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"[ABSTRAKKajian dilakukan dengan menganalisis seluruh komponen biaya yang mempengaruhiketetapan harga CNG, dengan simulasi Monte Carlo dengan bantuan perangkat lunakCrystal Ball yang mengacu pada kebijakan pemerintah berupa Peraturan MenteriESDM Nomor 19 Tahun 2010 yang telah menetapkan formula harga jual bahan bakargas untuk transportasi dengan mempertimbangkan harga di titik penyerahan (hulu),toll fee, investasi SPBG, biaya pengoperasian dan pemeliharaan SPBG, margin danpajak. Pada Kajian ini mengupas toll fee dengan memilih supply chain yang dianggaptepat untuk wilayah Jawa Bagian Barat. Hasil Kajian Harga CNG untuk RegionalJawa Bagian Barat, dimana simulasi dilakukan di wilayah DKI Jakarta didapatkanbahwa Keputusan Menteri Energi dan Sumber Daya Mineral Nomor: 2932K/12/MEM/2010: ?Harga Jual Bahan Bakar Gas yang digunakan untuk Transportasidi Wilayah Jakarta termasuk Bogor, Bekasi, Depok dan Tangerang adalah Rp3.100,00 (tiga ribu seratus rupiah) untuk tiap 1 (satu) Liter Setara Premium (LSP)termasuk pajak-pajak.? merupakan harga kompetitif yang dapat dilaksanakan untukwilayah Jawa bagian Barat. Dilihat dari hasil rekalkulasi yaitu harga CNG padatapping point Bitung sebesar $. 0.223 atau Rp. 2819,82 dan harga aggregasi sebesarRp. 2737,58 dengan harga riil berada pada rentang harga Rp.1857,43 hingga Rp.3890,32 (berdasarkan Indeks Harga Konsumen April 2015) dan pada wilayah tapingpoin Nagrak sebesar $. 0.209 atau Rp. 2631,02 dan harga aggregasi sebesar Rp.2795,51 dengan harga riil berada pada rentang harga Rp.2227,59 hingga Rp. 4533.44.

