Analysis of Outpatient Satisfaction and the Quality of Health Services

Quality is an important factor in health services. Bakunase Health Center is one of the primary accredited health centers in Kupang City. Based on data from the Health Department, there has been a decrease in the number of visits over the last three years. This happens due to external factors and internal factors. The external factor is the increasing degree of public health, while the internal factor is the decrease in the patients’ commitment to treatment. The purpose of this study is to describe the level of outpatient satisfaction with the quality of health services at Bakunase Health Center of Kupang City in 2020. This was a descriptive survey with a quantitative approach. The population in this study was all patients who visited and used outpatient services at Bakunase Health Center in Kupang City from January to October 2019. Accidental sampling was used in selecting the samples from each outpatient sub-group in 7 polyclinics at Bakunase Health Center using inclusion and exclusion criteria. The results indicated that the level of conformity between expectations and reality of the services are as follows:  98.78% tangible, 98.66% reliable, 98.33% responsive, 98.79% assurance 98.74% empathy. Based on the Cartesian Importance Performance Analysis (IPA) diagram, quadrant A was filled by one attribute from the responsiveness dimension, quadrant B was filled by most attributes from the reliability dimension, quadrant C was filled by most attributes from the empathy dimension and quadrant D was filled by one attribute from the responsiveness dimension

Perbandingan Kinerja Basis Data Relasionaldengan Basis Data Berorientasi-objek Studi Kasus: Aplikasi Jpetstore

Basis Data Berorientasi Objek (BDBO) menggunakan model berorientasi objek untuk penyimpanan data. Selama ini penggunaan BDBO tidak populer disebabkan oleh beberapa standar yang berbeda dalam pemodelan dan perancangan skema data, serta kinerja yang dianggap kurang baik. Padahal dengan pengembangan aplikasi berorientasi objek seyogyanya penggunaan BDBO dapat menurunkan kerumitan dan meningkatkan kualitas kode aplikasi. Penelitian ini bertujuan mengkaji standar penerapan model objek data dan metode perancangan skema data pada BDBO melalui pengukuran kinerja dan kualitas kode dari aplikasi. Penelitian ini mengkaji penerapan model data ODMG 3.0 dan notasi UML pada aplikasi JPetStore dengan menggunakan transformasi Muller untuk perancangan skema data. Aplikasi JPetStore versi MySQL (BDR) dibandingkan kinerjanya dengan versi DB4O (BDBO). Hasil kajian adalah beberapa tambahan pada model ODMG 3.0 dan tambahan notasi UML untuk pemodelan data pada BDBO serta penyesuaian proses transformasi Muller. Kinerja aplikasi versi DB4O secara umum lebih cepat dibandingkan versi MySQL, kecuali dalam membaca data sederhana secara berurut. Kualitas kode aplikasi versi DB4O lebih baik dibandingkan versi MySQL

Penerapan Perbaikan Mutu Berkelanjutan (Continous Quality Improvement) Pasca Akreditasi Puskesmas Kota Kupang terhadap Tingkat Kepuasan Masyarakat

This research aims to analyze the effect of implementing continuous quality improvement (Continuous Quality Improvement) through improving the quality of administration and management, performance targets for public health efforts, and improving clinical quality and patient safety (PMKP) after accreditation of community health centers on the level of community satisfaction. The research method used is quantitative observational analytical research using a cross-sectional study. The research results show that Continuous Quality Improvement significantly affects the Level of Community Satisfaction. This can be seen from the significance value of 0.000 0.05; the Fcount value is greater than the FTable value (315.333 3.127). Conclusion: Continuous Quality Improvement (CQI) simultaneously or together influences community satisfaction. Continuous Quality Improvement (CQI) by the Oesapa Community Health Center and Penfui Community Health Center by implementing Community Health Center Accreditation standards significantly affects the level of community satisfaction. Keywords: Community Satisfaction, Continuous Quality Improvement, Community Health Cente

Architectural heritage images classification using deep learning with CNN

© 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). Digital documentation of cultural heritage images has emerged as an important topic in data analysis. Increasing the size and number of images to be processed making the task of categorizing them a challenging task and may take an inordinate amount of time. This research paper proposes a solution to the mentioned challenges by classifying the subject of the image of the study using Convolutional Neural Network. Classification of available images leads to improve the management of the images dataset and enhance the search of a specific item, which helps in the tasks of studying and analysis the proper heritage object. Deep learning for architectural heritage images classification has been employed during the course of this study. The pre-trained convolutional neural networks GoogLeNet, resnet18 and resnet50 proposed to be applied on public dataset Cultural Heritage images. Experimental results have shown promising outcomes with an accuracy of “87.91”, “95.47” and “95.57” respectively

