Garuda - Garba Rujukan Digital

p-Index From 2020 - 2025

0.23

P-Index

This Author published in this journals

All Journal Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika

Hasbi Yasin

Unknown Affiliation

Author-ID : 452055

Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Other

Published : 47 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4 5

PEMODELAN FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS PEMBANGUNAN MANUSIA KABUPATEN/ KOTA DI JAWA TIMUR MENGGUNAKAN GEOGRAPHICALLY WEIGHTED ORDINAL LOGISTIC REGRESSION Rahma Nurfiani Pradita; Hasbi Yasin; Diah Safitri
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Human Development Index (HDI) is a measurement used for measuring human developmental achievement in certain area. Although, it does not measure all dimensions of human development, HDI seems able to measure principal dimension of human development that include longevity and health, knowledge and a good life. Geographically Weighted Ordinal Logistic Regression (GWOLR) Model is used to model a relationship between categorical response variable that have ordinal scale toward predictor variable that depend on geographical location where the data are observed. This research aims to know the factors that influence HDI of Regency/ City in East Java Province 2013 using ordinal logistic regression model and GWOLR with exponential kernel function weighting. Factors that are influencing HDI of Regency/ City in East Java are percentage of population that finish Junior High School (X2), the number of health facility (X4), and population density (X5). Based on HDI of Regency/ City in East Java’s accuracy classification result, between observations and prediction counted based on Apparent Error Rate (APER) value, it is known that GWOLR model with exponential kernel function weighting has better classification’s accuracy (86,84%) than ordinal logistic regression model (81,58%). Keywords: HDI, Ordinal Logistic Regression Model, GWOLR, Exponential Kernel Function, Classification’s Accuracy, APER

PEMODELAN PENDAPATAN ASLI DAERAH (PAD) DI KABUPATEN DAN KOTA DI JAWA TENGAH MENGGUNAKAN GEOGRAPHICALLY WEIGHTED RIDGE REGRESSION Depy Veronica; Hasbi Yasin; Tatik Widiharih
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Linear Regression Analysis is a statistical method for modeling the relation between response variable and predictor variable. Geographically Weighted Regression (GWR) is an expansion of linear regression model if spatial heterogeneity occurred. Local multicollinearity test is required to know the presence of linear correlation between independent variables for each observation location. Geographically Weighted Ridge Regression (GWRR) is a extension of GWR model to solve local multicollinearity problem. Parameter estimation for GWR and GWRR model is done using Weighted Least Square (WLS) method by applying optimum bandwith with Cross Validation (CV) criteria. GWRR model is applied on locally generated recurring revenues (PAD) at district and city of Central Java and its result shows the ability of GWRR model to erase multicollinearity problem. Based on Mean Squared Error (MSE) and Akaike Information Criterion (AIC) value for GWR and GWRR model, it is know that the best model to analyze locally generated recurring revenues (PAD) at district and city of Central Java is GWRR model with the smallest MSE and AIC value. Keywords : Akaike Information Crietion, Spasial Heterogeneity, Geographically Weighted Ridge Regression, Mean Square Error, Local Multicoliniearity

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

KLASIFIKASI DATA BERAT BAYI LAHIR MENGGUNAKAN PROBABILISTIC NEURAL NETWORK DAN REGRESI LOGISTIK (Studi Kasus di Rumah Sakit Islam Sultan Agung Semarang Tahun 2014) Erfan Sofha; Hasbi Yasin; Rita Rahmawati
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Birth Weight Infant (BWI) is the baby’s weight weighed in an hour after being born. Factors that may influence the BWI such as maternal age, length of gestation, body weight, height, blood pressure, hemoglobin and parity. One possibility of BWI is Low Birth Weight Infant (LBWI) (BWI < 2500 gram). LBWI is one of the causes of infant mortality. This study use the Probabilistic Neural Network (PNN) and Logistic Regression to classify the birth weight of infant in RSI Sultan Agung Semarang along the year of 2014. This study’s aims are to know the factors that affect the BWI by using logistic regression and finally finding the best method between PNN and logistic regression methods in classifying the BWI data. As a result, gestation, body weight and hemoglobin are the factors that affect the BWI in RSI Sultan Agung Semarang. The accuracy of PNN classification method on training data is 100%, which is better than the logistic regression method giving only about 88,2%, while the testing data has the same great accuracy at 86,67%. Keywords: BWI, LBWI, PNN, Logistic Regression, Classification

