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"When an exchange of goods and services takes place across national boundaries, it is called international trade. Import is the part of international trade. The focus of this research is only about import. Indonesia has a lot of airport and seaport where the part of controlling by customs. An individual customs officers has limited hours each day in which to do his job. During this time the officer must decide which cargo to search and how detailed the search should be. It is impossible to examine all movements with only the limited resources of manpower and equipment that customs authorities have.The Research Method that used in this research is qualitative method. The data collecting techniques that used are field and library research. While the analyzes technique which the writer used is descriptive technique. Risk from a customs viewpoint, consider what risks would be involved in clearing import consignments based solely on the trader declaration. Risk management is adopted by customs. Analysis of determination risk ranking in import is based on importer profile and goods profile. The Categories of Importer Profile are divided into three groups, which are Hi-Risk, Medium Risk, and Low Risk. Also, The categories of Goods Profile are divided into three groups. They are Very Hi-Risk (which is determined by Government), Hi-Risk and Low-Risk.Based on these two profile, will be applied risk management. The output of risk management is the line which is determined by Customs, they are Red Line and Green Line. For the Red Line which will be applied physics and document examination. For the green line, there will be no physics examination, only document examination. The aim of risk management is to reach an ideal condition from controlling function and service function which was doing by Customs. The Purpose of customs control is to ensure that all movements of goods, vessels, vehicles, aircraft crossing national borders occur within the framework of laws, regulation and procedures that comprise the customs clearance process.In addition, this research is also expected to give suggestions for government to make a transparency of profiling process, socializing goods profile in order to let importer know about the criteria of profiling and also systemic and integrated improvement through National Single Window within another Department."

"This new book presents a comprehensive overview of the current ?state of the art? of ranking in higher education and research, and introduces a completely new approach called ?multidimensional ranking?. In part 1 rankings are discussed in the broader context of quality assurance and transparency in higher education and research. In addition the many current ranking methodologies are analyzed and critized, and their impacts are explored. In part 2 a new approach to ranking is introduced, based on the basic idea that higher education and research institutions have different profiles and missions and that the performances of these institutions should reflect these differences. This multidimensional approach is operationalized in a new multidimensional and user-driven ranking tool, called U-Multirank. U-Multirank is the outcome of a pilot project, sponsored by the European Commission, in which the new ranking instrument was designed and tested at a global scale."

"Query becomes one of the most decisive factor on documents searching. A query contains several words, where one of them will become a key term. Key term is a word that has higher information and value than the others in query. It can be used in any kind of text documents, including Arabic Fiqh documents. Using key term in term weighting process could led to an improvement on result?s relevancy. In Arabic Fiqh document searching, not using the proper method in term weighting will relieve important value of key term. In this paper, we propose a new term weighting method based on Positive Impact Factor Query (PIFQ) for Arabic Fiqh documents ranking. PIFQ calculated using key term?s frequency on each category (mazhab) on Fiqh. The key term that frequently appear on a certain mazhab will get higher score on that mazhab, and vice versa. After PIFQ values are acquired, TF.IDF calculation will be done to each words. Then, PIFQ weight will be combine with the result from TF.IDF so that the new weight values for each words will be produced. Experimental result performed on a number of queries using 143 Arabic Fiqh documents show that the proposed method is better than traditional TF.IDF, with 77.9%, 83.1%, and 80.1% of precision, recall, and F-measure respectivel.

