Transparent Reporting Research Articles

Analysis of the Presentation of Financial Statements and the Morality of Apparatus on the Potential of Fraud in Village Financial Management

Referring to Permendagri (Minister of Home Affairs Regulation) No. 20 of 2018, the presentation of transparent and accountable financial reports can serve as a deterrent against fraud in village funds. Furthermore, the moral support of village officials can aid in the proper management of funds in accordance with the provisions outlined in Permendagri. Thus, the presentation of financial reports is expected to provide accurate information and assist users in their decision-making processes. The research method employed in this study is a case study with a descriptive analysis approach. Nonprobability sampling with saturated samples is utilized as the sampling technique. Data collection techniques involve observation, in-depth interviews, and documentation. The results indicate that the presentation of financial statements in Karyalaksana Village and Lampegan Village is considered satisfactory. Similarly, the level of moral conduct among the village officials ranges from conventional to post-conventional, thereby reducing the potential for fraud in village financial management.
 Keywords: financial statement presentation, morality, fraud potential

Open science practices need substantial improvement in prognostic model studies in oncology using machine learning

ObjectiveTo describe the frequency of open science practices in a contemporary sample of studies developing prognostic models using machine learning methods in the field of oncology. Study design and settingWe conducted a systematic review, searching the MEDLINE database between December 1, 2022, and December 31, 2022, for studies developing a multivariable prognostic model using machine learning methods (as defined by the authors) in oncology. Two authors independently screened records and extracted open science practices. ResultsWe identified 46 publications describing the development of a multivariable prognostic model. The adoption of open science principles was poor. Only one study reported availability of a study protocol, and only one study was registered. Funding statements and conflicts of interest statements were common. Thirty-five studies (76%) provided data sharing statements, with 21 (46%) indicating data were available on request to the authors and seven declaring data sharing was not applicable. Two studies (4%) shared data. Only 12 studies (26%) provided code sharing statements, including 2 (4%) that indicated the code was available on request to the authors. Only 11 studies (24%) provided sufficient information to allow their model to be used in practice. The use of reporting guidelines was rare: eight studies (18%) mentioning using a reporting guideline, with 4 (10%) using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis Or Diagnosis statement, 1 (2%) using Minimum Information About Clinical Artificial Intelligence Modeling and Consolidated Standards Of Reporting Trials-Artificial Intelligence, 1 (2%) using Strengthening The Reporting Of Observational Studies In Epidemiology, 1 (2%) using Standards for Reporting Diagnostic Accuracy Studies, and 1 (2%) using Transparent Reporting of Evaluations with Nonrandomized Designs. ConclusionThe adoption of open science principles in oncology studies developing prognostic models using machine learning methods is poor. Guidance and an increased awareness of benefits and best practices of open science are needed for prediction research in oncology.

Models and Approaches for Comprehension of Dysarthric Speech Using Natural Language Processing: Systematic Review.

Speech intelligibility and speech comprehension for dysarthric speech has attracted much attention recently. Dysarthria is characterized by irregularities in the speed, strength, pitch, breath control, range, steadiness, and accuracy of muscle movements required for articulatory aspects of speech production. This study examined the contributions made by other studies involved in dysarthric speech comprehension. We focused on the modes of meaning extraction used in generalizing speaker-listener underpinnings in light of semantic ontology extraction as a desired technique, applied method types, speech representations used, and databases sourced from. This study involved a systematic literature review using 7 electronic databases: Cochrane Database of Systematic Reviews, Web of Science Core Collection, Scopus, PubMed, ACM, IEEE Xplore, and Google Scholar. The main eligibility criterion was the extraction of meaning from dysarthric speech using natural language processing or understanding approaches to improve on dysarthric speech comprehension. In total, out of 834 search results, 30 studies that matched the eligibility requirements were acquired following screening by 2 independent reviewers, with a lack of consensus being resolved through joint discussion or consultation with a third party. In order to evaluate the studies' methodological quality, the risk of bias assessment was based on the Cochrane risk-of-bias tool version 2 (RoB2) with 23 of the studies (77%) registering low risk of bias and 7 studies (33%) raising some concern over the risk of bias. The overall quality assessment of the study was done using TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis). Following a review of 30 primary studies, this study revealed that the reviewed studies focused on natural language understanding or clinical approaches, with an increase in proposed solutions from 2020 onwards. Most studies relied on speaker-dependent speech features, while others used speech patterns, semantic knowledge, or hybrid approaches. The prevalent use of vector representation aligned with natural language understanding models, while Mel-frequency cepstral coefficient representation and no representation approaches were applied in neural networks. Hybrid representation studies aimed to reconstruct dysarthric speech or improve comprehension. Comprehensive databases, like TORGO and UA-Speech, were commonly used in combination with other curated databases, while primary data was preferred for specific or unique research objectives. We found significant gaps in dysarthric speech comprehension characterized by the lack of inclusion of important listener or speech-independent features in the speech representations, mode of extraction, and data sources used. Further research is therefore proposed regarding the formulation of models that accommodate listener and speech-independent features through semantic ontologies that will be useful in the inclusion of key features of listener and speech-independent features for meaning extraction of dysarthric speech.

