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Abstrak :
PT Pembiayaan XYZ menghadapi potensi kerugian operasional tapi belum memiliki pengukuran risiko operasional. Disamping itu ada kewajiban dari Holding Company dan juga dari regulator untuk kedepannya untuk menjalankan manajemen risiko. Penelitian ini mengukur risiko OpVaR dengan menggunakan metode Extreme Value Theory dan metode Loss Distribution Approach Aggregation. Dari kedua metode ini menghasilkan perhitungan yang valid, namun pengukuran risiko operasional yang lebih realistis adalah metode Loss Distribution Approach Aggregation Method. ...... PT. XYZ did not have any adequate operational risk management. Holding Company and the regulators required PT. XYZ to implement risk management for the operational activities. The purpose of this research is to measure the OpVaR by using Extreme Value Theory and Loss Distribution Approach Aggregation Method. Both methods indicate the valid measurement but the result of Loss Distribution Approach Aggregation Method shows more significant.

Abstrak :
Setiap transaksi valuta asing yang dilakukan Bank terdapat potensi keuntungan dan potensi risiko berupa kerugian. Untuk mengendalikan risiko tersebut, Bank perlu menerapkan manajemen risiko yang memadai, mulai dari identifikasi risiko, pengukuran risiko, dan Pengendalian Risiko. Pengukuran risiko nilai tukar dapat menggunakan Value at Risk dengan pendekatan Risk Metrics dan Variance-Covariance. Dalam pengendalian risiko dapat dilakukan dengan penentuan limit risiko berupa limitValue at Risk dan limit eksposur trading.Dalam penetapan limit risiko tersebut juga mempertimbangkan risk appettiteyang ditetapkan Bank. ......Every foreign exchange transactions by the Bank are has its potential of benefits risks of loss. To mitigate these risks, Bank needs to implement adequate risk management, ranging from risk identification, risk measurement, and risk control. Exchange rate risk measurement can use Value at Risk with Risk Metrics and Variance-Covariance approach. Risk controlling may contained with risk limit form as Value at Risk limit and trading exposure limit. The establishment of risk limits are also consider Bank risk appetite.

Abstrak :
[ABSTRAK
Bank dalam menjalankan pengelolaan likuiditasnya mempunyai potensi keuntungan dan kerugian yang selalu mengikuti. Untuk mengendalikan risiko tersebut perlu suatu proses manajemen risiko yang memadai, mulai dari identifikasi risiko, pengukuran risiko hingga implementasi mitigasi risiko. Pengukuran risiko likuiditas pada Bank Sinarmas yaitu menggunakan Liquidity Coverage Ratio. Penyediaan likuiditas sangat penting untuk mengantisipasi adanya kebutuhan likuiditas sehingga dapat mengcover kewajiban Bank baik dalam kondisi normal maupun krisis. Namun demikian, penyediaan likuiditas tidak boleh tersedia secara berlebihan karena timbul biaya likuiditas yang harus ditanggung oleh Bank. Oleh karena itu, diperlukan penetapan limit biaya pengelolaan likuiditas yang bersedia di tanggung oleh Bank berdasarkan risk appetite dari management serta batas limit maksimum Liquidity Coverage Ratio harus ditetapkan oleh Bank. Penetapan limit tersebut merupakan hal penting dalam proses mitigasi risiko agar pendapatan yang hilang karena adanya penyediaan likuiditas dapat diminimalkan sehingga dapat tercipta peningkatan laba bagi Bank. Data yang diperoleh dalam penelitian ini merupakan komponen dari Liquidity Coverage Ratio Bank Sinarmas selama 3 Tahun (2012-2014). Metode dalam penelitian ini secara kuantitatif. Pada kondisi saat ini Bank Sinarmas belum melakukan pengelolaan likuiditas jangka pendeknya secara efektif. Hal ini terbukti dari hasil perhitungan rata-rata Liquidity Coverage Ratio yang masih tinggi yaitu 206.01%. Bahkan pernah tertinggi sebesar 392% pada bulan Juli 2014. Regulator menetapkan batas Liquidity Coverage Ratio minimum sebesar 100%. Dengan adanya, penetapan pengelolaan biaya pemeliharaan likuiditas maksimum dan penetapan limit maksimum Liquidity Coverage Ratio diharapkan dapat diimplementasikan oleh Bank Sinarmas sehingga dapat tercipta peningkatan laba bagi Bank

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ABSTRACT
