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Ditemukan 14806 dokumen yang sesuai dengan query
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Solozhentsev, E.D.
"This book presents intellectual, innovative, information technologies (I3-technologies) based on logical and probabilistic (LP) risk models. The technologies presented here consider such models for structurally complex systems and processes with logical links and with random events in economics and technology. The volume describes the following components of risk management technologies : LP-calculus, classes of LP-models of risk and efficiency, procedures for different classes, special software for different classes, examples of applications, methods for the estimation of probabilities of events based on expert information. Also described are a variety of training courses in these topics. The classes of risk models treated here are : LP-modeling, LP-classification, LP-efficiency, and LP-forecasting. Particular attention is paid to LP-models of risk of failure to resolve difficult economic and technical problems. Amongst the discussed procedures of I3-technologies are the construction of LP-models, LP-identification of risk models; LP-risk analysis, LP-management and LP-forecasting of risk. The book further considers LP-models of risk of invalidity of systems and processes in accordance with the requirements of ISO 9001-2008, LP-models of bank operational risks in accordance with the requirements of Basel-2, complex risk LP-models for preventing ammunition depot explosions, enterprise electric power supply systems, debugging tests of technical systems, etc. The book also considers LP-models of credit risks, securities portfolios, operational risks in banking, conteraction of bribes and corruption, etc. A number of applications is given to show the effectiveness of risk management technologies. "
Dordrecht: Springer Science, 2012
e20398332
eBooks  Universitas Indonesia Library
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New York, NY: CRC Press, Taylor & Francis Group, 2008
332.632 CRE
Buku Teks  Universitas Indonesia Library
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Baker, G.A.
Michigan: Edwards Brothers, 1962
519.2 BAK s
Buku Teks SO  Universitas Indonesia Library
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Koller, Daphne
Cambridge, UK: MIT Press, 2009
519.542 KOL p
Buku Teks SO  Universitas Indonesia Library
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Texas: Teleometrics Int., 1980
658 MOD
Buku Teks  Universitas Indonesia Library
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Larson, Harold J., 1934-
New York: John Wiley & Sons, 1979
620.001 5 LAR p
Buku Teks SO  Universitas Indonesia Library
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Larson, Harold J., 1934-
New York: John Wiley & Sons, 1979
620.001 5 LAR p
Buku Teks SO  Universitas Indonesia Library
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Camili, Stephen J
Winsted, CT : ACTEX Publications, 2014
368.0120 CAM m
Buku Teks  Universitas Indonesia Library
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Veneshia Dian Prameswari
"Pemilahan sayuran sangat penting dilakukan untuk mendapatkan sayuran yang berkualitas saat di terima oleh pelanggan. Dengan demikian, suatu perusahaan dapat dikaitkan dengan ketepatan pengambilan keputusan dalam keseimbangan permintaan dan persediaan. Logika fuzzy digunakan sebagai membantu mendefinisikan dengan cara kerja yang tepat dan jelas dalam proses pemilahan sayuran. Pertama, analisis ABC untuk mengklasifikasikan sayuran yang akan diprioritasikan terlebih dahulu berdasarkan pendapatan penjualan yang tertinggi. Kedua, menggunakan fuzzy inference system mengembangkan model dengan Takagi-Sugeno berdasarkan karakteristik sayuran dari kualitas terhadap visual dan temperatur untuk mengetahui kesegaran sayuran bahwa sebagai peringatan dalam kualitas sudah mulai menandakan mulai memburuk kondisi kesegaran sayuran. Ketiga, melakukan pengujian dengan Fuzzy Associative Memory (FAM) pada dua pengujian yaitu ikut dijadikan sebagai aturan dan tidak ikut dijadikan sebagai aturan. Hasil dari perhitungan dengan FAM bahwa dijadikan sebagai batas maksimal jumlah hari yang diinginkan dalam kondisi kesegaran sayuran. Model ini diimplementasikan dengan membuat Standar Operasional Prosedur (SOP) sebagai alur peringatan kualitas pada proses pemilahan barang agar pengendalian persediaan dapat meminimalisirkan terjadinya kerusakan barang karena kualitas buruk yang menyebabkan perusahaan akan mengalami kehilangan penjualan.

Sorting vegetables is very important to get quality vegetables when received by customers. Thus, a company can be associated with the accuracy of decision making in the balance of demand and supply. Fuzzy logic is used as helping to define the proper and clear way of working in the process of sorting vegetables. First, ABC analysis to classify vegetables that will be prioritized based on the highest sales revenue. Second, using a fuzzy inference system develops a model with Takagi-Sugeno based on the characteristics of vegetables from the quality of the visual and temperature to determine the freshness of vegetables that as a warning in quality has begun to indicate deteriorating conditions of vegetable freshness. Third, do the testing with Fuzzy Associative Memory (FAM) in two tests, which are also used as rules and not as rules. The results of calculations with FAM that serve as a maximum limit of the number of days desired in conditions of vegetable freshness. This model is implemented by making the Standard Operating Procedure (SOP) as a quality warning flow in the process of sorting goods so that inventory control can minimize the occurrence of damage to goods due to poor quality that causes the company will suffer a loss of sales."
Depok: Fakultas Teknik Universitas Indonesia, 2020
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UI - Tesis Membership  Universitas Indonesia Library
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