ABSTRAK Cloud Computing atau komputasi awan adalah gabungan pemanfaatan teknologi komputer ('komputasi') dan pengembangan berbasis Internet ('awan'). Awan (cloud) adalah metafora dari internet, sebagaimana awan yang sering digambarkan pada diagram jaringan computer. Selain seperti awan dalam diagram jaringan komputer, awan (cloud) dalam cloud computing juga merupakan abstraksi dari infrastuktur kompleks yang disembunyikannya. Private Cloud Storage dengan kolaborasi komponen Service Oriented Architecture mampu menyediakan antarmuka yang efisien untuk proses berjalannya lembaga dan berfungsi sebagai Virtualization Server dan Online Storage yang dapat diakses menggunakan Fixed Device dan Mobile Device seperti Smartphone Android, Komputer Pad, dan PC Tablet melalui koneksi jaringan lokal dan internet.Sebagai fungsi manfaat dari cloud sendiri bisa di manfaatkan kedalam kebutuhan E-Learning, mengingat dari segi kemudahan, kebutuhan, dan keamanan, cloud computing terbilang metode yang pas dalam menerapkan kebutuhan tersebut. Dimana setiap data berhak di simpan secara bebas, luas dan aman tentunya. ABSTRACT Cloud Computing is a combination of the use of computer technology and cloud of Internet-based development. Clouds are metaphors of the Internet, as are clouds that are often depicted in computer network diagrams. In addition to clouds in computer network diagrams, clouds in computing technology are also an abstraction of the complex infrastructure it conceals. Private Cloud Storage with Service Oriented Architecture component collaboration is able to provide an efficient interface for the running process of the institution and serves as Virtualization Server and Online Storage that can be accessed using Fixed Devices and Mobile Devices such as Android Smartphone, Pad Computer and Tablet PC via local network connection and Internet.As function of the benefits of the cloud itself can be utilized into the needs of E-Learning, given the ease, needs, and security, cloud computing spelled out the right method in applying these needs. Where every data is entitled to save freely, broadly and safely of course.How to Cite : Santiko, I. Rosidi, R., Wibawa. S. A (2017). PEMANFAATAN PRIVATE CLOUD STORAGE SEBAGAI MEDIA PENYIMPANAN DATA E-LEARNING PADA LEMBAGA PENDIDIKAN. Jurnal Teknik Informatika, 10(2), 137-146. doi:10.15408/jti.v10i2.6992Permalink/DOI: http://dx.doi.org/10.15408/jti.v10i2.6992
Based on Indonesia's health profile in 2008, Diabetes Mellitus is the cause of the ranking of six for all ages in Indonesia with the proportion of deaths of 5.7% under stroke, TB, hypertension, injury and perinatal. This is reinforced by WHO (2003), Diabetes Mellitus disease reached 194 million people or 5.1 percent of the world's adult population and in 2025 is expected to increase to 333 million inhabitants. In particular, in Indonesia, people with Diabetes Mellitus are increasing. In 2000, Diabetes Mellitus sufferers have reached 8.4 million people and it is estimated that the prevalence of Diabetes Mellitus in 2030 in Indonesia reaches 21.3 million people.This allows researchers and practitioners to focus their attention on detecting/diagnosing diabetes mellitus and to prevent it because the disease can cause complications. The method used in this research was problem identification, data collection, pre-processing stage, classification method, validation and evaluation and conclusion. The algorithm used in this research was CART and Naïve Bayes using dataset taken from UCI Indian Pima database repository consisting of clinical data ofpatients who detected positive and negative diabetes mellitus. Validation and evaluation method used was 10-crossvalidation and confusion Matrix for the assessment of precision, recall and F-Measure. The result of calculation has been done, got the accuracy result on CART algorithm equaled to 76.9337% with precision 0.764%, recall 0.769%, and F-Measure 0.765%. Whilethe diabetes dataset was tested with the Naïve Bayes algorithm, got an accuracy of 73.7569% with precision 0.732%, recall 0.738%, and F-Measure 0.734%. From these results it can be concluded that to diagnose diabetes mellitus disease it is suggested to use CART algorithm.
