Valid Statistical Tests Research Articles

Towards Optimal Taxes: Impact of Tax Extensification and Intensification on Individual Income Tax Receipts

This study seeks to investigate the impact of tax extension and intensification on personal income tax collections. The sample was selected using a specific procedure to ensure that it was representative of the population; the sample size was 100 respondents. The data source employed is primary data, i.e., data collected directly from respondents via questionnaire by researchers. The methodology employed in this study is multiple linear analysis. In addition, descriptive statistical analysis, validity tests, reliability tests, normality tests, heteroscedasticity tests, multicollinearity tests, and hypothesis testing with the coefficient of determination test, t test, and f test were performed on the data. The results of the analysis indicate that Tax Extensification has a positive and significant impact on Individual Income Tax Receipts, while Tax Intensification has a similar effect.

Factors Affecting Taxpayer Compliance: A study during the Covid-19 Pandemic

The purpose of this study is to analyze whether aspects of the COVID-19 epidemic affect taxpayer compliance. The 92 MSME participants were all located in Jayapura City. Primary data, which is information collected by researchers through direct interaction with respondents, such as questionnaires, was used. In this study, multiple linear regression analysis was used. Data analysis was carried out through descriptive statistical tests, validity and reliability tests, normality and heteroscedasticity and multicollinearity tests, and hypothesis testing using the coefficient of determination, partial tests, and simultaneous tests. The results of this study indicate that tax knowledge, tax policy, attitudes, tax authorities' services, and the application of the self-assessment system are found to have a positive and statistically significant effect on taxpayer compliance. Taxpayer compliance among MSME players in Jayapura City is expected to increase if these elements are used more widely and effectively.

Development and Statistical Validation of E-Probe Diagnostic Nucleic Acid Analysis (EDNA) Assays for the Detection of Citrus Pathogens from Raw High-Throughput Sequencing Data

The cost for high-throughput sequencing (HTS) has decreased significantly and has made it possible for the application of this technology for routine plant diagnostics. There are constraints to the use of HTS as a diagnostic tool, including the need for dedicated personnel with a bioinformatic background for data analysis and the lack of a standardized analysis pipeline that makes evaluating and validating results generated at different HTS laboratories difficult. E-probe diagnostic nucleic acid analysis (EDNA) is an in-silico bioinformatic tool that utilizes short curated electronic probes (e-probes) designed from pathogen-specific sequences that allow users to detect and identify single or multiple pathogens of interest in raw HTS data sets. This platform streamlines the bioinformatic data analysis into a graphical user interface as a plant diagnostic tool used by diagnosticians. In this study, we describe the process for the development, validation, and use of e-probes for detection and identification of a wide range of taxonomically unique citrus pathogens that include citrus exocortis viroid, citrus tristeza virus, ‘ Candidatus Liberibacter asiaticus’, and Spiroplasma citri. We demonstrate the process for evaluating the analytical and diagnostic sensitivity and specificity metrics of the in-silico EDNA assays. In addition, we show the importance of including background noise (internal controls) to generate variance in noninfected samples for a valid statistical test using the quadratic discriminant analysis. The fully validated EDNA assays from this study can be readily integrated into existing citrus testing programs that utilize HTS. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Analysis of Factors Influencing the Use of Accounting Information in Small and Medium Enterprises at Palembang

This study aims to determine the analysis of factors affecting the accounting information utilization on small and medium enterprises in Palembang. The population in this study was the MSME manager of Palembang City. The sample collection method utilized Simple Random Sampling. The final total respondents were 100. The data were analyzed by descriptive statistical methods, validity tests, reliability tests, classical assumptions, and multiple regression analysis. The results of the study indicate that several factors influence the use of accounting information in small and medium businesses in Palembang, namely business scale has a significant effect on the use of accounting information. Then the age factor of the company, education, and accounting training also affect the use of accounting information. This research is expected to assist MSME to consider the factor that affects use the Accountant Information Application

On estimating the structure factor of a point process, with applications to hyperuniformity

