Z-score Method Research Articles

Effects of Social Media on Consumer Brand Awareness and Patronage of Nike Lake Resort Services in Enugu: An Innovation Adoption Theory & Hierarchy of Effects Model Exposition

Communication has initiated a paradigm shift from the traditional to new the new social media. This study investigated the influence of Twitter messages and Facebook messages on consumer brand awareness and patronage of Nike Lake Resort services in Enugu: an innovation adoption theory & hierarchy of effects model exposition. The specific objectives of the study were to ascertain the extent of the influence of Twitter messages on consumer brand awareness and patronage of Nike Lake Resort services. Also, to determine the extent of the influence of Facebook messages on consumer brand awareness and patronage of Nike Lake Resort services. This study contributed to the extant gap in marketing literature by using Twitter messages and Facebook messages to promote Nike Lake Resort services in Enugu. The population of the study includes guests of Nike Lake Resort selected through a convenient sampling technique. The survey method was adopted and the sample size of 384 was determined using Freud and William’s formula known as the Z-score method. Cronbach’s alpha was used to determine the reliability of the instrument of 0.870. The Pearson product-moment correlation coefficient was used to analyse data. Findings revealed a significant positive influence of Twitter messages on consumer brand awareness and patronage of Nike Lake Resort services (r = 0.937, p < 0.05). Also, it was revealed that there is a significant positive influence of Facebook messages on consumer brand awareness and patronage of Nike Lake Resort services (r = 0.943, p < 0.05). Twitter messages and Facebook messages are effective marketing tools for communicating Nike Lake Resort services to consumers. There is need for Nike Lake Resort to continuously improve on the use of Twitter messages and Facebook messages channels to help boost consumer awareness and patronage in future.

ANALISIS FINANCIAL DISTRESS BANK UMUM MILIK NEGARA (BUMN) MASA PANDEMI COVID 19

The purpose of this study was to analyze financial distress using the Altman (Z-Score) method at Bank Umum Milik Negara (BUMN) during pandemin Covid 19. The results showed that PT. BRI (Persero) Tbk with a condition that is not financial distress in years 2015 and 2016. In years 2017, 2018 and 2019 included in the gray area. PT. BNI 46 (Persero) Tbk in years 2015 meaning is not financial distress. Years 2016, 2017, 2018 and 2019 this means it is included in the gray area. PT. Bank Mandiri (Persero) Tbk, in year 2015, 2016, 2017, 2018 and 2019 it is included in a gray area. PT. BTN (Persero) Tbk in year 2015 included in the gray area, years 2016, 2017, 2018, 2019 this shows that PT. BTN (Persero) Tbk expriencing financial distress

QRS detection of ECG signal using U-Net and DBSCAN

QRS detection is a crucial task for ECG signal analysis, which is the preliminary and essential step to further recognition and diagnosis. This paper proposes a U-Net based method for QRS detection. The method consists of three steps including preprocessing, U-Net model, and density-based spatial clustering of applications with noise(DBSCAN). The normalization is carried out using the Z-score method in preprocessing. In this study, location prediction is conducted by the U-Net model. Subsequently, the U-Net outputs are thresholded and clustered by DBSCAN. Finally, the middle points of the cluster are regards as the R-peak of the QRS complex. We demonstrate that the proposed method achieving high accuracy on ECG signals from the MIT-BIH Arrhythmia Database(MITDB). The experimental results show an average sensitivity of 99.98 %, positive predictivity of 99.95 %, accuracy of 99.93 %, and F1-score of 99.97 %. Compared with other existing methods, the overall performance is comparable and even better in terms of accuracy and F1-score.

