Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia

Research Article

Construction of ANFIS Model Based on LM-Test for Forecasting of Chili Price Data in Semarang

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  • @INPROCEEDINGS{10.4108/eai.2-8-2019.2290494,
        author={Tarno  Tarno and Di Asih I  Maruddani and Rita  Rahmawati},
        title={Construction of ANFIS Model Based on LM-Test  for Forecasting of Chili Price Data in Semarang},
        proceedings={Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia},
        publisher={EAI},
        proceedings_a={ICSA},
        year={2020},
        month={1},
        keywords={anfis chili price data forecasting lm-test},
        doi={10.4108/eai.2-8-2019.2290494}
    }
    
  • Tarno Tarno
    Di Asih I Maruddani
    Rita Rahmawati
    Year: 2020
    Construction of ANFIS Model Based on LM-Test for Forecasting of Chili Price Data in Semarang
    ICSA
    EAI
    DOI: 10.4108/eai.2-8-2019.2290494
Tarno Tarno1,*, Di Asih I Maruddani1, Rita Rahmawati1
  • 1: Department of Statistics, Universitas Diponegoro, Semarang 50275, Indonesia
*Contact email: tarno.stat@gmail.com

Abstract

The research aim is constructing Adaptive Neuro-Fuzzy Inference System (ANFIS) model for forecasting time series data. The ANFIS model is constructed and applied to chili price data in Semarang. The daily data are written during December 2018 to May 2019. The input selection in ANFIS is done by using theLagrange Multiplier (LM) test. The lag-1 with 2 membership functions is selected as optimal input. The performance of prediction based on in-sample data is measured by the values of mean absolute percentage error (MAPE) and root mean squares error (RMSE). The values of MAPE and RMSE are 2.9% and 939.8 respectively.