Abstrak— Rumah Sakit Universitas Airlangga (RSUA) merupakan sarana pelayanan kesehatan yang dikelola di bawah naungan Universitas Airlangga. Seiring berjalannya proses bisnis, jumlah pasien RSUA yang semakin bertambah menyebabkan data kunjungan pasien rawat jalan yang harus dikelola oleh bagian rekam medis semakin banyak. Data tersebut dikelola untuk digunakan dalam pembuatan laporan. Informasi dalam laporan dihasilkan melalui perhitungan secara manual atau menggunakan formula Microsoft Excel menjadi kendala dalam pembuatan laporan selain adanya kebutuhan laporan dengan format beragam dan analisis multidimensional. Data warehouse berbasis Online Analytical Processing (OLAP) dapat diterapkan untuk menangani masalah tersebut. Tujuan penelitian ini adalah merancang dan membangun data warehouse berbasis OLAP agar dapat digunakan oleh bagian rekam medis RSUA dalam pembuatan laporan. Data warehouse dibangun melalui tujuh tahap yaitu analisis, desain, proses ETL (Extraction, Transformation, and Loading), penerapan OLAP, uji coba, eksplorasi untuk hasil laporan dan analisis, serta evalusi. Perancangan data warehouse menggunakan Nine Step Methodology dengan pemodelan berupa fact constellation schema. Hasil implementasi data warehouse adalah aplikasi OLAP yang dapat digunakan untuk membantu kinerja bagian rekam medis RSUA dalam pembuatan laporan, baik berupa tabel pivot maupun grafik. Penilaian pengguna terhadap sistem data warehouse menunjukkan kategori baik dengan hasil penilaian sebesar 73.61 persen. Kata Kunci— Data Warehouse, Rawat Jalan, ETL, Nine Step Methodology, OLAPAbstract— Airlangga University Hospital is a health care facilities managed by the auspices of Airlangga University. Increasing number of patients in RSUA caused more outpatients’ visits data must be managed by the medical record unit. The data was used to report making. The information in the reports generated through manual calculation or used function of Microsoft Excel became a problem of report making in addition to their reporting needs with diverse formats and multidimensional analysis. Data warehouse based on Online Analytical Processing (OLAP) could implemented to solved the problem. The goal of this research were to designing and implementing the data warehouse based on OLAP so it could be used by medical record unit to making report. Data warehouse was implemented in seven process : analysis, design, ETL (Extraction, Transformation, and Loading), implementing OLAP, trial, explore the report and analysis, and evaluation. Design of data warehouse were using Nine Step Methodology and fact constellation schema model.The outcome of this research was an OLAP application that can used to help the task of RSUA medical record unit to making report using pivot table or chart. User ratings against the data warehouse system showed good category with the results of 73.61 percent in assessment. Keywords— Data Warehouse, Outpatient, ETL, Nine Step Methodology, OLAP
Abstrak-Penelitian ini menghasilkan rencana arsitektur perusahaan yang dapat digunakan oleh Instalasi Rawat Jalan RSJ Menur Surabaya dengan kerangka kerja TOGAF ADM. Ada beberapa tahapan yang akan dilakukan yaitu pengumpulan data, penyusunan arsitektur visi, penyusunan arsitektur bisnis, penyusunan arsitektur data, penyusunan arsitektur aplikasi, penyusunan arsitektur teknologi, dan evaluasi arsitektur perusahaan. Dalam penyusunan arsitektur data, hal yang dilakukan adalah penyusunan arsitektur data berdasarkan dokumen laporan, membuat relasi antar entias data, membuat matriks fungsi bisnis dan entitas data, dan membuat analisis gap arsitektur data. Pada penyusunan arsitektur aplikasi, hal yang dilakukan adalah merencanakan kandidat aplikasi, membuat matriks fungsi bisnis, merancang kandidat aplikasi, serta membuat analisis gap arsitektur aplikasi. Sedangkan dalam tahap penyusunan arsitektur teknologi, hal yang dilakukan adalah merencanakan kandidat teknologi, membuat topologi jaringan dan membuat analisis gap arsitektur teknologi. evaluasi arsitektur perusahaan dilakukan dengan cara wawancara kepada stakeholder tentang hasil arsitektur. Hasil evaluasi menyatakan bahwa arsitektur perusahaan yang telah dibuat dapat diterima dan dipertimbangkan untuk diimplementasikan.Kata Kunci-Perencenaan Arsitektur Perusahaan, TOGAF ADM, Instalasi Rawat Jalan, Blueprint Abstract-This research resulted blueprint of the enterprise architecture which can be used by Outpatient Departement of RSJ Menur Surabaya with TOGAF ADM framework. . There were several stages that will be done that the first stage was data collection, the second stage was architecture vision, the third stage was business architecture, the fourth stage was information systems architectures, which includes the data architecture was the identification of data entities obtained based on documents and reports, created the relationship between data entities, created the matrix of business functions and the candidates of application and create the gap analysis of the application architecture. The fifth stage was technology architecture which planned the technology candidates, made the network topology and made the gap analysis of the technology architecture. Phase sixth was the evaluation of enterprise architecture, the stage which conducted interview was related to the architecture that has been planned, then explain the positive and negative impacts related to the architecture that has been planned. The results of this research was enterprise architecture planning. Based on the evaluation results, the enterprise architecture can be accepted and considered to all stakeholders to be implemented in the future. Beside that it was a need for Hospital Management Information System Installation that has roles and responsibilities related to the application and information technology.
