Hasbi Yasin - Academia.edu (original) (raw)

Papers by Hasbi Yasin

Research paper thumbnail of Evolving Hybrid Generalized Space-Time Autoregressive Forecasting with Cascade Neural Network Particle Swarm Optimization

Atmosphere

Background: The generalized space-time autoregressive (GSTAR) model is one of the most widely use... more Background: The generalized space-time autoregressive (GSTAR) model is one of the most widely used models for modeling and forecasting time series and location data. Methods: In the GSTAR model, there is an assumption that the research locations are heterogeneous. In addition, the differences between these locations are shown in the form of a weighting matrix. The novelty of this paper is that we propose the hybrid time-series model of GSTAR uses the cascade neural network and obtains the best parameters from particle swarm optimization. Results and conclusion: This hybrid model provides a high accuracy value for forecasting PM2.5, PM10, NOx, and SO2 with high accuracy forecasting, which is justified by a mean absolute percentage error (MAPE) accuracy of around 0.01%.

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Research paper thumbnail of Pemodelan Angka Harapan Hidup Provinsi Jawa Tengah Menggunakan Robust Spatial Durbin Model

Jurnal Gaussian

Spatial regression is a model used to determine relationship between response variables and predi... more Spatial regression is a model used to determine relationship between response variables and predictor variables that gets spatial influence. If there are spatial influences on both variables, the model that will be formed is Spatial Durbin Model. One reason for the inaccuracy of the spatial regression model in predicting is the existence of outlier observations. Removing outliers in spatial analysis can change the composition of spatial effects on data. One way to overcome of outliers in the spatial regression model is by using robust spatial regression. The application of M-estimator is carried out in estimating the spatial regression parameter coefficients that are robust against outliers. The aim of this research is obtaining model of number of life expectancy in Central Java Province in 2017 that contain outliers. The results by applying M-estimator to estimating robust spatial durbin model regression parameters can accommodate the existence of outliers in the spatial regression...

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Research paper thumbnail of PROBABILISTIC NEURAL NETWORK BERBASIS GUI MATLAB UNTUK KLASIFIKASI DATA REKAM MEDIS (Studi Kasus Penyakit Diabetes Melitus di Balai Kesehatan Kementerian Peridustrian Jakarta)

Jurnal Gaussian, Aug 30, 2016

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Research paper thumbnail of Pemodelan Jumlah Kasus Demam Berdarah Dengue (DBD) DI Jawa Tengah Dengan Geographically Weighted Negative Binomial Regression (GWNBR)

Jurnal Gaussian, 2021

Dengue Hemorrhagic Fever (DHF) is one of the diseases with unsual occurrence in Central Java and ... more Dengue Hemorrhagic Fever (DHF) is one of the diseases with unsual occurrence in Central Java and spread throughout the regency/city. The number sufferers of this disease is still high because the mortality rate is still above the national target. Regarding the less handling of DHF spread, it is necessary to make a plan by identify the factors that allegedly affect that case. Characteristics of data the DHF cases is count data, so this research is carried out using poisson regression. If in poisson regression there is overdispersion, it can be overcome using negative binomial regression. Meanwhile to see the spatial effect, we can use the Geographically Weighted Negative Binomial Regression (GWNBR) method. GWNBR modeling uses a fixed exponential kernel for weighting function. GWNBR is better at modeling the number of DHF cases because it has the smallest AIC value than poisson regression and negative binomial regression. The results of research with poisson regression obtained three ...

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Research paper thumbnail of Pemodelan Faktor-Faktor Yang Mempengaruhi Indeks Pembangunan Manusia Kabupaten/ Kota DI Jawa Timur Menggunakan Geographically Weighted Ordinal Logistic Regression

Jurnal Gaussian, Jul 22, 2015

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Research paper thumbnail of 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)

Jurnal Gaussian, 2021

The basic assumption that is often used in bond valuations is the assumption on the Black-Scholes... more 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 ...