Analisis Finansial Distress Untuk Memprediksi Risiko Kebangkrutan Perusahaan Sub Sektor Energi

This study aims to determine and analyze the financial performance of the energy sub-sector using the Almant Z-Score method. This research is a quantitative descriptive study. The population in this study are energy sub-sector companies listed on the Indonesia Stock Exchange 2015-2019. The sample in this study amounted to 4 energy sub-sector companies, namely PT. Perusahaan Gas Negara, PT. Leyand International, PT. Rukun Raharja, and PT. Mitra Energi Persada. The sampling technique in this study was using purposive sampling technique. The results of the financial distress predictions for the energy sub-sector companies, amounting to 4 publicly traded companies during the 2015 to 2019 research period using the Altman Z-Score method. This results in three companies in financial distress and one company in a safe area.
 Keywords: Finansial Distress, Bankrupty, Energy Sub-sector

Analisis Pembentukan Portofolio Optimal dengan Single Index Model dan Z-Score pada Emiten IDX BUMN 2O

This study aims to form an optimal portfolio and compare portfolio performance using a single index model and z-score. The z-score method is divided into 2 (two) according to the investment strategy, namely growth and value as investors' preferences in choosing a portfolio. The study population uses the IDX BUMN 20 for the period May 2018 - December 2020. The analysis results from the single index method have a portfolio return of 0.001339 with a risk to be faced of 0.0037724. The z-score growth investing method obtains a portfolio return value of 0.000989 and has a risk of 0.023369. Meanwhile, the z-score value investing method has a portfolio return of 0.001614 with a risk of 0.027416. Then the z-score value investing method has the highest performance evaluation value based on the sharpe ratio, treynor measure, and gen's alpha when compared to the other 2 (two) methods.

Energy and Collision Aware WSN Routing Protocol for Sustainable and Intelligent IoT Applications

Wireless Sensor Network (WSN) has wide range of applications including next generation intelligent IoT applications. Sensor nodes in WSNs don’t allow replacing batteries as phenomenon under consideration is not frequently accessible or inaccessible. Resource constrained WSN nodes run on batteries with limited capacity. For long running of the WSNs, energy consumption on each node and lifetime of overall network is a concern for IoT applications. To prolong lifetime of WSNs, use of energy efficient method is necessary and a challenging task. Most of the on-demand routing protocols use metrics like number of hops for the selection of path from the source node to the destination node. Purely hop count-based metrics leads to frequent broken paths as well as more energy consumption and results into reduced lifetime of IoT applications. Method proposed in this paper is a cross layer variant of AODV by replacing hop count metric with link quality and collision count. To establish a path, proposed method fetches link quality information from Physical layer and collision information from MAC layer to aid Network layer for making intelligent routing decisions using ZScore method. Using this information, proposed routing metric caters to select stable and sustainable routing path. Method proposed in this paper is implemented in well-known network simulator, NS-2 by incorporating necessary changes into existing physical and MAC layers as well as AODV protocol. A comparative analysis with existing methods is an indicator of improved performance in terms of energy efficiency, network lifetime, path stability and delay.

Correlation of cerebrospinal fluid amyloid β-protein 42 and neurofilament light protein levels with postoperative neurocognitive dysfunction in elderly patients

To detect cerebrospinal fluid levels of amyloid beta- protein 42 (Aβ42) and neurofilament light protein (NFL) and explore their correlation with postoperative neurocognitive dysfunction (PNCD) in elderly patients. A total of 90 elderly patients undergoing hip or knee replacement with joint epidural anesthesia in our Hospital between January, 2017 and December, 2018 were recruited in this study. The levels of Aβ42 and NFL in the cerebrospinal fluid were detected using ELISA. Simple cognitive status assessment scale (MMSE) was used to evaluate the cognitive status of the patients 1 day before and 7 days after the surgery. All the patients underwent neurocognitive function tests, and the z-score method was used to determine the occurrence of PNCD. Spearman rank correlation analysis was used to analyze the correlation of Aβ42 and NFL levels in the cerebrospinal fluid with MMSE scores. Receiver operating characteristic curve (ROC) was used to analyze the predictive value of cerebrospinal fluid Aβ42 and NFL levels for PNCD. PNCD occurred in 38 of the 90 elderly patients, with an incidence of 42.2%. The level of Aβ42 in the cerebrospinal fluid was significantly lower in PNCD group than in the nonPNCD group (1.96 vs 2.54 ng/mL; t=3.29, P < 0.05); the concentration of NFL in the cerebrospinal fluid was significantly higher in PNCD group than in non- PNCD group (4.59 vs 3.16 ng/mL; t=3.72, P < 0.05). Aβ42 level in the cerebrospinal fluid was positively correlated while NFL was negatively correlated with the MMSE score of the patients (r=-0.659, P < 0.05; r=-0.626, P < 0.05). ROC curve analysis showed that the area under the curve (AUC) of cerebrospinal fluid Aβ42 and NFL levels were 0.744 and 0.768, respectively; the AUC of their combination was 0.847 for prediction of PNCD. Elderly patients with PNCD have significantly higher levels of Aβ42 and NFL in the cerebrospinal fluid than those without PNCD. Both Aβ42 and NFL levels in the cerebrospinal fluid can help to predict the occurrence of POCD in elderly patients, and their combination has a higher diagnostic value.