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Query menjadi salah satu faktor penentu dalam pencarian dokumen. Dalam sebuah query terdiri dari beberapa kata, dimana salah satunya menjadi key term. Key term adalah kata yang memiliki nilai informasi dan bobot lebih tinggi dibandingkan kata lain. Hal tersebut berlaku untuk semua jenis dokumen teks, termasuk dokumen fiqih berbahasa Arab. Penitik beratan pada key term dalam proses pembobotan kata memungkinkan terjadinya peningkatan relevansi pencarian. Di dalam pencarian dokumen fiqih berbahasa Arab, jika metode pembobotan kata yang digunakan tidak tepat, key term tidak akan memberikan pengaruh berarti. Oleh karena itu diusulkanlah sebuah metode pembobotan baru pada kata berbasis Positive Impact Factor Query (PIFQ) untuk perangkingan dokumen fiqih berbahasa arab. PIFQ dihitung menggunakan frekuensi kemunculan key term pada setiap kategori (mazhab) dalam fiqih. Semakin tinggi frekuensi key term tersebut pada suatu mazhab semakin tinggi pula nilainya pada mazhab tersebut, begitu pula sebaliknya. Setelah didapat nilai PIFQ, kemudian dilakukan perhitungan TF.IDF untuk setiap kata. Selanjutnya bobot PIFQ akan dikom-binasikan dengan TF.IDF sehingga menghasilkan bobot baru untuk masing-masing kata. Hasil dari pengujian yang dil-akukan pada sejumlah query dengan 143 dokumen fiqih berbahasa Arab menunjukan bahwa metode usulan dapat lebih unggul jika dibandingkan metode TF.IDF, dengan nilai precision, recall, dan F-measure masing-masing sebesar 77,9%, 83,1%, dan 80,1%."

"Laporan ini menjelaskan tentang metode penilaian kinerja yang digunakan oleh perusahaan perjudian yang bernama Millenium Leisure. Laporan ini menjawab tentang pertanyaan yang ditanyakan sehubungan dengan keterbatasan penilaian kinerja lama (Stacked Ranking). Selanjutnya, kami mengajukan metode penilaian kinerja yang baru (Balanced Scorecard), yang dimana kami pun memasukkan beberapa keuntungan dalam pemakaiannya. Pada akhirnya, kami memberikan sistem pemberian upah yang berdasarkan dengan metode penilaian kinerja tersebut.

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This report explains about the performance ranking methods practiced by Gambling Company in Australia named Millenium Leisure. The report starts directly answering the question that we have been asked about limitations by using the old method of performance ranking (Stacked Ranking). Furthermore, we introduce the new performance ranking (Balanced Scorecard) method which we include the advantages of using it. At the end of the report, we give them the remuneration system based on the performance ranking method we suggest."

"Tujuan dari penelitian ini adalah untuk menganalisis peringkat risiko sistemik dari enam metodologi pengukuran risiko sistemik yang dikenal serta mengembangkan peringkat risiko sistemik komposit menggunakan metode Principal Component Analysis (PCA), mengacu pada Nucera et al. (2016). Systemically Important Financial Institutions (SIFIs) didefinisikan sebagai 10 perusahaan yang memiliki risiko sistemik tertinggi dalam setiap pemeringkatan dari total sampel 60 lembaga keuangan yang go public selama periode 2008-2016. Dari hasil studi, peringkat komposit yang kami kembangkan lebih konsisten dalam menjelaskan komposisi SIFIs dari kebanyakan pemeringkatan risiko sistemik individu lainnya. Dari hasil PCA, ditemukan bahwa peringkat komposit yang kami hasilkan terutama dijelaskan oleh metode pemeringkatan berbasis data pasar. Lebih lanjut, kami menemukan perbedaan yang substantial antara pemeringkatan berbasis data pasar dan pemeringkatan berbasis data fundamental dalam menjelaskan peringkat risiko komposit. Oleh karena itu, dapat diduga bahwa peringkat risiko sistemik komposit, yang menggabungkan aspek pasar dan fundamental, akan memberikan informasi yang lebih lengkap bagi pengambil kebijakan dalam membuat keputusan di masa depan.

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The aim of this study is to incorporate systemic risk ranking from six generally accepted metrics and develop a single composite ranking using Principle Component Analysis, based on Nucera et al. (2016). We analyze the Systemically Important Financial Institutions (SIFIs) to gather information difference between systemic risk metrics. We identify SIFIs as the top 10 companies in each systemic risk metrics ranking, using a sample of 60 listed financial institutions in Indonesia over the period 2008-2016. We find that our single composite ranking is more consistent in term of SIFIs composition than most individual risk rankings. Furthermore, according to factor loadings of the first component, our single composite ranking is mainly based on market-based instead of fundamental. Based on second factor loading, we find that market-based metrics and fundamental-based metrics deviated substantially in constructing our composite ranking. Therefore, we suspect that our single composite ranking, that combines both market and fundamental aspect, will provide better insight for the regulator to make a decision."

