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International Journal of Integrated Science and Technology
Published by MULTITECH PUBLISHER
ISSN : -     EISSN : 30264685     DOI : https://doi.org/10.59890/ijist.v2i2
Core Subject : Science, Education, Social,
Computer Science & IT Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Social Sciences
International Journal of Integrated Science and Technology (IJIST) is a scientific multidisciplinary research journal published by Multitech Publisher. The aim of this journal publication is to disseminate the research results, conceptual thoughts, improved research methodologies, and ideas that have been achieved in any area of research. The accepted articles are going to be published in the monthly publication. Any interested authors are required to submit their manuscripts in English. The mission of the International Journal of Integrated Science and Technology (IJIST) is to promote excellence by providing a venue for academics, students, and practitioners to publish current and significant empirical and conceptual research in the Enginering; health sciences; information technology; computer scince; religion; arts; business; humanities; applied, natural, and social sciences; and other areas that tests, extends, or builds theory. The International Journal of Integrated Science and Technology (IJIST) is a double-blind, peer reviewed, open access journal.
Arjuna Subject : Umum - Umum
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 6 (2024): June 2024" : 5 Documents clear
Efforts to Improve Employee Performance Through Interpersonal Communication in Creating an Effective Organization Joelianti Dwi Supratiningsih
International Journal of Integrated Science and Technology Vol. 2 No. 6 (2024): June 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i6.1986

Abstract

In order to improve employee performance, the Swadharma Jakarta Cooperative organization uses interpersonal communication, which is more dialogical in nature and places a strong emphasis on self-disclosure. This can frequently lead to feedback and a better understanding of one another. Finding out how interpersonal communication affects worker performance at the Swadharma Jakarta Cooperative is the goal of this study. This study employs a quantitative descriptive methodology, utilizing questionnaire distribution and library data gathering approaches. 50 Swadharma Jakarta Cooperative employees were sampled using a saturated sampling strategy in this study, and the data was analyzed using a straightforward linear regression technique. The study's findings indicate that interpersonal communication at the Swadharma Jakarta Cooperative has some bearing on worker performance. It is intended that this study's findings will aid in future investigations
Improving Employee Performance Through Teamwork as an Effort to Create a Solid Organization Yopie Alfiani
International Journal of Integrated Science and Technology Vol. 2 No. 6 (2024): June 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i6.1987

Abstract

Teamwork is a component inherent in each individual which is based on the experiences, actions and feelings of each team member which are interconnected in achieving task goals, as well as implementing performance in an organization. This is what makes the writer do research. The aim of this research is to determine the influence between teamwork on employee performance at the Swadharma Jakarta Cooperative. This research uses a quantitative descriptive method with data collection techniques through distributing questionnaires and library data. This research used a saturated sampling method of 50 employees at the Swadharma Jakarta Cooperative with a simple linear regression data analysis technique. The results of this research show that there is a partial influence between teamwork on employee performance at the Swadharma Jakarta Cooperative. It is hoped that the results of this research will contribute to further research.
Improving Employee Performance Through the Implementation of Individual Behavior as an Effort to Create an Organization with Character Allyya Saputra
International Journal of Integrated Science and Technology Vol. 2 No. 6 (2024): June 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i6.1988

Abstract

Because of our individuality and diversity, people interact socially with one another. Human behavior within an organization has the power to shape its trajectory, meaning that individual actions have an impact on organizational behavior, which in turn has an impact on an organization's objectives. The author carried out this investigation for this reason. Finding out how individual behavior affects worker performance at PT. PLN Distribution for Greater Jakarta Area is the aim of this study. This study employs a quantitative descriptive methodology, utilizing questionnaire distribution and library data gathering approaches. Using basic linear regression data analysis techniques, 62 employees of PT. PLN Distribution for the Greater Jakarta Area were included in this study, which employed a saturation sampling strategy. The findings of this study indicate that employee performance at PT. PLN Distribution for Greater Jakarta Area is somewhat influenced by individual behavior. It is intended that this study's findings will aid in future investigations.
Evaluating the Seismic Resilience of Newly Constructed Concrete Building in Zinda Jan District After the Devastating October 2023 Earthquake in Herat, Afghanistan Alkozay, Arif; Rahimullah Stankzai; Amanollah Faqiri
International Journal of Integrated Science and Technology Vol. 2 No. 6 (2024): June 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i6.2037

Abstract

This study aims to evaluate the impact of the October 2023 earthquake on the Zinda Jan district, focusing on the structural integrity of more than 2000 newly constructed buildings situated near fault lines. The specific objective is to identify any vulnerabilities in the design of these structures. Advanced computer analyses, including Linear and Non-linear (Push-over analysis) assessments using Etabs software, were employed to investigate the structural performance of the buildings. The analysis revealed significant insights into the structural integrity of the new constructions. It was observed that certain central columns exhibited inadequate strength, thereby posing a considerable risk of failure during seismic events. This vulnerability primarily stems from a disparity in strength between columns and beams, with the latter being stronger. This research contributes to the field by emphasizing the critical role of meticulous design and analysis in safeguarding buildings located in earthquake-prone regions.
Machine Learning-Based Classification of Truck Vehicles for a Comprehensive Algorithm CNN Approach Farizal, Mohamad Farizal Arifin; Muhamad Fatchan, Muhamad Fatchan; Suherman, Suherman
International Journal of Integrated Science and Technology Vol. 2 No. 6 (2024): June 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i6.2041

Abstract

This research tackles the challenge of classifying truck vehicles using a comprehensive machine learning-based CNN algorithm approach. Initially, we collected a raw dataset of 560 images of various truck vehicles, which was expanded to 844 images through data augmentation techniques, including automatic orientation adjustments and resizing each image to 640x640 pixels. To achieve correct labeling for model training, the dataset underwent further refinement through thorough annotation. To determine which model was the most successful, a number of machine learning techniques were investigated and contrasted, including deep learning, support vector machines, and decision trees. The preprocessed dataset was used to optimize and train the selected model. We used measures like accuracy, precision, recall, and F1-score to evaluate the model's performance. The results showed that our all-inclusive algorithmic strategy outperformed conventional techniques in effectively addressing the unique difficulties of truck vehicle categorization. This study concludes that integrating advanced machine learning techniques with domain-specific knowledge in transportation results in a robust and adaptive classification system, enhancing accuracy and paving the way for broader applications in the transportation and logistics industry.

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