The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error
Open accessAbstract
Prediction using a forecasting method is one of the most important things for an organization, the selection of appropriate forecasting methods is also important but the percentage error of a method is more important in order for decision makers to adopt the right culture, the use of the Mean Absolute Deviation and Mean Absolute Percentage Error to calculate the percentage of mistakes in the least square method resulted in a percentage of 9.77% and it was decided that the least square method be worked for time series and trend data.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Leys, C., Ley, C., Klein, O., Bernard, P., & Licata, L. (2013) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2013.03.013 · Cited by 4,147 · cited 1×
“MAD is useful when measuring prediction errors in the same unit as the original series[5][6].”
Mean Absolute Percentage Error for regression models
de Myttenaere, A., Golden, B., Le Grand, B., & Rossi, F. (2016) · Neurocomputing · doi:10.1016/j.neucom.2015.12.114 · Cited by 1,502
Surveying stock market forecasting techniques – Part II: Soft computing methods
Atsalakis, G. S., & Valavanis, K. P. (2009) · Expert Systems with Applications · doi:10.1016/j.eswa.2008.07.006 · Cited by 839
Kitani, K. M., Ziebart, B. D., Bagnell, J. A., & Hebert, M. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33765-9_15 · Cited by 701
Rautiainen, M., Korhonen, T., Mutafungwa, E., Ovaska, E., Katasonov, A., Evesti, A., Ailisto, H. J., Quigley, A. J., Häkkilä, J., Milić-Frayling, N., et al. (2012) · Lecture notes in computer science · Cited by 522
A literature review of wind forecasting technology in the world
Wu, Y., & Hong, J. (2007) · doi:10.1109/pct.2007.4538368 · Cited by 312
Mean absolute percentage error and bias in economic forecasting
McKenzie, J. (2011) · Economics Letters · doi:10.1016/j.econlet.2011.08.010 · Cited by 88
A robust mean absolute deviation model for portfolio optimization
Moon, Y., & Yao, T. (2010) · Computers & Operations Research · doi:10.1016/j.cor.2010.10.020 · Cited by 84
Cited by
Zheng, Y., Shen, R., Wang, Y., Li, X., Liu, S., Liang, S., Chen, J. M., Ju, W., Zhang, L., & Yuan, W. (2020) · Earth System Science Data · doi:10.5194/essd-12-2725-2020 · Cited by 432
A Machine-Learning-Based System for Prediction of Cardiovascular and Chronic Respiratory Diseases
Shah, W., Aleem, M., Iqbal, M. A., Islam, M. A., Ahmed, U., Srivastava, G., & Lin, J. C.-W. (2021) · Journal of Healthcare Engineering · doi:10.1155/2021/2621655 · Cited by 18
Retracted
Metadata
- Authors
- Khair, U., Fahmi, H., Hakim, S. A., & Rahim, R.
- Venue
- Journal of Physics: Conference Series
- Publisher
- IOP Publishing
- Published
- 2017-12
- Volume
- 930
- Pages
- 012002
- ISSN
- 1742-6588 (ISSN-L)
- 1742-6596
- OpenAlex
- W2773560649
- Cited by
- 319
- References
- 8
- FWCI
- 22.26
- Type
- conference paper
- Language
- en
- Open access
- diamond
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error. https://app.cochat.ai/papers/10.1088/1742-6596/930/1/012002
- The paper
- Khair, U., Fahmi, H., Hakim, S. A., & Rahim, R. (2017). Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error. Journal of Physics: Conference Series. https://doi.org/10.1088/1742-6596/930/1/012002
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