Bank in carrying out liquidity management always followed with potential gains and losses. There should be an adequate risk management process to manage these risks, starting from risk identification, risk measurement to risk mitigation implementation. Liquidity risk measurement in Bank Sinarmas using Liquidity Coverage Ratio. The providing of liquidity is very important to anticipate liquidity needs so as to cover the liabilities of the Bank both in normal and crisis conditions. However, the providing of liquidity should not be available to excess liquidity because there will be costs to be borne by the Bank. Therefore, it is necessary to establish limit liquidity management fee paid by the Bank prepared based on the risk appetite by management as well as the maximum limit of the Liquidity Coverage Ratio must be determined by the Bank. The limit setting process is important in order to mitigate the risk of lost revenue due to the providing of liquidity could be minimized so as to create an increase in profits for the Bank. Data obtained in this study is a component of the Liquidity Coverage Ratio Bank Sinarmas for 3 years (2012-2014). The method in this research is quantitative. In the current conditions the Bank Sinarmas not do short-term liquidity management effectively. This is evident from the results of the calculation of average Liquidity Coverage Ratio are still high at 206.01%. The highest ever amounted to 392% in July 2014. Regulator set a minimum limit of the Liquidity Coverage Ratio at 100%. With the, determination of maximum liquidity management of maintenance costs and maximum limits Liquidity Coverage Ratio is expected to be implemented by the Bank Sinarmas so as to create an increased Bank profitability;Bank in carrying out liquidity management always followed with potential gains and losses. There should be an adequate risk management process to manage these risks, starting from risk identification, risk measurement to risk mitigation implementation. Liquidity risk measurement in Bank Sinarmas using Liquidity Coverage Ratio. The providing of liquidity is very important to anticipate liquidity needs so as to cover the liabilities of the Bank both in normal and crisis conditions. However, the providing of liquidity should not be available to excess liquidity because there will be costs to be borne by the Bank. Therefore, it is necessary to establish limit liquidity management fee paid by the Bank prepared based on the risk appetite by management as well as the maximum limit of the Liquidity Coverage Ratio must be determined by the Bank. The limit setting process is important in order to mitigate the risk of lost revenue due to the providing of liquidity could be minimized so as to create an increase in profits for the Bank. Data obtained in this study is a component of the Liquidity Coverage Ratio Bank Sinarmas for 3 years (2012-2014). The method in this research is quantitative. In the current conditions the Bank Sinarmas not do short-term liquidity management effectively. This is evident from the results of the calculation of average Liquidity Coverage Ratio are still high at 206.01%. The highest ever amounted to 392% in July 2014. Regulator set a minimum limit of the Liquidity Coverage Ratio at 100%. With the, determination of maximum liquidity management of maintenance costs and maximum limits Liquidity Coverage Ratio is expected to be implemented by the Bank Sinarmas so as to create an increased Bank profitability;Bank in carrying out liquidity management always followed with potential gains and losses. There should be an adequate risk management process to manage these risks, starting from risk identification, risk measurement to risk mitigation implementation. Liquidity risk measurement in Bank Sinarmas using Liquidity Coverage Ratio. The providing of liquidity is very important to anticipate liquidity needs so as to cover the liabilities of the Bank both in normal and crisis conditions. However, the providing of liquidity should not be available to excess liquidity because there will be costs to be borne by the Bank. Therefore, it is necessary to establish limit liquidity management fee paid by the Bank prepared based on the risk appetite by management as well as the maximum limit of the Liquidity Coverage Ratio must be determined by the Bank. The limit setting process is important in order to mitigate the risk of lost revenue due to the providing of liquidity could be minimized so as to create an increase in profits for the Bank. Data obtained in this study is a component of the Liquidity Coverage Ratio Bank Sinarmas for 3 years (2012-2014). The method in this research is quantitative. In the current conditions the Bank Sinarmas not do short-term liquidity management effectively. This is evident from the results of the calculation of average Liquidity Coverage Ratio are still high at 206.01%. The highest ever amounted to 392% in July 2014. Regulator set a minimum limit of the Liquidity Coverage Ratio at 100%. With the, determination of maximum liquidity management of maintenance costs and maximum limits Liquidity Coverage Ratio is expected to be implemented by the Bank Sinarmas so as to create an increased Bank