefore Geographically Weighted Regression models are developed (GWR). GWR model is used to consider the element of geography or location as the weighting in estimating the model parameters. In the model GWR model parameter estimation is obtained by using Weighted Least Square (WLS) is to give a different weighting at each location. This study discusses the factors that affect the level of poverty in the District Wonosobo. The results of testing the suitability of the model shows that there is no spatial factors influence the level of poverty in the District Wonosobo. Based on research, there are 3 variables thought to affect the level of household poverty in Wonosobo district, percentage of the number of families that have slums, percentage number of families severely malnourished, percentage of the number of families who have agricultural land. These variables have a similar effect in each district.Keywords: Poverty, Geographically Weighted Regression, Weighted Least Square, Wonosobo

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

PERBANDINGAN METODE KLASIFIKASI REGRESI LOGISTIK BINER DAN RADIAL BASIS FUNCTION NETWORK PADA BERAT BAYI LAHIR RENDAH (Studi Kasus: Puskesmas Pamenang Kota Jambi) Samosir, Riama Oktaviani; Wilandari, Yuciana; Yasin, Hasbi
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Low Birth Weight (LBW) is one of the main causes of infant mortality. LBW must be identified and predicted before the baby birth by observing historical data of expectant. This research aims to analyze the classification of status newborn in order to reduce the risk of LBW. The statistical method used are the Binary Logistic Regression and Radial Basis Function Network. The data used in this final project is birth weight at Pamenang Jambi City health center in 2014. In this research, the data are divided into training data and testing data. Training data will be used to generate the model and pattern formation, while testing the data is used to measure how the accuracy of the representative model or pattern formed in classifying data through confusion tables. The results of analysis showed that the Binary Logistic Regression method gives 81,7% of classification accuracy for training data and 77,4% of classification accuracy for testing data, while Radial Basis Function Network method gives 92,96% of classification accuracy for training data and 80,64% of classification accuracy for testing data. Radial Basis Function Network method has better classification accuracy than the Binary Logistic Regression method. Keywords: Low Birth Weight (LBW), Binary Logistic Regression, Radial Basis Function Network, Classification, Confusion

PERBANDINGAN MODEL GWR DENGAN FIXED DAN ADAPTIVE BANDWIDTH UNTUK PERSENTASE PENDUDUK MISKIN DI JAWA TENGAH Pamungkas, Rifki Adi; Yasin, Hasbi; Rahmawati, Rita
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Regression analysis is statistical method for modeling the dependency relationship that might exist among the dependent variable with independent variable. Geographically Weighted Regression (GWR) is an expansion of linier regression model where each of the parameters from every observation sites is counted, so each sites have local regression parameter. Weighted Least Square (WLS) model is applied to estimate the parameter of GWR model. GWR method differentiates bandwidth kernel into two, fixed bandwidth kernel and adaptive bandwidth kernel. Fixed kernel has the same bandwidth in each observation location, meanwhile adaptive kernel has different bandwidth value in each observation location. Cross Validation (CV) is used to choose the most optimum bandwidth. The application of GWR model to show the percentage of poor population at district and city of Central Java shows that GWR model is significantly different in each location towards global regression model, also the estimated model will also give different result between one location and another. Based on Akaike Information Criterion (AIC) value between global regression models with GWR, it is know that GWR model with fixed exponentially weighted kernel is the best model to use to analyze the percentage poor population at district and city of Central Java because of it has the smallest AIC value. Keywords: Akaike Information Criterion, Bandwidth, Cross Validation, Exponential Kernel Function, Geographically Weighted Regression, Weighted Least Square

PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA CART (CLASSIFICATION AND REGRESSION TREES) (Studi Kasus: Kredit Macet di PD. BPR-BKK Purwokerto Utara) Mardika, Zulfa Wahyu; Mukid, Moch. Abdul; Yasin, Hasbi
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Modernization and globalization of the world today has entered into various lines of Indonesian society. One consequence is people's lifestyles are more consumptive. This lifestyle causes people take out a loan at a bank or other financial institution to fulfill his wish. Some people pay the loan on credit. But in implementation, there is a variety of things causes the credit not running properly or called with problem loan. As a service provider of credit institutions, PD. BPR-BKK Purwokerto Utara is also not free from this problem. Therefore, it is necessary to classify customers based on demographic variables using Classification and Regression Trees (CART) to minimize the chances of problem loans. Based on analysis of customer credit status data PD. BPR-BKK Purwokerto Utara, optimal classification tree formed by the number of terminal nodes as much as 6 nodes. This means there are 6 characteristics of customers PD. BPR-BKK Purwokerto Utara. And level of accuracy of the classification tree in classifying credit status of customers is 81.0 % . Keywords: Modernization, Globalization, Credit, Problem Loan, Customer, CART, Classification Tree.