Hyperuniformity is the study of stationary point processes with a sub-Poisson variance in a large window. In other words, counting the points of a hyperuniform point process that fall in a given large region yields a small-variance Monte Carlo estimation of the volume. Hyperuniform point processes have received a lot of attention in statistical physics, both for the investigation of natural organized structures and the synthesis of materials. Unfortunately, rigorously proving that a point process is hyperuniform is usually difficult. A common practice in statistical physics and chemistry is to use a few samples to estimate a spectral measure called the structure factor. Its decay around zero provides a diagnostic of hyperuniformity. Different applied fields use however different estimators, and important algorithmic choices proceed from each field’s lore. This paper provides a systematic survey and derivation of known or otherwise natural estimators of the structure factor. We also leverage the consistency of these estimators to contribute the first asymptotically valid statistical test of hyperuniformity. We benchmark all estimators and hyperuniformity diagnostics on a set of examples. In an effort to make investigations of the structure factor and hyperuniformity systematic and reproducible, we further provide the Python toolbox structure_factor, containing all the estimators and tools that we discuss.

Pengaruh Persepsi Return, Risiko, Pengetahuan dan Religiusitas Terhadap Minat Berinvestasi di Pasar Modal Syariah

In its development, the Islamic capital market in Indonesia has experienced various obstacles, especially during the Covid-19 pandemic that hit the world in recent years, which is thought to be the main cause due to the low level of knowledge of the Islamic capital market and public interest in the Islamic capital market. Therefore, the purpose of this study is to find out what factors are expected to influence the dependent variable, namely the interest in investing in the Islamic capital market, which includes perceived return, perceived risk, investment knowledge, and religiosity. This research is a type of quantitative research using primary data from research objects which are KSPM Ahmad Dahlan University (UAD) and Yogyakarta Muhammadiyah University (UMY) with a total sample of 60 respondents using a sampling technique that is simple random sampling. Tests carried out include descriptive statistical tests, validity and reliability tests, classical assumption tests, multiple linear regression tests, hypothesis testing (F test and t test), and test the coefficient of determination. Based on the results of this study, the results show that: Partially only the variable perceived return has a positive and significant effect on the dependent variable so that H1 is accepted, and for H2, H3, and H4 it is partially obtained that these variables have no effect on the dependen variable, therefore H2, H3, and H4 rejected..

DETERMINAN AUDIT JUDGMENT PADA AUDITOR PEMERINTAH

This study aims to determine the effect of audit experience, audit expertise, and task complexity on audit judgment. The research was conducted at Badan Pengawasan Keuangan dan Pembangunan (BPKP) Perwakilan Provinsi Kalimantan Barat. The data yang used in this study is the primary data in the form of questionnaire data. Audit experience, expertise, task complexity, and judgment are measured on a Likert score scale of 1-5. This research uses quantitative analysis methods, including descriptive statistical analysis, validity and reliability tests, classical assumption tests, multiple linear regression, T-tests, F tests, and coefficient of determination tests (R2). The results of this study show that audit experience and expertise do not affect audit judgment. Meanwhile, the complexity of the task affects the audit judgment.

The Effect of Service Quality and Product Attributes on Customer Loyalty

This study aims to examine and analyze the effect of service quality and product attributes on customer loyalty (Study on KFC Pengayoman in Makassar). The population in this study are residents in Makassar who are KFC consumers. The sampling method used by the researchers in this study was the proportional Stratified Random Sampling method and a total sample of 70 people was obtained. The type of data used is primary data collected by distributing questionnaires to all respondents. The data in this study will be tested with several stages of testing, namely descriptive statistical tests, validity and reliability tests, classical assumption tests consisting of (normality test, heteroscedasticity test, multicollinearity test) as well as testing all hypotheses through a coefficient of determination test, partial test (test t) and simultaneous test (test f). The results of this study indicate that the service quality variable has no significant effect on customer loyalty at KFC Pengayoman in Makassar. While product attribute variables have a significant effect on customer loyalty at KFC Pengayoman in Makassar. And product attributes are the most dominant variable affecting customer loyalty at KFC Pengayoman Makassar because it has a higher coefficient value and a better significant level than other variables.

Improving Brand Image of Television Electronic Products Through Integrated Marketing Communications

This study aims to examine and analyze the effect of integrated marketing communications (advertising, sales promotion, public relations, personal selling, direct & online marketing) on ​​the brand image of electronic television products. The population in this study were 2,576 customers or users of the 2018 Panasonic brand television. To determine the number of samples, the Slovin formula was used and 100 people were obtained spread across the city of Makassar. The data in this study used primary data collected by distributing questionnaires to all respondents. The data in this study will be tested with several stages of testing, namely descriptive statistical tests, validity and reliability tests and testing of all hypotheses through the coefficient of determination test, partial test (t test) and simultaneous test (f test). The results of this study indicate that the variables of advertising, promotion, public relations, personal selling and direct & online marketing have a positive and significant effect on the brand image of television electronic products at PT. Panasonic Goblet. And based on the test results on all variables in the integrated marketing communication program, the promotion variable has the most dominant value influencing the brand image of television electronic products at PT. Panasonic Goblet.