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Research paper thumbnail of Proyeksi Data Produk Domestik Bruto (PDB) Dan Foreign Direct Investment (Fdi) Menggunakan Vector Autoregressive (Var)

Jurnal Gaussian, Oct 30, 2015

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Research paper thumbnail of Optimasi Value at Risk Pada Reksa Dana Dengan Metode Historical Simulation Dan Aplikasinya Menggunakan Gui Matlab

Jurnal Gaussian, Apr 29, 2016

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Research paper thumbnail of ANALISIS LAMA KAMBUH PASIEN HIPERTENSI DENGAN SENSOR TIPE III MENGGUNAKAN REGRESI COX KEGAGALAN PROPORSIONAL (Studi Kasus di RSUD Kartini Jepara)

Jurnal Gaussian, Jul 22, 2015

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Research paper thumbnail of Pemodelan Tinggi Pasang Air Laut DI Kota Semarang Menggunakan Maximal Overlap Discrete Wavelet Transform (Modwt)

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Research paper thumbnail of Sosialisasi Pengelolaan Limbah Industri Batik pada Program IbPUD Kerajinan Batik Bakaran di Kabupaten Pati Jawa Tengah

E-Dimas: Jurnal Pengabdian kepada Masyarakat, 2018

Batik Bakaran merupakan batik tulis khas Kabupaten Pati yang berasal dari Desa Bakaran, Kecamatan... more Batik Bakaran merupakan batik tulis khas Kabupaten Pati yang berasal dari Desa Bakaran, Kecamatan Juwana Jawa Tengah. Proses pembuatan batik tulis tidak terlepas dari apa yang dinamakan limbah. Limbah industri batik terdiri atas limbah cair, limbah padat dan limbah gas. Pengelolaan limbah yang kurang baik akan mengakibatkan pencemaran lingkungan dan bisa merusak ekosistem sekitarnya. Oleh karenanya perlu dilakukan sosialisasi pengelolaan limbah terhadap UKM-UKM Batik di Desa Bakaran Juwana Pati dengan narasumber dari Balai Besar Kerajinan dan Batik (BBKB) Yogyakarta. Metode pelaksanaan dilakukan dengan paparan materi dan diskusi aktif dengan UKM. Penanganan limbah bisa dilakukan melalui tahapan proses yaitu proses Kimia, proses Fisika dan proses Biologi. Dalam sosialisasi ini dibahas beberapa teknik pengelolaan limbah, dan lebih difokuskan kepada proses pada IPAL batik BBKB Yogyakarta. Tahapan prosesnya adalah: penyisihan lilin, pengendapan, koagulasi dan flokulasi, proses Biologi d...

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Research paper thumbnail of Perbandingan Model Gwr Dengan Fixed Dan Adaptive Bandwidth Untuk Persentase Penduduk Miskin Di Jawa Tengah

Regression analysis is statistical method for modeling the dependency relationship that might exi... more 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 mo...

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Research paper thumbnail of PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA CART (CLASSIFICATION AND REGRESSION TREES) (Studi Kasus: Kredit Macet di PD. BPR-BKK Purwokerto Utara)

Modernization and globalization of the world today has entered into various lines of Indonesian s... more 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 class...

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Research paper thumbnail of Analisis Sistem Antrean Pelayanan DI Kantor Pertanahan Kota Semarang

Kantor Pertanahan Kota Semarang in charge of the land with an area of 373.70 km 2 coverage, every... more Kantor Pertanahan Kota Semarang in charge of the land with an area of 373.70 km 2 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...

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Research paper thumbnail of Uji Hipotesis Model Mixed Geographically Weighted Regression Dengan Metode Bootstrap

One of the models that can be used to analyze the spatial data is the Mixed Geographically Weight... more One of the models that can be used to analyze the spatial data is the Mixed Geographically Weighted Regression (MGWR) model. MGWR was used to solve the problem where certain predictor variables are influencing the response globally while others are locally. This paper tried to estimate the parameters of MGWR model using Weighted Least Square method, and then get the p-value of statistical test using the bootstrap procedure. The application of the bootstrap methode in this case is resample the statistical test base on the residual model. Key words: Bootstrap procedure, Mixed Geographically Weighted Regression, p-value, Weighted Least Square

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Research paper thumbnail of ANALISIS MODEL WAKTU ANTAR KEDATANGAN DAN WAKTU PELAYANAN PADA BAGIAN PENDAFTARAN INSTALASI RAWAT JALAN RSUP Dr. KARIADI SEMARANG