Ispring platform for learning Russian as a foreign language

ABSTRACT This study examined the efficiency of teaching Russian as a foreign language (L2) in two groups of students – the first benefited from the e-learning platform’s capabilities (experimental), and the second underwent a traditional in-class course. Students learning Russian as L2 at People’s Friendship University of Russia (Moscow, Russia) were enrolled in the experiment. The research sample comprised 75 individuals distributed to three experimental groups and 33 individuals allocated to three control groups. All data obtained as a result of the study were statistically analyzed. In order to study the overall effect of using the iSpring platform, the research outcomes were combined by Stouffer’s Z-score method. Together with this, at each examination stage, repeated analysis of variance (ANOVA) was conducted. Students’ progress in learning Russian was evaluated by way of pre- and post-testing. After the experiment finished, all respondents were surveyed to analyze their perception of the effectiveness, convenience, and satisfaction of the chosen learning mode. The study found that students from experimental groups spent significantly more time for learning, demonstrating better performance. It was remarked that iSpring’s adaptive learning features contribute to improving students’ performance by encouraging them to learn better and faster.

Analysis Application of Altman (Z-Score) Method and Springate (S-Score) Method to Assess Financial Distress Potential at PT Anugerah

The emergence of potential financial distress is an early indication of a decline in the company's financial condition. The purpose of this research is to determine the potential of financial distress at PT Anugerah, so that it will help management anticipate the potential financial distress in the company. In this research, the assessment of financial distress potential uses the Altman (Z-score) method and Springate (S-score) method. The type of data in this research is quantitative and qualitative sourced from secondary data and obtained through interviews, documentation, and observation. The data analysis technique used is a qualitative/descriptive analysis technique. The results of research study are the financial distress potential of PT Anugerah by using the Altman (Z-score) method in 2016-2019 shows PT Anugerah is in a non-financial distress condition, because the score is in the condition of Z’’&gt; 2.6. Furthermore, PT Anugerah financial distress potential using the Springate (S-score) method in 2016-2019 shows that PT Anugerah is in a non-financial distress condition, because the score is at S &gt; 0.862.

DETERMINASI MODEL ALTMAN Z SCORE TERHADAP RETURN SAHAM

This research goal is to determine the effect of the company's bankruptcy rate using the Altman Z-Score method on stock returns in the property and real estate sub-sector companies for the 2015-2019 period. The research population was 69 companies and the sample was 16 properties and real estates listed on the Indonesia Stock Exchange. The method used in this research is the method of Hypothesis Testing. The analytical tool used is multiple linear regression analysis tested using Statistical Package for The Social Science (SPSS) version 25. This research uses secondary data, in the form of complete financial statements during the research period. The results showed that the variables proxy by Altman Z-Score, namely Working Capital to Total Assets, Retained Earning to Total Assets, Earning Before Interest and Taxes to Total Assets, and Book Value of Equity to Book Value of Total Liabilities had a positive and significant effect on stock returns.

