scholarly journals ANALISIS ANTENATAL CARE (ANC) PADA SURVEILANS KESEHATAN IBU DAN ANAK DENGAN TAHAPAN AGREGASI PIPELINE NOSQL

2021 ◽  
Vol 4 (1) ◽  
pp. 16
Author(s):  
Dadang Heksaputra ◽  
M. J. U. Haris Bahrudin ◽  
Anni Karimatul Fauziyah ◽  
Dhina Puspasari Wijaya
Keyword(s):  
Antenatal Care ◽  
Time Series Data ◽  
Performance Indicator ◽  
Series Data ◽  
Research Results ◽  
Pipeline Stage ◽  
Indicator Analysis ◽  
Data Surveillance ◽  
The Village ◽  
Method Improvement

Case 30.8 percent of Indonesian children under five are stunted. Bantul is a district in the Province of D.I. Yogyakarta, Indonesia, is a locus of stunting. Bantul has ten villages. The ten villages include Patalan Jetis Village, Canden Jetis Village, Terong Dlingo Village, Argodadi Sedayu Village, Triharjo Pandak Village, Triwidadi Pajangan Village, Jatimulyo Dlingo Village, Datangharjo Sewon Village, Sendangsari Pajangan Village, and Trimulyo Jetis Village. The research focuses on the village of Argodadi Sedayu. In the village of Argodadi Sedayu, Antenatal Care (ANC) research would be conducted. Antenatal Care (ANC) is a pregnancy check by a doctor or midwife. Therefore, Antenatal Care Analysis (ANC) is needed to determine whether diet, parenting, and sanitation are well programmed. Antenatal care (ANC) research framework was a model of method improvement. The method improvement model consists of indicators, proposed methods, objectives, and measurements. The indicators consist of monitoring instruments and health visits. The proposed method uses an aggregation pipeline stage. The data was processed in the aggregation pipeline stage. The data were obtained from the time series data surveillance dataset. The research objective was to analyze the research results accurately according to the proposed method. Measurement of indicator analysis with the application of the dashboard as a performance indicator on the research results. Practically, it is hoped that the research results could consider the health office and related institutions in reducing or even elevating Argodadi Sedayu Village in Yogyakarta as a non-locus of stunting using massive monitoring of diet, parenting, and sanitation well programmed.

scholarly journals Loss of Control Prediction for Motorcycles during Emergency Braking Maneuvers Using a Supervised Learning Algorithm

2020 ◽  
Vol 10 (5) ◽  
pp. 1754 ◽  
Author(s):  
Pedro Huertas-Leyva ◽  
Giovanni Savino ◽  
Niccolò Baldanzini ◽  
Marco Pierini
Keyword(s):  
Supervised Learning ◽  
Predictive Models ◽  
Time Series Data ◽  
Performance Indicator ◽  
Learning Algorithm ◽  
Front Wheel ◽  
Series Data ◽  
Loss Of Control ◽  
Skill Levels ◽  
Emergency Situations

The most common evasive maneuver among motorcycle riders and one of the most complicated to perform in emergency situations is braking. Because of the inherent instability of motorcycles, motorcycle crashes are frequently caused by loss of control performing braking as an evasive maneuver. Understanding the motion conditions that lead riders to start losing control is essential for defining countermeasures capable of minimizing the risk of this type of crashes. This paper provides predictive models to classify unsafe loss of control braking maneuvers on a straight line before becoming irreversibly unstable. We performed braking maneuver experiments in the field with motorcycle riders facing a simulated emergency scenario. The latter involved a mock-up intersection in which we generated conflict events between the motorcycle ridden by the participants and an oncoming car driven by trained research staff. The data collected comprises 165 braking trials (including 11 trials identified as loss of control) with 13 riders representing four categories of braking skill, ranging from beginner to expert. Three predictive models of loss of control events during braking trials, going from a basic model to a more advanced one, were defined using logistic regressions as supervised learning methods and using the area under the receiver operating characteristic (ROC) curve as a performance indicator. The predictor variables of the models were identified among the parameters of the vehicle kinematics. The best model predicted 100% of the loss of control and 100% of the full control cases. The basic and the more advanced supervised models were adapted for loss of control identification with time series data, and the results detecting in real-time the loss of control events showed excellent performance as well as with the supervised models. The study showed that expert riders may maintain stability under dynamic conditions that normally lead less skilled riders to a loss of control or falling events. The best decision thresholds of the most relevant kinematic parameters to predict loss of control have been defined. The thresholds of parameters that typically characterize the loss of control such as the yaw rate and front-wheel lock duration were dependent on the rider skill levels. The peak-to-root-mean-square ratio of roll acceleration was the most robust parameter for identifying loss of control among all skill levels.