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ABSTRACTThe study was conducted by analyzing all the components that affect the cost of provision of CNG price, with a Monte Carlo simulation with the help of Crystal Ball software which refers to government policies such as the Minister of Energy and Mineral Resources Regulation No. 19 of 2010, which has set the pricing formula of gas fuel for transportation by considering the price at the point of delivery (upstream), toll fee, SPBGs investment, operating and maintenance costs SPBGs, margins and taxes. On This study peeling toll fee by choosing supply chain that is considered appropriate for the region Western of Java. Study results CNG price to Regional Java, where the simulation is done in Jakarta found that the Decree of the Minister of Energy and Mineral Resources No. 2932 K / 12 / MEM / 2010: "Selling Price Gas Fuel used for transportation in Jakarta area including Bogor, Bekasi, Depok and Tangerang is $ 3100.00 (three thousand one hundred dollars) for every 1 (one) liter Premium Equivalent (LSP), including taxes. "a competitive price that can be implemented for the region western of Java. Judging from the results of recalculation is the price of CNG at the tapping point Bitung of $. 0.223 or Rp. 2819.82 and aggregation price of Rp. 2737.58 with the real price is in the range of price Rp.1857, 43 up to Rp. 3890.32 (based on the Consumer Price Index April 2015) and in the region of Nagrak tapping points. $.0.209 or Rp. 2631.02 and aggregation price of Rp. 2795.51 with the real price is in the range of price Rp.2227,59 up to Rp.4533.44.;The study was conducted by analyzing all the components that affect the cost of provision of CNG price, with a Monte Carlo simulation with the help of Crystal Ball software which refers to government policies such as the Minister of Energy and Mineral Resources Regulation No. 19 of 2010, which has set the pricing formula of gas fuel for transportation by considering the price at the point of delivery (upstream), toll fee, SPBGs investment, operating and maintenance costs SPBGs, margins and taxes. On This study peeling toll fee by choosing supply chain that is considered appropriate for the region Western of Java. Study results CNG price to Regional Java, where the simulation is done in Jakarta found that the Decree of the Minister of Energy and Mineral Resources No. 2932 K / 12 / MEM / 2010: "Selling Price Gas Fuel used for transportation in Jakarta area including Bogor, Bekasi, Depok and Tangerang is $ 3100.00 (three thousand one hundred dollars) for every 1 (one) liter Premium Equivalent (LSP), including taxes. "a competitive price that can be implemented for the region western of Java. Judging from the results of recalculation is the price of CNG at the tapping point Bitung of $. 0.223 or Rp. 2819.82 and aggregation price of Rp. 2737.58 with the real price is in the range of price Rp.1857, 43 up to Rp. 3890.32 (based on the Consumer Price Index April 2015) and in the region of Nagrak tapping points. $.0.209 or Rp. 2631.02 and aggregation price of Rp. 2795.51 with the real price is in the range of price Rp.2227,59 up to Rp.4533.44.;The study was conducted by analyzing all the components that affect the cost of provision of CNG price, with a Monte Carlo simulation with the help of Crystal Ball software which refers to government policies such as the Minister of Energy and Mineral Resources Regulation No. 19 of 2010, which has set the pricing formula of gas fuel for transportation by considering the price at the point of delivery (upstream), toll fee, SPBGs investment, operating and maintenance costs SPBGs, margins and taxes. On This study peeling toll fee by choosing supply chain that is considered appropriate for the region Western of Java. Study results CNG price to Regional Java, where the simulation is done in Jakarta found that the Decree of the Minister of Energy and Mineral Resources No. 2932 K / 12 / MEM / 2010: "Selling Price Gas Fuel used for transportation in Jakarta area including Bogor, Bekasi, Depok and Tangerang is $ 3100.00 (three thousand one hundred dollars) for every 1 (one) liter Premium Equivalent (LSP), including taxes. "a competitive price that can be implemented for the region western of Java. Judging from the results of recalculation is the price of CNG at the tapping point Bitung of $. 0.223 or Rp. 2819.82 and aggregation price of Rp. 2737.58 with the real price is in the range of price Rp.1857, 43 up to Rp. 3890.32 (based on the Consumer Price Index April 2015) and in the region of Nagrak tapping points. $.0.209 or Rp. 2631.02 and aggregation price of Rp. 2795.51 with the real price is in the range of price Rp.2227,59 up to Rp.4533.44., The study was conducted by analyzing all the components that affect the cost of provision of CNG price, with a Monte Carlo simulation with the help of Crystal Ball software which refers to government policies such as the Minister of Energy and Mineral Resources Regulation No. 19 of 2010, which has set the pricing formula of gas fuel for transportation by considering the price at the point of delivery (upstream), toll fee, SPBGs investment, operating and maintenance costs SPBGs, margins and taxes. On This study peeling toll fee by choosing supply chain that is considered appropriate for the region Western of Java. Study results CNG price to Regional Java, where the simulation is done in Jakarta found that the Decree of the Minister of Energy and Mineral Resources No. 2932 K / 12 / MEM / 2010: "Selling Price Gas Fuel used for transportation in Jakarta area including Bogor, Bekasi, Depok and Tangerang is $ 3100.00 (three thousand one hundred dollars) for every 1 (one) liter Premium Equivalent (LSP), including taxes. "a competitive price that can be implemented for the region western of Java. Judging from the results of recalculation is the price of CNG at the tapping point Bitung of $. 0.223 or Rp. 2819.82 and aggregation price of Rp. 2737.58 with the real price is in the range of price Rp.1857, 43 up to Rp. 3890.32 (based on the Consumer Price Index April 2015) and in the region of Nagrak tapping points. $.0.209 or Rp. 2631.02 and aggregation price of Rp. 2795.51 with the real price is in the range of price Rp.2227,59 up to Rp.4533.44.]"

