scholarly journals APLIKASI K-MEANS DAN FUZY CLUSTERING DALAM PENGELOMPOKAN KECAMATAN DI KABUPATEN BANYUMAS

2021 ◽  
Vol 13 (2) ◽  
pp. 113
Author(s):  
Jajang Jajang ◽  
Nunung Nurhayati ◽  
Yhenis Apriliana
Keyword(s):  
Health Workers ◽  
Health Facilities ◽  
Total Variance ◽  
Variance Ratio ◽  
Clustering Methods ◽  
Cluster Membership ◽  
Fuzzy C Means ◽  
Degree Of Membership ◽  
Better Than

Clustering N objects into c clusters can be used to get information about data observation. Among the clustering methods are K-Means (KMC) and Fuzzy C-means (FCM) methods. In the K-means method, objects are members or not members of the cluster, while in the FCM method, objects are included in the cluster based on the degree of membership. This study discusses the implementation of KMC and FCM in the custering of sub-districts in Banyumas Regency based on total of population, the number of health workers and the number of health facilities and infrastructure. The results showed that the KMC and FCM methods produced the same cluster membership. Furthermore, the analysis of clustering based on the number of population, the number of health workers and the number of health facilities and infrastructure (scenario 1) and based on the number of health workers and the number of health facilities and infrastructure which have been corrected by population (scenario 2). The percentage of the variance ratio between clusters to the total variance in scenario 1 is 69% while in scenario 2 it is 85%. Clustering based on scenario 2 is better than scenario 1.

scholarly journals Relational Fuzzy c-Means and Kernel Fuzzy c-Means Using an Object-Wise β-Spread Transformation

2013 ◽  
Vol 17 (4) ◽  
pp. 511-519 ◽  
Author(s):  
Yuchi Kanzawa ◽  
Keyword(s):  
Positive Semidefinite ◽  
Relational Data ◽  
Gram Matrix ◽  
Clustering Methods ◽  
Numerical Examples ◽  
Fuzzy C Means ◽  
Indefinite Kernel ◽  
Conventional Methods ◽  
The Given ◽  
Better Than

Clustering methods of relational data are often based on the assumption that a given set of relational data is Euclidean, and kernelized clustering methods are often based on the assumption that a given kernel is positive semidefinite. In practice, non-Euclidean relational data and an indefinite kernel may arise, and a β-spread transformation was proposed for such cases, which modified a given set of relational data or a give a kernel Gram matrix such that the modified β value is common to all objects. In this paper, we propose an object-wise β-spread transformation for use in both relational and kernelized fuzzy c-means clustering. The proposed system retains the given data better than conventional methods, and numerical examples show that our method is efficient for both relational and kernel fuzzy c-means.

scholarly journals Optimization of Fuzzy c-means (FCM) Clustering in Cytology Image Segmentation Using the Gray Wolf Algorithm

2021 ◽  
Author(s):  
Maryam Mohammdian-khoshnoud ◽  
Ali Reza Soltanian ◽  
Arash Dehghan ◽  
Maryam Farhadian
Keyword(s):  
Image Segmentation ◽  
Gray Wolf ◽  
Clustering Methods ◽  
Local Optima ◽  
Fuzzy C Means ◽  
Significant Difference ◽  
Fuzzy C Means Clustering ◽  
Fcm Clustering ◽  
The Common ◽  
Better Than

Abstract Background: Image segmentation is considered an important step in image processing. Fuzzy c-means clustering is one of the common methods of image segmentation. However, this method suffers from drawbacks, such as sensitivity to initial values, entrapment in local optima, and the inability to distinguish objects with similar color intensity. This paper proposes the hybrid Fuzzy c-means clustering and Gray wolf optimization for image segmentation to overcome the shortcomings of fuzzy c-means clustering. The Gray wolf optimizationhas a high exploration capability in finding the best solution to the problem, which prevents the entrapment of the algorithm in local optima. In this study, breast cytology images were used to validate the methods, and the results of the proposed method were compared to those of c-means clustering.Results: FCMGWO has performed better than FCM in separating the nucleus from the other dark objects in the cell. The clustering was validated using Vpc, Vpe, Davies-Bouldin, and Calinski Harabasz criteria. The FCM and FCMGWO methods have a significant difference with respect to the Vpc and Vpe indices. However, there is no significant difference between the performances of the two clustering methods with respect to the Calinski-Harabasz and Davies-Bouldinindices. The results indicate the better efficacy of the proposed method.Conclusions: The hybridFCMGWO algorithm distinguishes the cells better in images with less detail than in images with high detail. However, FCM exhibits unacceptable performance in both low- and high-detail images.