scholarly journals Treatment of Outlier Using Interpolation Method in Malaysia Tourist Arrivals

2018 ◽  
Vol 7 (3.7) ◽  
pp. 51
Author(s):  
Maria Elena Nor ◽  
Norsoraya Azurin Wahir ◽  
G P. Khuneswari ◽  
Mohd Saifullah Rusiman
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Performance Indicator ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Forecast Accuracy ◽  
Linear Interpolation ◽  
Negative Influence ◽  
Series Data ◽  
Missing Value

The presence of outliers is an example of aberrant data that can have huge negative influence on statistical method under the assumption of normality and it affects the estimation. This paper introduces an alternative method as outlier treatment in time series which is interpolation. It compares two interpolation methods using performance indicator. Assuming outlier as a missing value in the data allows the application of the interpolation method to interpolate the missing value, thus comparing the result using the forecast accuracy. The monthly time series data from January 1998 until December 2015 of Malaysia Tourist Arrivals were used to deal with outliers. The results found that the cubic spline interpolation method gave the best result than the linear interpolation and the improved time series data indicated better performance in forecasting rather than the original time series data of Box-Jenkins model. 

scholarly journals Moderation of Non Performing Financing on Natural Uncertainty Contracts To The Profitability of Islamic Commercial Bank In Indonesia

2020 ◽  
Vol 4 (02) ◽  
Author(s):  
Taudlikhul Afkar ◽  
Grahita Chandrarin ◽  
Lilik Pirmaningsih
Keyword(s):  
Structural Equation ◽  
Quantitative Research ◽  
Time Series Data ◽  
Equation Model ◽  
Series Data ◽  
Islamic Banks ◽  
Business Managers ◽  
Quantitative Research Methods ◽  
Research Results ◽  
Analysis Technique

This study intends to provide an overview of the consistency of research results with theoretical and empirical points of view, it is done because many research results are inconsistent with the theory. Quantitative research methods are used to make generalizations using a sample of 14 Islamic Commercial Banks in Indonesia with time series data collection techniques for 5 years. The data analysis technique used is multivariate analysis using the Warp PLS structural equation model. The results showed that the level of profitability of Islamic banks is always overshadowed by the occurrence of credit risk that causes non-performing financing from financing of the type of natural uncertainty contracts because it is type of financing is a financing that does not provide certainty of results. The results of this study are consistent with agency theory that explains the existence of information asymmetry, and consistent with the theory of mixing that by providing opportunities to manage business to business managers (mudharib/mustyarik) without interference from the owner of the fund (shaibul maal) can lead to the risk of default and thus affect the ability of Islamic banks to obtain profitability.

scholarly journals COMPARISON OF VILLAGE DEVELOPMENT BEFORE AND AFTER VILLAGE FUND IMPLEMENTATION IN NAGAN RAYA DISTRICT

2021 ◽  
pp. 18-35
Author(s):  
Arroyyan Ramly
Keyword(s):  
Time Series Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Primary Data ◽  
Series Data ◽  
P Value ◽  
Analysis Method ◽  
Effect Model ◽  
The Village

This study aims to analyze and see the effectiveness of the distribution of the use of village funds in Kuala Subdistrict, Nagan Raya Regency and its relationship with poverty levels. The data used is in the form of time series data from 2015 to 2018 which is collected through primary and secondary data. Primary data were obtained by directly visiting villages in the Kuala sub-district. Meanwhile, secondary data were obtained from the website of the Central Statistics Agency (BPS), document review, articles related to the object of research. This study conducted observations of 10 villages as a sample of 17 villages in Kuala District. The analysis method uses panel data regression with the random effect model (REM) analysis method. From the regression results of the random effect model, it was found that the village fund variable had a positive and significant effect on poverty with a probability of 0.0000 = p-value α = 5%. Then the village fund allocation variable has a significant negative effect on poverty with a probability of 0.0000 = p-value α = 5%. This means that adding 1% of village funds or increasing village funds will reduce poverty in Kuala Subdistrict, Nagan Raya Regency.

scholarly journals Monitoring the geodynamic behaviour of earthquake using Landsat 8-OLI time series data: case of Gorkha and Imphal