"ABSTRAKTesis ini membahas harga keekonomian gas di sektor Hulu dengan menganalisa harga keekonomian pengembangan lapangan atau Plant of Development-POD, Biaya Operasional, Abandonment Site Restoration beserta seluruh komponen keekonomian lainya seperti Asumsi harga, IRR, NPV, Tax, Perjanjian Jual Beli Gas serta komponen harga pada rantai nilai Industri Gas bumi dari hulu ke hilir dengan mempertimbangkan biaya-biaya yang dibutuhkan diantaranya biaya transmisi dan distribusi, pengalokasian gas, strategi dan kebijakan penetapan harga, skema penjualan serta type kontrak yang digunakan. Analisa ekonomi dilakukan dengan menghitung Net Back Value (NBV) serta Simulasi Monte Carlo untuk menggambarkan perubahan variable yang tidak pasti untuk mendapatkan sensitivitas dalam analisa ekonomi. Pada akhir penelitian ini diharapkan dapat diketahui seberapa besar harga keekonomian gas bumi di sektor hulu untuk alokasi kebutuhan gas domestic.

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ABSTRACTThis Thesis discusses the economic price of gas in Indonesia by analyzing the economic price of field development and gas industry value chain from upstream to downstream taking into account the costs required by the producer gas (upstream costs), the cost of transmission and distribution, gas allocation, strategy and pricing policies, sales scheme and type of contract used. Economic analysis is done by calculating the Net Back Value (NBV) as well as Monte Carlo simulations to describe the uncertain variables change to get the sensitivity of the economic analysis. At the end of this study are expected to know how big the economic price of natural gas in the upstream sector for allocation of domestic gas demand, as a case study in this research will also be analyzed Gas Sale Contract in Upstream Oil Company which will be evaluated against the results of the analysis of economic gas prices in Indonesia based on the simulation results of the value chain"

"ABSTRAKUntuk memenuhi kebutuhan energi seiring dengan menurunnya produksi minyak, pemanfaatan gas menjadi solusi untuk dapat memenuhi kebutuhan energi. Produksi gas Indonesia pada tahun 2015 adalah 8,102 MMSCFD berdasarkan data dari SKK Migas.Saat ini pemerintah sedang menggalakkan pembangunan jaringan gas kota di Indonesia, salah satunya di Kecamatan Muara Satu Kota Lhokseumawe. Salah satu perusahaan pemerintah berencana akan membangun 89.383 sambungan rumah tangga sampai tahun 2017 di seluruh Indonesia.Mengingat akan ada banyak proyek jaringan gas kota, penting bagi kita menganalisis risiko yang mungkin terjadi selama konstruksi maupun selama operasi dari jaringan gas tersebut. Pada penelitian ini dilakukan identifikasi risiko, kemudian mengelompokkan risiko tersebut sesuai kategorinya, kemudian dilakukan analisis kualitatif dan analisis kuantitatif dengan simulasi Monte Carlo, lalu hasilnya dievaluasi. Dengan menghitung risiko secara keseluruhan, risiko proyek jaringan gas di Kota Lhokseumawe ini tergolong rendah dengan nilai risk 3,72.Hasil penelitian ini adalah berupa strategi untuk menurunkan risiko-risiko dan kerugian yang mungkin timbul. Dengan adanya strategi penanganan terhadap risiko-risiko yang mungkin timbul, kerugian biaya dapat diturunkan menjadi 10% atau sekitar 4,5 milyar rupiah.

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ABSTRACTTo fulfill energy demand because of decreasing oil production, converting oil to gas is a good choice. Based on data from SKK Migas in 2015, Indonesia produced 8.102 MMSCFD gas.Nowdays, Indonesia?s government encourages gas pipeline project for citygas in several cities in Indonesia. One of company owned by government plans to build 89.383 connection until 2017 in Indonesia.In the future, there are many citygas projects in Indonesia, risk analysis during construction and operation of pipeline project will be an important thing. This research included risk indentification, grouping the risk into their categories, then we analyze the risk both qualitative and quantitative using Monte Carlo simulation. The summary of all risk calculation shows that this project has low risk with value 3.72.The results of this research are strategies to reduce and manage the risks during pipeline construction and operation of citygas project. By applying the strategies, risks can be reduced from 29% to 10%. It is equivalent with 4,5 billion rupiahs."