scholarly journals A health worker knowledge, attitudes and practices survey of SARS-CoV-2 infection prevention and control in South Africa

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Saiendhra Vasudevan Moodley ◽  
Muzimkhulu Zungu ◽  
Molebogeng Malotle ◽  
Kuku Voyi ◽  
Nico Claassen ◽  
...  
Keyword(s):  
South Africa ◽  
Health Worker ◽  
Prevention And Control ◽  
Infection Prevention ◽  
Health Workers ◽  
Health Facilities ◽  
World Health ◽  
Infection Prevention And Control ◽  
Successful Implementation ◽  
And Control

Abstract Background Health workers are crucial to the successful implementation of infection prevention and control strategies to limit the transmission of SARS-CoV-2 at healthcare facilities. The aim of our study was to determine SARS-CoV-2 infection prevention and control knowledge and attitudes of frontline health workers in four provinces of South Africa as well as explore some elements of health worker and health facility infection prevention and control practices. Methods A cross-sectional study design was utilised. The study population comprised both clinical and non-clinical staff working in casualty departments, outpatient departments, and entrance points of health facilities. A structured self-administered questionnaire was developed using the World Health Organization guidance as the basis for the knowledge questions. COVID-19 protocols were observed during data collection. Results A total of 286 health workers from 47 health facilities at different levels of care participated in the survey. The mean score on the 10 knowledge items was 6.3 (SD = 1.6). Approximately two-thirds of participants (67.4%) answered six or more questions correctly while less than a quarter of all participants (24.1%) managed to score eight or more. A knowledge score of 8 or more was significantly associated with occupational category (being either a medical doctor or nurse), age (< 40 years) and level of hospital (tertiary level). Only half of participants (50.7%) felt adequately prepared to deal with patients with COVD-19 at the time of the survey. The health workers displaying attitudes that would put themselves or others at risk were in the minority. Only 55.6% of participants had received infection prevention and control training. Some participants indicated they did not have access to medical masks (11.8%) and gloves (9.9%) in their departments. Conclusions The attitudes of participants reflected a willingness to engage in appropriate SARS-CoV-2 infection prevention and control practices as well as a commitment to be involved in COVID-19 patient care. Ensuring adequate infection prevention and control training for all staff and universal access to appropriate PPE were identified as key areas that needed to be addressed. Interim and final reports which identified key shortcomings that needed to be addressed were provided to the relevant provincial departments of health.

scholarly journals Health workers’ perceptions on where and how to integrate tobacco use cessation services into tuberculosis treatment; a qualitative exploratory study in Uganda

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Elizeus Rutebemberwa ◽  
Kellen Nyamurungi ◽  
Surabhi Joshi ◽  
Yvonne Olando ◽  
Hadii M. Mamudu ◽  
...  
Keyword(s):  
Tobacco Use ◽  
Tobacco Cessation ◽  
Health Workers ◽  
High Volume ◽  
Health Facilities ◽  
Hospital Treatment ◽  
Management Support ◽  
Tobacco Use Cessation ◽  
Tb Treatment

Abstract Background Tobacco use is associated with exacerbation of tuberculosis (TB) and poor TB treatment outcomes. Integrating tobacco use cessation within TB treatment could improve healing among TB patients. The aim was to explore perceptions of health workers on where and how to integrate tobacco use cessation services into TB treatment programs in Uganda. Methods Between March and April 2019, nine focus group discussions (FGDs) and eight key informant interviews were conducted among health workers attending to patients with tuberculosis on a routine basis in nine facilities from the central, eastern, northern and western parts of Uganda. These facilities were high volume health centres, general hospitals and referral hospitals. The FGD sessions and interviews were tape recorded, transcribed verbatim and analysed using content analysis and the Chronic Care Model as a framework. Results Respondents highlighted that just like TB prevention starts in the community and TB treatment goes beyond health facility stay, integration of tobacco cessation should be started when people are still healthy and extended to those who have been healed as they go back to communities. There was need to coordinate with different organizations like peers, the media and TB treatment supporters. TB patients needed regular follow up and self-management support for both TB and tobacco cessation. Patients needed to be empowered to know their condition and their caretakers needed to be involved. Effective referral between primary health facilities and specialist facilities was needed. Clinical information systems should identify relevant people for proactive care and follow up. In order to achieve effective integration, the health system needed to be strengthened especially health worker training and provision of more space in some of the facilities. Conclusions Tobacco cessation activities should be provided in a continuum starting in the community before the TB patients get to hospital, during the patients’ interface with hospital treatment and be given in the community after TB patients have been discharged. This requires collaboration between those who carry out health education in communities, the TB treatment supporters and the health workers who treat patients in health facilities.

