Joint Workshop KO2PI and The 1st International Conference on Advance & Scientific Innovation

Research Article

IOWA Unemployment Insurance Claimants: A Comparison between α-Sutte Indicator and Other Forecasting Methods

Download738 downloads
Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.4108/eai.23-4-2018.2277578,
    author={Ansari Saleh Ahmar and Abdul Rahman and Heri Nurdiyanto and Darmawan Napitupulu and Dahlan Abdullah and Muhammad Ikhsan Setiawan and Janner Simarmata and Rahmat Hidayat and Wahyudin Albra and Robbi Rahim},
    title={IOWA Unemployment Insurance Claimants: A Comparison between α-Sutte Indicator and Other Forecasting Methods},
    proceedings={Joint Workshop KO2PI and The 1st International Conference on Advance \& Scientific Innovation},
    publisher={EAI},
    proceedings_a={ICASI},
    year={2018},
    month={7},
    keywords={forecasting unemployment insurance claimants α-sutte indicator arima},
    doi={10.4108/eai.23-4-2018.2277578}
}
  • Ansari Saleh Ahmar
    Abdul Rahman
    Heri Nurdiyanto
    Darmawan Napitupulu
    Dahlan Abdullah
    Muhammad Ikhsan Setiawan
    Janner Simarmata
    Rahmat Hidayat
    Wahyudin Albra
    Robbi Rahim
    Year: 2018
    IOWA Unemployment Insurance Claimants: A Comparison between α-Sutte Indicator and Other Forecasting Methods
    ICASI
    EAI
    DOI: 10.4108/eai.23-4-2018.2277578
Ansari Saleh Ahmar1,*, Abdul Rahman2, Heri Nurdiyanto3, Darmawan Napitupulu4, Dahlan Abdullah5, Muhammad Ikhsan Setiawan6, Janner Simarmata7, Rahmat Hidayat8, Wahyudin Albra9, Robbi Rahim10
  • 1: Department of Statistics, Universitas Negeri Makassar, Makassar, Indonesia
  • 2: Department of Mathematics, Universitas Negeri Makassar, Makassar, Indonesia
  • 3: Department of Informatics, STMIK Dharma Wacana, Metro Lampung, Indonesia
  • 4: Research Center for Quality System and Testing Technology, Indonesian Institute of Sciences, Indonesia
  • 5: Department Informatics, Universitas Malikussaleh, Lhokseumawe, Indonesia
  • 6: Department of Civil Engineering, Narotama University, Indonesia
  • 7: Universitas Negeri Medan, Medan, Indonesia
  • 8: Department of Information Technology, Politeknik Negeri Padang, Indonesia
  • 9: Department of Management, Universitas Malikussaleh, Aceh, Indonesia
  • 10: Sekolah Tinggi Ilmu Manajemen Sukma, Medan, Indonesia
*Contact email: ansarisaleh@unm.ac.id

Abstract

This UI program if it isn’t managed well so that can affect the insurance company performance and can make the company loss. One of the ways to know the development of this insurance claim for each month is that by forecasting the people who are interested in this insurance. The aim of this study is forecasting unemployment insurance claimants in IOWA, USA. This research uses ARIMA, NNETAR, Robus Exponensial Smooting, Theta Model, and α-Sutte Indicator forecasting method. The use of this method is intended to be compared the level of accuracy from various forecasting methods. To see the quality of the forecast, so that it will be used a comparison based on MSE score. The lower MSE Score, the better accuracy level that they have. The result of this study is α-Sutte Indicator is more appropriate in forecasting data unemployment insurance claim in IOWA. The accuracy level of α-Sutte Indicator is better if it is compared to any other methods.

Keywords
forecasting unemployment insurance claimants α-sutte indicator arima
Published
2018-07-04
Publisher
EAI
http://dx.doi.org/10.4108/eai.23-4-2018.2277578
Copyright © 2018–2024 EAI