FAKTOR-FAKTOR YANG MEMPENGARUHI STATUS KELULUSAN BERDASARKAN JALUR MASUK MAHASISWA DENGAN MODEL REGRESI LOGISTIK BINER BIVARIAT (Studi Kasus Mahasiswa FSM Universitas Diponegoro) Safitri Daruyani; Yuciana Wilandari; Hasbi Yasin
Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The acceptance of college students in public universities are divided into two ways, the National Selection of Public University Entrance by invitation and the National Selection of Public University Entrance by non invitation. The National Selection of Public University Entrance by invitation is a way to get candidate students from The Senior High Schools that have good achievement, where as the other one open wider access. Nevertheless, the college students who enter through the invitation or non invitation, they don’t necessarily have a better academic achievement or worse than each other. After through the learning process in college, the success of the students are marked with their academic achievement that shown by the index of academic achievement, that if they pass expressed by the status of graduation, cumlaude or not cumlaude. To find out the factors that affect the status of student graduation based on the entrance, the regretion model that can be used is bivariate biner logistic regretion, because it consist of two response variable, the status of graduation and the entrance of the college students. Maximum likelihood estimation is used to estimate the parameter model. To examine the significance of the parameter use Likelihood ratio test and Wald test. Major option and live adress are the significance variables that affect the status of graduation based on the entrance of the college student from predictor variable partially test of school report grades, national test grades, major option, live adress, study method, live cost, students’ relationship with friends and family,and study motivation. Whole test and individual test indicate that major option variable affect the status of graduation based on the entrance significantly.

PEMODELAN INDEKS PEMBANGUNAN MANUSIA MENGGUNAKAN SPATIAL PANEL FIXED EFFECT (Studi Kasus: Indeks Pembangunan Manusia Propinsi Jawa Tengah 2008 - 2013) Novian Trianggara; Rita Rahmawati; Hasbi Yasin
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The success of a country could be seen from the condition of it society. A country needs to have developed society, a way to establish it is by human development. Human development is formed by three basic components, they are long and healthy life, knowledge, and decent living. Some indicators that represent these three components are summarized in one single value, the Human Development Index. This study models the Human Development Index for each city in Central Java using econometric approach by considering the specific spatial effect. The independent variable used were health facilities representing health component, School Participation Rate that represents education component, and Poverty Percentage that represents component of decent living standard. By using Spatial Panel Fixed Effect the best model is Spatial Autoregressive Model (SAR) with the influencing independent variabels are school participation rate and poverty percentage, with R2 of 99.54%.Keyword: HDI, Spatial, Panel, Fixed Effect

IDENTIFIKASI BREAKPOINT DAN PEMODELAN AUTOREGRESSIVE STRUCTURAL CHANGE PADA DATA RUNTUN WAKTU (Studi Kasus Indeks Harga Konsumen Umum Kota Semarang Tahun 1994 – 2010) Mamuroh Mamuroh; Sudarno Sudarno; Hasbi Yasin
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Perubahan Indeks Harga Konsumen (IHK) merupakan indikator ekonomi makro yang cukup penting untuk memberikan gambaran tentang laju inflasi suatu daerah/wilayah serta pola konsumsi masyarakat. IHK Umum Kota Semarang dalam kurun waktu tahun 1994-2010 terlihat mengalami kenaikan terus menerus. Plot data menunjukkan IHK bergerak naik perlahan sebelum bulan Januari 1998 dan setelahnya IHK meningkat secara curam. Untuk mengetahui apakah dalam kurun waktu tersebut terdapat perubahan struktur pola data dan untuk mengetahui titik-titik patah (breakpoints / titik perubahan struktur) yang terjadi pada IHK maka perlu dilakukan uji perubahan struktur, hal ini dilakukan dengan pendekatan autoregressive structural change. Hasil penelitian menunjukkan terjadi perubahan struktur dengan titik patah pada t=47 yaitu Januari 1998 bertepatan dengan krisis moneter 1998 dan t=79 yaitu September 2000 bertepatan dengan kenaikan tarif angkutan per 1 September 2000, sehingga data memiliki 3 segmen model. Metode ini sesuai untuk mengidentifikasi titik-titik patah IHK serta dapat digunakan untuk memodelkan IHK Umum Kota Semarang tahun 1994-2010.

ESTIMASI PARAMETER REGRESI LOGISTIK MULTINOMIAL DENGAN METODE BAYES Wayaning Apsari; Hasbi Yasin; Sugito Sugito
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Multinomial logistic regression is a logistic regression where the dependent variable is polychotomous is dependent variable value of more than two categories. Multinomial logistic regression parameter estimation usually use classical method that is based only on current information obtained from the sample without taking into account the initial information of logistic regression parameters. If have early information about parameter is prior distribution, the parameter estimation can use Bayes method. Bayesian methods combine information on the sample with prior distribution of information, and the results are expressed in the posterior distribution. If posterior distribution can not be derived analytically so approximated using Markov Chain Monte Carlo (MCMC) algorithm especially Metropolis-Hastings algorithm. This algorithm uses acceptance and rejection mechanism to generate a sequence of random samples. Keyword: Multinomial Logistic Regression, Bayes Method, Markov Chain Monte Carlo algorithm (MCMC), Metropolis-Hastings algorithm.