Performance Analysis of TCP Tahoe, Reno, New Reno, Sack and Vegas using NS-2

The Transmission Control Protocol TCP is the dominating end-to-end protocol on the internet today but still it faces congestion problems in some cases To overcome congestion problems several congestion control and avoiding mechanisms namely Tahoe Reno Vegas and Sack etc all with different features and advantages but with maximal throughput as main objective which are termed as the clones of TCP have been incorporated into TCP IP protocol for handling congestion efficiently in different network scenarios However one clone cannot be suitable for each case So this paper has investigated the characteristics of the mentioned clones and calculated throughputs of them in simulated environment varying various performances metrics such as delay buffer size error rate number of traffic and bandwidth for finding which one is the best for what scenario The performance of these clones for varying network conditions and settings can effectively be evaluated using NS-2 In this work by doing simulation in NS-2 environment the throughputs of some exiting TCP implementations are calculated considering various metrics and then the calculated throughputs are compared among one another These comparisons show that which one is suitable in which case

Enhancing Transmission Capacity of a Cognitive Radio Network by Joint Spatial-Temporal Sensing with Cooperative Communication Strategy

In static cognitive radio network a secondary transmitter communicates directly with a secondary receiver only when the spectrum is not occupied by any primary user. The secondary user has to stop its transmission when no spectrum holes exist. To improve the transmission capacity, in this paper we approach to combine cognitive radio network with cooperative communication strategy employing spatial sensing as well as temporal sensing. In our proposed scheme when primary user is active, a secondary user transmits to another secondary user via a relay channel. By enabling the use of both the direct and relay channels, the transmission performance of the secondary system can be improved significantly. Our information-theoretic analysis as well as numerical results show that the proposed scheme significantly reduces the average symbol error probability compared to schemes based on pure temporal or spatial sensing

Performance Evaluation of Ad Hoc Network over Moving Vehicles in a City

A mobile ad hoc network (MANET) is a collection of wireless mobile nodes that can dynamically form a temporary network without the aid of any existing network infrastructure. Wireless connectivity on vehicles is an important mode of communication. It is more challenging to provide high-bandwidth networking over fast moving vehicles. Ad Hoc network can be formed on fast moving vehicles where the interior node acts as rely node. A dynamic routing protocol is needed for a node to exchange data with another. In this research work, we consider the traffic density of a typical district town where traffic density much lower than a metropolitan city and vehicle speed is regulated according to traffic law. We have studied two routing protocols AODV and DSR in city traffic. According to our study, AODV shows performance than DSR on city roa

Next generation proteomics with drug sensitivity screening identifies sub-clones informing therapeutic and drug development strategies for multiple myeloma patients

With the introduction of novel therapeutic agents, survival in Multiple Myeloma (MM) has increased in recent years. However, drug-resistant clones inevitably arise and lead to disease progression and death. The current International Myeloma Working Group response criteria are broad and make it difficult to clearly designate resistant and responsive patients thereby hampering proteo-genomic analysis for informative biomarkers for sensitivity. In this proof-of-concept study we addressed these challenges by combining an ex-vivo drug sensitivity testing platform with state-of-the-art proteomics analysis. 35 CD138-purified MM samples were taken from patients with newly diagnosed or relapsed MM and exposed to therapeutic agents from five therapeutic drug classes including Bortezomib, Quizinostat, Lenalidomide, Navitoclax and PF-04691502. Comparative proteomic analysis using liquid chromatography-mass spectrometry objectively determined the most and least sensitive patient groups. Using this approach several proteins of biological significance were identified in each drug class. In three of the five classes focal adhesion-related proteins predicted low sensitivity, suggesting that targeting this pathway could modulate cell adhesion mediated drug resistance. Using Receiver Operating Characteristic curve analysis, strong predictive power for the specificity and sensitivity of these potential biomarkers was identified. This approach has the potential to yield predictive theranostic protein panels that can inform therapeutic decision making.Peer reviewe