The Effect of Marketing Mix Strategy on Increasing Sales Volume of Silk Cloth

This study aims to examine and analyze the influence of the marketing mix strategy consisting of (product, price, place and promotion) on the increase in sales volume of silk fabrics to Silk Craftsmen of BNI Sengkang Village, Wajo Regency. The population in this study is all people who use or buy silk cloth products from silk craftsmen in Kampung BNI Sengkang, Wajo Regency. The number of samples used in this study were 100 people. The data in this study used primary data obtained by distributing questionnaires to all respondents and through direct interviews with consumers. The data in this study will be tested with several stages of testing, namely descriptive statistical tests, validity and reliability tests and testing of all hypotheses through the coefficient of determination test, partial test (t test) and simultaneous test (f test). The results of this study indicate that the marketing mix consisting of the 4Ps (product, price, place, promotion) has a positive and significant effect on increasing silk sales to Silk Craftsmen of BNI Sengkang Village, Wajo Regency. Among the marketing mix, the price strategy has the most dominant influence on silk sales to Silk Craftsmen of BNI Sengkang Village, Wajo Regency, based on the results of statistical analysis, the value of the regression coefficient shows the highest value among the other independent variables.

Can Audit Fees and Auditor Competence Affect Auditor Motivation?

The purpose of this study was to determine and analyze the effect of audit fees and auditor competence on auditor motivation at the Public Accounting Firm (KAP) in Makassar city. The population in this study were all auditors who worked at KAP in Makassar, totaling 48 auditors. The sample selection was carried out using the census method, in which all members of the population were used as samples. The data used in this study are primary data collected by distributing questionnaires to all respondents, with data analysis techniques that will be carried out namely descriptive statistical tests, validity and reliability tests, classical assumption tests, multiple linear regression analysis and hypothesis testing which consists of testing partial (t test) and simultaneous test (f test). The results of the study show that audit fees have a positive and significant effect on auditor motivation. This indicates that the greater the fee received by an auditor, the more motivated he is in carrying out his duties. Meanwhile, auditor competence has a negative and significant effect on auditor motivation at the Public Accounting Firm in Makassar city

Detection and classification of anxiety in university students through the application of machine learning

Mental Health has recently transformed into a domain that caused interest in almost every field and has garnered attention in recent years, millions of people suffer due to mental illnesses that are often left unaccounted for, a vast majority of these people are youngsters, a large chunk being students belonging to various universities. This research's aim was to pinpoint the extent of anxiety, in conjunction, its effects, as noticed in Indian university students. The dataset was gathered using a questionnaire, that was matching with Likert scale measurement criteria, which consisted of university engineering students. This questionnaire was distributed amongst 127 engineering students, as a result, the level of anxiety was quantified, and its causes and effects were identified, a series of statistical reliability and validity tests were performed on the dataset. Machine learning algorithms are applied in the end to classify the anxiety level based on the effects of anxiety after being trained on pre-existing data points. It was found that the Cronbach's alpha value for the entire dataset was 0.723 and Pearson's correlation coefficient was 0.823, the accuracy for the naïve bayes, decision tree, random forest and support vector machine algorithms were 71.05%, 71.05%, 78.9% and 75.5% respectively.

Improving the Validity of Scientific Research Results through Research Methodology Management

This article discusses the importance of research methodology management in enhancing the validity of scientific research findings. Validity refers to the accuracy and soundness of research findings and is a key element in determining the reliability and confidence of research outcomes. Research methodology management is a structured and organized approach to designing, collecting, analyzing, and reporting research data. In this article, the author highlights several strategies that can be used to improve the validity of research findings. Firstly, careful planning and appropriate selection of research methods are crucial. It involves a deep understanding of the research subject, the targeted population, and clear research objectives. Representative sampling techniques and adequate sample sizes should also be considered. Secondly, meticulous and consistent data collection is an important step in enhancing validity. Using valid and reliable measurement instruments and adequate training for researchers can help minimize errors and biases in data collection.Furthermore, proper data analysis and applying relevant statistical methods are highly important. The chosen analysis methods should align with the type of collected data and the research questions being addressed. Using valid statistical testing techniques and implementing control measures to address biases should also be considered. Lastly, transparent and accurate reporting of research findings is crucial in improving validity. The research results should be presented clearly and objectively, encompassing all significant aspects of the study. Additionally, prioritizing research reproducibility by providing sufficient detail about the utilized methodology is essential. Research methodology management plays a vital role in enhancing the validity of scientific research findings. Researchers can ensure their results are highly valid by implementing a structured approach and addressing the above aspects. It will increase confidence and the practical and scientific application of research findings.