Could Accountant Be Facilitator To Zero Net Emission Programs?

The study aims to highlight the role of accountants in supporting and facilitating the implementation of the Net Zero Emission Programme in Indonesia with a focus on emission measurement and reporting, sustainable financial management, related audits and verification, as well as its impact on environmental sustainability and the achievement of climate change targets. The research is based on a qualitative approach of literature review using data in the form of annual reports and sustainability reports from mining companies in 2022 as well as from various related research journals. The results of this study show that accountants have a key role to play in helping companies and organizations achieve zero emission targets while ensuring compliance with relevant regulations. They can also help in measuring the financial impact of sustainability initiatives and make transparent reports to stakeholders.

Increased endorsement of TRIPOD and other reporting guidelines by high impact factor journals: survey of instructions to authors

ObjectivesTo assess the endorsement of reporting guidelines by high impact factor journals over the period 2017–2022, with a specific focus on the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement. Study Design and SettingWe searched the online ‘instructions to authors’ of high impact factor medical journals in February 2017 and in January 2022 for any reference to reporting guidelines and TRIPOD in particular. ResultsIn 2017, 205 out of 337 (61%) journals mentioned any reporting guideline in their instructions to authors and in 2022 this increased to 245 (73%) journals. A reference to TRIPOD was provided by 27 (8%) journals in 2017 and 67 (20%) in 2022. Of those journals mentioning TRIPOD in 2022, 22% provided a link to the TRIPOD website and 60% linked to TRIPOD information on the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Network website. Twenty-five percent of the journals required adherence to TRIPOD. ConclusionAbout three-quarters of high-impact medical journals endorse the use of reporting guidelines and 20% endorse TRIPOD. Transparent reporting is important in enhancing the usefulness of health research and endorsement by journals plays a critical role in this.

Validity of Clinical Severity Scores for Respiratory Syncytial Virus: A Systematic Review.

Respiratory syncytial virus (RSV) is a widespread respiratory pathogen, and RSV-related acute lower respiratory tract infections are the most common cause of respiratory hospitalization in children <2 years of age. Over the last 2 decades, a number of severity scores have been proposed to quantify disease severity for RSV in children, yet there remains no overall consensus on the most clinically useful score. We conducted a systematic review of English-language publications in peer-reviewed journals published since January 2000 assessing the validity of severity scores for children (≤24 months of age) with RSV and/or bronchiolitis, and identified the most promising scores. For included articles, (1) validity data were extracted, (2) quality of reporting was assessed using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis checklist (TRIPOD), and (3) quality was assessed using the Prediction Model Risk Of Bias Assessment Tool (PROBAST). To guide the assessment of the validity data, standardized cutoffs were employed, and an explicit definition of what we required to determine a score was sufficiently validated. Our searches identified 8541 results, of which 1779 were excluded as duplicates. After title and abstract screening, 6670 references were excluded. Following full-text screening and snowballing, 32 articles, including 31 scores, were included. The most frequently assessed scores were the modified Tal score and the Wang Bronchiolitis Severity Score; none of the scores were found to be sufficiently validated according to our definition. The reporting and/or design of all the included studies was poor. The best validated score was the Bronchiolitis Score of Sant Joan de Déu, and a number of other promising scores were identified. No scores were found to be sufficiently validated. Further work is warranted to validate the existing scores, ideally in much larger datasets.

