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"Academia is an important site for producing knowledge, which is crucial in driving economies and societies around the globe at the beginning of the 21st century. Yet surprisingly little is known about how contemporary universities are shaped by the formal and multiple demands they face from national policy requirements, particularly performance measurement. What effects do these policies have on individual universities and the academics who work within them? While policy surely has impacts on institutions and academics, there are also numerous other things that shape academic life. This book’s starting point is that there are three main shaping forces that govern academia – intellectual curiosity, disciplinary traditions and research policy. Bringing these three levels together into a framework, this book examines how academia is governed, both formally and informally, bridging the different aspects of governing knowledge networks through a large multi-country study.Author Jenny Lewis uses a large empirical study of academics in three countries (Australia, Britain and New Zealand) and in the broad disciplinary areas of the humanities, social sciences and sciences, to demonstrate the analytical framework’s application. The book also offers some needed directions on what policy should and can do, providing a snapshot of contemporary academic life in different disciplines and in different countries, from the perspective of academics on the frontline."

"Pada saat ini telah dibangun Portal Open Data UI, yang merupakan portal berbasis Semantic Web untuk mengintegrasikan berbagai sistem administrasi akademik di UI. Penelitian ini ditujukan untuk membuat ontologi evaluasi akademik yang akan diimplementasikan pada portal tersebut. Ontologi evaluasi akademik adalah pemodelan representasi pengetahuan pada domain akademik yang sesuai dengan kebutuhan evaluasi akademik. Ontologi evaluasi akademik mencakup keterhubungan antar dosen, mahasiswa, perguruan tinggi beserta aktivitas-aktivitasnya di setiap tahun akademik. Ontologi ini dibuat dengan metode Ontology Development 101 dengan langkah-langkah (1) menentukan domain dan cakupan ontologi yaitu dengan cara membuat competency questions, (2) analisis menggunakan ontologi yang tersedia, (3) enumerasi kosakata, (4) mendefinisikan class dan hierarki antar class, (5) mendefinisikan property, dan (5) mendefinisikan slot. Penelitian ini menghasilkan ontologi evaluasi akademik yang mengacu pada proses evaluasi internal semester jenjang S1, S2 dan S3 di Universitas Indonesia. Ontologi yang dihasilkan telah dipublikasikan, agar tidak hanya dapat diterapkan pada Universitas Indonesia, namun juga dapat dimanfaatkan oleh perguruan tinggi lain di Indonesia.

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At this time there is Portal Open Data UI, which is a Semantic Web-based portal to integrate various systems of academic administration at the Universitas Indonesia. This research aimed to create academic evaluation ontology will be implemented in the portal. Academic evaluation ontology is modeling knowledge representation in the academic domain that fit the needs of academic evaluation. Academic evaluation ontology connectivity between faculty, students, colleges along its activities at every academic year. This ontology is made by the method of Ontology Development 101 with steps (1) determine the domain and scope of the ontology with competency questions, (2) consider reusing existing ontologies, (3) enumerate important terms in the ontology, (4) define the classes and the class hierarchy, (5) define property, and (5) define slot. This research has resulted ontology academic evaluation refers to the process of semester internal evaluation for undergraduate, master, and doctoral at the Universitas Indonesia. The ontology has been published, so that not only applied to Universitas Indonesia, but also can be used by other universities in Indonesia."

"Artikel ini membahas strategi dan kebijakan General Motors untuk bertahan pada masa Great Depression dari tahun 1929 sampai tahun 1935. Great Depression yang melanda negara Amerika Serikat mengakibatkan sektor industri goyah, tidak terkecuali General motors yang saat itu sedang mengalami kemajuan pesat sebagai manufaktur mobil tersukses mengungguli Ford dan Chrysler. Alfred P. Sloan sebagai direktur utama beserta jajaran direksi General Motors bertanggung jawab untuk mengeluarkan General Motors dari jurang depresi ekonomi. Sejumlah strategi diformulasikan untuk mempertahankan eksistensi General Motors, seperti menurunkan harga mobil mewah, mengurangi jumlah pekerja, hingga memberikan menggunakan bantuan kredit bernama General Motors Acceptance Corporation (GMAC) yang sudah lebih dulu dibentuk sejak 1919. Strategi perusahaan yang dirumuskan Sloan bersama timnya bertujuan membantu General Motors agar bisa bertahan ditengah kekacauan depresi ekonomi yang melanda Amerika Serikat. Oleh karena itu, penulis berargumen bahwa General Motors mengeluarkan kebijakan dan strategi seperti pemotongan biaya produksi dan pengurangan pekerja agar tetap bertahan selama gempuran Great Depression. Penelitian ini menggunakan metode sejarah yang meliputi empat tahapan, yaitu heuristik, kritik, interpretasi dan historiografi. Berbeda dengan kajian-kajian sebelumnya yang membahas dampak Great Depression terhadap manufaktur mobil di Amerika Serikat secara umum, penelitian ini terfokus pada strategi General Motors serta dampaknya terhadap perusahaan dan masyarakat Amerika Serikat. Sumber-sumber yang digunakan pada artikel ini adalah surat kabar, poster, buku serta jurnal yang terkait dengan General Motors.