OPTIMALISASI JUMLAH BATU BATA YANG PECAH MENGGUNAKAN DESAIN EKSPERIMEN TAGUCHI (Studi Kasus: Usaha Batu Bata Bapak Kholil Ds. Bulak Karangawen) Cakra Kurniawan; Hasbi Yasin; Sugito Sugito
Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Brick is a substansial element in building construction. The strength of building may depend on bricks, a solid construction uses the best quality brick’s, which is not crumbling and broken into two parts. There are two popular types of bricks in Semarang, Penggaron bricks and Welahan bricks, Penggaron bricks is the most desirable type in market, but the quality of Penggaron bricks is worse than Welahan bricks, because the Penggaron bricks broken pieces are much more than Welahan’s. So that Penggaron bricks were taken to do research in purpose of optimizing the number of brick’s broken pieces that occurred during the production process. The method being used was the "Taguchi Design of Experiments" using Smaller is Better as quality character. The outcome of pre-experimental study was 3 factors and 2 levels so that L4 Orthogonal Array was used. After analyzing and conducting confirmation experiment, the result was obtained as follow, at the initial conditions, there are 4.6% of broken bricks, the broken bricks became 1.8%, after the experiment. The 1.8% of broken bricks were still within the range of the predicted value 1% to 2%.

ANALISIS KECENDERUNGAN INFORMASI DENGAN MENGGUNAKAN METODE TEXT MINING (Studi Kasus: Akun twitter @detikcom) Syaifudin Karyadi; Hasbi Yasin; Moch. Abdul Mukid
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The internet is an extraordinary phenomenon. Starting from a military experiment in the United States, the internet has evolved into a 'need' for more than tens of millions of people worldwide. The number of internet users is large and growing, has been creating internet culture. One of the fast growing social media twitter. Twitter is a microblogging service that stores text database called tweets. To make it easier to obtain information that is dominant discussed, then sought the topic of twitter tweet using clustering. In this research, grouping 500 tweets from twitter account @detikcom using k-means clustering. The results of this study indicate that the maximum index Dunn, the best grouping K-means clustering to obtain the dominant topic as many as three clusters, namely the government, Jakarta, and politics.Keywords: text mining, clustering,, k-means , dunn index, and twitter.

Co-Authors Abdul Hoyyi Agus Rusgiyono Ahmat Dhani Riau Bahtiyar Ajeng Arum Sari Alan Prahutama Aldila Abid Awali Alfiyatun Rohmaniyah Alvita Rachma Devi Andreas Pedo Baluk Arief Rachman Hakim Budi Warsito Cakra Kurniawan Catra Aditya Wisnu Aji Christa Monica David Yuliandar Depy Veronica Diah Safitri Dody Apriliawan Dwi Ispriyanti Ely Fitria Rifkhatussa'diyah Erfan Sofha Firda Shintia Dewi Ilham Indra Bakti Al-Irsyad Indra Satria Indra Satria Ira Puspita Sari Ishlahul Kamal Johan Adi Wicaksana Khusnul Yeni Widiyanti Laily Nadhifah Lenti Agustina Lianasari Tambunan Lina Irawati Mamuroh Mamuroh Mega Fitria Andriyani Moch. Abdul Mukid Muh Najib Hilmi Muhammad Hilman Rizki Abdullah Muryanto Muryanto Muryanto Muryanto Novian Trianggara Novika Pratnyaningrum Nurmalita Sari Nursihan Nursihan Putri Aulia Netra Putri Aulia Wahyuningsih Rahafattri Ariya Fauzannissa Rahma Kurnia Widyawati Rahma Nurfiani Pradita Restu Dewi Kusumo Astuti Rezzy Eko Caraka Rima Nurlita Sari Rita Rahmawati Rizky Amanda Rukun Santoso Safitri Daruyani Sarita Budiyani Purnamasari Sudarno Sudarno SUGITO Sugito Sugito Suparti Suparti Syaifudin Karyadi Tarno Tarno Tatik Widiharih Tika Dhiyani Mirawati Triastuti Wuryandari Vita Dwi Rachmawati Wayaning Apsari Yuciana Wilandari

Title

Found 47 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 47 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 47 Documents
Search