Fast Ways to Detect Outliers

The occurrence of tremendous developments in the field of data has led to the formation of huge volumes of data, and it is normal that this leads to the presence of outliers in this data for many reasons, which may have small or large values ​​compared to the rest of the normal data, and the presence of outliers in the data affects the statistical analysis of this data, so we must try to reduce its impact in various ways. On the other hand, the presence of outliers ​​may be of great benefit, for example knowledge of geological activities that precede natural disasters such as (earthquakes, forest fires, floods ... etc.). Therefore, detection of outliers is of great importance in various fields. In this research, we aim to develop easy methods for detecting outliers in big data, as the problem that this research addresses is that many of the newly developed methods for detecting outliers suffer from computational complexity or are efficient when the sample size is small. An experimental approach was used in this research by suggesting three methods for detecting outliers, the first method is based on standard deviation and was tested and compared with the normal distribution method and the z-score method. The second method depends on the maximum and minimum value of the data, and the third method depends on the range between successive data points. The results of second and third methods are compared with Hample's Test method result. The accuracy of the results is measured based on the confusion matrix. The results of the proposed methods test showed the conformity of the first method with the results of the normal distribution method and the Z-Score method, as well as the superiority of the third method over the Hample's test method. In this paper, it was concluded that the Hample's test method suffers from a serious weakness when the zero values in the data constitute more than 50% of the number of elements.

ANALYSIS OF FINANCIAL STATEMENTS WITH ALTMAN Z-SCORE AND SPRINGATE MODELS ON PT. HERO SUPERMARKET, Tbk

The company was founded basically in the hope of generating profit, creating market segments or customers and carrying out development in products against the needs of the desired community. In fact, often these assumptions miss and are far from hopeful. Companies that have been doing activities for a certain time sometimes have to be liquidated due to financial difficulties and eventually go into bankruptcy. The threat of bankruptcy does not occur if the company conducts an analysis as early as possible using a company's financial statements. One method of analysis in predicting bankruptcy is the Altman Z-Score method and the Springate method. The purpose of this research is to find out the results of the prediction of potential bankruptcy PT. Hero, Tbk period 2016-2019 using Altman Z-Score and Springate models. Population in this study PT Financial Statements. Hero, Tbk, while the sample in this study is PT Financial Report. PT. Hero, Tbk Period 2016-2019.The results show pt. Hero Supermarket, Tbk based on the Altman Z-Score method, in 2016-2019 the company can be categorized as a company not bankrupt/ healthy company. Based on the Springate method in 2016 and 2019 the company is categorized as a company not bankrupt / healthy, while in 2017 and 2018 is predicted as a bankrupt company/unhealthy company.

Analisis Financial Distress Menggunakan Metode Altman Z–Score pada PT. Golden Plantation Tbk. Periode 2014-2018

The goal of this study is to decide how the effects of the analysis of predictions of financial distress using the Atlman Z-score method with estimates for the period 2014-2018 on PT Golden Plantation Tbk are determined. PT Golden Plantation, which is a business engaged in the oil palm plantation industry with the type of data used, is the focus of this study, namely quantitative data in the form of the financial statements of PT Golden Plantation for the period 2014 to 2018. And the Altman Z - Score Adjusted variable aproach is the data analysis method used in this study. It can be inferred that, based on the findings of the report, the organization started to encounter financial distress in 2014. In 2015 to 2018 the altman z - score of PT Golden Plantation was &lt;1.1 or a dangerous zone which means that PT Golden Plantation Tbk is in a bankrupt condition. And we can be sure that the company will also face financial problems in the next few years. This is attributable to the selection of debt used by the firm. The utilization of the company's existing debt tends to rise each year, exceeding the value of the company's current assets, so that the working capital of the company still has a negative variable. To Future research is suggested to add other variables in examining financial distress.