Chronic kidney disease is a disease that can cause death, because the pathophysiological etiology resulting in a progressive decline in renal function, and ends in kidney failure. Chronic Kidney Disease (CKD) has now become a serious problem in the world. Kidney and urinary tract diseases have caused the death of 850,000 people each year. This suggests that the disease was ranked the 12th highest mortality rate. Some studies in the field of health including one with chronic kidney disease have been carried out to detect the disease early, In this study, testing the Naive Bayes algorithm to detect the disease on patients who tested positive for negative CKD and CKD. From the results of the test algorithm accuracy value will be compared against the results of the algorithm accuracy before use and after feature selection using feature selection Featured Correlation Based Selection (CFS), it is known that Naive Bayes algorithm after feature selection that is 93.58%, while the naive Bayes without feature selection the result is 93.54% accuracy. Seeing the value of a second accuracy testing Naive Bayes algorithm without using the feature selection and feature selection, testing both these algorithms including the classification is very good, because the accuracy value above 0.90 to 1.00. Included in the excellent classification. higher accuracy results.
Sebuah wacana tingkat global pada tahun 2030 yaitu program internasional SDGs (Sustainable Development Goals) mengalami disruptif optimisme yang dirasakan negara global (PBB). Walaupun secara fakta bukan hanya dokumen legal berbadan hukum, namun merupakan sebuah konsistensi yang terus berlangsung dengan disepakati bersama untuk performa perencanaan implementasinya. Salah satu upayanya dimulai dari yang paling rendah yaitu program yang digagas tingkat desa. Sinkronisasi data Desa adalah sekelompok kinerja yang dilakukan pada tingkat desa, hingga sampai Kementerian Desa. Merujuk kepada Permendesa PDTT No 21/2020, bahwa yang dimaksud kelompok Relawan Pendataan Desa ini diantaranya adalah Kepala Desa, Sekretaris Desa, Ka.si. Pemerintahan Desa, Perangkat Desa, Ketua RW, Ketua RT, Karang Taruna, dan PKK. Relawan tersebut yang nantinya bertugas sebagai pengambil data (data collecting). Proses penyampaian di dapat beberapa hasil dengan tingkat efektivitas sosialisasi yang di Desa Rempoah Kecamatan Baturaden. Pada makalah ini akan disampaikan beberapa hasil tingkat efektivitas melalui kegiatan sosialisasi yang dilaksanakan pada Desa Rempoah Kecamatan Baturaden.
The community's need for higher education is very important. Given the regulations of UU No.234 u 2000 concerning guidelines for the establishment of higher education institutions, it is quite easy for foundations and institutions, several institutions are competing and interesting to establish universities. Higher education is currently an attractive business field. The existence of graduates in the community or the market will always be an attribute of the community's assessment of the original university. If the alumni are well absorbed by the market, the university will get a positive assessment. Every university has an interest in knowing the level of user satisfaction of its graduates as an important part of the evaluation and projections of the institution. Problems arise when graduates are not well absorbed. Many factors could be the cause. In a business, of course, you must look at it from the point of view of market needs, the same thing as higher education institutions. If you don't pay attention to the market aspect, it is certain that graduates are not well absorbed due to lack of quality. In this article, we will discuss the sustainability of business processes in higher education based on user reviews of graduates. The continuity of this business process using a supply chain model approach.
Education in the industrial era 4.0 experienced very significant changes. The role of information technology is a significant trend in education. Since the pandemic occurred at the beginning of 2020, almost all schools and even universities have indirectly demanded rapid changes in adapting to digitalization methods. It was also found that there were many obstacles during the pandemic in the implementation of information technology. The Indonesian state itself in education is still adapting and starting to develop with the existence of models of information technology approaches that can be implemented in academic activities, especially on campuses. Since 2010 it has been following the smart campus concept and model development. However, it was found to be varied due to the absence of a benchmark index in the campus's preparation, monitoring, and evaluation. Through the Rainbow Framework, this will be a solution in measuring the feasibility level through monitoring and evaluating the use of technology with a quality assurance approach. The results can be seen from the components that have been built using the calculation model for the quality of technology education in Indonesia.
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