Penentuan Beban Kerja dan Kebutuhan Tenaga Kerja dengan Menggunakan Metode Fte ( Full TIME Equivalent ) pada Bagian Produksi Non Betalaktam ( Tablet Tablet Salut Kapsul ) PT Phapros Tbk

A company needs human resources who are able to work effectively and efficiently tomotivate the achievement of company's vision, mision, and goal. In producing human resources who can work effectively and efficiently needs an accurate human resource management. Planning and managing of human resources can be carried out by using workload analysis. There is an interesting phenomenon in Phapros Tbk, that there is an incompatibility between the workload and the number of workers which cause inefficiency works. Therefore, it needs to be carried out the workload measurement as the basis of the measurement of optimal worker needs. In this research, it discusses the workload measurement from operator of PT Phapros Tbk, production departement, TTSK unit by using Full Time Equivalent method ( FTE) Based on the calculation of workload by using FTE (Full Time Equivalent), it is concluded that the amount of workload and workers are not appropriate for the current state, among others there are 6 positions : TTSK packing supervisor, counting machine operators, drying machine, coding machine, rewinder machine and tablet printers. Optimizing the performance of labors can be done by changing the composition of the workforce in accordance to the calculation of optimal labor amount or perform job description re-arranging

The Inequality of Labor Graduates of Electromedical Engineer Women in Medical Device, Hospital and Health Equipment Facilities

In medical device companies, hospitals and healthcare facilities, graduates of Electromedical engineering occupy positions as medical equipment technicians, medical device installations, and calibration (large equipment installations). The main problem of this research is the female Electromedical engineering graduate who works in the Electromedical equipment company almost all the time works only revolve around the administration, which in no way touches the repair and maintenance of health equipment that should be their competence.The purpose of this research is for the public to be fair and not to be subordinated to women.  Women acquire gender equality including in the field of employment in accordance with their competence. The method used is qualitative research with a perspective Phenomenology approach and gender that analyses to twelve the subjective experience of research informers while working in three places, namely in electromedical equipment companies, in hospitals, and in health facilities services in Indonesia. Variables used are the competence of electrical engineering graduates and the type of work of female electromedical engineering graduates worked. The contribution of this research is to give input to the stakeholders to give the same opportunity to all the electromedical graduates both male and female. Emphasis on education institutions to review the education curriculum based on gender.  The results of this research are There were 2 informants who work in hospitals and medical devices companies who still carry out Electromedical Engineering competencies with varying degrees, ranging from still doing maintenance, minimal calibration, but are mostly tasked with administrative and management assignments. There are 10 informants who work in medical devices and hospitals that hardly carry out maintenance, calibration and installation of medical devices. In other words, they are by purely serving as administrators of medical equipment companies. The Conclusions of this study are Female graduates of electromedical engineering programs felt that they had not yet achieved their expectations in accordance with with their competencies as electromedical technicians. Keywords:Competencies, Electromedical Engineering, gender, and phenomenology perspective DOI: 10.7176/RHSS/11-20-06 Publication date:October 31st 202

Photoplethysmograph Portable

Photoplethysmograph (PPG) merupakan metode yang digunakan untuk mengetahui kondisi sistem kardiovaskular dengan mengukur perubahan volume darah pada jaringan kulit. Dalam penerapannya, metode ini menggunakan sensor optik untuk menangkap sinyal elektrik yang berasal dari sumber cahaya yang lewat atau dipantulkan. Penelitian terakhir monitoring photoplethysmography yang memiliki kemampuan mengirim melalui Bluetooth HC-05 tetapi penelitian tersebut terpisah antara alat dan display sehingga kurang praktis. Maka dari itu dibuatlah perancangan ini, yang dapat menampilkan sinyal PPG disertai dengan nilai SpO2 (saturasi oksigen kapiler perifer) dan BPM (Beat per Minutes) ditampilkan pada LCD TFT agar dapat mempermudah dalam memonitoring sinyal PPG tersebut.Pengujian alat ini dilakukan dengan membandingkan modul dengan alat ukur oximeter yang menghasilkan rata-rata %error pengukuran SpO2 sebesar 0,486 % dengan toleransi maksimum yang diizinkan ± 1%, sedangkan pada parameter BPM didapatkan rata-rata %error sebesar 0,683 % dengan toleransi maksimum yang diizinkan ± 5%

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction.

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome

Peran Guru Pendidikan Agama Islam Dalam Meningkatkan Kedisiplinan Siswa Di Sekolah Menengah Atas Muhammadiyah 3 Surakarta Tahun Pelajaran 2018/2019

Abstact Seeing the current phenomenon, the world of education in Indonesia is faced with various kinds of challenges and problems. Among the problems are various forms of juvenile delinquency. In disciplining students the role of Islamic education teachers and counseling teachers is expected to be able to improve student discipline. This study aims to describe the role of Islamic religious education teachers and counseling counselors in improving the discipline of students in middle school over Muhammadiyah 3 Surakarta. This research is field research. Sources of data from this study were obtained at Muhammadiyah 3 High School Surakarta, while the subjects of this study were the Principal, PAI and BK Teachers. Data collection techniques using interviews, observation and documentation, analysis of data from this study using deductive analysis methods. This study shows that the role of PAI and BK teachers in improving student discipline at Muhammadiyah 3 High School in Surakarta. PAI teachers have a role in improving discipline, especially the discipline of time, learning and worship and the roles performed by PAI teachers are well done. Keywords : Role, Improve, discipline

