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"Implementasi Voice Over IP(VoIP) yaitu percakapan melalui jaringan IP (Internet Protocol), telah banyak digunakan oleh operator telekomunikasi mapun perusahaan-perusahaan besar di dunia. Hal tersebut disebabkan kecenderungan semua platform jaringan menggunakan teknologi IP. Dengan semakin terbukanya softswitch (sentral telepon berbasis IP) dan media gateway terhadap jaringan IP Publik dan jaringan IP Pelanggan, serta kebutuhan remote ke perangkatperangkat tersebut dengan menggunakan IP, maka hal tersebut meningkatkan resiko terhadap keamanan informasi. Operator telekomunikasi memerlukan suatu pengembangan atau penyempurnaan sistem keamanan informasi yang dapat menjamin availability, confidentiality dan integrity sehingga diharapkan target performansi perusahaan dan ekspektasi pelanggan dapat tercapai. Penelitian ini dilakukan untuk menyusun sistem keamanan informasi khususnya sub kebijakan keamanan informasi di Jaringan Telepon Tetap yang berbasis IP pada PT Indosat, Tbk serta strategi penerapannya. Penyusunan rancangan ini dilakukan dengan merujuk kepada kendali-kendali ISO (the International Organization for Standarization) 27001:2005, serta rujukan-rujukan lainnya termasuk materi kuliah Manajemen Resiko. Hasil dari penelitian diharapkan dapat memberikan masukan yang bermanfaat bagi penerapan sistem keamanan informasi untuk lingkup jaringan telepon tetap di PT Indosat.

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Voice Over Internet Protocol (VoIP) has been implemented by many telecommunication providers (Telco Provider) and many big companies in the world. That is caused of all telecommunication platform tend to use IP Platform. Since the softswitch as telephony switching can be accessed from public or customer using IP interconnection, and also need to access (remote) those equipment using IP, that will increase the risk of Information Security. They need to develop or improve the Information Security for ensuring the availability, confidentiality and integrity that be able to reach the performance target as customer or top management expectation. The purpose of this research is to develop information security for IP Based Fixed Telephony Network especially developing prioritized Information Security Policy and developing implementation strategy for improving Information Security. This research refer to controls of ISO (the International Organization for Standarization) 27001:2005 and other references (including handout of Risk Management program study) that mentioned in reference list. Hope the result of this research will be benefit for PT Indosat or other academic institutional regarding with Information Security Development For IP Based Fixed Telephony Network."

"The ITCS-12 will provide an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of ITCS. In addition, the conference will publish high quality papers which are closely related to the various theories, modeling, and practical applications in ITCS."

"If you continue to struggle to understand and measure how information and its quality affects your business, this book is for you. This reference is in direct response to the new challenges that all managers have to face. Our process helps your organization to understand the "pain points" regarding poor data and information quality so you can concentrate on problems that have a high impact on core business objectives. This book provides you with all the fundamental concepts, guidelines and tools to ensure core business information is identified, protected and used effectively, and written in a language that is clear and easy to understand for non-technical managers."

"Dalam era perkembangan teknologi, penerapan teknologi informasi menjadi kunci untuk meningkatkan efisiensi dan efektivitas operasional perusahaan. Data science memainkan peran penting dalam mengubah data besar menjadi pengetahuan yang berguna untuk pengambilan keputusan. Skripsi ini mengembangkan platform AutoML (Automated Machine Learning) pada aplikasi Lumba.ai yang dirancang untuk mempermudah proses prediksi tanpa memerlukan keterampilan teknis khusus. AutoML menawarkan tur otomatisasi untuk memilih model terbaik berdasarkan dataset yang diberikan, serta menyederhanakan proses pemrosesan data. AutoML diimplementasikan menggunakan message queuer dan worker secara asinkron. Prediksi pada tur AutoML dilakukan menggunakan tiga jenis metode prediksi, yaitu klasi kasi, regresi, dan klaster, dengan berbagai dataset untuk menilai kinerja model yang dihasilkan. Hasil penelitian menunjukkan bahwa Lumba.ai dapat memberikan hasil prediksi yang akurat dan e sien, serta memberikan visualisasi yang informatif untuk analisis lebih lanjut. Saran dan masukan dari pengguna juga diintegrasikan untuk meningkatkan fungsionalitas dan kegunaan platform.

