Using Prediction Intervals to Improve Information Quality of Bankruptcy Prediction Models

2014 ◽  
pp. 37-52 ◽  
Author(s):  
Marco Lam ◽  
Brad S. Trinkle
Keyword(s):  
Information Quality ◽  
Prediction Models ◽  
Bankruptcy Prediction ◽  
Prediction Intervals

scholarly journals Asset Quality as a Predictor of Rural Bank Bankruptcy in Indonesia

2021 ◽  
Vol 4 (1) ◽  
pp. 44-45
Author(s):  
Hesti Budiwati ◽  
Ainun Jariah
Keyword(s):  
Logistic Regression ◽  
Prediction Model ◽  
Classification Accuracy ◽  
Prediction Models ◽  
Predictor Variable ◽  
Financial Statements ◽  
Bankruptcy Prediction ◽  
Asset Quality ◽  
Productive Assets

The study aims to form a bankruptcy prediction model of rural bank in Indonesia at a time variation of 1 quarter (MP1), 2 quarters (MP2), 4 quarters (MP4), and 8 quarters (MP8) before bankruptcy. The quality of productive assets as a predictor variable consist of CEA, CEAEA, and NPL. The condition of rural bank bankrupt and non bankrupt as a dependent variable. The analytical method used is logistic regression followed by testing the model accuration. The population of this study is rural bank in Indonesia. The sample used was 241 rural banks that consist of 41 bankrupt rural banks and 200 non bankrupt rural banks. The data used are the quarterly financial statements of 2006 to 2019. The study result showed that of the four prediction models that successfully built, the 1 quarter (MP1) is the most feasible and accurate used as bankruptcy prediction model of rural banks in Indonesia that formed by CEAEA and NPL ratio. The MP1 has a classification accuracy of 93,8% at the level of modelling with cut off point of 0,29 and it has a classification accuracy of 83,93% at the level of validation with cut off point of 0,12. Based on those advantage, the MP1 was chosen as a model that able to predict the bankruptcy of rural bank in Indonesia.

Quality of Online Learning Applications

2008 ◽  
pp. 2154-2167
Author(s):  
Leping Liu
Keyword(s):  
Student Learning ◽  
Technology Use ◽  
Teaching And Learning ◽  
Information Quality ◽  
Prediction Models ◽  
Design Quality ◽  
Online Application ◽  
K 12 ◽  
Design Factors

The purpose of this study was to explore the influence of the design-quality of current online K-12 learning applications on student learning via three learning-related variables (student enjoyment, motivation, and anxiety level when using those online applications). Nine hundred online K-12 applications (WebQuests, online drills, games, tests and other applications) were evaluated in terms of four design factors (quality of information, design of information, quality of technology use, and design of technology use) in relation to the three learning-related variables. Three prediction models were generated and tested in this study. An intermediate effect was found between the design of online application and student learning, which may provide some insights for teachers when they integrate online applications into teaching and learning. The target audience of this paper may be school teachers, designers, or professionals who use online applications for education purposes.

Evaluating Online Learning Applications

2011 ◽  
pp. 956-970
Author(s):  
Leping Liu
Keyword(s):  
Student Learning ◽  
Technology Use ◽  
Teaching And Learning ◽  
Information Quality ◽  
Prediction Models ◽  
Design Quality ◽  
Online Application ◽  
K 12 ◽  
Design Factors

The purpose of this study was to explore the influence of the design-quality of current online K-12 learning applications on student learning via three learning-related variables (student enjoyment, motivation, and anxiety level when using those online applications). Nine hundred online K-12 applications (WebQuests, online drills, games, tests, and other applications) were evaluated in terms of four design factors (quality of information, design of information, quality of technology use, and design of technology use) in relation to the three learning-related variables. Three prediction models were generated and tested in this study. An intermediate effect was found between the design of online application and student learning, which may provide some insights for teachers when they integrate online applications into teaching and learning. The target audience of this paper may be school teachers, designers, or professionals who use online applications for education purposes.

Quality of Online Learning Applications

2011 ◽  
pp. 327-346
Author(s):  
Leping Liu
Keyword(s):  
Student Learning ◽  
Technology Use ◽  
Teaching And Learning ◽  
Information Quality ◽  
Prediction Models ◽  
Design Quality ◽  
Online Application ◽  
K 12 ◽  
Design Factors

The purpose of this study was to explore the influence of the design-quality of current online K-12 learning applications on student learning via three learning-related variables (student enjoyment, motivation, and anxiety level when using those online applications). Nine hundred online K-12 applications (WebQuests, online drills, games, tests and other applications) were evaluated in terms of four design factors (quality of information, design of information, quality of technology use, and design of technology use) in relation to the three learning-related variables. Three prediction models were generated and tested in this study. An intermediate effect was found between the design of online application and student learning, which may provide some insights for teachers when they integrate online applications into teaching and learning. The target audience of this paper may be school teachers, designers, or professionals who use online applications for education purposes.

scholarly journals Limitations in the Applicability of Bankruptcy Prediction Models

