Health Promotion with Counseling on Fulfilling Balanced Nutritional Needs for Community Groups in Pandemic Covid 19 Outbreak

Covid-19 pandemic could increase forms of malnutrition such as overweight and micronutrient deficiencies. Fruits and vegetables are the best sources of vitamins and minerals. The content of vitamins and minerals can act as antioxidant compounds. The method used in this service activity consists of the planning stage, the implementation of the activity, and ends with an evaluation as a measure of the level of success. Health education is carried out by means of lectures and question and answer sessions, educational media using leaflets and PowerPoint Presentations. Results: the evaluation shows that the activities have been carried out well in accordance with the results indicators and criteria on the Evaluation Sheet instrument. The sheet is based on five dimensions, namely Punctuality and Duration, Participation, Knowledge, Job Description and Problem Solving. The content of the evaluation is carried out by two independent observers.

Resume Parser with Natural Language Processing

<div>Because the online recruiting system has progressed, a large number of resumes were submitted. As a consequence, hiring new employees and reviewing a large number of resumes is a challenge for the human resource department or employer. Therefore, this system has helped employers by using an automated intelligent system based on natural language processing. This system can convert various formats of resumes to text format and can extract some important information. It is also possible to compare the applicant's resume and the job description to see the percentage of similarity as well. This system can assist the human resource department or employer in screening resumes before conducting interviews and finding the best candidate for the job position.</div>

Resume Parser with Natural Language Processing

<div>Because the online recruiting system has progressed, a large number of resumes were submitted. As a consequence, hiring new employees and reviewing a large number of resumes is a challenge for the human resource department or employer. Therefore, this system has helped employers by using an automated intelligent system based on natural language processing. This system can convert various formats of resumes to text format and can extract some important information. It is also possible to compare the applicant's resume and the job description to see the percentage of similarity as well. This system can assist the human resource department or employer in screening resumes before conducting interviews and finding the best candidate for the job position.</div>

Pentingnya Desain Ulang Pekerjaan Dan Deskripsi Pekerjaan Untuk Peningkatan Kinerja Pegawai Pada Masa Pandemi Covid 19

This study is to examine the effect of Job Redesign and Job Description on Employee Performance in the Public Works and Spatial Planning Office of Serang Regency. The method used is a quantitative method. The population is 55 employees and the sample is 35 employees. Data were collected using a questionnaire. To test the model and hypothesis, the SPSS version 25 program was used. Based on the results of this study indicate: Job Redesign partially has no effect on employee performance. Job description partially positive and significant effect on employee performance. Job redesign and job description simultaneously have a positive and significant effect on employee performance.

Talent Acquisition Process Optimization Using Machine Learning in Resumes’ Ranking and Matching to Job Descriptions

Employers commonly use time-consuming screening tools or online matching engines that are driven by manual roles and predefined keywords, to search for potential job applicants. Such traditional techniques have not kept pace with the new digital revolution in machine learning and big data analytics. This paper presents advanced artificial intelligent solutions employed for ranking resumes and CV-to-Job Description matching. Open source resumes and job descriptions' documents were used to construct and validate the machine learning models in this paper. Documents were converted to images and processed via Google cloud using Optical Character Recognition algorithm (OCR) to extract text information from all resumes and job descriptions' documents, with more than 97% accuracy. Prior to modeling, the extracted text were processed via a series of Natural Language Processing (NLP) techniques by splitting/tokenizing common words, grouping together inflected form of words, i.e. lemmatization, and removal of stop words and punctuation marks. After text processing, resumes were trained using the unsupervised machine learning algorithm, Latent Dirichlet Allocation (LDA), for topic modeling and categorization. Given the type of resumes used, the algorithm was able to categorize them into 4 main job sectors: marketing and business, engineering, computer science/IT and health. Scores were assigned to each resume to represent the maximum LDA probability for ranking. Another more advanced deep learning algorithm, called Doc2Vec, was also used to train and match potential resumes to relevant job descriptions. In this model, resumes are represented by unique vectors that can be used to group similar documents, match and retrieve resumes related to a given job description document provided by HR. The similarity is measured between each resume and the given job description file to query the top job candidates. The model was tested against several job description files related to engineering, IT and human resources, and was able to identify the top-ranking resumes from over hundreds of trained resumes. This paper presents an innovative method for processing, categorizing and ranking resumes using advanced computational models empowered by the latest fourth industrial resolution technologies. This solution is beneficial to both job seekers and employers, providing efficient and unbiased data-driven method for finding top applicants for a given job.