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In the era of technology development, the application of information technology is crucial for enhancing operational ef ciency and effectiveness. Data science plays a vital role in transforming big data into useful knowledge for decision-making. This thesis develops an AutoML (Automated Machine Learning) feature on Lumba.ai application, designed to facilitate prediction processes without requiring specialized technical skills. Lumba.ai offers automated features for selecting the best model based on the given dataset and simpli es data preprocessing. This feature is implemented by using asynchrnous worker and message queuer. Predictions from AutoML feature involves three types of prediction methods, that is classi cation, regression, and clustering, using various datasets to assess model performance. The results demonstrate that Lumba.ai provides accurate and ef cient predictions and offers informative visualizations for further analysis. User feedback is integrated to enhance the platform’s functionality and usability."

"Dalam era perkembangan teknologi, penerapan teknologi informasi menjadi kunci untuk meningkatkan efisiensi dan efektivitas operasional perusahaan. Data science memainkan peran penting dalam mengubah data besar menjadi pengetahuan yang berguna untuk pengambilan keputusan. Skripsi ini mengembangkan platform AutoML (Automated Machine Learning) pada aplikasi Lumba.ai yang dirancang untuk mempermudah proses prediksi tanpa memerlukan keterampilan teknis khusus. AutoML menawarkan tur otomatisasi untuk memilih model terbaik berdasarkan dataset yang diberikan, serta menyederhanakan proses pemrosesan data. AutoML diimplementasikan menggunakan message queuer dan worker secara asinkron. Prediksi pada tur AutoML dilakukan menggunakan tiga jenis metode prediksi, yaitu klasi kasi, regresi, dan klaster, dengan berbagai dataset untuk menilai kinerja model yang dihasilkan. Hasil penelitian menunjukkan bahwa Lumba.ai dapat memberikan hasil prediksi yang akurat dan e sien, serta memberikan visualisasi yang informatif untuk analisis lebih lanjut. Saran dan masukan dari pengguna juga diintegrasikan untuk meningkatkan fungsionalitas dan kegunaan platform.

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In the era of technology development, the application of information technology is crucial for enhancing operational ef ciency and effectiveness. Data science plays a vital role in transforming big data into useful knowledge for decision-making. This thesis develops an AutoML (Automated Machine Learning) feature on Lumba.ai application, designed to facilitate prediction processes without requiring specialized technical skills. Lumba.ai offers automated features for selecting the best model based on the given dataset and simpli es data preprocessing. This feature is implemented by using asynchrnous worker and message queuer. Predictions from AutoML feature involves three types of prediction methods, that is classi cation, regression, and clustering, using various datasets to assess model performance. The results demonstrate that Lumba.ai provides accurate and ef cient predictions and offers informative visualizations for further analysis. User feedback is integrated to enhance the platform’s functionality and usability."

"Dalam era perkembangan teknologi, penerapan teknologi informasi menjadi kunci untuk meningkatkan efisiensi dan efektivitas operasional perusahaan. Data science memainkan peran penting dalam mengubah data besar menjadi pengetahuan yang berguna untuk pengambilan keputusan. Skripsi ini mengembangkan platform AutoML (Automated Machine Learning) pada aplikasi Lumba.ai yang dirancang untuk mempermudah proses prediksi tanpa memerlukan keterampilan teknis khusus. AutoML menawarkan tur otomatisasi untuk memilih model terbaik berdasarkan dataset yang diberikan, serta menyederhanakan proses pemrosesan data. AutoML diimplementasikan menggunakan message queuer dan worker secara asinkron. Prediksi pada tur AutoML dilakukan menggunakan tiga jenis metode prediksi, yaitu klasi kasi, regresi, dan klaster, dengan berbagai dataset untuk menilai kinerja model yang dihasilkan. Hasil penelitian menunjukkan bahwa Lumba.ai dapat memberikan hasil prediksi yang akurat dan e sien, serta memberikan visualisasi yang informatif untuk analisis lebih lanjut. Saran dan masukan dari pengguna juga diintegrasikan untuk meningkatkan fungsionalitas dan kegunaan platform.