scholarly journals Infectious Disease Relational Data Analysis Using String Grammar Non-Euclidean Relational Fuzzy C-Means

2021 ◽  
Vol 18 (15) ◽  
pp. 8153
Author(s):  
Apiwat Budwong ◽  
Sansanee Auephanwiriyakul ◽  
Nipon Theera-Umpon
Keyword(s):  
High Risk ◽  
Dengue Fever ◽  
Policy Development ◽  
Dengue Infection ◽  
Prevention Policy ◽  
Fuzzy C Means ◽  
North East ◽  
B Virus ◽  
North And South ◽  
Better Than

Statistical analysis in infectious diseases is becoming more important, especially in prevention policy development. To achieve that, the epidemiology, a study of the relationship between the occurrence and who/when/where, is needed. In this paper, we develop the string grammar non-Euclidean relational fuzzy C-means (sgNERF-CM) algorithm to determine a relationship inside the data from the age, career, and month viewpoint for all provinces in Thailand for the dengue fever, influenza, and Hepatitis B virus (HBV) infection. The Dunn’s index is used to select the best models because of its ability to identify the compact and well-separated clusters. We compare the results of the sgNERF-CM algorithm with the string grammar relational hard C-means (sgRHCM) algorithm. In addition, their numerical counterparts, i.e., relational hard C-means (RHCM) and non-Euclidean relational fuzzy C-means (NERF-CM) algorithms are also applied in the comparison. We found that the sgNERF-CM algorithm is far better than the numerical counterparts and better than the sgRHCM algorithm in most cases. From the results, we found that the month-based dataset does not help in relationship-finding since the diseases tend to happen all year round. People from different age ranges in different regions in Thailand have different numbers of dengue fever infections. The occupations that have a higher chance to have dengue fever are student and teacher groups from the central, north-east, north, and south regions. Additionally, students in all regions, except the central region, have a high risk of dengue infection. For the influenza dataset, we found that a group of people with the age of more than 1 year to 64 years old has higher number of influenza infections in every province. Most occupations in all regions have a higher risk of infecting the influenza. For the HBV dataset, people in all regions with an age between 10 to 65 years old have a high risk in infecting the disease. In addition, only farmer and general contractor groups in all regions have high chance of infecting HBV as well.

scholarly journals ASSOCIATION BETWEEN DURATION AS A FISHERMAN, DISTANCE OF HEALTH FACILITIES AND SMOKING WITH PTERYGIUM'S DISEASE IN FISHERMAN IN BENGKULU

2021 ◽  
Vol 10 (1) ◽  
pp. 65-71
Author(s):  
Dwi Putri Sulistiya Ningsih ◽  
Ida Rahmawati
Keyword(s):  
Significant Relationship ◽  
Health Workers ◽  
Case Control ◽  
High Risk Group ◽  
Health Facilities ◽  
Observational Research ◽  
Validity And Reliability ◽  
Chi Square ◽  
Table Data ◽  
Methods Analytical

Background: Fishermen are a high risk group for developing pterygium. The high frequency of exposure to UV, wind, dust and sand when working makes the prevalence of pterygium among fishermen quite high. The city of Bengkulu, which is geographically located on the west coast of Sumatra Island which is directly facing the Indonesian Ocean, makes the majority of its population work as fishermen. Objectives: This study aims to determine the relationship between duration of being a fisherman, distance to health facilities and smoking with pterygium disease in a group of fishermen in, Bengkulu. Methods: Analytical observational research with case control design. The sample of 120 fishermen consisted of 40 cases and 80 controls, because researchers used a case-control ratio of 1:2. Sampling using purposive sampling method. The dependent variable was pterygium disease. Independent variables of duration as a fisherman, distance of health facilities and smoking. The research instrument uses a structured questionnaire that has been tested for validity and reliability with Alpha Cronbach value (0.996) > r table. Data were analyzed by Chi Square. Results: Based on the research results, it was found that there was a significant relationship with duration as a fisherman (≥ 21 years) (OR = 3.980; 95%CI = 1.404-11.284; p = 0.006) with pterygium disease. There is no relationship between smoking (OR = 1.246; 95%CI = 0.559-2.778; p = 0.590) with pterygium disease. There is a significant relationship between the distance of health facilities (OR = 5.133; 95%CI = 2.249-11.715; p = 0.000) with pterygium disease. Conclusion: The length of time working as a fisherman increases the risk of developing pterygium disease as the frequency of exposure to UV, dust, wind and sand increases. It is necessary to use personal protective equipment to reduce the risk of exposure and education from health workers so that the public can take good preventive measures.   Keywords: Duration as a fisherman, distance health facilities, smoking, pterygium.