2021 ◽  
Vol 27 (2) ◽  
pp. 19-31
Keyword(s):  
Prediction Models ◽  
Bankruptcy Prediction ◽  
Bankruptcy Risk ◽  
Wide Range ◽  
Quality Of Accounting Information ◽  
Uniform Definition ◽  
Definition Of ◽  
Specific Definition ◽  
Selection Of

The problems associated with the application of bankruptcy prediction models are of a wide range. A review of the literature shows the lack of a uniform definition of bankruptcy. The existing diversity in the definitions of bankruptcy complicates the comparability of the different studies, hence why it is considered appropriate to take the specific definition of bankruptcy that the bankruptcy prediction models are based on into account when applying them in practice. The selection of companies in the various studies has also been the subject of much criticism. The literature also raises the question of the quality of accounting information. There are also discussions about which indicators should be included in the models. Many studies have demonstrated the benefits of including market information as well as non-financial information in bankruptcy risk analysis. There is also no consensus on the statement that data on the cash flow of companies should be used to increase the predictive power of the models.

PENGARUH KUALITAS INFORMASI DAN KUALITAS LAYANAN TERHADAP SIKAP DALAM PENGGUNAAN SISTEM APLIKASI DENGAN KEMUDAHAN PENGGUNAAN SEBAGAI VARIABEL INTERVENING PADA JASA TRANSPORTASI ONLINE (GOJEK) DI YOGYAKARTA

2019 ◽  
Vol 27 (2) ◽  
pp. 119-133
Author(s):  
Putri Aprilia Isnaini ◽  
Ida Bagus Nyoman Udayana
Keyword(s):  
Social Media ◽  
Quality Of Service ◽  
Information Quality ◽  
Sampling Technique ◽  
Ease Of Use ◽  
Quality Of Services ◽  
Quality Of Information ◽  
Transportation Services ◽  
Application Systems

This writing is done to determine the effect of information quality and service quality on attitudes in the use of application systems with the ease of use of the system as an intervining variable in online transportation services (gojek) in Yogyakarta. The sample in this study is customers who use online motorcycle transportation services in Yogyakarta. The sampling technique uses accidental sampling technique. Data collection is done by distributing online questionnaires through the Goegle form and distributed with social media such as WhatsApp and Instagram on a 1-4 scale to measure 4 indicators. The results of this study show 1) the quality of information affects the ease of use, 2) the quality of service affects the ease of use, 3) the quality of information influences attitudes in use, 4) the quality of services does not affect attitudes in use, and 5) ease of use attitude in use.

Bankruptcy Prediction Models: A Bet on Artificial Neural Networks

2012 ◽  
Vol 3 (2) ◽  
pp. 48-50
Author(s):  
Ana Isabel Velasco Fernández ◽  
◽  
Ricardo José Rejas Muslera ◽  
Juan Padilla Fernández-Vega ◽  
María Isabel Cepeda González
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Prediction Models ◽  
Bankruptcy Prediction ◽  
Artificial Neural

Designing Information Product (IP) Maps On the Process of Data Processing and Academic Information

2017 ◽  
Vol 4 (1) ◽  
pp. 25-31 ◽  
Author(s):  
Diana Effendi
Keyword(s):  
Data Quality ◽  
Data Management ◽  
Information Management ◽  
Information Quality ◽  
Quality Data ◽  
Management Approach ◽  
Quality Of Data ◽  
Information Product ◽  
Academic Activities

Information Product Approach (IP Approach) is an information management approach. It can be used to manage product information and data quality analysis. IP-Map can be used by organizations to facilitate the management of knowledge in collecting, storing, maintaining, and using the data in an organized. The  process of data management of academic activities in X University has not yet used the IP approach. X University has not given attention to the management of information quality of its. During this time X University just concern to system applications used to support the automation of data management in the process of academic activities. IP-Map that made in this paper can be used as a basis for analyzing the quality of data and information. By the IP-MAP, X University is expected to know which parts of the process that need improvement in the quality of data and information management.   Index term: IP Approach, IP-Map, information quality, data quality. REFERENCES[1] H. Zhu, S. Madnick, Y. Lee, and R. Wang, “Data and Information Quality Research: Its Evolution and Future,” Working Paper, MIT, USA, 2012.[2] Lee, Yang W; at al, Journey To Data Quality, MIT Press: Cambridge, 2006.[3] L. Al-Hakim, Information Quality Management: Theory and Applications. Idea Group Inc (IGI), 2007.[4] “Access : A semiotic information quality framework: development and comparative analysis : Journal ofInformation Technology.” [Online]. Available: http://www.palgravejournals.com/jit/journal/v20/n2/full/2000038a.html. [Accessed: 18-Sep-2015].[5] Effendi, Diana, Pengukuran Dan Perbaikan Kualitas Data Dan Informasi Di Perguruan Tinggi MenggunakanCALDEA Dan EVAMECAL (Studi Kasus X University), Proceeding Seminar Nasional RESASTEK, 2012, pp.TIG.1-TI-G.6.

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