The arrival rate of patients that have occured at the registration Installation Outpatient is ran... more The arrival rate of patients that have occured at the registration Installation Outpatient is randomly, so condition would make difficult for hospital management to determine policies in operating the substation service. The duration of registration procedure can affect patient satisfaction of Installation Outpatient Hospital Dr. Kariadi Semarang in obtaining health care. Therefore, it’s necessary queuing models that suitable. so as to obtainable an effective service, balance and efficient which can reduce the long queues and long waiting time. Based on the results of the analysis, obtained by queueing models at its Installation Outpatient is (G/G/8):(GD/∞/∞). Keywords : Queue models, Registration, Installation Outpatient, RSUP Dr. Semarang

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Research paper thumbnail of Perbandingan Model Jaringan Syaraf Tiruan Dengan Algoritma Levenberg-Marquadt Dan Powell-Beale Conjugate Gradientpada Kecepatan Angin Rata-Rata DI Kota Semarang

Jurnal Statistika Universitas Muhammadiyah Semarang, 2020

Wind is one of the most important weather components. Wind is defined as the dynamics of horizont... more Wind is one of the most important weather components. Wind is defined as the dynamics of horizontal air mass displacement measured in two parameters, namely speed and direction. Wind speed and direction depend on the air pressure conditions around the place. High wind speed intensity can cause high sea water waves. To estimate wind speed intensity required a study of wind speed prediction. One of method that can be used is Artificial Neural Network (ANN). In ANN there are several models, one of which is backpropagation. Thepurpose of this researchis to compare between backpropagation model with Levenberg-Marquadt and Powell-Beale Conjugate Gradient algorithms. The results of this researchshowing that Powell-Beale Conjugate Gradient better than Levenberg-Marquadtalgorithms. The best model architecture obtained is a network with two input layer neurons, six hidden layer neurons, and one output layer neuron. The activation function used are the logistic sigmoid in the hidden layer and ...

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Research paper thumbnail of Peramalan Indeks Harga Saham Gabungan (Ihsg) Dengan Metode Radial Basis Function Neural Network Menggunakan Gui Matlab

Jurnal Gaussian, 2018

Capital market Indonesia is one of the important factors in the development of the national econo... more 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 to strengthen its financial position. The recent years, Jakarta Composite Index (JCI) in Capital Market tend to strengthen. JCI data are the time series data obtained from the past to predict the future with caracteristics of JCI data are non stationary and non linier. Neural network is a computational method that imitate the biological neural network. There are several types of methods that can be used in neural network that is: Radial Basis Function Neural Network (RBFNN) Generalized Regression Neural Network (GRNN), dan Probabilistic Neural Network (PNN). Model of Radial Basis Function Neural Network is suitable for time series data. This model has a network architecture in the form of input layer, hidden layer and output layer. This research is done with the help of GUI as a ...

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Research paper thumbnail of PEMODELAN REGRESI ROBUST S-ESTIMATOR UNTUK PENANGANAN PENCILAN MENGGUNAKAN GUI MATLAB (Studi Kasus : Faktor-Faktor yang Mempengaruhi Produksi Ikan Tangkap di Jawa Tengah)

Jurnal Gaussian, 2019

Multiple Linear Regression can be solved by using the Ordinary Least Squares (OLS). Some classic ... more 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 ...

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Research paper thumbnail of Pemodelan Indeks Pembangunan Manusia DI Jawa Tengah Dengan Regresi Komponen Utama Robust

Jurnal Gaussian, 2019

Robust principal component regression is development of principal component regression that appli... more Robust principal component regression is development of principal component regression that applies robust method at principal component analysis and principal component regression analysis. Robust principal component regression does not only overcome multicollinearity problems, but also overcomes outlier problems. The robust methods used in this research are Minimum Covariance Determinant (MCD) that is applied when doing principal component analysis and Least Trimmed Squares (LTS) that is applied when doing principal component regression analysis. The case study in this research is Human Development Index (HDI) in Central Java in 2017 which is influenced by labor force participation rates, school enrollment rates, percentage of poor population, population aged 15 years and over who are employed, health facilities, gross enrollment rates, and net enrollment rates. The model of HDI in Central Java in 2017 using robust principal component regression MCD-LTS provides the most effective...