Analisis Penerapan Akuntansi Isak 35 Pada Organisasi Keagamaan (Studi Kasus 5 Masjid Di Kabupaten Labuhanbatu Selatan)

This research aims to analyze the application of ISAK 35 accounting standards in religious organizations by taking case studies of five mosques in South Labuhanbatu Regency. ISAK 35 is an accounting standard that regulates the recognition, measurement, and placement of transactions and events in hazardous organizations. In the context of religious organizations, namely mosques, the implementation of ISAK 35 has an important importance in ensuring transparency and accountability in financial management. This research uses a qualitative approach with a case study method. Primary data was collected through in-depth interviews with mosque administrators and related financial staff. Secondary data was obtained through literature and documentation studies related to the implementation of ISAK 35 in religious organizations. The research results show that five mosques located in South Labuhanbatu Regency still have not implemented the ISAK 35 standard in preparing their financial reports. This shows that there are deficiencies in the presentation and delivery of financial information in accordance with applicable accounting standards. This research provides an overview of the importance of implementing ISAK 35 standards in producing more transparent, accurate and trustworthy financial reports for mosques in the region. These factors include limited knowledge and understanding of ISAK 35 by mosque administrators, a lack of human resources skilled in accounting, and a lack of support from external parties such as local governments or financial supervisory bodies.

Prognostic prediction models for oropharyngeal squamous cell carcinoma (OPSCC): a protocol for systematic review, critical appraisal and meta-analysis

IntroductionOropharyngeal squamous cell carcinoma (OPSCC) is increasingly prevalent and has significantly heterogeneous risks of survival for diagnosed individuals due to the inter-related risk factors. Precise prediction of the risk of...

Menakar Transparansi Keuangan Partai Politik Pada Pelaksanaan Pemilihan Umum

To support the implementation of the implementation of political party activities cannot be separated from the existence of large financial support. In the process of traveling political parties, political party funds come from contributions from party politicians, legitimate contributions in accordance with legal provisions; as well as financial assistance from the APBN and APBD from the government. Through the funds generated, an accountable and transparent report is needed to the public in order to create legal certainty and prevent acts of corruption originating from the party's funds. So through this research the authors underline the 2 (two) formulation of the problem that is important to be discussed. First, what is the urgency of disclosing political party financial information in preventing cultural practices of corruption in Indonesia? And Second, how is the accountability of political party financial funds sourced from APBN and APBD funds in Indonesia? This research uses the type of normative juridical research. The data used in the research comes from primary legal materials, secondary legal materials and literature studies from various literatures. The results of this study note that the form of political party financial reporting must record all sources of receipt of funds for the party and not only be accountable for funds originating from the APBN and APBD, then with regard to sanctions there must be strict action taken by the government not only the imposition of administrative sanctions imposed against a party.

APPRAISE-AI Tool for Quantitative Evaluation of AI Studies for Clinical Decision Support

