Suharjito

Disaster Recovery Planning Model in Manufacturing Company Using Multi Criteria Decision Making

The disaster recovery model has been considered as an appropriate solution in providing data backup if a disaster occurs especially in data center. However, selecting the required disaster recovery model based on functionality or usability, and the financial budget in manufacturing industry is not easy. It requires a method that can be used for technology selection. Top management has options for making decisions based on subjective assessments to select the appropriate disaster recovery model. An information systems typically support decision making process by offering the best alternative solutions. Multi Criteria Decision Making approach using Analytic Hierarchy Process method is proposed to support the decision support system.Results of this study are to provide a model of disaster recovery that can be chosen appropriately in accordance with desired criteria.

Pemodelan optimasi mitigasi risiko rantai pasok produk/komoditas Jagung

Besides more complexes, the agricultural product supply chain also was probabilistic, dynamic and higher dependencies. This happened because of the agricultural product was easy broken, the process of planting, the growth and the harvesting depended the season, the yield had variety form and measurement, and the agricultural product was bulky so that the agricultural product was difficult to be handled. The height of the dependency level and the complexity from the supply chain network of the agricultural product made this chain to be more susceptible to the disturbance. The risk of failure for the supply chain could be happen internally (the relations between the organization and the network of the supplier) and externally (between the network of the supplier and its environment). Therefore, the needs for supply chain risk management to avoid a result that can continuously occur at any point in the supply network. The purpose of this study was to describe a model of evaluation and risk management supply chain of agricultural products. Model could identify risks of every level of supply chain and provide solutions that can be done to minimize them. The index value of risk on farm level was 26 % higher than the risk at the level of collector (8.78 %) and distributors (8.31 %). The model can optimize farmers’ planting schedules to reduce supply risk and price, while also optimizing the selection of suppliers at the level of collectors and distributors with the consideration of minimizing risk and optimizing profits. ABSTRAK Selain lebih kompleks, rantai pasok produk pertanian juga bersifat probabilistik, dinamis dan kebergantungan yang tinggi. Hal ini terjadi karena produk pertanian bersifat mudah rusak, proses penanaman, pertumbuhan dan pemanenan tergantung musim, hasil panen memiliki bentuk dan ukuran yang bervariasi, dan produk pertanian bersifat kamba sehingga produk pertanian sulit untuk ditangani. Tingginya tingkat kebergantungan dan kompleksitas dari jaringan rantai pasok produk pertanian menjadikan rantai pasok lebih rentan terhadap gangguan. Risiko ganguan rantai pasok dapat terjadi secara internal (relasi antara organisasi dengan jaringan pemasok) dan eksternal (antara jaringan pemasok dengan lingkungannya). Oleh karena itu perlu pengendalian risiko rantai pasok agar dapat menghindarkan akibat berkelanjutan yang dapat terjadi pada setiap titik dalam jaringan pasokan. Tujuan dari kajian ini adalah menjelaskan suatu model evaluasi dan manajemen risiko rantai pasok produk pertanian. Hasil validasi model dapat mengidentifikasi risiko setiap tingkatan rantai pasok dan memberikan usulan tindakan yang dapat dilakukan untuk meminimalkan risikonya. Nilai indeks risiko pada tingkat petani sebesar 26 % yang lebih tinggi daripada risiko pada tingkat pengumpul (8,78 %) dan distributor (8,31 %). Model dapat mengoptimalkan jadwal tanam petani untuk mengurangi risiko pasokan dan harga, selain itu juga telah dimodelkan optimasi pemilihan pemasok pada tingkat pengumpul dan distributor dengan pertimbangan minimalisasi risiko dan optimalisasi keuntungan.