Indra Cahyadi
Department Of Industrial Engineering, Engineering Faculty, Universitas Trunojoyo Madura, Indonesia

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Development of Artificial Neural Network Model for Estimation of Salt Fields Productivity Indra Cahyadi; Heri Awalul Ilhamsah; Ika Deefi Anna
Jurnal Teknik Industri Vol. 20 No. 2 (2019): August
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (331.617 KB) | DOI: 10.22219/JTIUMM.Vol20.No2.152-160

Abstract

In recent years, Indonesia needs import millions of tons of salt to satisfy domestic industries' demand. The production of salt in Indonesia is highly dependent on the weather. Therefore, this article aims to develop a prediction model by examining rainfall, humidity, and wind speed data to estimate salt production. In this research, Artificial Neural Network (ANN) method was used to develop a model based on data collected from Sumenep Madura Indonesia.  The model analysis used the complete experimental factorial design to determine the effect of the ANN parameter differences. Furthermore, the selected model performance compared with the estimate predictor of Holt-Winters. The results presented that ANN-based models were more accurate and efficient for predicting salt field productivity.
Penggunaan Metode Multi-criteria Decision Aid dalam Proses Pemilihan Supplier Indra Cahyadi
Performa: Media Ilmiah Teknik Industri Vol 3, No 2 (2004): PERFORMA Vol. 3 No 2, September 2004
Publisher : Industrial Engineering Study Program, Faculty of Engineering, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (124.765 KB) | DOI: 10.20961/performa.3.2.11138

Abstract

Nowdays, an increasing trend in industrial companies is to conduct outsourcing for those products and activities considered to be outside the company's core business. Because of the financial importance and the multi-objective nature of supplier selection decision, in this paper we make an effort to highlight those crucial aspects to process qualitative and quantitative performance measures. In this paper, we use a multi-criteria decision aid method (PROMETHEE) to solve such problems, and then perform a sensitivity analysis to analyze simultaneous change of the weights importance of performance criteria. The whole suppliers selection model presented here (PROMETHEE techniques plus sensitivity analysis) seems to be a useful tool inside the final decision phase of a supplier selection process.