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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi TELKOMNIKA (Telecommunication Computing Electronics and Control) JDM (Jurnal Dinamika Manajemen) Jurnal Matematika: MANTIK Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Aplikasi Statistika & Komputasi Statistik Inferensi
Yudhie Andriyana
Universitas Padjadjaran
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences

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Regularized Ordinal Regression with Elastic Net Approach (Case Study: Poverty Modeling in Yogyakarta Province 2018) Sihombing, Pardomuan Robinson; Andriyana, Yudhie; Tantular, Bertho
CAUCHY Vol 6, No 4 (2021): CAUCHY: Jurnal Matematika Murni dan Aplikasi
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v6i4.11758

Abstract

Generally, modeling poverty aims to obtain the best criteria for assessing poverty status. There are two approaches to model the factors that affect poverty, namely consumption approach and discrete choice model. The advantage of the discrete choice model compared to the consumption approach is that the discrete choice model provides a probabilistic estimate for classifying samples into different poverty categories. This study aims to examined how the factors that affect poverty in Yogyakarta through Regularized Ordinal Regression with elastic net approach both for parallel, non-parallel, and semi-parallel models. The data used in this study is Susenas March 2018 for Yogyakarta provinces. The result of this study shows that the best discrete choice model for Yogyakarta’s modelling is the parallel model. Households that live in villages, have a large number of household members, are headed by women, have elderly household heads, have low education, and work in the primary sector tend to be more vulnerable to poverty. Therefore, a simultaneous policy with inclusive economic development is needed to reduce cross-border, cross-gender, and cross-sector inequality
The Forecasting Technique Using SSA-SVM Applied to Foreign Tourist Arrivals to Bali Yosep Oktavianus Sitohang; Yudhie Andriyana; Anna Chadidjah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.7293

Abstract

In order to achieve a targeted number of foreign tourist arrivals set by the Indonesian government in 2017, we need to predict the number of foreign tourist arrivals. As a major tourist destination in Indonesia, Bali plays an important role in determining the target. According to the characteristic of the tourist arrivals data, one shows that we need a more flexible forecasting technique. In this case we propose to use a Support Vector Machine (SVM) technique. Furthermore, the effects of noise components have to be filtered. Singular Spectrum Analysis (SSA) plays an important role in filtering such noise. Therefore, the combination of these two methods (SSA-SVM) will be used to predict the number of foreign tourist arrivals to Bali in 2017. The performance of SSA-SVM is evaluated via simulation studies and applied to tourist arrivals data in Bali. As the results, SSA-SVM shows better performances compare to other methods.
Regresi Nonparametrik dengan Pendekatan Deret Fourier pada Data Debit Air Sungai Citarum Intaniah Ratna Nur Wisisono; Ade Irma Nurwahidah; Yudhie Andriyana
Jurnal Matematika MANTIK Vol. 4 No. 2 (2018): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (368.256 KB) | DOI: 10.15642/mantik.2018.4.2.75-82

Abstract

River discharge is one of the factors that affect the occurrence of floods. It varies over time and hence we need to predict the flood risk. Since the plot of the data changes periodically showing a sines and cosines pattern, a nonparametric technique using Fourier series approach may be interesting to be applied. Fourier series can be estimated using OLS (Ordinary Least Square). In a Fourier series, nonparametric regression the level of subtlety of its function is determined by their bandwidth (K). Optimal bandwidth determined using the GCV (Generalized Cross Validation) method. From the calculation results, we have optimal bandwidth which is equal to 16 with R2 is 0.7295 which means that 72.95% of the total variance in the river discharge variable can be explained by the Fourier series nonparametric regression model. Comparing to a classical time series technique, ARIMA Box Jenkins, we obtained ARIMA (1,0,0) with RMSE 83.10 while using Fourier series approach generate a smaller RMSE 50.51.
The Analysis of Factors Influencing Incidence Rates of Toddler Pneumonia in Purwakarta Districts Using Panel Data Spatial Regression Nadiyah Nisrina; Budhi Handoko; Yudhie Andriyana
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 02 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol24-iss02/396

Abstract

Pneumonia is an acute respiratory infection that attacks the lungs and can cause inflammation of the air sacs due to the alveoli is filled with pus and fluid. This research aims at identifying factors influencing pneumonia and mapping its incidence rate for toddlers in the Purwakarta Regency. Many factors influence pneumonia, but due to the limitation of data or information, some factors cannot be included in the model and are called omitted variables. The incidence rate of toddler pneumonia in sub-districts of Purwakarta Regency is assumed to be related to one another or have a spatial dependency. Therefore, modeling pneumonia with the Fixed Effect Spatial Model can accommodate spatial aspects. The results show that MR2 measles immunization, low birth weight, exclusive breastfeeding, and clean and healthy living habits significantly affect the incidence rate of toddler pneumonia. Based on the mapping results, Wanayasa sub-district has a high incidence rate of toddler pneumonia, while some sub-districts such as Campaka, Pondoksalam, and Darangdan have low incidence rates.
Unveiling Spatial Disparities: Exploring High-Risk Diarrhea Among Children Under Five Using Geographically Weighted Quantile Regression Syukrilla, Wara Alfa; Andriyana, Yudhie; Verhasselt, Anneleen
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 15 No 2 (2023): Journal of Statistical Application and Computational Statistics
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v15i2.536