Peramalan Inflasi Menurut Kelompok Pengeluaran Makanan Jadi, Minuman, Rokok dan Tembakau Menggunakan Model Variasi Kalender (Studi Kasus Inflasi Kota Semarang) Berlian, Amanda Lucky; Wilandari, Yuciana; Yasin, Hasbi
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Inflation is rising prices in general and continuously. Inflationary expenditure groups are divided into seven groups, and one group which spending considerable influence current inflation in Indonesia is by expenditure groups, food, beverages, cigarettes and tobacco. This is because the Indonesian people are very consumptive, especially when it coming to Eid. The movement of the month when Eid occurs once in every three years, so that changes raises a calendar variation. Calendar variation method is a method which modifies the dummy regression models with ARIMA models. In this final project, modeling and forecasting of inflation data by type of expenditure, food, beverages, cigarettes and tobacco in Semarang using variations of the calendar with holidays variation effects due to Eid. Based on the analysis and discussion shows that the best calendar variation model is ARIMA (1,0,0), with the forecasting results shows a significant increase of inflation when the month of Ramadan come.Keywords : inflation, calendar variation, the dummy regression, ARIMA

PREDIKSI INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN SUPPORT VECTOR REGRESSION (SVR) DENGAN ALGORITMA GRID SEARCH Septiningrum, Lutfia; Yasin, Hasbi; Sugito, Sugito
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The existence of capital market Indonesia is one of the important factors in the development of the national economy, proved to have many industries and companies that use these institutions as a medium to absorb investment and media to strengthen its financial position. Capital market Indonesia is an emerging market development is very vulnerable to global economic conditions and capital markets of the world. Prediction JCI (Jakarta Composite Index) is necessary to know the great value that will occur in the future so as investors can take the right policy. To predict in this study used a Support Vector Regression (SVR) method to find the hyperplane in the best regression function to predict the closing price of the JCI using a linear kernel function with output in the form of continuous data. Parameter selection cost and epsilon using a grid search algorithm combined with cross validation and obtained best cost 1 and best epsilon 0.1. While the criteria to measure the goodness of the model is MAPE (Mean Absolute Percentage Error) and R2 (Coefficient Determination). The results of this study showed that SVR with linear kernel function provides excellent accuracy in the prediction of JCI with R2 results on training data 98.4% with a MAPE 0.873% while the testing of data R2 90.9% with a MAPE 0.613%.Keywords: JCI, Support Vector Regression (SVR), Hyperplane, Kernel Linear, Grid Search Algorithm, Cross Validation, Accuracy

PENGGUNAAN SIMULASI MONTE CARLO UNTUK PENGUKURAN VALUE AT RISK ASET TUNGGAL DAN PORTOFOLIO DENGAN PENDEKATAN CAPITAL ASSET PRICING MODEL SEBAGAI PENENTU PORTOFOLIO OPTIMAL (Studi Kasus: Index Saham Kelompok SMinfra18) Pradana, Danang Chandra; Maruddani, Di Asih I; Yasin, Hasbi
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In financial markets, a stock is a unit of account for various investments. It often means the stock of a corporation, but also used for collective investments such as mutual funds, limited partnerships, and real estate investment trusts. In this era, most investors establish a stock portfolio as one way to reduce the risk of loss or risk which may be obtained when investing in stocks. Formation of portfolio in this research, investors is used to calculate the weight of the investment using the Capital Asset Pricing Model (CAPM). Risks of investing often called Value at Risk (VaR), calculate the VaR using Monte Carlo simulation. From the results and analysis conducted on a group of SMInfra18 stocks, there are two stocks into the portfolio with an allocation of the largest given to the ISAT (PT. Indosat, Tbk) and the allocation of funds smallest given to stock TBIG (PT. Tower Bersama Infrastructure Tbk). While the losses or the estimated risk of the portfolio at 95% confidence level is IDR 18,860,237.00 of the initial capital of IDR 1,000,000,000.00 during the holding period 1 day after portfolio formation. Keywords: Stock, Portfolio, SMInfra18, CAPM, Monte Carlo

