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Afrisal Akmal
Implementasi stax api versi 1.0 pada parser apache xerces-J-2.6.2
"Selain untuk mem-parse dan memvalidasi dokumen XML, parser XML juga berfungsi untuk menyampaikan isi dokumen yang di-parse ke aplikasi. Penyampaian informasi dari parser ke aplikasi dilakukan melalui suatu antar muka. Dua antar muka standar yang terdapat saat ini adalah SAX dan DOM. Spesifikasi SAX dan DOM mengatur cara aplikasi dalam mengakses isi dokumen XML. SAX menyatakan bahwa aplikasi dapat mengakses setiap event didalam dokumen XML segera setelah event tersebut selesai di-parse oleh parser. Aplikasi tidak dapat mengakses kembali eventevent yang telah di-parse. DOM menyatakan bahwa dokumen XML direpresentasikan kedalam struktur tree sehingga aplikasi dapat mengakses isi dokumen XML secara acak dengan menavigasi tree tersebut. Namun, spesifikasi SAX dan DOM tidak menjelaskan cara parser memenuhi aturan-aturan tersebut. Implementasi spesifikasi diserahkan kepada parser.
Saat ini sedang dikembangkan sebuah antar muka baru yang bernama StAX (Streaming API for XML). Sama seperti SAX, StAX tidak membentuk tree. Perbedaan terletak pada metode yang digunakan. StAX menggunakan metode pullbased, dimana aplikasilah yang meminta parser untuk mem-parse event berikutnya dalam dokumen XML. SAX bekerja dengan metode push-based, dimana parser terusmenerus mem-parse setiap event didalam dokumen XML hingga selesai, tanpa mempertimbangkan apakah aplikasi membutuhkan event tersebut atau tidak. Metode pull-based pada StAX ini memungkinkan aplikasi untuk menghentikan proses parsing tanpa perlu mem-parse seluruh isi dokumen XML. Kelebihan lain StAX dibandingkan SAX adalah bahwa StAX adalah antar muka yang bersifat bidirectional yang memungkinkan aplikasi untuk membaca dan sekaligus menulis dokumen XML.
StAX dikembangkan oleh tim yang dipimpin oleh BEA Weblogic. Saat ini, StAX telah memasuki tahap final pada JSR-173 (Java Specification Request) dan diupayakan untuk dijadikan antar muka standar. Sama seperti SAX dan DOM, implementasi spesifikasi StAX diserahkan kepada parser. Didalam Tugas Akhir ini dilakukan pengimplementasian StAX API kedalam parser Apache Xerces-J-2.6.2, yang merupakan parser open source yang banyak digunakan. Setelah dilakukan pengimplementasian StAX API kedalam Xerces-J- 2.6.2, pengguna Xerces-J-2.6.2 memiliki antar muka alternatif selain SAX dan DOM."
Depok: Fakultas Ilmu Komputer Universitas Indonesia, 2005
S-Pdf
UI - Skripsi Membership  Universitas Indonesia Library
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Goodwin, Grenville
Social organization of the Western Apache
Chicago: University of Chicago Press, 1942
970.3 GOO s
Buku Teks SO  Universitas Indonesia Library
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López, Daniel
SAMS teach yourself Apache 2 in 24 hours
Indiana: SAMS Publishing, 2002
005.7 LOP s
Buku Teks  Universitas Indonesia Library
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Raden Roro Isti Mardiana
Hubungan Skor Acute Physiology And Chronic Health Evaluation (APACHE) II dengan kejadian desaturasi pada pasien Pneumonia Covid-19 di RSUP Persahabatan = Correlation of Acute Physiology And Chronic Health Evaluation (APACHE) II Score with desaturation in Pneumonia COVID-19 patients at National Refferal Respiratory Center Persahabatan Hospital
"Latar Belakang : Lima belas persen (15%) pasien yang terinfeksi COVID- 19 jatuh ke dalam kondisi penyakit yang berat dan memerlukan suplementasi oksigen (O2). Lima persen (5%) lainnya mengalami perburukan lebih lanjut dan jatuh ke dalam penyakit kritis dengan komplikasi. Pemberian terapi O2 dilakukan segera kepada pasien dengan atau tanpa tanda-tanda kegawatdaruratan dengan saturasi oksigen (SpO2) < 90%. Penelitian ini bertujuan untuk mengetahui hubungan antara Skor Acute Physiology and Chronic Health Evaluation (APACHE) II dengan kejadian desaturasi pada pasien Pneumonia COVID-19.
