Judul: Design of risk management model on pepper agroindustrial investment
Abstrak: The spectrum of investment instruments will provide different degree of uncertainty. This is influenced by the level of risk faced. Analysis of investment performance then need an analysis that integrates the aspects of return and risk within a framework of analysis. The competitiveness of pepper industry, which can be expressed in the achievement of quality, market share, profitability and sustainability, is still low. Pepper agroindustrial is integrated with farming systems and conducted on a small scale and traditional approach. The decisions on mechanical pepper agroindustrial and its investment on value chain are very limited. It has typically been driven by practical factors such as risk. The objective of this paper is to propose a comprehensive method in risk analysis, risk management design, and risk based financial analysis as a model of decision support systems. The methods of this research are Fuzzy Logic, FMEA, Vulnerability Analysis which expressed in Radar Chart, Analytical Hierarchy Process, and Cash Flow Analysis. On the other hand, fuzzy weighting approach on expert and risk compenent is one method that can improve risk assessment. This study provides an analysis tool that integrates financial and risk analysis in a framework, risk management models, and support facility analysis, which is integrated in Decision Support System called SMART INVEST. It consists of data based management system, model based management system, integrated analysis, and user interface. The model provides integrated risk analysis for pepper commodity system agent, description of financial analysis for investor, and a guideline for government and other stakeholders in the process of providing instrument for risk management. Further analysis of the risk in the form of vulnerability analysis, will provide the basis for determining the support type for the risk management. Application of the model in Bangka showed that the total value of risk was in the high class. Based on risk group, the biggest risk faced by investment on the pepper agroindustrial was the marketing and followed by agriculture, agroindustry, institutional, and financial. The analysis showed that the biggest risks were the price, competition, steam rot disease, cooperation, and dependence between actors. The project generates a surplus of benefits over cost in 202,8 billion IDR. It would be found in this case that the IRR was 45,28%. The benefi cost ratio was 1,95, and the payback period was 3,75 years. If there is no risk management, the risk is expected to effect on the pepper processing services (28,89%), the amount of processed pepper (31,03%), and yield (10,70%). Changes in its variables will consequence in large changes in NPV, IRR, BC ratio, and Pay Back Period. It is therefore necessary to develop risk management system which completed by support facilities.
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Judul: Pemodelan Manajemen Risiko Rantai Pasok di
Agroindustri Pati Sagu
Abstrak: The supply chain system is increasingly exposed to various risks that may interrupt product, fund, and information flows among supply chain parties. Those supply chain risks (SCRs) may contribute to losses for the actors of the supply chain. In response, the supply chain risk management (SCRM) framework is employed to manage SCRs effectively. Sago is a strategic commodity in Indonesia as the largest sago producer in the world. However, the sago starch agro-industry encounter crucial issues, including supply reliability, quality consistency, and price. These issues were related to the existing risks across the sago starch supply chain. This research aims to develop an SCRM model for the sago starch agro-industry. Specifically, it has achieved three objectives; (1) identification of risks in the sago starch supply chain, (2) modelling of uncertain and interdependent SCRs in the sago starch agro-industry, and (3) modelling of coordination strategy with risk-sharing schemes for the sago starch supply chain. This research took a case study of the sago starch agro-industry supply chain in Kepulauan Meranti Regency, Riau Province, as the largest sago starch producer in Indonesia. It focused on investigating the supply chain of dried sago starch. Risk identification is the first stage of the SCRM framework as the basis for the risk assessment and mitigation stages. In this case, the system characteristics of the sago starch supply chain were identified and analyzed. The IPO (input-process-output) of the investigated system was described, including the actor's requirements. Furthermore, risk identification was started with literature reviews to identify the possible risks in the sago starch supply chain. Next, the risk candidates were confirmed to the related industry experts. Finally, the relevant SCRs were listed and classified into supply, operation, logistics, demand, price-financial, environmental, and external risks. The risk assessment stage focused on evaluating the SCR impacts on the performance of the sago starch agro-industry. The uncertainty and interdependency of SCRs were modelled into the Bayesian network (BN), a class of a probabilistic graph model. In its application, the risk and performance variables were selected to be modelled. The expert knowledge was utilized to generate the dataset through Monte Carlo simulations and rule bases. The directed acyclic graph (DAG) of the BN structure is constructed by applying hybrid methods. The Hill-climbing algorithm, a search and score-based method, was applied to learn datasets given to prior knowledge (rule of links among variables. In the next stage, Bayesian inference was applied to risk scenarios with sensitivity analysis to examine the impact strength of SCRs on the performance measures. The results of the simulation indicated that the natural and external-risk factors, supply and quality of logs and water, inbound and outbound-logistics factors might contribute to the industry performance. This research also recommended mitigation strategies to eliminate or at least minimize the adverse SCR impacts. Finally, risk mitigation stage, this research developed the coordination models with risk-sharing schemes to mitigate uncertain supply risks between sago collector (supplier) and sago mill (agro-industry). The system identification and literature review were carried as the basis for developing those coordination models. The developed models include non-risk sharing (NRS), undersupply
Keyword: Bayesian network, modelling, risk-sharing, sago starch agro-industry, supply chain risks, supply chain risk management

Judul: Karakteristik Anatomi Skelet Kepala Buaya senyulong (Tomistoma schlegelii).
Abstrak: Buaya sepit atau senyulong (Tomistoma schlegelii) merupakan jenis buaya asli Indonesia yang berhabitat di sungai-sungai Sumatera, Kalimantan, dan juga pedalaman Sulawesi. Salah satu ciri khas buaya senyulong adalah bentuk moncong yang runcing dan sempit, namun hingga saat ini informasi mengenai struktur skelet kepala buaya senyulong sangat terbatas. Penelitian ini bertujuan untuk mempelajari karakteristik anatomi skelet kepala buaya senyulong yang dikatikan dengan fungsi dan perilakunya. Penelitian dilakukan secara eksploratif dengan melakukan pengamatan, pencatatan, dan pengambilan gambar dari skelet kepala buaya senyulong. Skelet kepala berukuran panjang 70 cm, lebar 29 cm, dan tingggi 17 cm dengan permukaan kasar pada os nasale, os frontale, os maxilla, os mandibula, os lacrimale, os jugale. Jumlah gigi pada buaya ini sebanyak 78 buah, terdiri dari 4 buah gigi premaxila, 16 buah gigi maxila, dan 19 buah gigi mandibula. Pada regio orbitalis ditemukan dua pasang fenestrae temporales yang berkembang baik. Fenestra supratemporale merupakan lubang oval yang membentang di sepanjang os parietale. Fenestra infratemporale berbentuk segitiga dan dibatasi oleh os squamosum, os postorbitale, os jugulare, dan os quadratum. Os mandibula hewan ini mempunyai symphysis mandibularis yang panjang yaitu garis yang melintang di corpus mandibulae. Secara fungsional ukuran symphysis mandibularis berkaitan dengan adaptasi hewan terhadap diet makan.
Keyword: kepala, moncong, Tomistoma schlegelii