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Research paper thumbnail of Evolving Hybrid Generalized Space-Time Autoregressive Forecasting with Cascade Neural Network Particle Swarm Optimization

Atmosphere

Background: The generalized space-time autoregressive (GSTAR) model is one of the most widely use... more Background: The generalized space-time autoregressive (GSTAR) model is one of the most widely used models for modeling and forecasting time series and location data. Methods: In the GSTAR model, there is an assumption that the research locations are heterogeneous. In addition, the differences between these locations are shown in the form of a weighting matrix. The novelty of this paper is that we propose the hybrid time-series model of GSTAR uses the cascade neural network and obtains the best parameters from particle swarm optimization. Results and conclusion: This hybrid model provides a high accuracy value for forecasting PM2.5, PM10, NOx, and SO2 with high accuracy forecasting, which is justified by a mean absolute percentage error (MAPE) accuracy of around 0.01%.

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Research paper thumbnail of Pemodelan Angka Harapan Hidup Provinsi Jawa Tengah Menggunakan Robust Spatial Durbin Model

Jurnal Gaussian

Spatial regression is a model used to determine relationship between response variables and predi... more Spatial regression is a model used to determine relationship between response variables and predictor variables that gets spatial influence. If there are spatial influences on both variables, the model that will be formed is Spatial Durbin Model. One reason for the inaccuracy of the spatial regression model in predicting is the existence of outlier observations. Removing outliers in spatial analysis can change the composition of spatial effects on data. One way to overcome of outliers in the spatial regression model is by using robust spatial regression. The application of M-estimator is carried out in estimating the spatial regression parameter coefficients that are robust against outliers. The aim of this research is obtaining model of number of life expectancy in Central Java Province in 2017 that contain outliers. The results by applying M-estimator to estimating robust spatial durbin model regression parameters can accommodate the existence of outliers in the spatial regression...

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Research paper thumbnail of PROBABILISTIC NEURAL NETWORK BERBASIS GUI MATLAB UNTUK KLASIFIKASI DATA REKAM MEDIS (Studi Kasus Penyakit Diabetes Melitus di Balai Kesehatan Kementerian Peridustrian Jakarta)

Jurnal Gaussian, Aug 30, 2016

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Research paper thumbnail of Pemodelan Jumlah Kasus Demam Berdarah Dengue (DBD) DI Jawa Tengah Dengan Geographically Weighted Negative Binomial Regression (GWNBR)

Jurnal Gaussian, 2021

Dengue Hemorrhagic Fever (DHF) is one of the diseases with unsual occurrence in Central Java and ... more Dengue Hemorrhagic Fever (DHF) is one of the diseases with unsual occurrence in Central Java and spread throughout the regency/city. The number sufferers of this disease is still high because the mortality rate is still above the national target. Regarding the less handling of DHF spread, it is necessary to make a plan by identify the factors that allegedly affect that case. Characteristics of data the DHF cases is count data, so this research is carried out using poisson regression. If in poisson regression there is overdispersion, it can be overcome using negative binomial regression. Meanwhile to see the spatial effect, we can use the Geographically Weighted Negative Binomial Regression (GWNBR) method. GWNBR modeling uses a fixed exponential kernel for weighting function. GWNBR is better at modeling the number of DHF cases because it has the smallest AIC value than poisson regression and negative binomial regression. The results of research with poisson regression obtained three ...

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Research paper thumbnail of Pemodelan Faktor-Faktor Yang Mempengaruhi Indeks Pembangunan Manusia Kabupaten/ Kota DI Jawa Timur Menggunakan Geographically Weighted Ordinal Logistic Regression

Jurnal Gaussian, Jul 22, 2015

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Research paper thumbnail of 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)

Jurnal Gaussian, 2021

The basic assumption that is often used in bond valuations is the assumption on the Black-Scholes... more 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 ...