Financial Distress Analysis in an Indonesian Textile Company

This research aimed to examine the health of textile companies by using the Altman Z-Score method. The Altman model is used to determine the effect on financial distress through Working Capital to Total Asset (WCTA), Retained Earning to Total Asset (RETA), Earning Before Interest and Tax to Total Asset (EBITA), Market Value of Equity to Book Value of Liabilities (MVEBL) and Sales to Total Asset (STA). The population in this study was textile companies for the period 2016-2019. The sample was 14 textile companies with a research time of 4 years resulting in 56 samples obtained by purposive sampling. The results indicated that WCTA, RETA, EBITA, MVEBL and STA had a simultaneous effect on financial distress, but they had no effect separately.&#x0D; Keywords: Altman Z-Score, financial distress, bankruptcy

“Pulmonary dysfunction in children with Duchenne muscular dystrophy may appear earlier than we thought – analysis using novel methodology based on z-scores."

IntroductionRespiratory status is one of the main factors affecting the length of survival in patients with Duchenne muscular dystrophy (DMD) – the most common, severe, progressive muscular dystrophy.The aim: (1) to assess pulmonary function in DMD patients using the z-score method and (2) to identify factors affecting it, irrespective of the disease progress.Material and methodsWe evaluated 55 boys (aged 5 – 18 years) with DMD. The spirometry was performed with: forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), peak expiratory flow (PEF) analysis as absolute values (in litres or litres/min), % predicted value (%pv) and z-scores [z]. The need of ventilation support, ambulatory status, steroid therapy were collected.Results25(45%) subjects were non-ambulatory, 38(69%) used steroid therapy. Mean FVC[z] -2.4±2.2, FEV1[z] -2.0±1.9, PEF[z] -1.5±1.3 value significantly decrease with age (r=-0.62/-0.65/-0.55; p&lt;0.001 respectively), after reaching the peak values between 9-12 or 6-9 years of age depending on analysis method (absolute, %pv or z-score). The results fell below normal range (z-score&lt;-1.64) at the age of 9.8/10.4/11.6 years and below 80%pv at 10.7/13.2/13.2 for FVC/FEV1/PEF, respectively. The pulmonary function test results were significantly lower in non-ambulant (p&lt;0.001) and non-steroid patients (p&lt;0.02).ConclusionsAnalysis of pulmonary function test based on z-score shows that deterioration of pulmonary function in DMD males may appear earlier than we thought measured by %pv and absolute values. Early loss of ambulation, lack of or delayed steroid therapy are risk factors for worse pulmonary outcomes. To confirm these findings cohort longitudinal studies are necessary.

How does area-level deprivation depress an individual\u2019s self-rated health and life satisfaction? Evidence from a nationwide population-based survey in Japan

BackgroundArea-level deprivation is well known to have an adverse impact on mortality, morbidity, or other specific health outcomes. This study examined how area-level deprivation may affect self-rated health (SRH) and life satisfaction (LS), an issue that is largely understudied.MethodsWe used individual-level data obtained from a nationwide population-based internet survey conducted between 2019 and 2020, as well as municipality-level data obtained from a Japanese government database (N = 12,461 living in 366 municipalities). We developed multilevel regression models to explain an individual’s SRH and LS scores using four alternative measures of municipality-level deprivation, controlling for individual-level deprivation and covariates. We also examined how health behavior and interactions with others mediated the impact of area-level deprivation on SRH and LS.ResultsParticipants in highly deprived municipalities tended to report poorer SRH and lower LS. For example, when living in municipalities falling in the highest tertile of municipality-level deprivation as measured by the z-scoring method, SRH and LS scores worsened by a standard deviation of 0.05 (p < 0.05) when compared with those living in municipalities falling in the lowest tertile of deprivation. In addition, health behavior mediated between 17.6 and 33.1% of the impact of municipality-level deprivation on SRH and LS, depending on model specifications.ConclusionResults showed that area-level deprivation modestly decreased an individual’s general health conditions and subjective well-being, underscoring the need for public health policies to improve area-level socioeconomic conditions.

