Pengaruh Kedisiplinan Kerja dan Motivasi Terhadap Kinerja Pegawai (Studi Kasus Pada SMP Negeri 3 Surakarta)

This research aims to find out: 1) the influence of the discipline of work on performance clerk; 2) influence the motivation of working against the performance of employees; and 3) the influence of the discipline of work and motivation on performance clerk in SMP Negeri 3. Type of this research is a survey research with quantitative approach. The population in this study are all the employees in the SMP Negeri 3 Surakarta which consists of 112 people. The sample in this research totaled 53 people who were selected using random sampling techniques. The technique of data collection conducted using questionnaires. Technique of data analysis performed multiple linear regression using two predictors, test F, t-test, and the coefficient of determination (R2). Based on the results of the analysis, this study concludes that: 1) there is a significant and positive influence on performance of work discipline employees; 2) there is significant motivation and a positive influence on performance clerk; 2) there is a significant and positive influence of the discipline of work and motivation together on performance clerk in SMP Negeri 3. Key words: work, discipline, performance motivation

Varietal preference of okra jassid, Amrasca devastans (Dist.) under field condition of Bangladesh

An experiment was conducted in the Field Laboratory, Department of Entomology, (BAU), Mymensingh on the varietal preference of okra jassid, Amrasca devastans (Dist.) using 14 okra varieties viz. F1 Tamanna, Hybrid Okra Gunyon, Okra F1 Green Soft, OK 285, Okra F1 Green Star 33, F1 Hybrid Fresh Power, F1 Hybrid Sarosh 3, Hybrid Okra (MDR), Okra Nabil, BARI-1 (Samrat), Hybrid Chamak and Local variety during March to June 2014. The results indicated that host preference of jassid differed significantly among the 14 varieties tested. Three varieties viz. Hybrid Chamak, Arka Anamika and Kolatia were the least preferred by jassid. Five varieties viz. Okra Nabil, Hybrid Okra (MDR), F1 Hybrid Fresh Power, Local variety, and OK 285 were comparatively highly preferred and rest of the six varieties viz. Okra F1 Green Star 33, BARI-1 (Samrat), F1 Tamanna, F1 Hybrid Sarosh 3, Hybrid Okra Gunyon, and Okra F1 Green Soft were moderately preferred by jassid. This variation of preference of okra jassid might be due to different morphological and physiological characters of selected varieties. It could be concluded that comparatively resistant varieties selected from the present study might be incorporated to develop of IPM package for jassid

Pengembangan Media Poster Pada Pembelajaran Ekonomi Dalam Meningkatkan Motivasi Belajar Siswa Kelas XI SMA Muhammadiyah 1 Sragen

This research and development is carried out in order to produce a learning media product in the form of posters that can be used in teaching in economic subjects at Muhammadiyah 1 Sragen High School. This study aims to determine learning outcomes and the level of student motivation to use poster-shaped learning media and find out the feasibility of poster learning media on the material of Economic Growth and Development. This development and research model is using the 4D Research and Development model (Define, Design, Development, and Dissemination). The types of data used in this study are qualitative and quantitative data. Data analysis technique used is quantitative descriptive analysis. The results of this research and development are producing a poster-shaped learning media product that contains material for Economic Growth and Development. Learning outcomes without using poster media showed an average pre-test score of 46 while the learning outcomes using poster media average score of post-test was 86.8, so there could be a difference in learning outcomes, namely a difference of 40.8. The feasibility of poster learning media is assessed by media experts and material experts

DistB-Condo: Distributed Blockchain-based IoT-SDN Model for Smart Condominium

Condominium network refers to intra-organization networks, where smart buildings or apartments are connected and share resources over the network. Secured communication platform or channel has been highlighted as a key requirement for a reliable condominium which can be ensured by the utilization of the advanced techniques and platforms like Software-Defined Network (SDN), Network Function Virtualization (NFV) and Blockchain (BC). These technologies provide a robust, and secured platform to meet all kinds of challenges, such as safety, confidentiality, flexibility, efficiency, and availability. This work suggests a distributed, scalable IoT-SDN with Blockchain-based NFV framework for a smart condominium (DistB-Condo) that can act as an efficient secured platform for a small community. Moreover, the Blockchain-based IoT-SDN with NFV framework provides the combined benefits of leading technologies. It also presents an optimized Cluster Head Selection (CHS) algorithm for selecting a Cluster Head (CH) among the clusters that efficiently saves energy. Besides, a decentralized and secured Blockchain approach has been introduced that allows more prominent security and privacy to the desired condominium network. Our proposed approach has also the ability to detect attacks in an IoT environment. Eventually, this article evaluates the performance of the proposed architecture using different parameters (e.g., throughput, packet arrival rate, and response time). The proposed approach outperforms the existing OF-Based SDN. DistB-Condo has better throughput on average, and the bandwidth (Mbps) much higher than the OF-Based SDN approach in the presence of attacks. Also, the proposed model has an average response time of 5% less than the core model