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Research paper thumbnail of Proyeksi Data Produk Domestik Bruto (PDB) Dan Foreign Direct Investment (Fdi) Menggunakan Vector Autoregressive (Var)

Jurnal Gaussian, Oct 30, 2015

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Research paper thumbnail of Optimasi Value at Risk Pada Reksa Dana Dengan Metode Historical Simulation Dan Aplikasinya Menggunakan Gui Matlab

Jurnal Gaussian, Apr 29, 2016

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Research paper thumbnail of ANALISIS LAMA KAMBUH PASIEN HIPERTENSI DENGAN SENSOR TIPE III MENGGUNAKAN REGRESI COX KEGAGALAN PROPORSIONAL (Studi Kasus di RSUD Kartini Jepara)

Jurnal Gaussian, Jul 22, 2015

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Research paper thumbnail of Pemodelan Tinggi Pasang Air Laut DI Kota Semarang Menggunakan Maximal Overlap Discrete Wavelet Transform (Modwt)

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Research paper thumbnail of Sosialisasi Pengelolaan Limbah Industri Batik pada Program IbPUD Kerajinan Batik Bakaran di Kabupaten Pati Jawa Tengah

E-Dimas: Jurnal Pengabdian kepada Masyarakat, 2018

Batik Bakaran merupakan batik tulis khas Kabupaten Pati yang berasal dari Desa Bakaran, Kecamatan... more Batik Bakaran merupakan batik tulis khas Kabupaten Pati yang berasal dari Desa Bakaran, Kecamatan Juwana Jawa Tengah. Proses pembuatan batik tulis tidak terlepas dari apa yang dinamakan limbah. Limbah industri batik terdiri atas limbah cair, limbah padat dan limbah gas. Pengelolaan limbah yang kurang baik akan mengakibatkan pencemaran lingkungan dan bisa merusak ekosistem sekitarnya. Oleh karenanya perlu dilakukan sosialisasi pengelolaan limbah terhadap UKM-UKM Batik di Desa Bakaran Juwana Pati dengan narasumber dari Balai Besar Kerajinan dan Batik (BBKB) Yogyakarta. Metode pelaksanaan dilakukan dengan paparan materi dan diskusi aktif dengan UKM. Penanganan limbah bisa dilakukan melalui tahapan proses yaitu proses Kimia, proses Fisika dan proses Biologi. Dalam sosialisasi ini dibahas beberapa teknik pengelolaan limbah, dan lebih difokuskan kepada proses pada IPAL batik BBKB Yogyakarta. Tahapan prosesnya adalah: penyisihan lilin, pengendapan, koagulasi dan flokulasi, proses Biologi d...

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Research paper thumbnail of Perbandingan Model Gwr Dengan Fixed Dan Adaptive Bandwidth Untuk Persentase Penduduk Miskin Di Jawa Tengah

Regression analysis is statistical method for modeling the dependency relationship that might exi... more 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 mo...

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Research paper thumbnail of PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA CART (CLASSIFICATION AND REGRESSION TREES) (Studi Kasus: Kredit Macet di PD. BPR-BKK Purwokerto Utara)

Modernization and globalization of the world today has entered into various lines of Indonesian s... more 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 class...

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Research paper thumbnail of Analisis Sistem Antrean Pelayanan DI Kantor Pertanahan Kota Semarang

Kantor Pertanahan Kota Semarang in charge of the land with an area of 373.70 km 2 coverage, every... more Kantor Pertanahan Kota Semarang in charge of the land with an area of 373.70 km 2 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...

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Research paper thumbnail of Uji Hipotesis Model Mixed Geographically Weighted Regression Dengan Metode Bootstrap

One of the models that can be used to analyze the spatial data is the Mixed Geographically Weight... more One of the models that can be used to analyze the spatial data is the Mixed Geographically Weighted Regression (MGWR) model. MGWR was used to solve the problem where certain predictor variables are influencing the response globally while others are locally. This paper tried to estimate the parameters of MGWR model using Weighted Least Square method, and then get the p-value of statistical test using the bootstrap procedure. The application of the bootstrap methode in this case is resample the statistical test base on the residual model. Key words: Bootstrap procedure, Mixed Geographically Weighted Regression, p-value, Weighted Least Square

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Research paper thumbnail of ANALISIS MODEL WAKTU ANTAR KEDATANGAN DAN WAKTU PELAYANAN PADA BAGIAN PENDAFTARAN INSTALASI RAWAT JALAN RSUP Dr. KARIADI SEMARANG