Metode : Penelitian ini merupakan penelitian analitik observasional
kohort prospektif yang dilakukan di Instalasi Gawat Darurat (IGD) dan ruang rawat inap RSUP Persahabatan periode 31 Juli 2021 – 30 September 2021. Subjek penelitian didapatkan dari pasien yang datang ke IGD RSUP Persahabatan sejak 30 Juli 2021 – 30 September 2021 dan terdiagnosis COVID-19 dari hasil pemeriksaan PCR usap tenggorok positif. Dilakukan pengumpulan data klinis, tanda vital, pemeriksaan penunjang dan Skor APACHE II sejak subjek tiba di IGD hingga masuk ruang rawat dalam 24 jam pertama. Hasil : Pada penelitian ini didapatkan 100 subjek penelitian. Hasil penelitian ini menyatakan bahwa tidak terdapat hubungan yang bermakna antara Skor APACHE II dengan kejadian desaturasi pada pasien Pneumonia COVID-19 (p 0,257). Selain itu, tidak ditemukan perbedaan bermakna skor APACHE II pada kelompok pasien dengan derajat keparahan COVID-19 yang berbeda pada PaO2 sesuai hasil pemeriksaan AGD (p 0,073) namun didapatkan hubungan yang bermakna pada penggunaan PaO2 seusai kurva disosiasi O2 (p <0,001).
Kesimpulan : Tidak terdapat hubungan yang bermakna antara Skor
APACHE II dengan kejadian desaturasi pada pasien Pneumonia COVID-19.
Background : Fiftheen percents (15%) patients infected with COVID-19
falls to severe disease and require oxygen (O2) therapy and the other 5% suffered
progressive worsening to critical disease with complications. Oxygen therapy
conducted in patients with or without emergency condition with low O2 saturation
(SpO2 < 90%). This study aim to determine the correlation between Acute
Physiology and Chronic Health Evaluation (APACHE) II score with desaturation
in Pnuemonia COVID-19 patients.
Methods : A prospective cohort observational analytic study
conducted at National Respiratory Ceter Persahabatan Hospital Emergency Unit
from July 2021-September 2021. The study subjects were patients admitted to
Emergency Unit and diagnosed with COVID-19 from positive result of
nasopharing PCR swab. Clinical data, vital signs, supportive examination and
APACHE II score are collected since Emergency Unit admission to inward unit in
first 24 hours.
Results : There were 100 subjects participating in this study. The
result stated there were no significant correlation between APACHE II Score with
desaturation in Pneumonia COVID-19 patients (p-value 0,257). There was also no
significant correlation between APACHE II score with disease severity of COVID-
19 based on O2 partial pressure collected from blood gas analysis examination (pvalue
0,073) but there was a significant correlation between APACHE II score with
disease severity of COVID-19 based on O2 partial pressure referred to O2
dissociation curve (p-value <0,001).