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In the era of technology development, the application of information technology is crucial for enhancing operational ef ciency and effectiveness. Data science plays a vital role in transforming big data into useful knowledge for decision-making. This thesis develops an AutoML (Automated Machine Learning) feature on Lumba.ai application, designed to facilitate prediction processes without requiring specialized technical skills. Lumba.ai offers automated features for selecting the best model based on the given dataset and simpli es data preprocessing. This feature is implemented by using asynchrnous worker and message queuer. Predictions from AutoML feature involves three types of prediction methods, that is classi cation, regression, and clustering, using various datasets to assess model performance. The results demonstrate that Lumba.ai provides accurate and ef cient predictions and offers informative visualizations for further analysis. User feedback is integrated to enhance the platform’s functionality and usability."

"[ABSTRAKSeiring dengan pesatnya perkembangan teknologi informasi dan internet dewasa ini membawa perkembangan bisnis di segala bidang termasuk juga bagi penyedia jasa permainan rsquo game online rsquo Agar bisa melayani pelanggannya dengan baik dengan tingkat ketersedian yang tinggi diperlukan data center yang memiliki tingkat kehandalan yang baik Selain itu dengan berkembangnya bisnis penyewaan data center perusahaan juga berinisiatif untuk berinvestasi dalam pembangunan data center ini Karena investasi yang besar untuk pembangunan data center maka diperlukan perancangan data center yang bisa bertumbuh sesuai dengan kepentingan perusahaan atau organisasi termasuk didalamnya kepentingan bisnis dan ekonomi Untuk itu diperlukan penelitian yang mendalam tentang faktor faktor yang diperlukan dalam perancangan data center yang bisa bertumbuh dan sekaligus juga sesuai bagi kebutuhan spesifik perusahan Metodologi yang digunakan dalam pembuatan karya tulis ini adalah diawali oleh studi literatur untuk mendapatkan seluruh faktor termasuk seluruh opsinya untuk bisa merancang data center yang bisa bertumbuh Kemudian menyusunnya agar bisa didiskusikan dalam bentuk wawancara dan diskusi kelompok kepada lebih 9 orang ahli data center yang meliputi ahli perancangan data center para ahli sekaligus praktisi pembuat data center dan ahli sekaligus pengguna data center Dari hasil masukan wawancara dan diskusi kelompok Focus Group Discussion dengan peserta ahli data center penulis melakukan analis Pros Cons kepada faktor faktornya termasuk opsi yang memungkinkan data center bisa bertumbuh untuk perusahaan yang dimaksud analisis Pros Cons ini mengelompokan semua faktor tersebut ke dalam kategori untuk kemudian dirangkum dan disajikan kepada pihak perusahaan dalam rangka validasi hasil yang merupakan hasil final karya akhir ini Hasil finalisasi yang diharapkan bisa digunakan untuk perusahaan sebagai strategi pembangunan data centernya yang bisa bertumbuh dan sesuai dengan kebutuhan perusahaan Disamping itu juga hasilnya ini bisa menjadi bahan acuan bagi perancang data center lainnya tentang faktor faktor yang penting dalam perancangan data center yang bisa bertumbuh