scholarly journals Evaluation of Infection, Prevention and Control Program in Goromonzi District, Zimbabwe, 2018: A process outcome evaluation

2019 ◽  
Author(s):  
Govha Emmanuel ◽  
Zizhou Simukai Tirivanhu ◽  
Shambira Gerald ◽  
Gombe Tafara Notion ◽  
Tsitsi Juru ◽  
...  
Keyword(s):  
Health Facility ◽  
Prevention And Control ◽  
Infection Prevention ◽  
Health Workers ◽  
Outcome Evaluation ◽  
Hazard Identification ◽  
Health Facilities ◽  
Infection Prevention And Control ◽  
Hiv Test ◽  
And Control

Abstract Background A healthcare-associated infection (HAI) is defined as an infection originating in the environment of a health facility that was not present or incubating at the time of patient admission. HAIs can be prevented through infection, prevention and control (IPC) measures. No hazard identification and risk assessment IPC rounds and monthly meetings were conducted in Goromonzi district since 1st of January to 30th of June 2018. No trainings nor orientation for the new employees was conducted. We therefore evaluated Goromonzi District IPC program. Methods A process-outcome evaluation using the logic model was conducted in Goromonzi district’s 15 health facilities. Checklists, interviewer administered questionnaires and key informant guides were used to collect data on availability of inputs, knowledge of health workers, processes performed, outputs and outcomes achieved. Data were entered into Epi Info 7TM, which was used to generate frequencies and proportions. Qualitative data from checklists and key informants interviews was sorted manually into themes and analysed. Results All 15 health facilities had adequate stocks of HIV test kits and PEP kits. Adequate bins and detergents were found in only 3/15 (20%) of health facilities. All facilities failed to hold a single IPC meeting and none had specific budget for IPC in 2018. No IPC mentorship activities were carried out in the district. Only 7/13 (54%) health workers who had needle pricks received PEP with 2/7 (29%) of them finishing the course. No health facility had a functional HAI surveillance system. The overall knowledge rating was fair. Conclusion The IPC program inputs in Goromonzi district were inadequate hence its failure to achieve the intended outputs and outcomes. Inadequate knowledge, unavailability of health worker training plans, specific budgets and absence of IPC committees reflected non prioritisation of the program.

scholarly journals Health Workers’ Perceptions on Where and How to Integrate Tobacco use Cessation Services into Tuberculosis Treatment; A Qualitative Exploratory Study in Uganda

2020 ◽  
Author(s):  
Elizeus Rutebemberwa ◽  
Kellen Nyamurungi ◽  
Surabhi Joshi ◽  
Yvonne Olando ◽  
Hadii M. Mamudu ◽  
...  
Keyword(s):  
Tobacco Use ◽  
Health Workers ◽  
High Volume ◽  
Health Facilities ◽  
Treatment Programs ◽  
Tobacco Use Cessation ◽  
Tb Treatment ◽  
Routine Basis ◽  
Referral Hospitals ◽  
The Media

Abstract Background: Tobacco use is associated with exacerbation of tuberculosis (TB) and poor TB treatment outcomes. Integrating tobacco use cessation within TB treatment could improve healing among TB patients. The aim was to explore perceptions of health workers on where and how to integrate tobacco use cessation services into TB treatment programs in Uganda.Methods: Between March and April 2019, nine focus group discussions (FGDs) and eight key informant interviews were conducted among health workers attending to patients with tuberculosis on a routine basis in nine facilities from the central, eastern, northern and western parts of Uganda. These facilities were high volume health centres, general hospitals and referral hospitals. The FGD sessions and interviews were tape recorded, transcribed verbatim and analysed using content analysis to identify themes.Results: Participants indicated that tobacco use cessation activities should be integrated in TB treatment starting from communities when people are still healthy. Cessation should also be implemented in health facilities including referral facilities, and be extended to those who have been healed as they go back to communities. This calls for collaborations beyond health workers to TB treatment supporters, peers and the media. Conclusions: Tobacco use cessation should take place in communities as well as health facilities. Partnerships with media and families are needed. Health system challenges need to be addressed to support effective implementation.