Conclusion : There was no significant correlation between APACHE II
Score with desaturation in Pneumonia COVID-19 patients"
Jakarta: Fakultas Kedokteran Universitas Indonesia, 2023
T-pdf
UI - Tesis Membership  Universitas Indonesia Library
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Radhita Fatma Kamil
Manfaat skor APACHE II, MPI, dan ARPI sebagai penentu On Demand Relaparotomy = Benefits of APACHE II, MPI, and ARPI as determinants of On Demand Relaparotomy
"[ABSTRAK
Pendahuluan: Keputusan relaparotomi yang terlambat menambah morbiditas dan mortalitas. Keputusan on demand relaparotomy bersifat subjektif dari klinis, sehingga diperlukan pemeriksaan diagnostik tambahan dan alat untuk menentukan keputusan secara tepat, yaitu sistem skor. Metode penelitian: kasus kontrol dengan menggunakan 32 kasus on demand relaparotomy dan 64 kasus laparotomi, secara retrospektif. Hasil penelitian: Analisis perbedaan dua kelompok menunjukkan bahwa skor APACHE II tidak mempunyai perbedaan bermakna (p=0,144) sedangkan skor MPI dan ARPI mempunyai perbedaan yang bermakna (p<0,0001). Dari kurva ROC didaptkan APACHE II mempunyai AUC 59,2% dengan cut off point 10, MPI mempunyai AUC 86,4% dengan cut off point 20 dan ARPI mempunyai AUC 77,6% dengan cut off point 10. Kesimpulan: MPI dan ARPI bermanfaat sebagai penentu on demand relaparotomy.ABSTRACT Background: Delayed decision to do relaparotomy add morbidity and mortality. The decision to do on demand relaparotomy is subjective based on the clinical nature, therefore, it is necessary to have an examination and additional diagnostic and tools to determine the correct decisions, that is the scoring system. Methods: this is a case-control using 32 cases of on demand relaparotomy and 64 cases of laparotomy, retrospectively. Results: The analysis of the two groups showed that APACHE II has no significant difference (P = 0.114) while the MPI and ARPI has significant difference (P <0.0001) and on ROC curve obtained APACHE II had AUC of 59.2% with a cut-off point of 10, MPI had AUC of 86.4% with a cut-off point of 20 and ARPI had AUC of 77.6% with a cut-off point of 10.
Conclusion: MPI and ARPI can be used as determinants on demand relaparotomy. ;Background: Delayed decision to do relaparotomy add morbidity and mortality. The decision to do on demand relaparotomy is subjective based on the clinical nature, therefore, it is necessary to have an examination and additional diagnostic and tools to determine the correct decisions, that is the scoring system. Methods: this is a case-control using 32 cases of on demand relaparotomy and 64 cases of laparotomy, retrospectively. Results: The analysis of the two groups showed that APACHE II has no significant difference (P = 0.114) while the MPI and ARPI has significant difference (P <0.0001) and on ROC curve obtained APACHE II had AUC of 59.2% with a cut-off point of 10, MPI had AUC of 86.4% with a cut-off point of 20 and ARPI had AUC of 77.6% with a cut-off point of 10.
Conclusion: MPI and ARPI can be used as determinants on demand relaparotomy. ;Background: Delayed decision to do relaparotomy add morbidity and mortality. The decision to do on demand relaparotomy is subjective based on the clinical nature, therefore, it is necessary to have an examination and additional diagnostic and tools to determine the correct decisions, that is the scoring system. Methods: this is a case-control using 32 cases of on demand relaparotomy and 64 cases of laparotomy, retrospectively. Results: The analysis of the two groups showed that APACHE II has no significant difference (P = 0.114) while the MPI and ARPI has significant difference (P <0.0001) and on ROC curve obtained APACHE II had AUC of 59.2% with a cut-off point of 10, MPI had AUC of 86.4% with a cut-off point of 20 and ARPI had AUC of 77.6% with a cut-off point of 10.
Conclusion: MPI and ARPI can be used as determinants on demand relaparotomy. ;Background: Delayed decision to do relaparotomy add morbidity and mortality. The decision to do on demand relaparotomy is subjective based on the clinical nature, therefore, it is necessary to have an examination and additional diagnostic and tools to determine the correct decisions, that is the scoring system. Methods: this is a case-control using 32 cases of on demand relaparotomy and 64 cases of laparotomy, retrospectively. Results: The analysis of the two groups showed that APACHE II has no significant difference (P = 0.114) while the MPI and ARPI has significant difference (P <0.0001) and on ROC curve obtained APACHE II had AUC of 59.2% with a cut-off point of 10, MPI had AUC of 86.4% with a cut-off point of 20 and ARPI had AUC of 77.6% with a cut-off point of 10.