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Examining queue-jumping phenomenon in heterogeneous traffic stream at signalized intersection using UAV-based data

© 2020, Springer-Verlag London Ltd., part of Springer Nature. This research presents an in-depth microscopic analysis of heterogeneous and undisciplined traffic at the signalized intersection. Traffic data extracted from the video recorded using an unmanned aerial vehicle (UAV) at an approach of a signalized intersection is analyzed to study the within green time dynamics of traffic flow. Various parameters of Wiedemann 74, Wiedemann 99, and lateral behavior models used in microscopic traffic simulation package, Vissim, are calibrated for the local heterogeneous traffic. This research is aimed at exploring the queue-jumping phenomenon of motorbikes at signalized intersections and its impact on the saturation flow rate, travel time, and delay. The study of within green time flow dynamics shows that the flow of traffic within green time is not uniform. Surprisingly, the results indicate that the traffic flow for the first few seconds of the green time is significantly higher than the remaining period of green time, which shows a contradiction to the fact that traffic flow for the first few seconds is lower due to accelerating vehicles. Mode-wise traffic counted per second shows that this anomaly is attributed to the presence of motorbikes in front of the queue. Consequently, the outputs of simulation results obtained from calibrated Vissim show that the simulated travel time for motorbikes is significantly lower than the field-observed travel times even though the average simulated traffic flow matches accurately with the field-observed traffic flow. The findings of this research highlight the need to incorporate the queue-jumping behavior of motorbikes in the microsimulation packages to enhance their capability to model heterogeneous and undisciplined traffic

Epidemiology and antimicrobial resistance trends of Acinetobacter species in the United Arab Emirates: a retrospective analysis of 12 years of national AMR surveillance data

Introduction: Acinetobacter spp., in particular A. baumannii, are opportunistic pathogens linked to nosocomial pneumonia (particularly ventilator-associated pneumonia), central-line catheter-associated blood stream infections, meningitis, urinary tract infections, surgical-site infections, and other types of wound infections. A. baumannii is able to acquire or upregulate various resistance determinants, making it frequently multidrug-resistant, and contributing to increased mortality and morbidity. Data on the epidemiology, levels, and trends of antimicrobial resistance of Acinetobacter spp. in clinical settings is scarce in the Gulf Cooperation Council (GCC) and Middle East and North Africa (MENA) regions. Methods: A retrospective 12-year analysis of 17,564 non-duplicate diagnostic Acinetobacter spp. isolates from the United Arab Emirates (UAE) was conducted. Data was generated at 317 surveillance sites by routine patient care during 2010-2021, collected by trained personnel and reported by participating surveillance sites to the UAE National AMR Surveillance program. Data analysis was conducted with WHONET. Results: Species belonging to the A. calcoaceticus-baumannii complex were mostly reported (86.7%). They were most commonly isolated from urine (32.9%), sputum (29.0%), and soft tissue (25.1%). Resistance trends to antibiotics from different classes during the surveillance period showed a decreasing trend. Specifically, there was a significant decrease in resistance to imipenem, meropenem, and amikacin. Resistance was lowest among Acinetobacter species to both colistin and tigecycline. The percentages of multidrug-resistant (MDR) and possibly extensively drug-resistant (XDR) isolates was reduced by almost half between the beginning of the study in 2010 and its culmination in 2021. Carbapenem-resistant Acinetobacter spp. (CRAB) was associated with a higher mortality (RR: 5.7), a higher admission to ICU (RR 3.3), and an increased length of stay (LOS; 13 excess inpatient days per CRAB case), as compared to Carbapenem-susceptible Acinetobacter spp. Conclusion: Carbapenem-resistant Acinetobacter spp. are associated with poorer clinical outcomes, and higher associated costs, as compared to carbapenem-susceptible Acinetobacter spp. A decreasing trend of MDR Acinetobacter spp., as well as resistance to all antibiotic classes under surveillance was observed during 2010 to 2021. Further studies are needed to explore the reasons and underlying factors leading to this remarkable decrease of resistance over time