"Penelitian ini membahas mengenai potensi antrian yang mungkin ditimbulkan oleh restoran "Warung Nagih" dengan menggunakan data observasi yang sudah dikumpulkan dan dilakukan perhitungan menggunakan simulasi dengan metode Monte Carlo. Metode perhitungan simulasi Monte Carlo dilakukan dengan menggunakan program Microsoft Excel. Metode penelitan yang digunakan adalah deskriptif studi kasus dengan pendekatan kuantitatif. Dari simulasi yang dilakukan didapatkan hasil baik pada hari jumat dan hari sabtu tidak ditemukan adanya potensi antrian. Namun didapatkan hasil meja available lebih banyak pada hari jumat dibandingkan hari sabtu. Selain itu dilakukan peramalan dengan simulasi Monte Carlo dengan kapasitas 75% dari maksimal yang dimiliki restoran "Warung Nagih" yaitu sebanyak 23 meja dari 31 meja saat maksimum. Didapatkan hasil pada hari jumat terjadi 2 kejadian antrian dari 52 minggu percobaan simulasi dengan probabilitas terjadi antrian sebesar 3,8% dan pada hari sabtu terjadi 20 kejadian antrian dari 52 minggu percobaan simulasi dengan probabilitas terjadinya antrian sebesar 38%. Didapatkan hasil potensi antrian lebih besar pada hari sabtu dibandingkan jumat karena pada hari sabtu lebih banyak pelanggan yang datang dibandingkan hari jumat. Hasil peramalan ini dilakukan untuk persiapan guna menghadapi jika terjadi antrian di masa depan.

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This study discusses the queue potential that maybe occured in "Warung Nagih" restaurant by using observational data that already collected and performed calculations using Monte Carlo simulation method. Monte Carlo simulation method of calculation is done using Microsoft Excel program. This research is using descriptive, case study method with quantitative approach. The results obtained both on Friday and Saturday did not reveal any queues potential. But the results obtained more available table on Friday than Saturday. After that we doing forecast using Monte Carlo simulation method with 75 % of the maximum capacity owned by the restaurant "Warung Nagih" which is 23 tables from 31 tables on maximum capacity. That simulation results is on Friday occurred 2 queue events of 52 week simulation experiment with queue probability occurance is 3,8% and on Saturday occurred 20 queue events of 52 week simulation experiment with queue probability occurance is 38%. This simulation result showed greater potential queues on Saturday than Friday because more customer coming on Saturday than Friday This forecasting is done in preparation to face queue situation in the future."

"Pemerintah Indonesia melalui Undang-Undang Nomor 44 Tahun 2009 mewajibkan semua alat Kesehatan untuk dikalibrasi. Sebagai implementasi dari peraturan tersebut, Kementerian Kesehatan menerbitkan Peraturan Menteri Kesehatan Nomor 54 Tahun 2015 yang mengharuskan alat kesehatan untuk dikalibrasi minimal sekali dalam satu tahun. Defibrillator adalah salah satu alat kesehatan yang berfungsi untuk memberikan kejutan listrik kepada pasien yang mengalami gangguan jantung. Untuk memastikan akurasi dan ketertelusuran metrologi, defibrillator harus dikalibrasi minimal satu kali dalam setahun. Dalam melakukan kalibrasi defibrillator, digunakan perangkat bernama defibrillator analyzer. Seperti halnya defibrillator, defibrillator analyzer juga harus dikalibrasi untuk memastikan akurasi dan ketertelusuran metrology. Metode Monte Carlo digunakan dalam kegiatan kalibrasi defibrillator analyzer dengan menggunakan high voltage differential probe untuk melakukan estimasi ketidakpastian pengukuran. Metode Monte Carlo menggunakan propagasi distribusi dan umumnya memberikan hasil yang lebih dekat dengan kenyataan serta menghasilkan nilai ketidakpastian yang lebih baik. Hasil dari kalibrasi defibrillator analyzer adalah nilai pengukuran (measurand) dengan persentase antara 93% hingga 95%, dan perhitungan ketidakpastian menggunakan Metode Monte Carlo menghasilkan ketidakpastian yang valid sebesar 100%.

