scholarly journals TIME SERIES ANALYSIS FOR FORESCASTING THE NUMBER OF TUBERCULOSIS IN KENDARI CITY 2018-2023

2019 ◽  
Vol 1 (1) ◽  
pp. 72-79
Author(s):  
Noviati Novi
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Linear Trend ◽  
Health Agency ◽  
Developed Countries ◽  
Quadratic Model ◽  
Pulmonary Tb ◽  
Average Decrease ◽  
Series Analysis ◽  
Quantitative Descriptive

Tuberculosis is a contagious disease that is still a problem in the world today, not only in developing countries but also in developed countries. That is what happened in Kendari City in 2012 - 2017. Efforts made to prevent the increasing number of tuberculosis in the future is to make predictions. This study aims to study time series analysis in predicting the incidence of tuberculosis based on sex and working area of ​​health centers in Kendari City in 2018-2022. This type of research is quantitative descriptive using the series analysis. Sources of research data obtained from the Kendari City Health Agency in Southeast Sulawesi Province consisted of data on pulmonary TB cases in which sex and working area of ​​Puskesmas in 2012 - 2017 in Kendari City would be processed and analyzed by time series using the trend method into 3 linear trend models, quadratic trends and exponential trends. The results showed the best model for prediction of pulmonary TB cases in Kendari City was the quadratic model. Based on the number of cases predicted to increase in the period 2018 to 2022, with an average decline with an average decrease of 79 cases in men and 286 cases in women. Pulmonary TB cases based on puskesmas area are predicted to increase in 2018 until 2022 with the highest average increase in Kemaraya puskesmas area. While the average decline in cases is highest in the Mata Puskesmas area. It is expected to be able to be information for policy makers, so that prevention and early promotion efforts can be made for the community.

RISK OF KNOWLEDGE, SMOKING AND PATIENT'S CONTACT ON TUBERCULOSIS DISEASE IN PUUWATU HEALTH CENTRE IN KENDARI CITY

2020 ◽  
Vol 2 (1) ◽  
pp. 46-53
Author(s):  
La Djabo Buton ◽  
Fitri Rachmillah Fadmi
Keyword(s):  
Time Series ◽  
Linear Trend ◽  
Health Centre ◽  
Developed Countries ◽  
Quadratic Model ◽  
Pulmonary Tb ◽  
Average Decrease ◽  
Series Analysis ◽  
Exponential Trend ◽  
The City

Background: Tuberculosis is a contagious disease that is still a problem in the world today, not only in developing countries but also in developed countries. Likewise in Kendari City in 2012 - 2017. Efforts that can be made to prevent the increasing number of tuberculosis cases in the future is to make predictions. This study aims to determine the time series analysis in predicting the incidence of tuberculosis by sex and working area of ??health centre in the city of Kendari in 2018-2022. Methods: This type of research is quantitative descriptive with times series analysis design. The source of the research data was obtained from the Kendari City Health Institution, Southeast Sulawesi Province, namely the data on the case of pulmonary TB which included the gender and working area of ??the Health Centre in 2012 - 2017 in the city of Kendari to be processed and analyzed in time series using the trend method approach into 3 models. linear trend, quadratic trend, and an exponential trend. Results: The results showed that the best model for the prediction of pulmonary TB cases in Kendari City was the quadratic model. Cases of tuberculosis by sex are predicted to decrease in the period 2018 to 2022, with an average decline with an average decrease of 79 cases in men and 286 cases in women. Pulmonary TB cases based on the health centre area are predicted to experience an increase in cases from 2018 until 2022 with the highest average increase being in the Kemaraya Health Centre area. While the highest average decrease in cases in the area of ??the Eye Health Center. It is expected to become information for policymakers so that prevention and promotion efforts can be made early to the community. Conclusion: Based on the results of the study, the conclusion of this study is the Science, knowledge about risk and Patient Contact History is a risk factor for tuberculosis in the work area of Puuwatu Health Centre, Kendari City.