2017 ◽  
Author(s):  
Biswajit Nath ◽  
Zheng Niu ◽  
Shukla Acharjee ◽  
Hailang Qiao
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Vertical Surface ◽  
Series Data ◽  
Landsat 8 ◽  
Length Variation ◽  
Landsat 8 Oli ◽  
Research Results ◽  
Earthquake Monitoring ◽  
Lineament Extraction

Abstract. Prediction of earthquake in advance is really a challenging task for the scientific community till now. But research results from various scientists regarding lineament extraction using satellite imageries help us to way forward for earthquake monitoring study. For the present study, Landsat 8 OLI Time series data analyzed by integrating four different remote sensing and GIS software’s for automatic lineament extraction, its change, including lineament lengths and directions study by creating rose diagrams and finally vertical surface transect profile curve drawing. Two recent major earthquakes (in different geological settings Gorkha of Nepal 7.8 Mw and Imphal, Manipur of Eastern India 6.8 Mw) epicenter based single tile and corresponding same temporal scenes (three for before and one for after quake respectively) were considered for each case to perform lineament extraction, length variation and vertical surface transect profile change analysis. The research results witnessed major variations in lineament number, lineament length and its trends. The major trends found in an ESE-WNW, N-E, N-S, E-W, NNE-SSW directions and ESE-WSW, ESE-WNW, NE-SW on pre-earthquake scenes compared to post earthquake ESE-WNW, NE-SW, NNE-SSW were found for Gorkha, and ESE-WSW for Imphal regions respectively and in both cases, it was observed that the lineation trends return to its earlier status after an earthquake strike. The results obtained using the automated and geo-integrated methods compared cross validation with each other showed our method worked practically for earthquake monitoring and one can apply this new novel combined approach to predict the probable earthquake occurrence in advance just a few days before it strikes.

scholarly journals The impact of foreign direct investment on sustainable urbanization in Binh Duong province

2021 ◽  
pp. 139-153
Keyword(s):  
Foreign Direct Investment ◽  
Urban Development ◽  
Direct Investment ◽  
Time Series Data ◽  
Series Data ◽  
Policy Makers ◽  
Research Results ◽  
Sustainable Urbanization ◽  
The World ◽  
The Impact

In urban development, urbanization is an important and decisive process of transformation. In the current globalization period, the urbanization of cities around the world is strongly influenced by the foreign direct investment (FDI). It is considered an important catalyst for economic growth. This paper aims to analyze the effect of FDI on sustainable urbanization in Binh Duong province by utilizing the time series data throughout 2000 - 2018, expressed through statistical and analytical methods. The research results show that FDI contributes to promoting economic, social and urban development in Binh Duong province, but it still has some limitations. The research results are also the basis for researchers and policy makers to develop orientations to attract, use and manage FDI, proposing solutions to improve the efficiency of it to urbanization in a sustainable way in Binh Duong province in the future.

scholarly journals A method to estimate the demand for freight transport in absence of historical data. A case study of the Oder Waterway

2018 ◽  
Vol 58 ◽  
pp. 01009
Author(s):  
Ludmiła Filina-Dawidowicz ◽  
Izabela Kotowska ◽  
Marta Mańkowska ◽  
Michał Pluciński
Keyword(s):  
Time Series ◽  
Qualitative Methods ◽  
Time Series Data ◽  
Historical Data ◽  
Freight Transport ◽  
Series Data ◽  
Class Iii ◽  
Research Results

The aim of the research described in this article is to work out a method to estimate the demand for freight transport in a situation when no historical data are available, thus rendering it impossible to apply methods based on time series data. The method presented in this article was developed and verified on the basis of an analysis of potential inland shipping operations on the Oder Waterway to/from the seaports in Szczecin and Świnoujście, assuming that the waterway has been upgraded to navigability class III. The analysis was predicated on a demand survey performed among cargo shippers. The obtained research results made it possible to specify the advantages and drawbacks of forecasting based on qualitative methods, and to identify the factors which significantly reduce the reliability of freight transport forecasts.

scholarly journals Impact of Capital Adequacy on Banks’ Performance: Considering the Basel International Regulatory Framework for Banks

ETIKONOMI ◽  
2021 ◽  
Vol 20 (1) ◽  
pp. 45-54
Author(s):  
Sampson Agyapong Atuahene ◽  
Kong Yusheng ◽  
Geoffrey Benturn-Micah ◽  
Abigail Konadu Aboagye
Keyword(s):  
Time Series Data ◽  
Performance Indicator ◽  
Fixed Effect Model ◽  
Regulatory Framework ◽  
Capital Adequacy ◽  
Series Data ◽  
Effect Model ◽  
Net Profit ◽  
The Impact ◽  
Negative Link