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ABSTRACTAlong with the rapid development of information technology and the Internet today bringing business development in all areas including the game for service providers 39 online games 39 In order to serve its customers well with a high degree of availability the necessary data center that has a good level of reliability Moreover with the development of data center rental business the company also took the initiative to invest in the construction of this data center Because of a large investment for the construction of data centers it is necessary to design a data center that can grow in accordance with the interests of the company or organization including business and economic interests It required in depth research into the factors that are needed in the design of the data center that can grow and also according to the specific needs of the company The methodology used to create this thesis is preceded by a study of the literature to obtain all the factors including the option to be able to design the entire data center that could grow Then arrange them in order to be discussed in the form of interviews and group discussions to over 9 expert data center which includes data center design experts the experts at the same data center practitioners and experts maker and user of the data center From the feedback interviews and group discussions Focus Group Discussion with participants of data center experts the authors conducted a Pros Cons analyst to the factors including the option that allows data centers can grow to the company in question the Pros Cons analysis is to group all of these factors into categories for then summarized and presented to the company in order to validate the results of the final results of this thesis Finalization of the expected results can be used for enterprise data center as a development strategy that can grow and in accordance with company requirements Besides it is also the result of this could be a reference for data center designers other important factors in the design of the data center that could grow , Along with the rapid development of information technology and the Internet today bringing business development in all areas including the game for service providers 39 online games 39 In order to serve its customers well with a high degree of availability the necessary data center that has a good level of reliability Moreover with the development of data center rental business the company also took the initiative to invest in the construction of this data center Because of a large investment for the construction of data centers it is necessary to design a data center that can grow in accordance with the interests of the company or organization including business and economic interests It required in depth research into the factors that are needed in the design of the data center that can grow and also according to the specific needs of the company The methodology used to create this thesis is preceded by a study of the literature to obtain all the factors including the option to be able to design the entire data center that could grow Then arrange them in order to be discussed in the form of interviews and group discussions to over 9 expert data center which includes data center design experts the experts at the same data center practitioners and experts maker and user of the data center From the feedback interviews and group discussions Focus Group Discussion with participants of data center experts the authors conducted a Pros Cons analyst to the factors including the option that allows data centers can grow to the company in question the Pros Cons analysis is to group all of these factors into categories for then summarized and presented to the company in order to validate the results of the final results of this thesis Finalization of the expected results can be used for enterprise data center as a development strategy that can grow and in accordance with company requirements Besides it is also the result of this could be a reference for data center designers other important factors in the design of the data center that could grow ]"

"Gangguan fungsi TI pada organisasi dapat mengganggu bisnis organisasi. Oleh karena itu menjaga kualitas layanan yang tinggi dengan memaksimalkan ketersediaan layanan dan meminimalkan jumlah incident layanan TI menjadi hal yang penting. Pada kasus insiden mayor yang terjadi, penyelesaian gangguan TI yang berlangsung lama mengakibatkan terganggunya bisnis organisasi. Kecepatan memulihkan layanan setelah terjadinya gangguan tergantung pada seberapa cepat organisasi mengidentifikasi insiden dan seberapa baik disiapkan. Atas kejadian insiden mayor yang terjadi, Pimpinan tertinggi organisasi XYZ berharap adanya langkah taktis dan sistematis dalam antisipasi dan penanganan gangguan terhadap seluruh layanan TIK. Berdasarkan kondisi tersebut, tujuan penelitian ialah mengetahui faktor utama penyebab utama keterlambatan pemulihan layanan TIK yang terjadi sehingga dapat memberikan rekomendasi terhadap masalah dalam pemulihan layanan. Permasalahan pemulihan layanan dilihat dari empat faktor, yaitu Teknologi, Organisasi, Lingkungan dan Individu. Masing-masing faktor tersebut memiliki subfaktor yang didefinisikan pada penelitian sebelumnya. Untuk mengetahui masalah yang terjadi dilakukan wawancara dengan responden yang terlibat langsung serta dokumen terkait dengan pemulihan layanan. Untuk mengetahui faktor/subfaktor yang paling memengaruhi pemulihan layanan, maka dilakukan pembobotan terhadap faktor/subfaktor menggunakan teknik AHP. Hasil pembobotan faktor tertinggi ialah organisasi, sedangkan hasil pembobotan subfaktor tertinggi ialah persepsi manfaat kelangsungan bisnis. Setelah itu dilakukan penyusunan rekomendasi berdasarkan studi literatur. Hasil dari studi literature dilakukan validasi oleh organisasi melalui FGD dan pakar. Hasil penelitian memberikan rekomendasi perbaikan dari masalah yang ditemukan menggunakan pendekatan best practice ITIL.

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Impaired IT functions in organizations can disrupt the business organization. Therefore maintaining high service quality by maximizing service availability and minimizing the incident number of IT services becomes important. In the case of major incidents, resolving long standing IT disruptions results in disruption of the business organization. The speed of restoring services after the occurrence of interference depends on how quickly the organization identifies the incident and how well it is prepared. On the occurrence of major incidents, top level management of XYZ organization expects a tactical and systematic step in anticipating and handling disruptions to all ICT services. Based on these conditions, this research aim to study the main cause factors of IT disaster recovery problem that occurs so as to provide recommendations for it.