Abstract

We investigate the impact of the percentage of clean water access, the percentage of handwashing habits, and the toilet category factors on the upper quantile of toddlers’ diarrhea risks in Bandung City, Indonesia, using the Geographically Weighted Quantile Regression model on the 75th percentile. The breusch-Pagan test was used to detect spatial heterogeneity. The results show that the significance, strength, and direction of the relationship between diarrhea and its risk factors depend on the location. At the upper quantile, the Panyileukan district is predicted to have the highest diarrhea risk. In this district, all three predictors significantly affect the toddlers’ diarrhea risk, with the variable of the percentage of houses practicing hand washing habits observed to reduce diarrhea risk the most. In conclusion, clean water access, handwashing habits, and toilet category are the potential risk factors for high-risk childhood diarrhea. This method is powerful as it would allow the decision maker to handle the diarrhea problem aptly based on which predictor has a substantial effect at a specific district of interest. And it can be used to investigate the effect of various intervention strategies and effectively allocate the limited available resources according to the most important locations.
The Analysis of Nascent Entrepreneurs’ Happiness Level in Indonesia Sitohang, Yosep Oktavianus; Sasmita, Yoga; Andriyana, Yudhie; Pawitan, Gandhi
JDM (Jurnal Dinamika Manajemen) Vol 8, No 2 (2017): September 2017
Publisher : Department of Management, Faculty of Economics and Business, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jdm.v8i2.12765

Abstract

This study tried to analyze the factors that influence the happiness level of entrepreneurs in Indonesia especially the nascent entrepreneurs. The level of entrepreneurs’ happiness has a positive effect on the sustainability of their business. The research data are secondary data from 1,148 respondents who are included in the category of Total Early-stage Entrepreneurial Activity (TEA) at Global Entrepreneurship Monitor (GEM) in 2013. The variables employed are motivation, perception and innovation and demographic variables (gender, education and income). Analyzer used is multiple linear regressions with dummy variable. From  the result, it is found that only the motivation, education level and level of income that significantly influence the level of happiness. The nascent entrepreneurs, who have motivation to start a business because of opportunity, have a higher level of happiness than necessity motivation due to necessity. The level of education and income are also proportional to the level of happiness, but the level of education gives greater influence to the level of happiness of nascent entrepreneurs in Indonesia.
Implementation of Spatial Autoregressive with Autoregressive Disturbance (SARAR) using GMM to Identify Factors Caused Poverty in West Java Ningtias, Yunita Dwi Ayu; Andriyana, Yudhie; Pravitasari, Anindya Apriliyanti
Inferensi Vol 7, No 2 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i2.20309

Abstract

Poverty is one of the crucial problems that has a negative impact on all sectors. As a developing country, Indonesia has a fairly high poverty rate. The government's efforts to overcome the problem of poverty can be circumvented by detecting the factors that influence it to determine the policies taken by using statistical modeling. There is a spatial effect on poverty in West Java Province. Spatial Data Analysis is the only statistical model that can explain the relationship between an area and the surrounding area. If the response variable contains a lag that correlates with each other, it is called a Spatial Autoregressive with Autoregressive Disturbances (SARAR) model. The Generalized Method of Moment (GMM) approach is used to get an estimator from the model. This method is applied to obtain the factors that influence poverty in West Java Province. The results of this study indicate that the GMM SARAR poverty modeling with customized weights provides relatively better estimation results. In addition, the relationship between locations (spatial lag dependence) is positive and significant. Expected Years of Schooling and Per capita Expenditure have a negative and significant effect on the increase in the percentage of poor people in West Java.
Co-Authors Ade Irma Nurwahidah Anna Chadidjah Bertho Tantular Budhi Handoko Gandhi Pawitan Intaniah Ratna Nur Wisisono Nadiyah Nisrina Ningtias, Yunita Dwi Ayu Pardomuan Robinson Sihombing Pravitasari, Anindya Apriliyanti Sasmita, Yoga Sitohang, Yosep Oktavianus Syukrilla, Wara Alfa Verhasselt, Anneleen Yosep Oktavianus Sitohang