Evaluasi Konsep Value for Money terhadap Penilaian Kinerja Pelayanan Sektor Publik

This study aims to determine the effect of efficiency and effectiveness on the performance of public sector services of the Gadingan Village Government in 2020. This research is quantitative. A sample of 100 respondents. Data collection techniques through surveys by distributing questionnaires to respondents to be targeted. Data analysis methods include descriptive statistical analysis, validity, reliability, and classical assumption tests. The results showed that 1) economic elements, efficiency, and effectiveness simultaneously as elements of value for money affect the performance of public sector services, 2) economic elements partially as one of the elements of value for money affect the performance of public sector services in the Gadingan Village Head's Office, 3) the element of efficiency partially as one of the elements of value for money affects the performance of public sector services in the Village Head's Office Gadingan, and 4) the element of partial effectiveness as one of the elements of value for money affects the performance of public sector services in the Gadingan Village Head's Office

Pengaruh Pajak Pertambahan Nilai dan Pajak Kendaraan Bermotor Tarif Progresif terhadap Daya Beli Konsumen

This study aims to determine the effect of Value Added Tax and Progressive Tariff Motor Vehicle Tax on Consumer Purchasing Power. This research was conducted at SAMSAT Bekasi City in 2021. The quantitative research method with a sample of 100 respondents was obtained through the slovin technique. The data analysis technique used descriptive statistical analysis, validity and reliability tests, multiple linear regression, coefficient of determination and hypothesis testing. For quantitative data analysis method, SPSS version 25 is used. Based on the results of the analysis, it is stated that the value added tax has a significant effect on consumer purchasing power with a significance level of 0.043 which is smaller than = 0.05. The progressive rate motor vehicle tax has a significant effect on consumer purchasing power with a significance level of 0.000 which is smaller than = 0.05.

The Garbage Class Mixed Logit Model: Accounting for Low-Quality Response Patterns in Discrete Choice Experiments

ObjectivesTo introduce the garbage class mixed logit (MIXL) model as a convenient alternative to manually screening and accounting for respondents with low data quality in discrete choice experiments. MethodsGarbage classes are typically used in latent class logit analyses to designate or identify group(s) of respondents with low data quality. Yet, the same concept can be applied to MIXL models as well. ResultsBased on a reanalysis of 4 discrete choice experiments that were originally analyzed using a standard MIXL model, it is shown that garbage class MIXL models can achieve the same effect as manually screening for (and excluding) respondents with low data quality based on the more commonly used root likelihood test, but with less effort and ambiguity. ConclusionsIncluding a garbage class in MIXL models removes the influence of respondents with a random choice pattern from the MIXL model estimates, provides an estimate of the number of low-quality respondents in the dataset, and avoids having to manually screen for respondents with low data quality based on internal or statistical validity tests. Although less versatile than the combination of standard MIXL estimates with separate assessments of data quality and sensitivity analyses, the proposed garbage class MIXL model provides an attractive alternative.

The Natural Product Domain Seeker version 2 (NaPDoS2) webtool relates ketosynthase phylogeny to biosynthetic function