Community Workforce Differences in Mental Health Across Gender and Job Description in Southwest Indiana

Background and Hypothesis: In May 2020, a community partnership was built in Southwest Indiana to determine the local prevalence of COVID-19 to guide reopening in the region. One year later, a follow-up survey study was launched to address new, pressing questions related to mental health in the community workforce. We hypothesized that adverse mental health symptoms would be disproportionately experienced by specific worker groups based on degree of in-person contact over the past year and demographic characteristics such as age and gender. Methods: For the 2021 survey, participants were invited through their place of employment or via phone to participate in a short online survey consisting of questions related to demographics, general work roles, company policies over the past year, and wellness. When examining mental health, the Patient Health Questionnaire-2 (PHQ-2) and General Anxiety Disorder-2 (GAD-2) were used to determine feelings of depression and anxiety, respectively. Results: 480 participants filled out the 2021 online survey (73% of which were returning). 442 of these responses were complete and eligible for analysis of mental health and degree of in-person contact. 345 responses were complete and eligible for information regarding age. No correlation was found between age and mental health. However, differences were observed based on gender and job description. Women (n=244) and customer-facing employees (n=99) reported more frequent symptoms of anxiety and depression, with customer-facing women reporting the most. Comparing only employees that did not work remotely during the pandemic, customer-facing employees still reported more frequent symptoms of anxiety and depression. Conclusion and Potential Impact: The impacts of COVID-19 on the workforce are still being studied, but the pandemic continues to take its toll. These mental health trends will help guide future policies to support and improve employee wellbeing, both within participating companies and the workforce at large.

STUDI KASUS ANALISIS BEBAN KERJA BERDASARKAN WAKTU KERJA KARYAWAN PADA UNIT PEMANENAN AFDELING 1 DI KEBUN KELAPA SAWIT PT. XYZ

The importance of quality human resources in oil palm plantations in the field of harvesting to achieve high productivity, the success of harvesters is also very much determined by the pressure of the workload that is owned by workers, the workload depends on the job description compiled by the company. also the possibility of a workload that is too high. This study aims to analyze the working time of harvest employees and determine the productive, unproductive and personal time of harvest employees and analyze the number of harvest employees needed at PT. XYZ. This research was conducted at PT. XYZ Tanjung Batu Village, Derawan Island District, Berau Regency, East Kalimantan. This research was conducted using work sampling data collection method, namely observing the working time of harvest employees with 10 minutes intervals for 7 working hours by noting productive time, unproductive time and personal time. The results from the observations of researchers through the characteristics of harvest workers that affect the characteristics of age and height characteristics, it is proven that the age of 20 - 29 years is faster to reach the target or basis compared to the age of 30 - 49 years. And the characteristics of height have an effect on reaching the target, it is proven that height 170 - 179 cm reaches the target or base faster than 150 - 159 cm. And the observations of researchers from 16 respondents harvest productive working time an average of 73.52%, 17.20% unproductive time and 9.28% personal time. Calculation of the need for harvest workers in 1 division (763.33 ha) results in 33,644 rounded up to 34 harvest workers, the results needed in 1 division (763.33 ha) through the calculation of the time of completion of tasks (WPT).

Diagnosing occupational COVID-19 in Croatian healthcare workers

Coronavirus disease 2019 (COVID-19) can be diagnosed as occupational disease by an occupational health physician (OHP), if supported by relevant work-related and medical documentation. The aim of this study was to analyse such documentation submitted by Croatian healthcare workers (HCWs) and discuss its relevance in view of European and Croatian guidelines. The study included 100 Croatian HCWs who were SARS-CoV-2-positive and requested that their infection be diagnosed as occupational disease by their OHPs from 1 May 2020 to 10 March 2021. As participants they were asked to fill out our online Occupational COVID-19 in Healthcare Workers Questionnaire. For the purpose of this study we analysed answers about the type of close contact at the workplace, COVID-19 symptoms, and enclosed work-related (job description, employer statement about exposure to SARS-CoV-2) and medical documentation (positive SARS-CoV-2 polymerase chain reaction test and patient history confirming the diagnosis of COVID-19). Most participants were working in hospitals (N=95), mostly nurses (N=75), who became infected by a patient (N=68) or colleague (N=31), and had at least one COVID-19 symptom (N=87). Eighty participants did not enclose obligatory documents, 41 of whom failed to submit job description and 31 both job description and employer statement. These findings confirm that the major risk of occupational COVID-19 in HCWs is close contact with patients and colleagues, and points out the need for better cooperation between OHPs, occupational safety experts, employers, and diseased workers.

Development of Tourism Villages Based on Promotion Integration Through Websites

Galengdowo Village has both natural and artificial tourism potential. The problem is that the promotion has not been carried out optimally and has not been integrated into one website and the lack of tourist information for prospective tourists. The goal of this action is to progress tourist villages through digitization and web sites. The methods used are training, mentoring, supervising, and asessment. The findings indicate this the tutoring and assistance in operating the web and the design of the promotion greatly impact the participants, it can regarded the finding of monitoring through the galengdowo. id web. he tourist information center is very much needed by the manager because it can provide information about tourist attractions to tourists. The results of the organizational management training, namely increasing the quality of Pokdarwis managers, which initially did not have a job description and after the training, there was a job description for each administrator