KOMPUTASI GUI UNTUK INFERENSI VEKTOR MEAN DAN INFERENSI MATRIKS KOVARIANSI DENGAN MENGGUNAKAN SOFTWARE R Subakti, Yudha; Mukid, Moch. Abdul; Yasin, Hasbi
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Multivariate statistics is a branch of statistical science that discuss the analysis for multivariable case. Some analysis in multivariate statistics are discussing about inferences, there are inferences about mean vector and inferences of covariance matrices. Along with the development of technology, to support statistical analysis from both of inferences is requiring a statistical software, R is one of it with open source based. R is often used in statistical computing with command line interface (CLI) as the interface. In implementation, CLI requires the R user to remember names of used syntax and function. It makes less effective when the inferences have many related statistical analysis, so graphical user interface (GUI) needed to giving an easy way to accessing all of it. Testing for mean vectors of two populations will be performed using S. Rockiki’s data about measures of oxygen consumption for 25 males and 25 females. Results about assumptions showing both populations are normal multivariate distributed and have different covariannce matrix. The conclusion from the testing for mean vectors of two populations has performed is both populations have different mean vectors. There are packages are used on construction of GUI in R, including gdata, tcltk2, and devtools with additional software like Rtools and ActivePerl. The GUI has four main menus such as File, Analysis, Plot, and Help. Based on GUI usage, the GUI has been able to processing the chosen analysis and showing valid output.. Keywords: Multivariate Statistics, Inferences about mean vector, Inferences of covariancematrices, R, GUI.

Co-Authors Abdul Hoyyi Achmad Choiruddin Adi Waridi Basyiruddin Adi Waridi Basyirudin Arifin Agus Rusgiyono Ajeng Arum Sari Alan Prahutama Alvita Rachma Devi Amanda Lucky Berlian Andreanto Andreanto Anggun Perdana Aji Pangesti Arief Rachman Hakim Arief Rachman Hakim Baluk, Andreas Pedo Bens Pardamean Budi Warsito Budi Warsito Danang Chandra Pradana, Danang Chandra Dani Al Mahkya Darwanto Darwanto Devi Wijayanti Dewi Setya Kusumawardani Dharmawan, Bagus Dwiky Dhea Kurnia Mubyarjati Di Asih I Maruddani Di Asih I Maruddani Di Asih I Maruddani Diah Safitri Dwi Hasti Ratnasari Dwi Ispriyanti Eko Siswanto Fadhilla Atansa Tamardina Felinda Arumningtyas Fiqria Devi Ariyani Gera Rozalia Hanien Nia H Shega Hari Susanta Nugraha Hidayatul Musyarofah Hindun Habibatul Mubaroroh Ika Chandra Nurhayati Inas Hasimah Inayati, Syarifah Indah Suryani Indri Puspita Sari Innosensia Adella Intan Monica Hanmastiana Isna Wulandari Isna Wulandari Ispriyansti, Dwi Jody Hendrian Johanes Roisa Prabowo Kadi Mey Ismail Kurniawan, Isma Dwi Lutfia Septiningrum Maghfiroh Hadadiah Mukrom Maria Odelia Mas'ad, Mas'ad Maulana Taufan Permana Mega Fitria Andriyani Meilia Kusumawardani, Meilia Moch. Abdul Mukid Mochammad Iffan Zulfiandri MUHAMMAD HARIS Muhammad Mujahid Muhammad Tahmid Muryanto Muryanto Muryanto, Muryanto Mustafid Mustafid Mutiara, Dinar Nova Delvia Nur Azizah Nur Indah Yuli Astuti, Nur Indah Yuli Pandu Anggara Purhadi Purhadi Puspita Kartikasari Ragil Saputra Rahmasari Nur Azizah Reza Dwi Fitriani Rezzy Eko Caraka Riama Oktaviani Samosir, Riama Oktaviani Rifki Adi Pamungkas, Rifki Adi Rina Br Siahaan Rita Rahmawati Rita Rahmawati Riza Fahlevi Rizki Brendita Br Tarigan Rose Debora Julianisa, Rose Debora Rukun Santoso Rung Ching Chen Saepudin, Yunus Sakhinah Abu Bakar Salma Farah Aliyah Sari, Ajeng Arum Satriyo Adhy Setiawan Setiawan Setyoko Prismanu Ramadhan Siska Alvitiani Siti Maulina Meutuah Sri Endah Moelya Artha Sudarno Sudarno Sudarno Sudarno Sugito Sugito - Sugito Sugito Suhartono Suhartono Suparti Suparti Tarno Tarno Tarno Tarno Tatik Widiharih Tiani Wahyu Utami Tsania Faizia Ubudia Hiliaily Chairunnnisa Via Risqiyanti Wahyu Sabtika Wawan Sugiarto, Wawan Wulandari, Heni Dwi Youngjo Lee Yuciana Wilandari Yudha Subakti, Yudha Zulfa Wahyu Mardika, Zulfa Wahyu

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