scholarly journals Estimation of Subsurface Soil Layers using H/V Spectrum of Densely Measured Microtremor Observations (Case Study: Yogyakarta City, Central Java-Indonesia)

2014 ◽  
Vol 2 (1) ◽  
pp. 13-20 ◽  
Author(s):  
Zaw Lin Kyaw ◽  
◽  
Subagyo Pramumijoyo ◽  
Salahuddin Husein ◽  
Teuku Faisal Fathani ◽  
...  
Keyword(s):  
Soil Layers ◽  
Central Java ◽  
Subsurface Soil ◽  
Yogyakarta City

scholarly journals Predicting subsurface soil layering and landslide risk with Artificial Neural Networks: a case study from Iran

2011 ◽  
Vol 62 (5) ◽  
pp. 477-485 ◽  
Author(s):  
Farzad Farrokhzad ◽  
Amin Barari ◽  
Lars Ibsen ◽  
Asskar Choobbasti
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Training Data ◽  
Landslide Risk ◽  
Northern Iran ◽  
Soil Layers ◽  
Subsurface Soil ◽  
Soil Layering ◽  
Artificial Neural

Predicting subsurface soil layering and landslide risk with Artificial Neural Networks: a case study from Iran This paper is concerned principally with the application of Artificial Neural Networks (ANN) in geotechnical engineering. In particular the application of ANN is discussed in more detail for subsurface soil layering and landslide analysis. Two ANN models are trained to predict subsurface soil layering and landslide risk using data collected from a study area in northern Iran. Given the three-dimensional coordinates of soil layers present in thirty boreholes as training data, our first ANN successfully predicted the depth and type of subsurface soil layers at new locations in the region. The agreement between the ANN outputs and actual data is over 90 % for all test cases. The second ANN was designed to recognize the probability of landslide occurrence at 200 sampling points which were not used in training. The neural network outputs are very close (over 92 %) to risk values calculated by the finite element method or by Bishop's method.

THE CHANGING OF SANTRI’s PREFERENCE TOWARDS STUDIES AND PROFESSIONS: A Case Study at Pondok Pesantren Alhikmah 2 Brebes, Central Java

Al-Qalam ◽  
2017 ◽  
Vol 23 (2) ◽  
Author(s):  
Hayyadin Ode
Keyword(s):  
Subject Matter ◽  
Central Java ◽  
Religious Subject

<p>This research aimed to figure out the santri’s preference toward studies and professions in which conduct study at pesantren. Common perceived and stated also at Government Ordinancenumber 55, 2007, that pesantren purposes was to reproduce Islamic scholar (ulama). However, through this study, it proved that not all santri wanted to be ulama, most of them wanted to be a scientist. This study was a case study, conducted in 2015 at Pesantren Alhikmah2 Brebes. Data collected using questionnaire, interview, and document. Those all derived from santris, Kyais, and teachers (asatidz). The research concluded as showed from questionnaire that santri’s  preferences toward study has gotten  changing to general subject matters instead of religious subject matters; and the santri’s professions and jobspreference has gotten changing to the jobs and professions that based on general subject matter, instead of choose to be ulama (Islamic scholar) most of santri wanted to be scientists, or researchers, or doctors as well as athlete.</p>

scholarly journals Female Candidates, Islamic Women’s Organisations, and Clientelism in the 2019 Indonesian Elections

2021 ◽  
Vol 40 (1) ◽  
pp. 73-92
Author(s):  
Muhammad Mahsun ◽  
Misbah Zulfa Elizabeth ◽  
Solkhah Mufrikhah
Keyword(s):  
Structural Barriers ◽  
Women Candidates ◽  
Electoral Success ◽  
Female Candidates ◽  
Central Java ◽  
Grassroots Support ◽  
Nahdlatul Ulama ◽  
And Gender ◽  
Women's Networks

This article analyses the factors leading to the success of women candidates in the 2019 elections in Central Java. Recent scholarship on women’s representation in Indonesia has highlighted the role that dynastic ties and relationships with local political elites play in getting women elected in an environment increasingly dominated by money politics and clientelism. Our case study of women candidates in Central Java belonging to the elite of the Nahdlatul Ulama (NU)-affiliated women’s religious organisations Muslimat and Fatayat shows that strong women candidates with grassroots support can nonetheless win office. Using the concepts of social capital and gender issue ownership, and clientelism, we argue that women candidates can gain a strategic advantage when they “run as women.” By harnessing women’s networks and focusing on gender issues to target women voters, they are able to overcome cultural, institutional, and structural barriers to achieve electoral success even though they lack resources and political connections.

scholarly journals The importance of socialization in achieving universal health coverage: case study of Jaminan Kesehatan Nasional (JKN) implementation in two different region in Central Java province

2019 ◽  
Vol 10 (2) ◽  
pp. 110-120
Author(s):  
Ema Nur Fitriana ◽  
Ari Natalia Probandari ◽  
Eti Poncorini Pamungkasari ◽  
Tonang Dwi Ardyanto ◽  
Rizky Amalia Puspitaningrum
Keyword(s):  
Universal Health Coverage ◽  
Health Coverage ◽  
Central Java ◽  
Universal Health ◽  
Central Java Province

scholarly journals PEMODELAN REGRESI RIDGE ROBUST-MM DALAM PENANGANAN MULTIKOLINIERITAS DAN PENCILAN (Studi Kasus : Faktor-Faktor yang Mempengaruhi AKB di Jawa Tengah Tahun 2017)

2019 ◽  
Vol 8 (1) ◽  
pp. 24-34
Author(s):  
Eka Destiyani ◽  
Rita Rahmawati ◽  
Suparti Suparti
Keyword(s):  
Least Squares ◽  
Robust Regression ◽  
Ordinary Least Squares ◽  
Regression Method ◽  
Predictor Variables ◽  
Healthy Life ◽  
Significance Level ◽  
Central Java ◽  
Regression Parameters

The Ordinary Least Squares (OLS) is one of the most commonly used method to estimate linear regression parameters. If multicollinearity is exist within predictor variables especially coupled with the outliers, then regression analysis with OLS is no longer used. One method that can be used to solve a multicollinearity and outliers problems is Ridge Robust-MM Regression. Ridge Robust-MM  Regression is a modification of the Ridge Regression method based on the MM-estimator of Robust Regression. The case study in this research is AKB in Central Java 2017 influenced by population dencity, the precentage of households behaving in a clean and healthy life, the number of low-weighted baby born, the number of babies who are given exclusive breastfeeding, the number of babies that receiving a neonatal visit once, and the number of babies who get health services. The result of estimation using OLS show that there is violation of multicollinearity and also the presence of outliers. Applied ridge robust-MM regression to case study proves ridge robust regression can improve parameter estimation. Based on t test at 5% significance level most of predictor variables have significant effect to variable AKB. The influence value of predictor variables to AKB is 47.68% and MSE value is 0.01538.Keywords:  Ordinary  Least  Squares  (OLS),  Multicollinearity,  Outliers,  RidgeRegression, Robust Regression, AKB.

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