scholarly journals THE CHILDBIRTH UTILIZATION IN HEALTH FACILITIES IN THE WORKING AREA OF SUNGAI LOKAN PHC TANJUNG JABUNG TIMUR REGENCY: A CROSS SECTIONAL STUDY

NSC Nursing ◽  
2021 ◽  
pp. 20-33
Author(s):  
Lia Artika Sari ◽  
Yuli Suryanti ◽  
Enny Susilawati
Keyword(s):  
Health Center ◽  
Family Support ◽  
Health Workers ◽  
Community Health Center ◽  
Cross Sectional Study ◽  
Health Facilities ◽  
Service Access ◽  
Cross Sectional ◽  
Family Culture ◽  
Work Area

Introduction: The low number of deliveries assisted by midwives or health workers is an indicator of the low utilization of health facilities by mothers in labor. This study analyzes the factors related to the utilization of childbirth in health facilities in the Sungai Lokan Community Health Center Work Area, Tanjung Jabung Timur Regency. Materials and Methods: This research is an analytic observational using a cross-sectional approach involving 74 participants. The research was conducted from January to July 2019 in the Sungai Lokan Health Center Work Area, Tanjung Jabung Timur Regency. Results: The results showed that the factor of the utilization of childbirth in health facilities was related to family culture (p = 0.0001) and family support (p = 0.003), while the service access factor was not related (p = 0.364). Conclusion: The role of health workers in socializing the importance of utilizing health facilities as a place of delivery is significant in reducing maternal mortality Keywords: Health Facilities; Family Culture; Family Support; Access To Services

scholarly journals KOMPARASI METODE CLUSTERING K-MEANS DAN K-MEDOIDS DENGAN MODEL FUZZY RFM UNTUK PENGELOMPOKAN PELANGGAN

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Elly Muningsih - AMIK BSI Yogyakarta
Keyword(s):  
Data Clustering ◽  
Small Data ◽  
Clustering Methods ◽  
Monetary Model ◽  
Clustering Method ◽  
Online Sales ◽  
Rfm Model ◽  
Potential Customers ◽  
Cluster 2 ◽  
Better Than

Abstract ~ The K-Means method is one of the clustering methods that is widely used in data clustering research. While the K-Medoids method is an efficient method used for processing small data. This study aims to compare two clustering methods by grouping customers into 3 clusters according to their characteristics, namely very potential (loyal) customers, potential customers and non potential customers. The method used in this study is the K-Means clustering method and the K-Medoids method. The data used is online sales transaction. The clustering method testing is done by using a Fuzzy RFM (Recency, Frequenty and Monetary) model where the average (mean) of the third value is taken. From the data testing is known that the K-Means method is better than the K-Medoids method with an accuracy value of 90.47%. Whereas from the data processing carried out is known that cluster 1 has 16 members (customers), cluster 2 has 11 members and cluster 3 has 15 members. Keywords : clustering, K-Means method, K-Medoids method, customer, Fuzzy RFM model. Abstrak ~ Metode K-Means merupakan salah satu metode clustering yang banyak digunakan dalam penelitian pengelompokan data. Sedangkan metode K-Medoids merupakan metode yang efisien digunakan untuk pengolahan data yang kecil. Penelitian ini bertujuan untuk membandingkan atau mengkomparasi dua metode clustering dengan cara mengelompokkan pelanggan menjadi 3 cluster sesuai dengan karakteristiknya, yaitu pelanggan sangat potensial (loyal), pelanggan potensial dan pelanggan kurang (tidak) potensial. Metode yang digunakan dalam penelitian ini adalah metode clustering K-Means dan metode K-Medoids. Data yang digunakan adalah data transaksi penjualan online. Pengujian metode clustering yang dilakukan adalah dengan menggunakan model Fuzzy RFM (Recency, Frequenty dan Monetary) dimana diambil rata-rata (mean) dari nilai ketiga tersebut. Dari pengujian data diketahui bahwa metode K-Means lebih baik dari metode K-Medoids dengan nilai akurasi 90,47%. Sedangkan dari pengolahan data yang dilakukan diketahui bahwa cluster 1 memiliki 16 anggota (pelanggan), cluster 2 memiliki 11 anggota dan cluster 3 memiliki 15 anggota. Kata kunci : clustering, metode K-Means, metode K-Medoids, pelanggan, model Fuzzy RFM.

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