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: Adaptive Decision Support System For Potato Commodity Supply Chain Risk Management (Case Study: Wonosobo District)
Abstrak: Kentang merupakan salah satu komoditas unggulan di Kabupaten Wonosobo yang berpotensi untuk dikembangkan diiringi oleh pengelolaan risiko yang tepat. Penelitian ini bertujuan menganalisis kinerja rantai pasok, mengidentifikasi dan menyusun strategi mitigasi risiko rantai pasok, serta merancang model penunjang keputusan manajemen risiko rantai pasok kentang. Pengukuran kinerja rantai pasok kentang dengan pendekatan Supply Chain Operation Reference (SCOR) dan Analytical Hierarchy Process (AHP). Hasil tersebut menunjukkan bahwa tingkat kinerja untuk petani (91.93%), pengepul (93.05%), dan industri UKM (89.15%) sangat baik. Identifikasi sumber risiko dengan House of Risk (HOR) 1 dan pendekatan fuzzy Failure Mode Effect Analysis (FMEA). Hasil identifikasi didapatkan 7 sumber risiko prioritas pada petani, 5 sumber risiko prioritas pada pengepul, dan 5 sumber risiko prioritas pada industri UKM. Upaya mitigasi risiko diidentifikasi dengan pendekatan HOR 2 dan Fuzzy Inference System (FIS). Hasil menunjukkan terdapat 7 prioritas aksi mitigasi pada petani, 4 prioritas aksi mitigasi pada pengepul, dan 5 prioritas aksi mitigasi pada industri UKM. Penyusunan strategi mitigasi risiko dengan fuzzy AHP menunjukkan 3 aksi mitigasi terpenting yaitu 3 aksi mitigasi pada petani. Model sistem penunjang pengambilan keputusan merupakan pemodelan berorientasi objek yang dapat membantu pengguna dalam melakukan evaluasi kinerja dan pengambilan keputusan dalam manajemen risiko rantai pasok yang lebih efisien., Potatoes are one of the leading commodities in Wonosobo Regency which have the potential to be developed with good risk management. This study aims to analyze supply chain performance, identify and develop supply chain risk mitigation strategies, and design a decision support model for the management of potato supply chain risk. Measuring the performance of the potato supply chain using the Supply Chain Operation Reference (SCOR) and Analytical Hierarchy Process (AHP) approach. These results indicate that the level of performance for farmers (91.93%), collectors (93.05%), and the industry (89.15%) is very good. The risk agent identification was done by using House of Risk (HOR) and fuzzy Failure Mode Effect Analysis (FMEA) approach. It found 7 priority risk agents in farmer’s level, 5 risk agents in collector’s level, and 5 risk agent in industries level. HOR 2 and Fuzzy Inference System (FIS) approaches were used in identifying risk mitigation. The result showed there were 7 preventive acton priorities to the farmers, 4 priority mitigation action on the collectors, and 5 priority mitigation action on the industry. The formulation of risk mitigation strategies using fuzzy AHP shows the 3 most important mitigation actions that can be implemented. The decision support system model is an object-oriented modeling that can assist users in evaluating performance and making decisions in a more efficient supply chain risk management.
Keyword: Decision support system, fuzzy analysis, potato, supply chain performance, supply chain risk

Judul: Infeksi Virus Parainfluenza Pada Anjing
Abstrak: Virus parainfluenza anjing termasuk famili Paramyxoviridae, berbentuk pleomorf dengan ukuran bervariasi (bergaris tengah antara 100-500 nm), berpembungkus peka ether, berisi genom RNA dan secara serologis mempunyai kesamaan dengan virus SV-5 kera; dikenak sebagai salah satu kausa penting dari sindrom "kennel cough". Infeksinya dapat mengenai anjing semua umur yang belum pernah terinfeksi atau mendapatkan vaksinasi mengakibatkan gejala klinis ringan yang terbatas pada traktus respirasi atu infeksi yang secara klinis tidak memperlihatkan gejala nyata. Gejala klinis yang nampak setelah masa inkubasi (1-5 hari) terlewati berupa batuk yang tidak berat selama beberapa hari, berbagai tingkat tonsilitis dan pharyngitis dan kadang-kadang ditemukan kenaikan temperatur rektal antara 1-2 derajat C dari temperatur normal rat-rata. Anjing terinfeksi mengandung virus pada traktus respirasi bagian atas dan bawah serta limfonoduli sampai hari ke 9 setelah infeksi. Penyebaran virus antar anjing terjadi secara aerogen.
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