Judul: Rancang Bangun Sistem Pakar Manajemen Risiko Untuk Perencanaan Agroindustri Rumput Laut
Abstrak: The seaweed agroindustry performance is depend on quantity and quality of its raw material. Beside that, processing technology, marketing, and financial problem give influence to its achievment. Since those factors contains potential risk, there is need to identify and manage those factors trough risk management. The main aim of this study is to design expert system of risk management for seaweed agro industry planning. The scope of the research object is a small and medium enterprises (SMEs). The case study was done at PT Madura Prima Interna, East Java, which produce semi refined carrageenan for exports. The development of this expert system is composed by 6 activities which are knowledge acquisition through expert survey, knowledge conceptualization, knowledge representation., inference mechanism, computer programming, implementation and evaluation (Liebowitz, 1998). Method used for risk analysis and consultation of risk controlling was protocol method, using if-then formulation. In the case of choosing the criterion, we used Method of Exponential Comparison (MPE). In doing forecasting, is used time serried analysis method. Financial feasibility was analyzed using variables IRR B/C ratio, BEP, PBP and NPV. Knowledge acquisition was attained from 6 experts in business and professional with seaweed industry. The result of this knowledge acquisition was risk management factors in the seaweed agro industry, impact and risk possibility, and risk control. SeaWeed-Risk 1.0 was designed by using Borland Delphi 7.0 programming language. The knowledge representation of the acquisition was done with if-then production scheme. Control mechanism used backward chaining control strategy, while detection strategy used depth-first search. Model base management system is composed of selection for cultivation location, selection for pre-eminent product, risk analysis, risk management consultation, cultivation technology consultation, product quality consultation, and financial feasibility. Verification result of financial analysis with investment Rp. 24,310,953,724,- and capcity of production 756 tons/year are IRR 42%; NPV Rp. 15,167,878,918; PBP 2 years and 10 months; BEP 1,206.40 ton; and B/C Ratio 1.64. Consultation model possess input in the form of user's answer on factor or condition which was asked followed with certainty level of the mentioned condition. The output of the model is various risk diagnose and consultation result which were provided with certainty level. Consultation with this model may improve the effectiveness and quality in the decision making process in risk mamagement. There is a need for routine updating parameter of raw material supply, marketing, and processing technology modification in order for adjustment to development in seaweed agro industry. Design addition was proposed to accommodate other marine product and internet application to be more user friendly.
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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: Cycle Hamilton pada Graf Lengkap, Graf Regular, dan Graf 2-Connected 4-Regular Berorder Kurang dari Sepuluh
Abstrak: Suatu graf disebut graf Hamilton apabila graf tersebut memuat cycle Hamilton, yaitu cycle yang melewati setiap vertex tepat satu kali. Menentukan keberadaan cycle Hamilton pada suatu graf dapat menggunakan syarat cukup yang berupa teorema-teorema yang telah diperkenalkan sejak tahun 1950-an. Beberapa syarat cukup yang dibahas dalam karya ilmiah ini adalah syarat cukup yang berhubungan dengan graf lengkap dan graf regular. Suatu graf lengkap berorder 𝑛������ ≥ 3 dan graf r-regular berorder 𝑛������ ≤ 2𝑟������ + 1 merupakan graf Hamilton, Karena kedua graf tersebut memuat cycle Hamilton. Selanjutnya, syarat cukup tersebut digunakan untuk menentukan keberadaan cycle Hamilton pada graf 2-connected 4- regular berorder kurang dari 10.
Keyword: graf Hamilton, graf regular, graf lengkap, graf 2-connected 4-regular