profitability;Bank in carrying out liquidity management always followed with potential gains and losses. There should be an adequate risk management process to manage these risks, starting from risk identification, risk measurement to risk mitigation implementation. Liquidity risk measurement in Bank Sinarmas using Liquidity Coverage Ratio. The providing of liquidity is very important to anticipate liquidity needs so as to cover the liabilities of the Bank both in normal and crisis conditions. However, the providing of liquidity should not be available to excess liquidity because there will be costs to be borne by the Bank. Therefore, it is necessary to establish limit liquidity management fee paid by the Bank prepared based on the risk appetite by management as well as the maximum limit of the Liquidity Coverage Ratio must be determined by the Bank. The limit setting process is important in order to mitigate the risk of lost revenue due to the providing of liquidity could be minimized so as to create an increase in profits for the Bank. Data obtained in this study is a component of the Liquidity Coverage Ratio Bank Sinarmas for 3 years (2012-2014). The method in this research is quantitative. In the current conditions the Bank Sinarmas not do short-term liquidity management effectively. This is evident from the results of the calculation of average Liquidity Coverage Ratio are still high at 206.01%. The highest ever amounted to 392% in July 2014. Regulator set a minimum limit of the Liquidity Coverage Ratio at 100%. With the, determination of maximum liquidity management of maintenance costs and maximum limits Liquidity Coverage Ratio is expected to be implemented by the Bank Sinarmas so as to create an increased Bank profitability, Bank in carrying out liquidity management always followed with potential gains and losses. There should be an adequate risk management process to manage these risks, starting from risk identification, risk measurement to risk mitigation implementation. Liquidity risk measurement in Bank Sinarmas using Liquidity Coverage Ratio. The providing of liquidity is very important to anticipate liquidity needs so as to cover the liabilities of the Bank both in normal and crisis conditions. However, the providing of liquidity should not be available to excess liquidity because there will be costs to be borne by the Bank. Therefore, it is necessary to establish limit liquidity management fee paid by the Bank prepared based on the risk appetite by management as well as the maximum limit of the Liquidity Coverage Ratio must be determined by the Bank. The limit setting process is important in order to mitigate the risk of lost revenue due to the providing of liquidity could be minimized so as to create an increase in profits for the Bank. Data obtained in this study is a component of the Liquidity Coverage Ratio Bank Sinarmas for 3 years (2012-2014). The method in this research is quantitative. In the current conditions the Bank Sinarmas not do short-term liquidity management effectively. This is evident from the results of the calculation of average Liquidity Coverage Ratio are still high at 206.01%. The highest ever amounted to 392% in July 2014. Regulator set a minimum limit of the Liquidity Coverage Ratio at 100%. With the, determination of maximum liquidity management of maintenance costs and maximum limits Liquidity Coverage Ratio is expected to be implemented by the Bank Sinarmas so as to create an increased Bank profitability]

Abstrak :
Penelitian ini bertujuan untuk menganalisis kegagalan pada tahap pertama proyek implementasi sistem ERP di PT Angkasa Pura II (Persero) yang nantinya bisa digunakan sebagai dasar manajemen risiko pada tahap-tahap selanjutnya implementasi ERP di PT Angkasa Pura II (Persero) dan untuk menunjukkan pentingnya manajemen risiko untuk mengurangi prosentase kegagalan implementasi ERP. Analisis yang dilakukan menggunakan metode Fault Tree analysis untuk menghitung estimasi kegagalan implementasi sistem ERP tahap pertama, lalu melakukan identifikasi faktor-faktor risiko yang berpengaruh terhadap implementasi sistem ERP tahap pertama berdasarkan faktor-faktor risiko dari studi literatur, lalu membuat kuesioner untuk menentukan urutan faktor-faktor risiko yang paling berpengaruh tersebut, kemudian dilakukan analisis dari hasil dari survey dan dilakukan estimasi terhadap kegagalan implementasi sistem ERP jika manajemen risiko diterapkan. Penelitian menggambarkan 19 (Sembilan belas) faktor-faktor risiko yang paling berpengaruh terhadap proyek implementasi sistem ERP di PT Angkasa Pura II (Persero) yang apabila tidak dikontrol dengan baik akan menyebabkan kegagalan terhadap proyek.