The Natural Product Domain Seeker (NaPDoS) webtool detects and classifies ketosynthase (KS) and condensation domains from genomic, metagenomic, and amplicon sequence data. Unlike other tools, a phylogeny-based classification scheme is used to make broader predictions about the polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) genes in which these domains are found. NaPDoS is particularly useful for the analysis of incomplete biosynthetic genes or gene clusters, as are often observed in poorly assembled genomes and metagenomes, or when loci are not clustered, as in eukaryotic genomes. To help support the growing interest in sequence-based analyses of natural product biosynthetic diversity, here we introduce version 2 of the webtool, NaPDoS2, available at http://napdos.ucsd.edu/napdos2. This update includes the addition of 1417 KS sequences, representing a major expansion of the taxonomic and functional diversity represented in the webtool database. The phylogeny-based KS classification scheme now recognizes 41 class and subclass assignments, including new type II PKS subclasses. Workflow modifications accelerate run times, allowing larger datasets to be analyzed. In addition, default parameters were established using statistical validation tests to maximize KS detection and classification accuracy while minimizing false positives. We further demonstrate the applications of NaPDoS2 to assess PKS biosynthetic potential using genomic, metagenomic, and PCR amplicon datasets. These examples illustrate how NaPDoS2 can be used to predict biosynthetic potential and detect genes involved in the biosynthesis of specific structure classes or new biosynthetic mechanisms.

Compressive Strength of Steel Fiber-Reinforced Concrete Employing Supervised Machine Learning Techniques.

Recently, research has centered on developing new approaches, such as supervised machine learning techniques, that can compute the mechanical characteristics of materials without investing much effort, time, or money in experimentation. To predict the 28-day compressive strength of steel fiber–reinforced concrete (SFRC), machine learning techniques, i.e., individual and ensemble models, were considered. For this study, two ensemble approaches (SVR AdaBoost and SVR bagging) and one individual technique (support vector regression (SVR)) were used. Coefficient of determination (R2), statistical assessment, and k-fold cross validation were carried out to scrutinize the efficiency of each approach used. In addition, a sensitivity technique was used to assess the influence of parameters on the prediction results. It was discovered that all of the approaches used performed better in terms of forecasting the outcomes. The SVR AdaBoost method was the most precise, with R2 = 0.96, as opposed to SVR bagging and support vector regression, which had R2 values of 0.87 and 0.81, respectively. Furthermore, based on the lowered error values (MAE = 4.4 MPa, RMSE = 8 MPa), statistical and k-fold cross validation tests verified the optimum performance of SVR AdaBoost. The forecast performance of the SVR bagging models, on the other hand, was equally satisfactory. In order to predict the mechanical characteristics of other construction materials, these ensemble machine learning approaches can be applied.

A STUDY ON CUSTOMER SATISFICATION TOWARD ARAVIND MILK FOOD PRODUCTS

Dairy products have become inevitable of habitual diet. This study aims to investigate the consumers’ satisfaction towards dairy products so as to provide useful information for the manufacturers which would serve as useful inputs for enriching the quality of products delivered. The study involved consumers of dairy products from various demographical backgrounds across South India. The questionnaire focussed on quality aspects of dairy products and also the service provided. A customer satisfaction model was developed based on various factors identified, with robust hypotheses that govern the use of the product. The developed model proved to be statistically significant as it passed the required statistical tests for reliability, construct validity and interdependency between the constructs. Some major concerns detected were regarding the fat content, taste and odor of packaged milk. A minor proportion of people (15.64%) were unsatisfied with the quality of service provided, which is another issue to be addressed to eliminate the sense of dissatisfaction in the minds of consumers.

Analisis Faktor Keputusan Mahasiswa Dalam Memilih Belajar di Fakultas Ekonomi Universitas Darma Persada

The Faculty of Economics, Darma Persada University (FE Unsada) is higher education institution’s unit, that aims to prepare skilled professionals educated in the fields of economics, business and accounting, by specifically adding Japanese-style management knowledge as a reference from developed countries in the fields of economy, industry and technology, which is expected to provide special characteristics and added value in learning to attract students' interest, compared to those offered by other similar higher education institutions as competitors.
 However, in its progress over the last two years (2018-2020), there has been a decrease in the number of students who are interested in studying at FE Unsada. So, through this research, it is expected to be able to find out and measure the dominant factors that are taken into consideration by students choosing to study at FE Unsada, so that further anticipation can be done to decrease the number of students and restore increased interest of students through attractive strategy programs and answer the needs and expectations of students.
 This research was conducted with a quantitative descriptive method, factor analysis through a series of statistical validity tests and values tests, using a questionnaire technique with a random sample of 126 students of FE Unsada class 2016-2020, where from the results of the study it was found that there were three main factors that formed the choice of students to study at FE Unsada, namely: 1. Campus Reputation (36.49%), 2. Social Environment Influences (12.12%), 3. Socio-economic Status (9.72%).
 
 Keywords : Factor analysis; Student intention; Economic Faculty; Consumer Behavior.