Artificial intelligence (AI) has gained considerable attention in health care, yet concerns have been raised around appropriate methods and fairness. Current AI reporting guidelines do not provide a means of quantifying overall quality of AI research, limiting their ability to compare models addressing the same clinical question. To develop a tool (APPRAISE-AI) to evaluate the methodological and reporting quality of AI prediction models for clinical decision support. This quality improvement study evaluated AI studies in the model development, silent, and clinical trial phases using the APPRAISE-AI tool, a quantitative method for evaluating quality of AI studies across 6 domains: clinical relevance, data quality, methodological conduct, robustness of results, reporting quality, and reproducibility. These domains included 24 items with a maximum overall score of 100 points. Points were assigned to each item, with higher points indicating stronger methodological or reporting quality. The tool was applied to a systematic review on machine learning to estimate sepsis that included articles published until September 13, 2019. Data analysis was performed from September to December 2022. The primary outcomes were interrater and intrarater reliability and the correlation between APPRAISE-AI scores and expert scores, 3-year citation rate, number of Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) low risk-of-bias domains, and overall adherence to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statement. A total of 28 studies were included. Overall APPRAISE-AI scores ranged from 33 (low quality) to 67 (high quality). Most studies were moderate quality. The 5 lowest scoring items included source of data, sample size calculation, bias assessment, error analysis, and transparency. Overall APPRAISE-AI scores were associated with expert scores (Spearman ρ, 0.82; 95% CI, 0.64-0.91; P < .001), 3-year citation rate (Spearman ρ, 0.69; 95% CI, 0.43-0.85; P < .001), number of QUADAS-2 low risk-of-bias domains (Spearman ρ, 0.56; 95% CI, 0.24-0.77; P = .002), and adherence to the TRIPOD statement (Spearman ρ, 0.87; 95% CI, 0.73-0.94; P < .001). Intraclass correlation coefficient ranges for interrater and intrarater reliability were 0.74 to 1.00 for individual items, 0.81 to 0.99 for individual domains, and 0.91 to 0.98 for overall scores. In this quality improvement study, APPRAISE-AI demonstrated strong interrater and intrarater reliability and correlated well with several study quality measures. This tool may provide a quantitative approach for investigators, reviewers, editors, and funding organizations to compare the research quality across AI studies for clinical decision support.

Bankruptcy prediction with low-quality financial information

The corporate bankruptcy prediction literature has traditionally relied on data from public, audited companies. However, the vast majority of firms worldwide are privately-held and lack the same level of scrutiny over their financial statements. As a result, these businesses usually produce less accurate and transparent accounting reports. Our research problem is to address this gap: how stakeholders deal with these less reliable information? Using a novel dataset of 503 private firms that filed for reorganization in Brazil between 2007 and 2020, we found that financial ratios had a significantly lesser effect on explaining default and bankruptcy than what previous research suggested, due in part to the lower information content in the accounting statements within our database. Instead, lenders seem to focus on harder-to-conceal variables, such as collateralizable assets, as well as on institutional factors, like proxies of financial statement quality. There is also concerning evidence that specialized attorneys can ”work the system” in favor of distressed companies regardless of their financial fundamentals. Additionally, we found that machine learning models outperformed traditional statistical ones in different sorts of metrics, corroborating the literature on the superior performance of non-linear approaches on datasets having synergistic causality among its features.

Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis.

Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis.

Development of the TrAnsparent ReportinG of observational studies Emulating a Target trial (TARGET) guideline

BackgroundObservational studies are increasingly used to inform health decision-making when randomised trials are not feasible, ethical or timely. The target trial approach provides a framework to help minimise common biases...

Abstract P301: Predicting Complete Resolution Of Hypertension After Adrenalectomy In Primary Aldosteronism: A Systematic Review And Meta-analysis Of Prognostic Models. Surgical Outcome of PRimary Aldosteronism progNostic mOdels (SOPRANO) Study

Background: Unilateral primary aldosteronism (PA) is the most common surgically curable form of hypertension, despite complete clinical success after adrenalectomy being far from certain. Several presurgical factors were associated with complete resolution of hypertension (CRH). However, it remains unclear which of the available prognostic models combining those factors can be used in clinical practice to predict blood pressure-related outcomes after surgery for PA. Objectives: To identify, describe and appraise all prognostic models developed to predict CRH, and meta-analyse their predictive performances. Methods: We searched MEDLINE, Embase, and Web of Science, for development and validation studies of prognostic models according to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) statement. The quality assessment used adapted TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) and PROBAST (Prediction model Risk Of Bias ASsessment Tool) criteria. After selection, we extracted descriptive statistics and aggregated area under the receiver operator curve (AUC) using meta-analysis. Results: From 25 eligible studies, we identified 12 prognostic models used for predicting CRH after total adrenalectomy in PA. We report the results for three models that had available data from at least three external validation studies: the Primary Aldosteronism Surgical Outcome (PASO) score (AUC: 0.81; 95% confidence interval [CI]: 0.74–0.86; 95% predictive interval [PI]: 0.04–1.00), Utsumi nomogram (AUC: 0.79; 95% CI: 0.72–0.85; 95% PI: 0.03–1.00), and the Aldosteronoma Resolution Score (ARS) model (AUC: 0.77; 95% CI: 0.74–0.80; 95% PI: 0.59–0.86 for all studies and AUC: 0.80; 95% CI: 0.75–0.85; 95% PI: 0.57–0.93 for the studies with the same adrenal vein sampling-guided adrenalectomy rate compared to the models meta-analyzed). Conclusions: The PASO score, Utsumi nomogram, and ARS model showed good and comparable discrimination performance to predict CRH after unilateral adrenalectomy in PA. However, unlike the ARS model, the number of external validation studies for the PASO score and the Utsumi nomogram was relatively low to draw definite conclusions.