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The Indonesian Government, through Law Number 44 of 2009, mandates calibration for all healthcare equipment. As an implementation of this provision, the Ministry of Health issued Ministerial Regulation Number 54 of 2015 concerning Testing and Calibration of Healthcare Equipment, which requires healthcare equipment to be calibrated at least once a year. A defibrillator is a medical device used to deliver an electric shock to patients with heart problems. To ensure accuracy and metrological traceability, a defibrillator must be calibrated at least once a year. During the calibration of a defibrillator, a device called a defibrillator analyzer is used. Similar to the defibrillator, the defibrillator analyzer also needs to be calibrated to ensure accuracy and metrological traceability. The Monte Carlo method is used in the calibration of the defibrillator analyzer, utilizing a high voltage differential probe to estimate measurement uncertainty. The Monte Carlo method employs distribution propagation and generally yields results closer to reality, producing better uncertainty values. The result of the defibrillator analyzer calibration is a measurand value (measurement value) ranging between 93% and 95%, and the uncertainty calculation using the Monte Carlo method yields a valid uncertainty value of 100%."

"Keadaan masa depan tidak dapat diketahui dengan pasti. Investasi yang kita lakukan sekarang belum tentu menguntungkan pada masa yang akan datang, begitu pula dengan investasi jalan tol. Dengan adanya ketidakpastian ini, maka pemasukan analisa risiko dalam kaitannya dengan penganggaran modal dan investasi menjadi sangat penting.Dalam identifikasi risiko keterlibatan para pakar investasi sangat dibutuhkan. Oleh karena itu, dibuatlah kuesioner. Dari penelitian ini teridentifikasi risiko-risiko yang terjadi dalam investasi jalan tol dan probabilitas masing-masing, dengan menggunakan metode Analitical Hierarchy Process (AHP). Risiko ini dikelompokkan dalam risiko kebijakan pemerintah, risiko dalam pelaksanaan konstruksi, risiko keuangan dan ekonomi, serta risiko lingkungan. Risiko yang paling, besar adalah risiko tarif.Salah satu teknik analisa risiko adalah Simulasi Mama Carlo. Simulasi untuk risiko tarif dan biaya pernbebasan tanah, dengan mempertimbangkan faktor inflasi dan tingkat suku bunga menghasilkan berbagai tingkat kelayakan untuk distribusi NPV dan IRR, antara lain probabilitas kelayakan NPV hampir 100%, dan probabilitas kelayakan IRR senilai 92.69% ketika tarif tol sesuai harapan investor dan tidak ada kenaikan biaya pembebasan tanah.

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Future is uncertainty. Money we invest now is uncertainly to give benefit in the future, i.e. in toll road investment. Therefore, incorporating risk analysis in capital budgeting and investment is really important.

In order to identify the risks, expert judgment is actually needed. This research has identified the risks and their likelihood, by Analytical Hierarchy Process (AHP) method, in group of government risks, construction risks, financial and economics risks, and environmental risks. The big risk is toll fee risk with the likelihood of 0.221.

One of risk analysis tools is Monte Carlo simulation. The simulation of toll fee risk and land acquisition cost risk, regarding inflation rate and discount rate, results several certainty level for NPV and IRR, for example almost 100% certainty level for NVP, and 92.69% certainty level for IRR when the toll fee is suitable for investor and no added cost for the land acquisition."

"Di industri minyak bumi dan gas, pipa merupakan komponen utama yang ada dalam industri tersebut. Karena pipa merupakan komponen utama, maka pipa tersebut harus mendapatkan perhatian lebih dikarenakan kegagalan dalam sistem perpipaan, khususnya dalam industri minyak bumi dan gas, menjadi permasalahan yang sangat serius karena menimbulkan kerugian yang cukup besar. Salah satu cara untuk meminimalisir kegagalan tersebut adalah melalui inspeksi berbasis risiko. Dalam inspeksi berbasis risiko, digunakan simulasi Monte Carlo untuk mengetahui probabilitas komponen mengalami kegagalan. Pada umumnya, simulasi Monte Carlo menggunakan distribusi Normal dalam penentuan Random Variabel Generator. Namun, terdapat kemungkinan data yang dihasilkan adalah Bias, yaitu terdapat error sampling sehingga data tersebut menjadi kurang akurat dikarenakan nilai hasil dari distribusi Normal dapat bernilai negatif. Pada distribusi Normal, dihasilkan data yang sifatnya overestimation data. Maka dari itu, dibutuhkan metode lain untuk penentuan Random Variabel dimana data yang dihasilkan tidaklah bias sehingga akurasi hasil dari Inspeksi Berbasis Risiko meningkat. Metode Weibull dapat mengurangi biased data yang dihasilkan dari distribusi Normal.