Conclusion: MPI and ARPI can be used as determinants on demand relaparotomy. , Background: Delayed decision to do relaparotomy add morbidity and mortality. The decision to do on demand relaparotomy is subjective based on the clinical nature, therefore, it is necessary to have an examination and additional diagnostic and tools to determine the correct decisions, that is the scoring system. Methods: this is a case-control using 32 cases of on demand relaparotomy and 64 cases of laparotomy, retrospectively. Results: The analysis of the two groups showed that APACHE II has no significant difference (P = 0.114) while the MPI and ARPI has significant difference (P <0.0001) and on ROC curve obtained APACHE II had AUC of 59.2% with a cut-off point of 10, MPI had AUC of 86.4% with a cut-off point of 20 and ARPI had AUC of 77.6% with a cut-off point of 10.
Conclusion: MPI and ARPI can be used as determinants on demand relaparotomy. ]"
Fakultas Kedokteran Universitas Indonesia, 2015
SP-PDF
UI - Tugas Akhir  Universitas Indonesia Library
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Hayatun Na Imah
Peta kuman pasien infeksi paru yang dirawat di intesive care unit RSUP Persahabatan dan hubungannya dengan derajat keparahan penyakit yang dinilai dengan skor APACHE II = Microbiological pattern of patients with lung infection in Persahabatan Hospital intesive care unit and it s relationship with severity of the disease measure with APACHE II score
"ABSTRAK
Pendahuluan: Infeksi paru merupakan penyebab morbiditas dan mortalitas terbesar di Intensive Care Unit ICU. Pasien ICU umumnya dalam kondisi critically ill dan riwayat penggunaan antibiotic sebelumnya sehingga memiliki risiko resistensi terhadap antibiotik yang berpengaruh terhadap luaran pasien.Sistem skoring digunakan di ICU untuk menilai derajat keparahan penyakit dan luaran pasien. Penelitian ini menilai eta kuman pasien infeksi paru dan hubungannya dengan derajat keparahan penyakit yang dinilai dengan skor APACHE II. Metode: Penelitian ini menggunakan metode potong lintang yang dilaksanakan pada bulan Agustus-September 2017 di ICU RSUP Persahabatan. Total subjek terdiri atas 59 subjek dengan cara pengambilan sampel consecutive sampling. Semua pasien didiagnosis infeksi paru oleh dokter spesialis dan dikonfirmasi melalui foto toraks kemudian dinilai derajat keparahan penyakit dengan skor APACHE II dan dilakukan biakan dan resistensi mikroorganisme. Hasil: Kuman yang banyak ditemukan merupakan gram negative (37,2%) dengan risiko mortalitas tertinggi 75% jenis Acinetobacter pada skor (APACHE II 30-34). Rerata skor APACHE II 15,78+ 6,04 dengancut off point skor APACHE II 16,5 dan skor APACHE II >16 memiliki mortalitas terbesar (64%) (p=0,032). Diagnosis infeksi paru dengan mortalitas terbesar didapatkan pada CAP (56%). Kesimpulan: Acinetobacter baumanii merupakan kuman terbanyak yang menyebabkan kematian pada pasien infeksi paru dan skor APACHE II merupakan prediktor yang baik dalam menilai derajat keparahan penyakit dan luaran pasien.