The Central Bureau of Statistics of Indonesia (BPS) classified the target households into three different categories which were very poor households (RSTM), poor households (RTM), and nearly-poor households (RTSM). BPS need some method that can accelerate the classification process to assist the performance of BPS in order to shorten the processing time. The data scale that used in the classification of poor households was ordinal. Generally, calculations of classification using ordinal asscales only can be found in the software WEKA Ordinal Class Classifier (OCC) that was one of the existing classification in WEKA. OCC could be resolve to attributes that are nominal, numerical, and ordinal. So in this research, OCC would be using to classify poor households. By comparing the algorithms performance there were several stages that need to be traversed. The first was the data collection stage, the second was the data processing stage and information by using preprocessing, the third was the analysis stage with tools WEKA. The fourth was a test stage by counting the value of accuracy, precision, and recall. The last stage was evaluation by comparing actual data with predictive data of the result of calculating system. From the classification process, it can be concluded that OCC has the highest accuracy, precision, and recall level which is 90% (3803) of training set and 10% (423) of testing set with accuracy of 90.5437%, precision 0.919, and recall 0.905.
The need for domestic salt every year has increased, both for consumption and industrial salt. Some of the fisheries service programs include providing assistance to people's businesses, providing geomembrane, and online marketing training. A large number of salt farmers and official work programs have caused the implementation of the program to be less than optimal, resulting in low salt production. This study uses a type-2 fuzzy method by integrating two methods, namely type-2 Fuzzy Analytical Hierarchy Process AHP (FAHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Fuzzy type-2 has higher accuracy than fuzzy type-1 and is more efficient and more flexible in determining the linguistic scale for criteria. The Fuzzy Analytical Hierarchy Process AHP (FAHP) interval is used to determine the weight of the salt farmer mapping criteria. Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), used to determine. The findings of this study are that the indicators that most influence the mapping of salt farmers are land area, marketing, and market. The results of the mapping of salt farmers are the classification of salt farmer class groups and recommendations for improvement for each salt farmer. Hybrid type-2 Fuzzy Analytical Hierarchy Process AHP (FAHP) method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), can be used for mapping salt farmers based on the consistency ratio value below 10 percent, 37 percent enter high class, 28 percent enter the middle class and 35 percent enter low class
Development of an optimal face recognition system will greatly depend on the characteristics of the selection process are as a basis to pattern recognition. In the characteristic selection process, there are 2 aspects that will be of mutual influence such the reduction of the amount of data used in the classification aspects and increasing discrimination ability aspects. Linear Discriminat Analysis method helps presenting the global structure while Laplacianfaces method is one method that is based on appearance (appearance-based method) in face recognition, in which the local manifold structure presented in the adjacency graph mapped from the training data points. Linear Discriminant Analysis QR decomposition has a computationally low cost because it has small dimensions so that the efficiency and scalability are very high when compared with algorithms of other Linear Discriminant Analysis methods. Laplacianfaces QR decomposition was a algorithm to obtain highly speed and accuracy, and tiny space to keep data on the face recognition. This algorithm consists of 2 stages. The first stage maximizes the distance of between-class scatter matrices by using QR decomposition and the second stage to minimize the distance of within-class scatter matrices. Therefore, it is obtained an optimal discriminant in the data. In this research, classification using the Euclidean distance method. In these experiments using face databases of the Olivetti-Att-ORL, Bern and Yale. The minimum error was achieved with the Laplacianfaces QR decomposition and Linear Discriminant Analysis QR decomposition are 5.88% and 9.08% respectively.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.