scholarly journals Prediksi Kejadian Penyakit Tuberkulosis Paru Berdasarkan Jenis Kelamin

2020 ◽  
Vol 8 (2) ◽  
pp. 135-140
Author(s):  
Sri Andayani
Keyword(s):  
Time Series ◽  
Pulmonary Tuberculosis ◽  
Time Series Analysis ◽  
Tuberculosis Control ◽  
Cross Sectional ◽  
Pulmonary Tb ◽  
Series Analysis ◽  
Lung Tuberculosis ◽  
Cross Sectional Design ◽  
Quantitative Descriptive

Tuberculosis (TBC) is a case that is always increasing every year. Assessment of progress and success of pulmonary tuberculosis control in Ponorogo Regency uses indicators of suspicion screening numbers with health promotion, especially pulmonary TB. The purpose of this study was to analyze the prediction of the incidence of pulmonary tuberculosis based on gender in Ponorogo Regency from 2016 to 2020. This research is a quantitative descriptive study using a cross-sectional design with time series analysis approach with trend method. The population and sample in this study were all data on cases of smear positive lung tuberculosis which included the sex of the patient during 2011-2015 in Ponorogo Regency. Research Results The distribution of smear positive lung TB cases in the period 2011-2015 tended to increase with the number of cases respectively 276, 392, 378, 293 and 334 cases. After predicting, pulmonary TB cases in 2016-2020 will decline with cases of 299, 348, 366, 352, and 306 respectively.Based on the results of time series analysis with the trend method based on gender in Ponorogo Regency in 2016-2020, It is predicted that pulmonary TB cases will continue to increase and it is estimated that in 2018 the highest number of cases is male with 222 cases, and female sex with 141 cases. In conclusion, there has been an increase in cases of pulmonary tuberculosis in men in 2018.Keywords: Incidence Prediction, TB, Gender

scholarly journals Seasonality in extra-pulmonary tuberculosis notifications in Germany 2004-2014- a time series analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Tanja Charles ◽  
Matthias Eckardt ◽  
Basel Karo ◽  
Walter Haas ◽  
Stefan Kröger
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Disease Onset ◽  
Age Groups ◽  
Age Group ◽  
Pulmonary Tb ◽  
Series Analysis ◽  
Disease Site ◽  
Extra Pulmonary

Abstract Background Seasonality in tuberculosis (TB) has been found in different parts of the world, showing a peak in spring/summer and a trough in autumn/winter. The evidence is less clear which factors drive seasonality. It was our aim to identify and evaluate seasonality in the notifications of TB in Germany, additionally investigating the possible variance of seasonality by disease site, sex and age group. Methods We conducted an integer-valued time series analysis using national surveillance data. We analysed the reported monthly numbers of started treatments between 2004 and 2014 for all notified TB cases and stratified by disease site, sex and age group. Results We detected seasonality in the extra-pulmonary TB cases (N = 11,219), with peaks in late spring/summer and troughs in fall/winter. For all TB notifications together (N = 51,090) and for pulmonary TB only (N = 39,714) we did not find a distinct seasonality. Additional stratified analyses did not reveal any clear differences between age groups, the sexes, or between active and passive case finding. Conclusion We found seasonality in extra-pulmonary TB only, indicating that seasonality of disease onset might be specific to the disease site. This could point towards differences in disease progression between the different clinical disease manifestations. Sex appears not to be an important driver of seasonality, whereas the role of age remains unclear as this could not be sufficiently investigated.

scholarly journals INTERACTION BETWEEN THE ECONOMIC GROWTH AND THE CONSTRUCTION INDUSTRY: A TIME SERIES ANALYSIS ON TURKEY (2000-2012)

2013 ◽  
Vol 3 (1) ◽  
pp. 20-34 ◽  
Author(s):  
Bilal Kargı
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Time Series Analysis ◽  
Construction Industry ◽  
Developed Countries ◽  
The Other ◽  
Gdp Growth ◽  
Quarterly Data ◽  
Series Analysis ◽  
Gdp Growth Rate