Influence of Audit Committee Meetings on the Quality of Audit Reports of Saccos in Homabay County, Kenya

Every operating organization keeps tabs on its development by producing accurate financial statements at the conclusion of each fiscal year, which are subsequently distributed to various individual users who are concerned with the organization's development. The audit procedure then confirms the accuracy of the financial accounts, and the audit committee then provides the specific business with a transparent audit report to seal the deal. The main objective of this study was to examine the influence of audit committee meetings on the quality of audit reports at Sacco’s in Homabay County, Kenya. This was supported by the fact that there are numerous Sacco’s in Homabay County, many of which had apparently experienced audit problems in the past. The institutional theory served as the study's compass. This study adopted a descriptive causal research design; the target population was 104 audit committee members of deposit taking Sacco’s in Homabay County as of December 2021. Out of the target population determined using the Krejcie and Morgan formula, 82 members of the audit committee provided responses for the study. Primary data was collected using a research questionnaire that involved the drop-and-pick method. Descriptive statistics, including a frequency table, mean, and standard deviation, were used for data analysis, while inferential statistics included Pearson’s correlation analysis. The study found that audit committee meetings in Homabay County, Kenya, had a positive and significant impact on the caliber of audit reports on Sacco’s (r = 0.568, p&lt;0.05). The study recommends that Sacco’s audit committee members should conduct the maximum number of meetings as much as they can. In extension, those meetings should be objectively aimed at attaining quality audits.

An investigation of the Iranian audit firms’ transparency: evidence from an Islamic context

Purpose This study aims to investigate factors that drive or deter audit firms (AFs) from disclosing audit quality (AQ) information to stakeholders in Iran. Furthermore, information items that should be contained in their disclosures are examined. Design/methodology/approach The study followed an interpretive approach. In this regard, 21 semi-structured and face-to-face interviews were conducted to explore the viewpoints of audit partners and investment managers. Interviewees were selected by snowball sampling method. The transcripts of audio records were prepared, and a thematic perspective was applied to evaluate transcriptions. Findings Participants’ interpretations indicate that certain factors, such as signaling to stakeholders, active audit committees and investor demand, promote transparency among Iranian AFs. Nonetheless, this inclination is deterred by some concerns, including poor AQ, lack of financial resources, lack of legal enforcement, fear of raising stakeholders’ expectations, inactive professional associations and contextual factors which should be addressed. Interviewees believe five items should be contained in AFs’ disclosures to enhance transparency. Practical implications This study contributes to recognizing factors explaining AFs’ behavior in the context of an Islamic country. Furthermore, the type of disclosure that should be contained can provide good insight for standard setters or oversight bodies. Originality/value The semi-structured interviews shed light on the contextual factors that influence transparency within the accountancy profession, either enabling or hindering it. Additionally, it is crucial to consider each country’s unique characteristics when determining the disclosure items in transparency reports.