This study examines the impact of banks' capital on the performance of banks. The studies adopted a fixed-effect model estimation. Time-series data covering the period 2008-2017 for Ghanaian listed universal banks was considered. We found out that the bank’s capital and banks’ net profit after tax has a positive and significant relationship with banks’ total asset base as a performance indicator. We further discovered through correlational analysis that there is a strong negative link between banks' outstanding loans (credit advancement) and banks' performance. The fundamental implications of this study are to encourage the monitoring of capital adequacy of banks since it creates opportunities for banks to perform effectively.JEL Classification: E5, E44, G21, G30How to Cite:Atuahene, S. A., Yusheng, K., Bentum-Micah, G., & Aboagye, A. K. (2021). Impact of Capital Adequacy on Banks’ Performance: Considering the Basel International Regulatory Framework for Banks. Etikonomi: Jurnal Ekonomi, 20(1), 45 – 54. https://doi.org/10.15408/etk.v20i1.15590.

scholarly journals A Novel Hybrid Method for KPI Anomaly Detection Based on VAE and SVDD

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2104
Author(s):  
Yun Zhao ◽  
Xiuguo Zhang ◽  
Zijing Shang ◽  
Zhiying Cao
Keyword(s):  
Anomaly Detection ◽  
Hybrid Method ◽  
Latent Variables ◽  
Time Series Data ◽  
Short Term Memory ◽  
Performance Indicator ◽  
Series Data ◽  
Support Vector ◽  
Support Vector Data Description ◽  
Leibler Divergence

Key performance indicator (KPI) anomaly detection is the underlying core technology in Artificial Intelligence for IT operations (AIOps). It has an important impact on subsequent anomaly location and root cause analysis. Variational auto-encoder (VAE) is a symmetry network structure composed of encoder and decoder, which has attracted extensive attention because of its ability to capture complex KPI data features and better detection results. However, VAE is not well applied to the modeling of KPI time series data and it is often necessary to set the threshold to obtain more accurate results. In response to these problems, this paper proposes a novel hybrid method for KPI anomaly detection based on VAE and support vector data description (SVDD). This method consists of two modules: a VAE reconstructor and SVDD anomaly detector. In the VAE reconstruction module, firstly, bi-directional long short-term memory (BiLSTM) is used to replace the traditional feedforward neural network in VAE to capture the time correlation of sequences; then, batch normalization is used at the output of the encoder to prevent the disappearance of KL (Kullback–Leibler) divergence, which prevents ignoring latent variables to reconstruct data directly. Finally, exponentially weighted moving average (EWMA) is used to smooth the reconstruction error, which reduces false positives and false negatives during the detection process. In the SVDD anomaly detection module, smoothed reconstruction errors are introduced into the SVDD for training to determine the threshold of adaptively anomaly detection. Experimental results on the public dataset show that this method has a better detection effect than baseline methods.

scholarly journals Mesothelioma Risk Associated with Asbestos Production in Slovenia

2010 ◽  
Vol 61 (1) ◽  
pp. 45-52 ◽  
Author(s):  
Marko Vudrag ◽  
Tatja Rihtar ◽  
Miljana Vegnuti
Keyword(s):  
Risk Assessment ◽  
Time Series ◽  
Malignant Mesothelioma ◽  
Total Population ◽  
Time Series Data ◽  
Series Data ◽  
Crude Incidence ◽  
The Village

Mesothelioma Risk Associated with Asbestos Production in SloveniaThe aim of this study was to assess malignant mesothelioma morbidity due to exposure to asbestos in a population living in districts Nova Gorica and Tolmin (49,850 people) near the asbestos manufacturing village Anhovo (Slovenia) and to compare it with the entire Slovene population (1,949,750 people). Crude rates per 100,000 people were calculated from the total number of mesotheliomas, and risk assessment in the studied vs. total population was based on 23 years worth of data. Time series data on mesothelioma cases were also processed as a forecast of new cases by 2010.The crude incidence of mesothelioma per 100,000 individuals for all of Slovenia was 21.4, while for the Nova Gorica district including the village Anhovo it is 170.2 and for the Tolmin district 60.9. The probability of a mesothelioma case in the studied population was 8.5 times the probability of the same diagnosis in the whole of Slovenia. Over 23 years, 28% of all mesothelioma cases in Slovenia were diagnosed in the studied population, which makes only 2.5% of the total Slovene population.The outbreak of asbestosis and mesothelioma epidemics in the studied population is associated with manufacture of asbestos products in the local factory from 1922 to 1996.

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