In this study the relation between the economic growth and the construction industry has been tackled. While the growth the rate of the construction industry in the developing countries is more than the GDP growth rate, it is detected that the percent age it takes in the GDP of developed countries relatively diminishes. On the other hand the construction industry’s growth in the economic fluctuation periods, in the aftermath of a recession, is more than the GDP. These two proposals are tested by the quarterly data of 2000:01-2012:03 for Turkey. Additionally the relation between the economic growth and the construction industry is subjected to the Granger causality test.Keywords: Economic growth, construction industry, time series analysis.

scholarly journals TIME SERIES ANALYSIS OF SURFACE DEFORMATION OF BENGALURU CITY USING SENTINEL-1 IMAGES

2018 ◽  
Vol IV-5 ◽  
pp. 473-477
Author(s):  
N. Ittycheria ◽  
D. S. Vaka ◽  
Y. S. Rao
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Surface Deformation ◽  
Linear Trend ◽  
Polarization Data ◽  
Persistent Scatterer Interferometry ◽  
Advanced Technique ◽  
Interferometric Technique ◽  
Series Analysis ◽  
Persistent Scatterers

<p><strong>Abstract.</strong> Persistent Scatterer Interferometry (PSI) is an advanced technique to map ground surface displacements of an area over a period. The technique can measure deformation with a millimeter-level accuracy. It overcomes the limitations of Differential Synthetic Aperture Radar Interferometry (DInSAR) such as geometric, temporal decorrelation and atmospheric variations between master and slave images. In our study, Sentinel-1A Interferometric Wide Swath (IW) mode descending pass images from May 2016 to December 2017 (23 images) are used to identify the stable targets called persistent scatterers (PS) over Bengaluru city. Twenty-two differential interferograms are generated after topographic phase removal using the SRTM 30 m DEM. The main objective of this study is to analyze urban subsidence in Bengaluru city in India using the multi-temporal interferometric technique such as PSI. The pixels with Amplitude Stability Index &amp;geq;<span class="thinspace"></span>0.8 are selected as initial PS candidates (PSC). Later, the PSCs having temporal coherence &amp;gt;<span class="thinspace"></span>0.5 are selected for the time series analysis. The number of PSCs that are identified after final selection are reduced from 59590 to 54474 for VV polarization data and 15611 to 15596 for VH polarization data. It is interesting to note that a very less number of PSC are identified in cross-polarized images (VH). A high number of PSC have identified in co-polarized (VV) images as the vertically oriented urban targets produce a double bounce, which results in a strong return towards the sensor. The velocity maps obtained using VV and VH polarizations show displacement in the range of &amp;plusmn;<span class="thinspace"></span>20<span class="thinspace"></span>mm<span class="thinspace"></span>year<sup>&amp;minus;1</sup>. The subsidence and the upliftment observed in the city shows a linear trend with time. It is observed that the eastern part of Bengaluru city shows more subsidence than the western part.</p>

scholarly journals Comparative Analysis of Financial Performance Upon Automotive Companies Registered in BEI

2021 ◽  
Vol 2 (3) ◽  
pp. 882-817
Author(s):  
Ninik Mas'adah ◽  
Ira Megasyara ◽  
Amrizal Imawan ◽  
Rizky Wahyudha Rosiawan
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Financial Performance ◽  
Comparison Method ◽  
Cross Sectional ◽  
Leverage Ratio ◽  
Series Analysis ◽  
Net Profit ◽  
Quantitative Descriptive ◽  
Turn Over

