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The Forecasting of Foreign Tourists Arrival in Indonesia based on the Supply Chain Management: an Application of Artificial Neural Network and Holt winters Approaches Supriatna, Agus; Hertini, Elis; Saputra, Jumadil; Subartini, Betty; Azkiya Robbani, Alfan
International Journal of Supply Chain Management Vol 8, No 3 (2019): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

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Abstract

Tourism plays crucial role for improving the social and economic development of a country through open employment opportunities in surrounding tourism area. The supply chain mangement strategy can be effective in developing the turisim industry.The number of foreign tourists who come to Indonesia continues to increase from time to time. Therefore, tourist arrivals need to be forecasted to assist the government in providing optimal infrastructure and accommodation for tourists to avoid an imbalance between the number of tourists with the infrastructure and accommodation provided. The purpose of this study is to forecast the arrival of foreign tourists in Indonesia by using Artificial Neural Network and Holt-Winters approach esutilising the historical data from January 2011 to December 2017. From the calculation process, we found that MAPE (Mean Absolute Percentage Error) value of Artificial Neural Network and Holt-Winters approaches are 5.60% and 5.43%, respectively. So it can be concluded that the Holt-Winters approach is better than the Artificial Neural Network approaches in forecasting the foreign tourists arrival in Indonesia.
Determining Sustainable Rice Farming through Supply Chain Risk Management: A Case Study in Central Java, Indonesia Prabowo, Agung; Pratikno, Budi; Saputra, Jumadil; Sukono, Sukono
International Journal of Supply Chain Management Vol 8, No 3 (2019): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Original Source | Check in Google Scholar

Abstract

The government through the Department of Agriculture has been cooperating with Indonesian Insurance Services or PT. A suransiJasa Indonesia (PT. Jasindo), to implement an insurance program for farmers throughout the country known as rice farming insurance (RFI).The supply chain efficiency and risk management may be two causal factors to uplift the economic conditions of the agricultural communities. The premium rate for 1 hectare of land designated at 3% of the maximum benefit value of IDR 6,000,000. Consequently, the premium received by PT. Jasindo for each hectare is IDR 180,000 of which the Government subsidy pays IDR 144,000,andfarmers will pay the remaining IDR 36,000 of the premium. This research will determine the actuarially fair premium rate, both theoretically and using the data of rice harvest yield in Central Java Province from 1990-2017. The calculation, employing the rice harvest yield data, results in the premium rate. The farmers must pay for each hectare from IDR 56,000 (minimum) to IDR 161,600 (maximum) with an average value of IDR 110,750.Meanwhile,the standard deviation principle used, the premium results between IDR 78,151 and IDR 143,349. The rate of IDR 208,458 per hectare has theoretically generated if there are 100 participants per regency (city) or in size of 3,500 hectares throughout Central Java Province and IDR 182,846 per hectare if there are 10,000 participants or about 350,000 hectares. These values are not much different from RFI premium currently applied to farmers throughout Indonesia.