Dono, Prajoko Aji (2018) ANALISIS RISIKO OPERASI INDUSTRI GULA DENGAN PENDEKATAN BAYESIAN NETWORK. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Industri gula di Indonesia masih rentan terhadap risiko yang dimilikinya. Selain itu risiko sendiri tidak hanya berdiri sendiri tetapi memiliki keterkaitan satu dengan yang lain. Salah satu metode yang dapat digunakan untuk menganalisa risiko dengan mempertimbangan keterkaitan antar risiko adalah Bayesian Network. Dalam melakukan analisa dengan menggunakan metode Bayesian Network dilakukan identifikasi risiko dan pembuatan model risiko dengan menggunakan Directed Acyclic Graph (DAG). Berasarkan model ini dikelompokkan risiko mana yang termasuk risiko prior dan posterior. Selanjutnya risiko prior akan dicari nilai probabilitas masing-masing dan probabilitas risiko posterior dicari dengan menggunakan Conditional Probability Tabel(CPT). Risiko selanjutnya dipetakan dengan megkalikan nilai likelihood dan consequences, dipilih risiko kritis dengan nilai hasil perkalian terbesar dan selanjutnya dilakukan pemberian usulan mitigasi risiko. Mitigasi yang diberikan selanjutnya dianalisis untuk melihat dampak dari usulan mitigasi tersebut dengan menggunakan Expected Monetery Value (EMV). Berdasarkan hasil identifikasi didapatkan 42 risiko yang terdiri dari 1 Risiko Utama 9 risiko source, 26 risiko make dan 10 risiko delivery. Berdasarkan hasil pemetaan didapatkan bahwa Risiko RS7 Tebu kotor sebagai risiko kritis yang paling berdampak pada pabrik gula. Berdasarkan risiko kritis, usulan mitigasi yang diberikan adalah menerapkan prinsip MBS (Manis, Bersih dan Segar) dan pemberian subisdi kepada petani, terdiri dari subsidi bibit, pupuk dan biaya traktor. Hasil perkalian EMV menunjukkan penerapan mitigasi 1 memberikan hasil EMV terbesar. ========================================================================================================
The sugar industry in Indonesia is still vulnerable to the risks their own. In addition, the risks themselves not only stand alone but also interrelationship with one another. One method that can be used to analyze risk by considering the relationship between risk is Bayesian Network. In performing the analysis using the Bayesian Network method, risk identification and risk modeling were performed using Directed Acyclic Graph (DAG). Based on this model, risks are classified which risks include prior and posterior risks. Furthermore the prior risk will be searched for each probability value and posterior risk probability calculated by using Conditional Probability Table (CPT). Further risk is mapped by multiplying the value of likelihood and consequences, choosing the critical risk with the greatest multiplication value and subsequent to the proposed risk mitigation. The mitigation provided is then analyzed to see the impact of the mitigation proposal using Expected Monetery Value (EMV). Based on the results of the identification obtained 42 risks consisting of 1 Main Risk 9 risk source, 26 risk make and 10 risk delivery. Based on the results of the mapping, it was found that the risk of RS7 Sugarcane was dirty as the most critical risk to the sugar factory. Based on the critical risks, the proposed mitigation proposals are to apply the principles of SBM (Sweet, Clean and Fresh) and subsidy to farmers, consisting of seed subsidies, fertilizers and tractor costs. The results of the EMV multiplication indicate that the implementation of mitigation 1 gives the largest EMV result.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSI 658.155 Don a-1 3100018078585 |
| Uncontrolled Keywords: | Industri Gula, Risiko, Bayesian network |
| Subjects: | T Technology > T Technology (General) > T174.5 Technology--Risk assessment. |
| Divisions: | Faculty of Industrial Technology > Industrial Engineering > 26201-(S1) Undergraduate Thesis |
| Depositing User: | prajoko aji dono |
| Date Deposited: | 06 Dec 2020 07:46 |
| Last Modified: | 23 Feb 2021 03:08 |
| URI: | http://repository.its.ac.id/id/eprint/53533 |
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