Financial Information System in Increasing Organizational Stability (Case Study on Ar-Ruhama Organized Foundation)

The current development of Information Technology has increased the need for effective and efficient financial transaction recording. Yatim Piatu Ar-Ruhama Foundation needs to have a financial information system that can assist in managing and reporting their finances. This research aims to develop a Financial Information System to enhance the organization's stability of Ar-Ruhama Foundation. The research methodology includes software requirement analysis, such as budget management, financial transaction recording, financial reporting, donation management, and data security. This Financial Information System will enable the foundation to record financial transactions, manage budgets, generate accurate financial reports, and handle received donations. The findings of this research are expected to help Ar-Ruhama Foundation in preparing transparent and accurate financial reports and improving organizational stability through efficient financial management.

PEMANFAATAN TEKNOLOGI INFORMASI DAN PENERAPAN PENGENDALIAN INTERN KAS

Internal cash control is a control process to achieve specific goals. Internal control is carried out by people from each organization, including management and all employees. Internal control is expected to provide reasonable assurance to managers and employees in an organization. The data analysis method in this study uses simple linear regression to predict the effect of independent variables. The population in this study amounted to 100 employees in the Aceh SKPD. The results showed that the use of information technology affected the implementation of internal cash control. However, it indicates that information technology can play an essential role in the performance of internal cash control in the Regional Work Unit (SKPD). By utilizing information technology, SKPD can improve efficiency and effectiveness in controlling and managing cash internally, such as identifying potential fraud or weaknesses in the cash control system, monitoring financial transactions in real-time, and making more accurate and transparent financial reports.

Sentiment Analysis of Towards Electric Cars using Naive Bayes Classifier and Support Vector Machine Algorithm

The use of non-renewable energy sources causes a reduction in fossil fuel resources, and greenhouse gas emissions. Based on the 2020 Climate Transparency Report, G20 member countries are trying to minimize gas emissions according to the target of the Nationally Determined Contribution (NDC), that the transportation sector contributes 27% of air pollution. The solution to reduce greenhouse gas emissions is to start using electric cars. The change from conventional transportation to electric transportation is expected to reduce carbon emissions and dependency on fossil fuels. However, the transition from conventional transportation to electric transportation raises pros and cons for the people of Indonesia. Social media Twitter is a forum for sharing opinions. Twitter users can express opinions on a matter. This study uses the sentiment analysis method to determine public opinion on the use of electric cars in Indonesia. Sentiment classification was performed using the NBC and SVM Algorithms. The results of this study indicate the use of two different algorithms, namely the Naive Bayes Classifier and SVM with the highest accuracy in Naive Bayes with k = 2 and k = 9 is 88%, while the highest accuracy in SVM with k = 9 and k = 10 is 90%. Thus, SVM has better capabilities than Naive Bayes in this study.

Analysis of approaches to the preparation of social reporting of pharmaceutical enterprises

Aim. The work aims are to find and justify unified approaches to social reporting for pharmaceutical enterprises, which would enable the evaluation and comparison of the social activities of organizations across different market segments by all stakeholders. Materials and methods. Materials are scientific and scientific-methodical publications, regulatory and legislative documents on social responsibility, and information from the official websites of domestic manufacturing pharmaceutical enterprises, which were included in the top 20 marketing organizations by the volume of drugs’ pharmacy sales in 2022, to social reporting. Methods: critical analysis, content analysis, generalization, and interpretation of results. Results. The study found that while social reporting of pharmaceutical enterprises is an established practice abroad, there is no unified approach to their preparation, resulting in a diverse range of content. In Ukraine, it was observed that only JSC “Pharmak”, Arterium Corporation, and PJSC RPC “Borshchagivskyi chemical and pharmaceutical plant” publish reports on their corporate social responsibility. Other pharmaceutical companies provide information on their social measures either in management reports or in news. The phenomenon of social reporting of domestic pharmaceutical enterprises and the approaches to its preparation are still in the early stages of development. Therefore, this study proposes a framework for the content of such reports that caters to various stakeholders. Conclusions. Domestic manufacturing pharmaceutical enterprises apply different criteria and different approaches to inform society about their social activities, making it difficult to compare their contribution to the sustainable development of the country. It has been established that domestic pharmaceutical manufacturing enterprises need to strengthen their efforts in this direction. The preparation of transparent social reports based on international standards is one of the tools for promoting openness, improving the company’s activities, and ensuring accountability in the context of social responsibility.