ANALISIS KOMPARASI POTENSI KEBANGKRUTAN PADA PERUSAHAAN HUAWEI TECHNOLOGIES DENGAN METODE ALTMAN Z – SCORE DAN ZMIJEWSKI X – SCORE

The purpose of this study is to know potential bankruptcy by using Altman Z-Score and Zmijewski X-Score method on Huawei Technologies company in 2014 – 2019 period. This study used two methods of bankruptcy prediction, they are Altman Z-Score and Zmijewski X-Score. The data used is the annual financial report of the Huawei Corporation at the website www. Investing.com. the study uses quantitative research and samples used in this study the Huawei company’s financial report period 2014-2019. The choice of that span is based on the opinion that, at this time, restrictions on huawei products are imposed by the United States Government. The study shows that since 2014-2019 after blocking of Huawei in America was healthy or did not have the potential for bankruptcy using the Altman Z-Score and Zmijewski X-Score.Keywords: Potential Bankruptcy, Method of Altman Z-Score, Method of Zmijewski X-Score

Inclusive Growth: Comprehensive Dimension of Income Distribution

The article aims to solve the problem of unequal income distribution in Malaysia. Income inequality did not change significantly since 1990. Inclusive growth is an alternative way that can help the government overcome the unequal distribution of income. However, there are no measurements or detailed studies conducted in Malaysia. Moreover, the country’s distribution policy for the 2016–2030 period focuses on inclusive economic growth. Based on the above gaps, we constructed the Malaysia Inclusive Index and estimated the income distribution using this new composite index. To construct the index, we applied the Z-score method. We obtained data for this study from the World Development Indicator, Economic Planning Unit, Department of Statistics, Malaysia and annual reports from various ministries. The main research findings show yearon-year growth from 1990 to 2016, indicating that economic growth in Malaysia is increasingly inclusive. Therefore, to achieve inclusive and equitable economic growth in distribution, the government is advised to consider not only fiscal aspects, but also holistic components comprised of education, health, housing and employment of the B40 group (lower class). Simultaneously, the M40 group (middle class) should not be left out. Income distribution factors and the Malaysia Inclusive Index (MII) determinants such as investment, inflation, education and national income should be considered when developing national distribution policies, as these factors are crucial for inclusive growth in Malaysia

Comparison of Min-Max normalization and Z-Score Normalization in the K-nearest neighbor (kNN) Algorithm to Test the Accuracy of Types of Breast Cancer

The purpose of this study was to examine the results of the prediction of breast cancer, which have been classified based on two types of breast cancer, malignant and benign. The method used in this research is the k-NN algorithm with normalization of min-max and Z-score, the programming language used is the R language. The conclusion is that the highest k accuracy value is k = 5 and k = 21 with an accuracy rate of 98% in the normalization method using the min-max method. Whereas for the Z-score method the highest accuracy is at k = 5 and k = 15 with an accuracy rate of 97%. Thus the min-max normalization method in this study is considered better than the normalization method using the Z-score. The novelty of this research lies in the comparison between the two min-max normalizations and the Z-score normalization in the k-NN algorithm.

The Accuracy of Financial Distress Measurement on Altman Z-Score, Grover, Springate, and Zmijewski Methods (Study on Companies in LQ-45 Index Listed in Indonesia Stock Exchange During the 2015 - 2019 Period)

The aim of this study is to identify the accuracy level of Altman Z-Score, Springate, Grover, and Zmijewski methods in predicting the financial distress condition and to see if there is distinctive result from each method in predicting potential financial distress. The population of this study comprised of the entire companies in LQ-45 index, listed in Indonesia Stock Exchange (BEI) during the 2015-2019 period. The technique in selecting the samples was purposive sampling. It was obtained from 28 companies in LQ-45 index during the 2015-2019 period. The technique analysis used in this research was paired sample t-test, which defined as a comparison of the significance of the four financial distress prediction methods that made of the company real condition. The result of the analysis indicated that there was a significant difference between several prediction methods of potential financial distress in LQ-45 index companies listed in Indonesia Stock Exchange (BEI), and it was unearthed by Grover prediction which showed the highest level of accuracy, in which the accuracy was at 100%, whilst the accuracy rate of the Springate method and the Altman Z-Score method are 96% and 75% respectively. Finally, Zmijewski's prediction method resulted an accuracy rate at 43%.