This research was conducted to determine the financial performance of automotive companies listed on the IDX for the period 2012 to 2015. This type of research is a quantitative descriptive study, with a total population of 13 companies and a sample of 6 automotive companies that have been selected from the population with using purposive sampling method. The data analysis method used is a comparison method consisting of a cross sectional approach and time series analysis. The results show that the results of calculations using the cross-sectional approach, automotive companies in Indonesia for the 2012-2015 period experienced fluctuations and experienced a decline in the industry average at the end of 2015 and many automotive companies were in unhealthy condition in the 2012-2015 period. Based on the results of time series analysis of automotive companies in 2012-2015, it is known that the Total Assets Turn Over has decreased, the results on Net Profit Margin have decreased, the results on the current ratio have decreased, the result of the leverage ratio has increased. The management of automotive companies in Indonesia needs to increase investment in assets, because if the level of liquidity is high but the investment in assets is small, the money or cash available will only be stored and have less value for the company.

scholarly journals Was School Closure Effective in Mitigating Coronavirus Disease 2019 (COVID-19)? Time Series Analysis Using Bayesian Inference

2020 ◽  
Author(s):  
Kentaro Iwata ◽  
Asako Doi ◽  
Chisato Miyakoshi
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Linear Trend ◽  
Credible Interval ◽  
School Closure ◽  
Sensitivity Analyses ◽  
Series Analysis ◽  
Daily Data ◽  
Coronavirus Infection ◽  
Novel Coronavirus

Background: Coronavirus disease 2019 (COVID-19) pandemic are causing significant damages to many nations. For mitigating its risk, Japan&rsquo;s Prime Minister called on all elementary, junior high and high schools nationwide to close beginning March 1, 2020. However, its effectiveness in decreasing disease burden has not been investigated. Methods: We used daily data on the report of COVID-19 and coronavirus infection incidence in Japan until March 31, 2020. Time series analysis were conducted using Bayesian method. Local linear trend models with interventional effect were constructed for number of newly reported cases of COVID-19, including asymptomatic infections. We considered that the effects of intervention start to appear 9 days after the school closure; i.e., on March 9. Results: The intervention of school closure did not appear to decrease the incidence of coronavirus infection. If the effectiveness of school closure began on March 9, mean coefficient &alpha; for effectiveness of the measure was calculated to be 0.08 (95% credible interval -0.36 to 0.65), and the actual reported cases were more than predicted, yet with rather wide credible interval. Sensitivity analyses using different dates also showed similar results. Conclusions: School closure carried out in Japan did not show the effectiveness to mitigate the transmission of novel coronavirus infection.

Time series analysis in forecasting pririrodno focal infections

2015 ◽  
Vol 9 (4) ◽  
pp. 0-0
Author(s):  
Евстегнеева ◽  
V. Evstegneeva ◽  
Честнова ◽  
Tatyana Chestnova ◽  
Смольянинова ◽  
...  
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Time Series Analysis ◽  
Bank Vole ◽  
Linear Trend ◽  
Random Variables ◽  
Vole Population ◽  
Long Term Effects ◽  
Series Analysis

Mathematical methods and models used in forecasting problems may relate to a wide variety of topics: from the regression analysis, time series analysis, formulation and evaluation of expert opinions, simulation, systems of simultaneous equations, discriminant analysis, logit and probit models, logical unit decision functions, variance or covariance analysis, rank correlation and contingency tables, etc. In the analysis of the phenomenon over a long timeperiod, for example, the incidence of long-term dynamics with a forecast of further development of the process, you should use the time series, which is influenced by the following factors: • Emerging trends of the series (the trend in cumulative long-term effects of many factors on the dynamics of the phenomenon under study - ascending or descending); • forming a series of cyclical fluctuations related to the seasonality of the disease; • random factors. In our study, we conducted a study to identify cyclical time series of long-term dynamics of morbidity of HFRS and autumn bank vole population. This study was performed using the autocorrelation coefficient. As a result of time-series studies of incidence of HFRS, indicators autumn bank vole population revealed no recurrence, and these figures are random variables, which is confirmed by three tests: nonrepeatability of time series, the assessment increase and decrease time-series analysis of the sum of squares. This shows that a number of indicators of the time series are random variables, contains a strong non-linear trend, to identify which need further analysis, for example by means of regression analysis.

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