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction☆

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome

A fusion of salient and convolutional features applying healthy templates for MRI brain tumor segmentation

This paper proposes an improved brain tumor segmentation method based on visual saliency features on MRI image volumes. The proposed method introduces a novel combination of multiple MRI modalities used as pseudo-color channels for highlighting the potential tumors. The novel pseudo-color model incorporates healthy templates generated from the MRI slices without tumors. The constructed healthy templates are also used during the training of neural network models. Based on a saliency map built using the pseudo-color templates, combination models are proposed, fusing the saliency map with convolutional neural networks’ prediction maps to improve predictions and to reduce the networks’ eventual overfitting which may result in weaker predictions for previously unseen cases. By introducing the combination technique for deep learning techniques and saliency-based, handcrafted feature models, the fusion approach shows good abstraction capabilities and it is able to handle diverse cases that the networks were less trained for. The proposed methods were tested on the BRATS2015 and BRATS2018 databases, and the quantitative results show that hybrid models (including both trained and handcrafted features) can be promising alternatives for reaching higher segmentation performance. Moreover, healthy templates can provide additional information for the training process, enhancing the prediction performance of neural network models

A generative approach for image-based modeling of tumor growth

22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011. ProceedingsExtensive imaging is routinely used in brain tumor patients to monitor the state of the disease and to evaluate therapeutic options. A large number of multi-modal and multi-temporal image volumes is acquired in standard clinical cases, requiring new approaches for comprehensive integration of information from different image sources and different time points. In this work we propose a joint generative model of tumor growth and of image observation that naturally handles multi-modal and longitudinal data. We use the model for analyzing imaging data in patients with glioma. The tumor growth model is based on a reaction-diffusion framework. Model personalization relies only on a forward model for the growth process and on image likelihood. We take advantage of an adaptive sparse grid approximation for efficient inference via Markov Chain Monte Carlo sampling. The approach can be used for integrating information from different multi-modal imaging protocols and can easily be adapted to other tumor growth models.German Academy of Sciences Leopoldina (Fellowship Programme LPDS 2009-10)Academy of Finland (133611)National Institutes of Health (U.S.) (NIBIB NAMIC U54-EB005149)National Institutes of Health (U.S.) (NCRR NAC P41- RR13218)National Institutes of Health (U.S.) (NINDS R01-NS051826)National Institutes of Health (U.S.) (NIH R01-NS052585)National Institutes of Health (U.S.) (NIH R01-EB006758)National Institutes of Health (U.S.) (NIH R01-EB009051)National Institutes of Health (U.S.) (NIH P41-RR014075)National Science Foundation (U.S.) (CAREER Award 0642971

Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing

<p>Abstract</p> <p>Background</p> <p>In recent years, magnetic resonance imaging (MRI) has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images.</p> <p>This paper uses an algorithm integrating fuzzy-c-mean (FCM) and region growing techniques for automated tumor image segmentation from patients with menigioma. Only non-contrasted T1 and T2 -weighted MR images are included in the analysis. The study's aims are to correctly locate tumors in the images, and to detect those situated in the midline position of the brain.</p> <p>Methods</p> <p>The study used non-contrasted T1- and T2-weighted MR images from 29 patients with menigioma. After FCM clustering, 32 groups of images from each patient group were put through the region-growing procedure for pixels aggregation. Later, using knowledge-based information, the system selected tumor-containing images from these groups and merged them into one tumor image. An alternative semi-supervised method was added at this stage for comparison with the automatic method. Finally, the tumor image was optimized by a morphology operator. Results from automatic segmentation were compared to the "ground truth" (GT) on a pixel level. Overall data were then evaluated using a quantified system.</p> <p>Results</p> <p>The quantified parameters, including the "percent match" (PM) and "correlation ratio" (CR), suggested a high match between GT and the present study's system, as well as a fair level of correspondence. The results were compatible with those from other related studies. The system successfully detected all of the tumors situated at the midline of brain.</p> <p>Six cases failed in the automatic group. One also failed in the semi-supervised alternative. The remaining five cases presented noticeable edema inside the brain. In the 23 successful cases, the PM and CR values in the two groups were highly related.</p> <p>Conclusions</p> <p>Results indicated that, even when using only two sets of non-contrasted MR images, the system is a reliable and efficient method of brain-tumor detection. With further development the system demonstrates high potential for practical clinical use.</p

Regional Gray Matter Growth, Sexual Dimorphism, and Cerebral Asymmetry in the Neonatal Brain

Although there has been recent interest in the study of childhood and adolescent brain development, very little is known about normal brain development in the first few months of life. In older children, there are regional differences in cortical gray matter development, whereas cortical gray and white matter growth after birth has not been studied to a great extent. The adult human brain is also characterized by cerebral asymmetries and sexual dimorphisms, although very little is known about how these asymmetries and dimorphisms develop. We used magnetic resonance imaging and an automatic segmentation methodology to study brain structure in 74 neonates in the first few weeks after birth. We found robust cortical gray matter growth compared with white matter growth, with occipital regions growing much faster than prefrontal regions. Sexual dimorphism is present at birth, with males having larger total brain cortical gray and white matter volumes than females. In contrast to adults and older children, the left hemisphere is larger than the right hemisphere, and the normal pattern of fronto-occipital asymmetry described in older children and adults is not present. Regional differences in cortical gray matter growth are likely related to differential maturation of sensory and motor systems compared with prefrontal executive function after birth. These findings also indicate that whereas some adult patterns of sexual dimorphism and cerebral asymmetries are present at birth, others develop after birth