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The article discusses General Motors strategies and policies to survive the Great Depression from 1929 to 1935.The Great Depression that hit the United States caused the industrial sector to falter, including General Motors, which at that time was experiencing rapid progress as the most successful car manufacturer outperformed Ford and Chrysler. Alfred P. Sloan as the president director and board of directors of General Motors is responsible for getting General Motors out of the brink of the economic depression. Strategies are formulated to maintain the existence of General Motors, such as reducing the price of luxury cars, reducing the number of workers, to providing credit assistance called the General Motors Acceptance Corporation (GMAC) which was formed in 1919. The company strategy formulated by Sloan together aims to help General Motors to can survive amid the economic turmoil that engulfs the United States. Therefore, the authors argue that General Motors issued policies and strategies such as cutting production and worker costs in order to survive during the Great Depression. This study uses a historical method which includes stages, namely heuristics, criticism, interpretation and historiography. In contrast to previous studies that discussed the impact of the Great Depression on car manufacturing in the United States in general, this study focuses on General Motors' strategy and its impact on US companies and society. The sources used in this article are newspapers, posters, books and journals related to General Motors."

"Drug related problems (DRPs) adalah suatu keadaan yang tidak diinginkan yang terjadi pada pasien yang disebabkan oleh terapi obat dan secara nyata atau potensial mengurangi hasil terapi yang diharapkan.Sistem informasi drug related problems merupakan sistem informasi untuk mengetahui DRPs yang terjadi pada pasien yang sedang menjalani terapi obat yang diberikan dokter, agar dapat diatasi dan dicegah adanya masalah yang ditimbulkan diluar penyakit yang sedang diterapi. Supaya sistem dapat berjalan dengan baik harus didukung informasi yang lengkap dan terdokumentasi dengan baik.Sistem informasi drug related problems di RSUD Ulin Banjarmasin belum ada. Selama ini data tentang DRPs tidak terdokumentasi dengan baik dan lengkap. Tidak ada basis data yang mendukung sistem tersebut. Penanganan kejadian DRPs bersifat tindakan langsung berdasarkan respon pasien terhadap obat dan keluhan pasien. Hal itu disebabkan tidak ada SOP yang mengaturnya.Tujuan pengembangan sistem informasi drug related problems adalah membuat sistem informasi yang dapat mengetahui adanya DRPs yang terjadi pada pasien dengan penambahan formulir khusus DRPs dan pembuatan basis data DRPs.Metode pengumpulan data yang digunakan adalah wawancara mendalam dan studi dokumentasi. Pengembangan sistem menghasilkan formulir pemantauan obat untuk yang memuat kejadian DRPs dan prototype DRPs dengan basis data. Hasil uji coba prototype menunjukkan sistem berjalan baik berdasarkan input, proses, basis data, kendali dan platform teknologi.Hasil analisis DRPs dari 109 orang pasien hipertensi di RSUD Ulin Banjarmasin berdasarkan data sekunder tahun 2003 ditemukan pasien yang mengalami DRPs 49 orang (44,95%). Proporsi jenis DRPs yang ditemukan paling banyak adalah interaksi obat 54,2%, efek samping obat 33,9% dan duplikasi obat 11,9%.

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Drug related problems (DRPs) is an unwanted condition that occurred in patient caused by drugs therapy, actual and potentially reduced the expected therapy results.

Information system of drug related problems is an information system to find out DRPs which occurred in patient who endure on drug therapy which has been given by doctor, in order to handle and prevent the problems that may be occurred beyond the disease that being treated. The system can be going on all right, if be supported by complete information and well documented.

There is no information system for drug related problems in RSUD Ulin Banjarmasin. Until now, data of DRPs uncompleted and not well documented. No databases support to this system. Incident DRPs handling only by direct action based on patient response to drugs and patient complaints. That case caused no standard operational procedure to arrange.