ABSTRACT<>br>
Introduction: Lung infection are the most common cause of high mortality and morbidity in Intensive Care Unit (ICU). Patients in ICU mostly critically ill with history of antibiotic use and risk of drug resistant that will influence the outcome of the patients. Scoring system used in ICU to measure severity of the disease and the outcome of the patients. This study asseses the microbiological pattern of patients with lung infection and severity of the disease using APACHE II Score. Methods: This study used cross sectional methods that heldbetween August 2017-September 2017in Persahabatan Hospital Intensive Care Unit. Total subjects consisted of 59 patients with lung infection base on consecutive sampling. All of the patients diagnosed with lung infection from specialist and confirmed with radiological findings, measured the APACHE II Score and performed sputum culture and resistance. Results: The most common isolation found in lung infection patients was gram negative (37,2%) with mortality risk of Acinetobacter baumanii75% (APACHE II Score 30-34). Mean APACHE II Score was 15,78+ 6,04 with cut off point APACHE II Score 16,5 and APACHE II Score > 16 has the highest mortality (64%) (p=0,032). Diagnose of lung infection with the highest mortality found in patients with CAP (56%). Conclusions: Acinetobacter baumanii are the most common cause of mortality in lung infection patients. The APACHE II Score has good predictor in measure severity of the diseases and the outcome of the patients."
Depok: Fakultas Kedokteran Universitas Indonesia, 2017
SP-Pdf
UI - Tugas Akhir  Universitas Indonesia Library
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Ida Bagus Sila Wiweka
Faktor Prognosis Penderita Gawat Napas yang dirawat di Instalasi Perawatan Intensif Rumah Sakit Persahabatan Jakarta dengan Kriteria Apache III
Jakarta: Fakultas Kedokteran Universitas Indonesia, 2003
T59028
UI - Tesis Membership  Universitas Indonesia Library
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Pedro Reis
Predicting mortality in patients admitted to the intensive care unit after open vascular surgery
"
ABSTRACT
Purposes
Vascular surgery (VS) has a higher perioperative mortality than other types of surgery. We compared different scores for predicting mortality in patients admitted to the intensive care unit (ICU) after open VS.
Methods
Patients admitted to the ICU after open VS from 2006 to 2013 were included. We calculated the Acute Physiology and Chronic Health Evaluation (APACHE), Simplified Acute Physiology Score (SAPS), Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) and Preoperative Score to Predict Postoperative Mortality (POSPOM). We performed multivariate logistic regression to assess independent factors with the calculation of odds ratios (ORs) and 95% confidence intervals (CIs). We tested the predictive ability of the scores using the area under the receiver operating characteristics curve (AUROC).
Results
A total of 833 consecutive patients were included. Hospital mortality was 5,1% (1,3% after intermediate-risk and 8,4% after high-risk surgery). In the multivariate analysis, the age (OR 1,04, 95% CI 1,01-1,08, p = 0,013), smoking status (OR 2,46, 95% CI 1,16-5,21, p = 0,019), surgery risk (OR 2,92, 95% CI 1,058,08, p = 0,040), serum sodium level (OR 1,17, 95% CI 1,10-1,26, p < 0,001), urea (OR 1,01, 95% CI 1,01-1,02, p = 0,001) and leukocyte count (OR 1,05, 95% CI 1,01-1,10, p = 0,009) at admission were considered independent predictors. Hematocrit (0,86, 95% CI 0,80-0,93, p < 0.001) was considered an independent protective factor. The AUROC of our model was 0,860, compared to SAPS (0,752), APACHE (0,774), POSPOM (0,798) and POSSUM (0,829).
Conclusion
The observed mortality was within the predicted range (1-5% after intermediate-risk and > 5% after high-risk surgery). POSSUM and POSPOM had slightly better predictive capacity than SAPS or APACHE."
