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The Strategy For Selecting Institutional Model And Financial Analysis Of Sesame Agroindustry Luluk Sulistiyo Budi; M. Syamsul Ma’arif; Illah Sailah; Sapta Raharja
Jurnal Teknologi Industri Pertanian Vol. 19 No. 2 (2009): Jurnal Teknologi Industri Pertanian
Publisher : Department of Agroindustrial Technology, Bogor Agricultural University

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Abstract

Business institution is one of the important components to develop an agroindustry.  The aim of this  research was to find the appropriate institutional model for sesame agroindustry based on financial feasibility analysis comprises Net Present Value  (NPV), Internal Rate of Return (IRR), Pay Back Period (PBP) and Net B/C Ratio. The method to develop strategy was Analytical Hirarchy Process (AHP) approach, while to choose an institution was exponential comparison method (MPE).  The results of analysis showed that the main factor in developing strategy of sesame agroindustry based on evaluation value were market demand (0.209), and material quality and availability (0.198).  The main actors were bussinessman (0.129) and the local goverment (0.123). The main objective for sesame agroindustrial development was increasing farmer income (0.216). The results of analysis based on aggregate weighting showed that the appropriate development institutions were integrated agroindustrial cooperative pattern (117,106,036) and self-sufficient bussiness pattern (107,560,765).  Based on financial analysis, it was known that  opportunity level (discount rate) was 20%, NPV was Rp 292,796,108.90, Net B/C was 1.27, IRR 22.04% and PBP was 1.34%. In conclusion, the development of the sesame-based agroindustry with cooperative institutional pattern was feasible. Keyword  : strategy, institution, cooperation,  sesame agroindustry, financial analysis.
PREDIKSI PRODUKSI JAGUNG DALAM MODEL PENYEDIAAN TEPUNG JAGUNG PADA RANTAI PASOK JAGUNG Dorina Hetharia; M. Syamsul Ma’arif; Yandra Arkeman; Titi Candra S
JURNAL TEKNIK INDUSTRI Vol. 7 No. 1 (2017): Volume 7 Nomor 1 Maret 2017
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Indusri Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (417.882 KB) | DOI: 10.25105/jti.v7i1.2202

Abstract

Corn flour as one of the products made from corn is an intermediate product. This product can be consumed directly, also can be used as raw materials in the food industry, feed industry and other industrial raw materials. In the supply chain system, corn flour industry is a part of the maize supply chain . To maintain the continuity of the flow of raw materials in the supply chain , the industry needs to provide corn flour that meets quantity with good quality according to consumer demand . It is closely related to the supply of corn as a raw material for corn flour. The provision of corn are also closely related to the availability of the amount of corn production obtained from the farmers. This paper discussed about prediction of maize production using artificial neural networks and a statistical forecasting . The input variables of corn production forecast in causal models were land and rainfall, while the output variable was the amount of corn production per month . The forecasting results would be used as input for the corn flour industry
Model Konseptual Analisis Perbaikan Kinerja Industri Gula Triwulandari S. Dewayana; M. Syamsul Ma’arif; Sukardi Sukardi; Sapta Raharja
JURNAL TEKNIK INDUSTRI Vol. 1 No. 2 (2011): Volume 1 No 2 Juli 2011
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Indusri Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (351.119 KB) | DOI: 10.25105/jti.v1i2.7000

Abstract

Research related to the analysis of performance improvement (as used in a systematic process to identify performance, determine the desired performance targets, and to determine the priority of improvement at the sugar industry in Indonesia has not been done. This research aims to produce a conceptual model that can be used to analyze the sugar industry performance improvement. The model produced an integrated model to achieve the objectives of the analysis phase of performance improvement. The resulting model consists of five sub-models : 1) grouping, 2) performance measurement, 3) selection of the best performance, 4) analysis of best practices, and 5) determination of priorities for improvement.