The arrival rate of patients that have occured at the registration Installation Outpatient is ran... more The arrival rate of patients that have occured at the registration Installation Outpatient is randomly, so condition would make difficult for hospital management to determine policies in operating the substation service. The duration of registration procedure can affect patient satisfaction of Installation Outpatient Hospital Dr. Kariadi Semarang in obtaining health care. Therefore, it’s necessary queuing models that suitable. so as to obtainable an effective service, balance and efficient which can reduce the long queues and long waiting time. Based on the results of the analysis, obtained by queueing models at its Installation Outpatient is (G/G/8):(GD/∞/∞). Keywords : Queue models, Registration, Installation Outpatient, RSUP Dr. Semarang

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Research paper thumbnail of Perbandingan Model Jaringan Syaraf Tiruan Dengan Algoritma Levenberg-Marquadt Dan Powell-Beale Conjugate Gradientpada Kecepatan Angin Rata-Rata DI Kota Semarang

Jurnal Statistika Universitas Muhammadiyah Semarang, 2020

Wind is one of the most important weather components. Wind is defined as the dynamics of horizont... more Wind is one of the most important weather components. Wind is defined as the dynamics of horizontal air mass displacement measured in two parameters, namely speed and direction. Wind speed and direction depend on the air pressure conditions around the place. High wind speed intensity can cause high sea water waves. To estimate wind speed intensity required a study of wind speed prediction. One of method that can be used is Artificial Neural Network (ANN). In ANN there are several models, one of which is backpropagation. Thepurpose of this researchis to compare between backpropagation model with Levenberg-Marquadt and Powell-Beale Conjugate Gradient algorithms. The results of this researchshowing that Powell-Beale Conjugate Gradient better than Levenberg-Marquadtalgorithms. The best model architecture obtained is a network with two input layer neurons, six hidden layer neurons, and one output layer neuron. The activation function used are the logistic sigmoid in the hidden layer and ...

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Research paper thumbnail of Peramalan Indeks Harga Saham Gabungan (Ihsg) Dengan Metode Radial Basis Function Neural Network Menggunakan Gui Matlab

Jurnal Gaussian, 2018

Capital market Indonesia is one of the important factors in the development of the national econo... more 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 to strengthen its financial position. The recent years, Jakarta Composite Index (JCI) in Capital Market tend to strengthen. JCI data are the time series data obtained from the past to predict the future with caracteristics of JCI data are non stationary and non linier. Neural network is a computational method that imitate the biological neural network. There are several types of methods that can be used in neural network that is: Radial Basis Function Neural Network (RBFNN) Generalized Regression Neural Network (GRNN), dan Probabilistic Neural Network (PNN). Model of Radial Basis Function Neural Network is suitable for time series data. This model has a network architecture in the form of input layer, hidden layer and output layer. This research is done with the help of GUI as a ...

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Research paper thumbnail of PEMODELAN REGRESI ROBUST S-ESTIMATOR UNTUK PENANGANAN PENCILAN MENGGUNAKAN GUI MATLAB (Studi Kasus : Faktor-Faktor yang Mempengaruhi Produksi Ikan Tangkap di Jawa Tengah)

Jurnal Gaussian, 2019

Multiple Linear Regression can be solved by using the Ordinary Least Squares (OLS). Some classic ... more 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 ...

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Research paper thumbnail of Pemodelan Indeks Pembangunan Manusia DI Jawa Tengah Dengan Regresi Komponen Utama Robust

Jurnal Gaussian, 2019

Robust principal component regression is development of principal component regression that appli... more Robust principal component regression is development of principal component regression that applies robust method at principal component analysis and principal component regression analysis. Robust principal component regression does not only overcome multicollinearity problems, but also overcomes outlier problems. The robust methods used in this research are Minimum Covariance Determinant (MCD) that is applied when doing principal component analysis and Least Trimmed Squares (LTS) that is applied when doing principal component regression analysis. The case study in this research is Human Development Index (HDI) in Central Java in 2017 which is influenced by labor force participation rates, school enrollment rates, percentage of poor population, population aged 15 years and over who are employed, health facilities, gross enrollment rates, and net enrollment rates. The model of HDI in Central Java in 2017 using robust principal component regression MCD-LTS provides the most effective...

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