Tokyo: Springer, 2019
617 SUT 49:10 (2019)
Artikel Jurnal  Universitas Indonesia Library
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Proficz, Jerzy
Processing of satellite data in the cloud
"The dynamic development of digital technologies, especially those dedicated to devices generating large data streams, such as all kinds of measurement equipment temperature and humidity sensors, cameras, radio telescopes and satellites Internet of Things enables more in depth analysis of the surrounding reality, including better understanding of various natural phenomenon, starting from atomic level reactions, through macroscopic processes e.g. meteorology to observation of the Earth and the outer space. On the other hand such a large quantitative improvement requires a great number of processing and storage resources, resulting in the recent rapid development of Big Data technologies. Since 2015, the European Space Agency ESA has been providing a great amount of data gathered by exploratory equipment a collection of Sentinel satellites which perform Earth observation using various measurement techniques. For example Sentinel 2 provides a stream of digital photos, including images of the Baltic Sea and the whole territory of Poland. This data is used in an experimental installation of a Big Data processing system based on the open source software at the Academic Computer Center in Gdansk. The center has one of the most powerful supercomputers in Poland the Tryton computing cluster, consisting of 1600 nodes interconnected by a fast Infiniband network 56 Gbps and over 6 PB of storage. Some of these nodes are used as a computational cloud supervised by an OpenStack platform, where the Sentinel 2 data is processed. A subsystem of the automatic, perpetual data download to object storage based on Swift is deployed, the required software libraries for the image processing are configured and the Apache Spark cluster has been set up. The above system enables gathering and analysis of the recorded satellite images and the associated metadata, benefiting from the parallel computation mechanisms. This paper describes the above solution including its technical aspects."
[s.l.]: Task, 2017
600 SBAG 21:4 (2017)
Artikel Jurnal  Universitas Indonesia Library
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Aldi Naufal Fitrah
Extensible High-Throughput Streaming Platform Berbasis Kafka untuk Pemrosesan Data dari Media Sosial = Kafka-Based Extensible High Throughput Streaming Platform for Data Processing from Social Media
"Dengan bertambahnya jumlah pengguna internet seiring waktu, bertambah pula jumlah data yang dihasilkan dari aktivitas yang berasal dari media sosial. Data tersebut dapat digunakan untuk berbagai keperluan, salah satunya untuk keperluan moderasi supaya aktivitas pengguna internet tetap tunduk pada hukum yang berlaku. Namun, diperlukan cara yang optimal untuk melakukan proses tersebut mengingat data yang jumlahnya sangat besar. Penelitian ini mengajukan sebuah platform yang dapat menjadi salah satu pilihan untuk memproses data media sosial yang berjumlah besar tersebut. Rancangan platform pada penelitian ini ditujukan untuk dapat memiliki throughput yang besar. Selain itu, platform dirancang untuk dapat dimodifikasi demi memenuhi berbagai kebutuhan. Karenanya, aspek extensibility juga menjadi perhatian utama dalam proses pengembangan platform. Kedua tujuan utama dalam pengembangan platform ini dapat diwujudkan dengan bantuan sebuah klaster Apache Kafka yang membuat platform memiliki sifat loosely-coupled dan juga extensible. Dengan berpusat pada klaster Apache Kafka, proses pengolahan data yang ada dapat dilakukan secara paralel, dan terbukti dapat meningkatkan throughput dari platform secara keseluruhan. Sebagai pembanding, penelitian ini diuji coba dengan suatu skenario bersama dengan platform Tweetream yang dikembangkan oleh Susanto (2022). Hasil dari uji coba tersebut membuktikan bahwa platform pada penelitian ini dapat mengungguli Tweetream.
As the number of internet users increases over time, so does the amount of data generated from activities originating from social media. This data can be used for various purposes, one of which is for moderation purposes so that the activities of internet users remain subject to applicable laws. However, an optimal way to do the process is needed considering the huge amount of data. This research proposes a platform that can be one of the options for processing large amounts of social media data. The design of the platform in this research is intended to have a large throughput. In addition, the platform is designed to be modifiable to meet various needs. Therefore, extensibility is also a major concern in the platform development process. These two main objectives in the development of the platform can be realized with the help of an Apache Kafka cluster that makes the platform loosely-coupled and extensible. By centering on the Apache Kafka cluster, the data processing can be done in parallel, which has been proven to increase the throughput of the platform as a whole. For comparison, this study was tested in a scenario with the Tweetream platform developed by Susanto (2022). The results of the test proved that the platform in this study can outperform Tweetream."
Depok: Fakultas Ilmu Komputer Universitas Indonesia, 2023
S-pdf
UI - Skripsi Membership  Universitas Indonesia Library
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