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The purpose of this study is to analyze the risk factors on the first phase of ERP system implementation project in PT Angkasa Pura II (Persero) and the result can be used for the next phase of implementation and to show the importance of risk management in the project to reduce the failure percentage of the ERP Implementation. The method used to estimate the failure percentage of the project is the Fault Tree Analysis (FTA) and by analyzing the credentials of the identified risk factors from the existing literature review. Based on the risk factors identified a questionnaire were made to determine the order of the risk factors that have the most significant impact to the ERP system implementation project and the result were analyzed with the FTA to estimate the failure percentage assuming risk management was being used in the first phase. This study finds that by managing and controlling the identified risk, the failure percentage of the project could be reduced. This study also described the 19 (nineteen) risk factor that have a significant impact in the ERP system implementation project in PT Angkasa Pura II (Persero) that if those risks are not controlled well enough it would cause the project to fail.

Abstrak :
Salah satu konsep pengukuran risiko di bidang industri keuangan adalah pengukuran yang mengacu pada probability-based risk yang dikenal dengan value at risk atau VaR. Dalam melakukan pengukuran VaR, digunakan metode historical simulation dan montecarlo simulation. Faktor risiko pasar yang menjadi obyek pengukuran VaR adalah harga saham dari beberapa emiten yang diperdagangkan pasar. Untuk menaksir nilai VaR yang dikehendaki, diambil data harga saham periode Januari 2006 sampai dengan 28 Desember 2007. Sementara itu, dalam suatu periode waktu tertentu, harga saham pasar dapat bergerak turun atau naik, sebagai dampak akibat kejadian yang luar biasa atau ekstrim dalam pasar keuangan. Model VaR tidak dapat menangkap situasi yang ekstrim ini, karena modal VaR hanya dapat digunakan dalam kondisi pasar yang normal. Untuk menghitung nilai VaR dalam situasi yang ekstrim ini, digunakan metode Stress Testing. Historical scenarios adalah salah satu teknik untuk menghitung VaR stress testing. Teknik ini berdasarkan kejadian-kejadian masa lampau (historical scenarios) yang dapat diaplikasikan pada kondisi sekarang. ......One of the concepts of risk measurement method known as the "value at risk" or VaR. In VaR measurement, the historical simulation and the montecarlo simulation are exercised with the stock market index postulated as the market risk factor. To measure the desired VaR value, the stock market prices data for the period of January 2006 to December 2007 are employed. During the period, certain stock market prices showed increase or decrease movement as a result of financial extreme event in the global market system. VaR model can not capture this extreme financial event, because VaR should be use in normal market condition only. To calculate VaR value in the extreme financial events, stress testing method is employed. Historical scenarios is but one of the techniques to assess VaR stress testing . This technique is based on historical event (historical scenarios) and the calculation results may be applied to present condition.