"Banyaknya dokumen pada Internet menuntut adanya mesin pencari. Mesin pencari yang ada saat ini dapat menemukan dokumen atau informasi berdasarkan kata kunci tertentu. Namun terkadang dokumen hasil pencarian tidak relevan dengan informasi yang dibutuhkan. Penelitian dalam tugas akhir ini bertujuan untuk membuat sistem yang dapat melakukan ekspansi kata kunci pada mesin pencari dengan menggunakan metode relasi fuzzy.Relasi fuzzy merupakan suatu metode yang dapat menggambarkan hubungan antara dua buah objek. Dengan adanya ekspansi kata kunci, diharapkan hasil pencarian yang didapatkan akan lebih banyak dan dapat ditemukan dokumen dengan kata kunci lain namun memiliki relevansi dengan informasi yang dibutuhkan.Dengan ekspansi kata kunci sebagai dasar, penelitian tugas akhir ini juga kemudian melakukan pemeringkatan hasil pencarian dengan menggunakan sistem inferensi fuzzy Takagi-Sugeno-Kang (TSK) orde-satu. Penelitian tugas akhir ini dibatasi pada kata kunci berbahasa Indonesia dan ekspansinya dibatasi maksimal tiga kata kunci.

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The existence of search engine is required due to the increasing number of documents on the Internet. Search engines are able to find documents or information based on certain keyword. But the search results are seldom irrelevant with the necessary information. The aim of this final project research is to build a system which is able to expand the keyword on search engine using fuzzy relation.Fuzzy relation is a method which is capable of describing the relationship between two objects. The expectation of the keyword expansion is to enable users to get more search results and perhaps some of them are relevant with the necessary information.With the keyword expansion as basic, this final project research then ranks the search results using the orde-one Takagi-Sugeno-Kang (TSK) fuzzy inference system. The system can only accept keyword in Indonesian language, and will only have three keyword expanded in maximum."

"The cloud is an outstandingplatform to deal with functionally equivalent services which are exponentiallyincreasing day-by-day. The selection of servicesto meet the client requirements is a subtle task. The services can be selected byranking all the candidate services using their network and non-network Quality-of-Service (QoS) parameters, which is formulated as a NP hard optimization problem. In this paper, weproposed a linear discriminant analysis (LDA) based a four level matching model for service selection based on QoS parameters,which includes description matching of a service, matchmaking phase, LDA-based QoS matching and ranking. The LDA-serviceselection agent is deployed on each cloud to classify services into classes andrank the services based on the aggregate QoS value of each service. Finally,the test results show the efficiency in service selection with minimaldiscovery overhead, significant reduction in the computation time and thenumber of candidate services to be considered."

"Federated Cloud Architecture is a heterogeneous and distributed model that providesinfrastructures related to the cloud by aggregating different Infrastructure-as-a-Service (IaaS) providers. In this case, it is an exciting task toselect the optimal service cloud provider for the customer and then deploy it. In this paper,a new provider discoveryalgorithm and fuzzy sets ranking model is proposed in the modified federatedarchitecture and thenthe performance isevaluated. The proposeddiscovery method shortlists the provider based on the Quality of Service (QoS)indicators suggested by the Service Measurement Index (SMI) with the Service LevelAgreement (SLA) thatprovides improved performance. In addition to that, the cost is also included thatrepresents thefulfillment at the level of the end user. The ranking mechanism is based on a Fuzzy set approach, having three general phases, such as problem decomposition, judgment ofpriorities and an aggregationof these priorities. With some simple rules, the fuzzy set may be combined with the QoS indicators. The WeightedTuned Queuing Scheduling (WTOS) Algorithm is proposed to resolve the issue of starvation in theexisting architecture and manage the requests effectively. Experimental resultsshow that the proposedarchitecture has abetter successful selection rate, average response time and less overhead,compared to the existing architecture that had supported the Cloud environment."