The purpose of development information system of drug related problems is to build information system which could find DRPs that occur in patient by adding special form for drugs and DRPs monitoring and establishing DRPs database.

Results of the prototype testing showed that the system working well based on input, process, output, control and technology platform.

Result of DRPs from 109 patients with hypertension in RSUD Ulin Banjarmasin based on secondary data year of 2003 found that patient who experience DRPs is 49 patients (45,9%). The high proportion the type of DRPs that has been found are drug interactions (54,2%), adverse drug reactions (33,8%) and drug duplications (11,9%)"

"Molecular biology is advancing through the protein - protein interaction studies. Its wet experiment has generated a massive amount of data. Bioinformatics was set up for converting those data into useful information. Protein - protein interaction wet experiment was a long and expensive labors. Bioinformatics are here to remedy those labors. Online experiments in protein - protein interaction database are possible.. The available databases are InterPare, ClusPro and PROTORP. InterPare is an open and public database server for protein interaction interface information. ClusPro is an algoritm for filtering docked protein conformations, and rank them. PROTORP is a database that can be used to calculate a series of physical and chemical parameters of the protein interaction sites that contribute to the binding energy of the association. The online databases are useful tools for aiding the wet laboratory protein - protein interaction experiment."

"Indonesia merupakan daerah rawan multi bencana alam, yang sering terjadi tanpa dapat diprediksikan terlebih dahulu. Bencana alam tersebut telah berdampak pada timbulnya korban jiwa, kerusakan lingkungan, kerugian harta benda, dan dampak psikologis sehingga dalam keadaan tertentu dapat menghambat pembangunan nasional. Kebutuhan data dan informasi geospasial (IG) terkait kebencanaan ini, sangat penting dalam pengelolaan bencana, termasuk proses mitigasi, penanganan kondisi darurat, maupun rehabilitasi. Sebagai institusi yang berwenang dan bertanggung jawab terhadap penyelenggaraan IG dasar dan pembinaan IG tematik nasional, Badan Informasi Geospasial (BIG) perlu menyediakan layanan data terkait kebencanaan, yang melibatkan berbagai data dan informasi geospasial tematik. Dalam penyediaan layanan tersebut, BIG membangun sebuah Geospatial Support Command Center (GSCC), yang diperlukan untuk menyediakan layanan data dan IG terintegrasi dalam suatu data warehouse.Penelitian ini dilakukan untuk memberikan rekomendasi desain dan pengintegrasian data melalui perancangan dan pengimplementasian data warehouse spasial di BIG yang dapat mendukung layanan ? layanan IG, termasuk layanan IG untuk kebencanaan. Pendekatan data warehouse spasial yang digunakan adalah pendekatan analysis-driven yang dikemukakan oleh Malinowski dan Zimanyi. Pengumpulan data didapatkan dari hasil observasi lapangan, dokumen ? dokumen internal organisasi, dan wawancara dengan dengan narasumber dari unit-unit kerja yang berkaitan dengan pengelolaan data geospasial terkait kebencanaan.Hasil akhir dari penelitian ini adalah implementasi data warehouse spasial serta dashboard spasial, sehingga dapat mempermudah pemanfaatan informasi terkait bencana. Hasil penelitian ini memberikan rekomendasi berupa lokasi kejadian, sehingga penanganan bencana dapat tepat dan sesuai sasaran.

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Indonesia is an area of multi disaster risks that often happen unpredictably. Those disasters have caused the loss of lives, environmental damages, loss of properties, and psychological impacts that under certain circumstances have hindered national development. The need for geospatial data and information related to disasters is very important in the management of disasters, including mitigation process, emergency supports, as well as rehabilitation process. As a state government agency that is responsible for providing basic geospatial information (GI) and as a supervisor in the thematic geospatial development, Geospatial Information Agency (BIG) needs to provide GI services related to disasters, which of course involve variety of thematic geospatial data and information. In the provision of GI services, BIG has developed a Geospatial Support Command Center (GSCC), that provides geospatial data and information services, integrated in a data warehouse.

This research was conducted to provides recommendations for the design and integration of data through the design and implementation of spatial data warehouse in BIG that can support the GI services, including GI to support disasters. Spatial data warehouse approach which is used is analysis-driven approach that proposed by Malinowski and Zimanyi. Data collecting is obtained from field observations result, the internal documents of the organization, and interview with speaker from related working units who manage geospatial data and information related to disasters.

The final results of this research are spatial data warehouse implementation and spatial dashboard, to facilitate the utilization of disaster-related information. It provides recommendations to the location of incident, so that disaster management can be done precisely."