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Pipes are the main component in the oil and gas industries, and it needs a serious attention due to the high risk of the piping system failure. The failure of the piping system leads to a very serious consequence since it caused huge material losses, and the Risk-Based Inspection can minimize the failure. Risk-Based Inspection using the Monte Carlo Simulation for calculating the failure probabilities of the component. In general, Normal distribution is used in Monte carlo simulation for Random Variable Generator. However, it is possible that the generated data is called Bias, i.e. there is an error sampling, so the resulting data becomes inaccurate. In the Normal distribution, the result of the data produce an overestimation data because the result of the data can be negative on the corrosion rate. Therefore, we need another method for determining Random Variables where the generate data is not biased so the accuracy of the results of the Risk-Based Inspection increases, and the Weibull method can reduce the biased data generated from the Normal distribution."

"Permasalahan industri gas domestik di Indonesia saat ini adalah ketidakpastian alokasi pasokan gas domestik, minimnya infrastruktur, serta permasalahan harga jual gas. Untuk meningkatkan alokasi gas industri, harga gas domestik seharusnya dinaikkan, sehingga disparitasnya tidak terlalu jauh dengan harga gas ekspor. Di sisi lain, adanya monopoli akses transportasi jalur pengangkutan gas di Indonesia menyebabkan industri harus membayar harga gas lebih mahal dari yang sewajarnya. Pada penelitian ini dilakukan simulasi untuk mendapatkan harga gas yang layak dalam rangka membantu Pemerintah dalam menetapkan harga gas agar tidak selalu terpaku pada harga gas yang ditetapkan oleh pedagang gas (trader) dan pengangkut gas (transporter). Metode yang digunakan dalam penentuan harga gas ini adalah metode Netback Value (NBV). Pengolahan data dalam penelitian ini menggunakan analisis ketidakpastian untuk mendapatkan validasi ketidakpastian dengan simulasi Monte Carlo menggunakan piranti lunak Crystal Ball. Berdasarkan penelitian, didapatkan rasio pembiayaan antara sektor hulu dan hilir untuk harga jual gas rekalkulasi dengan kondisi ideal (biaya transmisi jalur pipa Pertagas serta prediksi biaya distribusi didasarkan informasi laporan tahunan PGN) sebesar lebih dari satu atau mendekati satu. Hal ini masih wajar mengingat sektor hulu memiliki nilai investasi lebih tinggi untuk melakukan aktivitas ekplorasi dan produksi, dibandingkan dengan sektor hilir. Sementara itu, jika dibandingkan dengan harga jual gas bumi PGN baik untuk sektor listrik dan sektor industri non pupuk, terdapat perbedaan yang sangat signifikan sehingga menyebabkan rasio pembiayaan sektor hulu dan hilir tidak realistis.

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Domestic gas industry?s problems in Indonesia are uncertain allocation for domestic gas supply, lack of infrastructure, and also gas price issue. To improve the gas allocation for domestic industrial sector, domestic gas prices should be raised, so that the disparity between domestic gas price and export gas price is not too far away. On the other hand, the existence of monopoly of gas trader and transporter in Indonesia caused the industry has to pay the price of gas more expensive than normal. In this study conducted a simulation to get decent gas prices in order to give recommendation to the Government in determining the price of gas that does not always get hung up on the price of gas that is determined by gas traders and transporters. The method used in determining the gas price is the Netback Value method (NBV). The data in this study is processed using uncertainty analysis to with Monte Carlo simulation using Crystal Ball software. Based on the study, the cost ratio between the upstream and downstream sectors for gas price recalculation with ideal conditions (using Pertagas pipeline transmission costs and distribution cost based on annual report of PGN) is more than one or close to one. It is still reasonable considering the upstream sector has a higher investment value for exploration and production activities than the downstream sector. Meanwhile, when compared with the gas price from PGN, there are very significant differences that cause the cost ratio of the upstream and downstream sector is not realistic."

"This book has two objectives. First, it is a primer on the kMC method (predominantly using the lattice-gas model) and thus much of the book will also be useful for applications other than to surface reactions. Second, it is intended to teach the reader what can be learned from kMC simulations of surface reaction kinetics. "