IT disaster recovery problem can be identified by 4 factors, which are technology, organization, environment and individual. Each of these factors has a subfactors defined in the previous study. To find out the problem, interviews with the respondents who involved directly as well as documents related to service recovery. To know the factors subfactors that most affect the recovery of services, then weighted factor subfaktor using AHP techniques. The result of the highest weighted factor is the organization, while the highest weighted subfactor result is the perception of business continuity benefit. After that, do the preparation of recommendations based on literature study. The results of the literature study were validated by the organization through FGDs and experts. The results provide an improvement recommendation of the problems using the best practice approach of ITIL."

"The book is a collection of invited papers on Computational Intelligence for Privacy and Security. The majority of the chapters are extended versions of works presented at the special session on Computational Intelligence for Privacy and Security of the International Joint Conference on Neural Networks (IJCNN-2010) held July 2010 in Barcelona, Spain."

"ABSTRACTThe endless development of technology and the proliferating usage of the Internet along with a pronounced financial transaction around the world generated Financial Technology. In Indonesia, the notoriety of Financial Technology is exhibited through the rapid development of startups within the society. Despite such progress, the legal aspect of financial technology regulations under the Indonesian law is deemed contentious. One of the implications of Financial Technology is the utilization of big data and monetization that is in correspondence with data privacy. Thus, this research will further expound the legal framework of Financial Technology in Indonesia and its repercussion on the availability of customer protection regarding data privacy in correlation to the practice of monetization. By way of juridical normative research, several laws and regulations regarding financial technology are assessed in correlation to the its implication on data privacy. Thrugh the analysis, it is found that although the legal framework has developed as regards its mechanism and correlation to the protection of data privacy through the enactment of laws and regulations, certain aspects still lack of legal protection and remain ambiguous. Furthermore the absence of codified law UU concerning data privacy and codified law undang undang, UU concerning the consumer protection of financial technology services, makes consumer protection in this respect rather lenient. However, aside from the laws and regulations, official institutions namely BI, OJK, KOMINFO, PPATK, and AFTECH provides consumer protection through the establisment of BI Fintech Office, Desk PPATK, Digital Economic and Finance Innovation Development Team and Fintech, as well as OJK and BI Regulatory Sandbox that directly assists the growth of financial technology fintech in the society.

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ABSTRAKPerkembangan teknologi yang tiada henti dan penggunaan Internet yang semakin banyak seiring dengan transaksi keuangan yang nyata di seluruh dunia menghasilkan Teknologi Keuangan. Di Indonesia, ketenaran Teknologi Keuangan terefleksi melalui pesatnya perkembangan startup dalam masyarakat. Terlepas dari kemajuan tersebut, aspek hukum peraturan teknologi keuangan menurut hukum Indonesia dianggap kontroversial. Salah satu implikasi Teknologi Finansial adalah pemanfaatan big data dan data monetisasi yang berkorespondensi dengan privasi data. Dengan demikian, penelitian ini akan menjelaskan lebij lanjut mengenai kerangka hukum Teknologi Keuangan di Indonesia dan dampaknya terhadap tersedianya perlindungan konsumen dalam aspek privasi data yang berkorelasi dengan praktik monetisasi. Melalui penelitian normatif yuridis, beberapa undang-undang dan peraturan mengenai teknologi keuangan akan dinlai korelasinya terhadap privasi data. Melalui analisa, ditemukan bahwa walaupun kerangka hukum telah berkembang baik terkait mekanisme dan korelasi terhadap perlindungan privasi data melalui pemberlakuan undang-undang dan peraturan, beberapa aspek masih dalam kekurangan perlindungan hukum dan tetap dalam keadaan ambigu. Selanjutnya tidak adanya undang-undang yang dikodifikasi mengenai privasi data dan undang-undang yang dikodifikasi mengenai perlindungan konsumen terhadap layanan teknologi keuangan, menjadikan perlindungan konsumen dalam hal ini agak kurang tegas. Namun, selain undang-undang dan peraturan, institusi resmi seperti BI, OJK, KOMINFO, PPATK, dan AFTECH ikut memberikan perlindungan konsumen melalui pendirian Kantor Fintech BI, Desk PPATK, Tim Pengembangan Inovasi Ekonomi dan Keuangan Digital dan Fintech, dan Sandbox Resmi OJK dan BI yang secara langsung membantu pertumbuhan teknologi keuangan fintech di masyarakat"