cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Husni Teja Sukmana
Contact Email
husni@bright-journal.org
Phone
+62895422720524
Journal Mail Official
jads@bright-journal.org
Editorial Address
Gedung FST UIN Jakarta, Jl. Lkr. Kampus UIN, Cemp. Putih, Kec. Ciputat Tim., Kota Tangerang Selatan, Banten 15412
Location
Kota adm. jakarta pusat,
Dki jakarta
INDONESIA
Journal of Applied Data Sciences
Published by Bright Publisher
ISSN : -     EISSN : 27236471     DOI : doi.org/10.47738/jads
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
One of the current hot topics in science is data: how can datasets be used in scientific and scholarly research in a more reliable, citable and accountable way? Data is of paramount importance to scientific progress, yet most research data remains private. Enhancing the transparency of the processes applied to collect, treat and analyze data will help to render scientific research results reproducible and thus more accountable. The datasets itself should also be accessible to other researchers, so that research publications, dataset descriptions, and the actual datasets can be linked. The journal Data provides a forum to publish methodical papers on processes applied to data collection, treatment and analysis, as well as for data descriptors publishing descriptions of a linked dataset.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 518 Documents
 12   13   14   15   16 
Asynchronous Programming based on Services with Application of Neural Networks as a Method of Taking Legitimate Measures at DDoS Attacks Tokpayev, Kairat; Bedelbayev, Agyn
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.276

Abstract

The relevance of this study is conditioned by the growing threat of various attacks in the modern information space. The purpose of this study was to analyze and evaluate the effectiveness of applying asynchronous programming and neural networks to combat availability attacks. A rudimentary C# programme was created to simulate a DDoS attack detection system, and a comparative table was generated to assess different DDoS attack countermeasure services. The results illustrate the pragmatic importance of utilizing neural networks and asynchronous programming in detecting DDoS attacks, emphasizing their capacity to enhance the effectiveness, precision, and flexibility of detection systems. Such methods allow for a quick and effective response to attacks and ensure the stability of information systems, reducing the risk of loss of availability and financial losses. The study also highlights the importance of evaluating the scalability and performance of these methods in actual network environments. The practical significance of this study is that it provides new ways and tools to protect information resources from attacks, contributes to the advancement of scientific knowledge and provides certain solutions to combat information threats.
Entrepreneurial Orientation and MSME’s Tourism Performance: The Mediating Role of Social Media Capability Parlyna, Ryna; Susanto, Perengki; Abror, Abror; Marsal, Arif
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.377

Abstract

This study explores the mediating role of social media capability on entrepreneurial orientation (EO) and MSME’s tourism performance in DKI Jakarta Province, Indonesia (MP). MSMEs contributes largely to Indonesia's economy. However, these enterprises often struggle with limited resources leading to weaker performance. The research problem centers on identifying factors that can enhance the MP, mainly through EO and SMC. The objective is to investigate both EO's direct impact on MP and SMC's mediating role. Quantitative research was used, utilizing a survey-based method with data collected from 300 MSME owners and managers in the tourism sector. Structural Equation Modeling (SEM) was used to examine the relationships between EO, SMC and MP. The results reveal a favorable positive relationship between EO and MP, with a path coefficient (β) of 0.425 and a p-value of 0.000. It underscores the importance of EO in intensifying the MP. It also found that EO significantly affects SMC, with a path coefficient (β) of 0.353 and a p-value of 0.000. This suggests that MSMEs with a strong EO are expected to enhance SMC. SMC was also found to have a positive and favorable effect on MP, with a path coefficient (β) of 0.179 and a p-value of 0.001. This suggest that SMC is crucial for improving MP. It also confirmed the mediating role of SMC in the relationship between EO and MP, with an indirect path coefficient (β) of 0.063 and a p-value of 0.006. It proposed that EO directly enhanced MP through SMC. However, the study is narrowed by its focal point on a specific geographic area and sector, which may impact the relevancy of the results. Forthcoming study could address these limitations by exploring different contexts. This study contributes to broaden the literature on the mediating role of SMC in the EO- MP in DKI Jakarta, Indonesia.
Exploring The Factors Influencing the Adoption of ChatGPT in Educational Institutions: Insights from Innovation Resistance Theory Alghamdi, Salem; Alhasawi, Yaser
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.198

Abstract

The ability of ChatGPT to increase student interaction and personalize learning has the capacity to dramatically change educational institutions. It can help students to ask questions and receive immediate answers from their teachers, provide personalized feedback, as well as provide dynamic experiential learning. This research explores the factors affecting the intention to use ChatGPT for educational purposes, based on Innovation Resistance Theory (IRT). A structural equation modeling was used to analyze data that was gathered from 340 American learners. The results show that usage barrier construct, value barrier, risk barrier, image barrier, traditional barrier, and perceived cost barriers are negatively associated with the intention to use ChatGPT. These findings have important ramifications for ChatGPT developers, educators, and academic institutions. Educators can leverage ChatGPT's capabilities to enhance student learning experiences, facilitate personalized learning paths, and foster collaborative learning environments.
Assessing Leadership Styles, Self-Efficacy, Job Satisfaction, and Organizational Commitment in Rural Administrative Officials Through Mixed-Methods and Quantitative Data Analysis Aheruddin, Aheruddin; Eryanto, Henry; Sariwulan, Tuty
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.315

Abstract

This study explores the relationship between leadership styles, self-efficacy, job satisfaction, and organizational commitment among rural administrative officials on Sumbawa Island. Utilizing a mixed-methods approach, the research combines quantitative data from surveys and qualitative insights from interviews across four districts: Bima, Dompu, Sumbawa, and Sumbawa Barat. The findings indicate that transformational leadership significantly enhances organizational commitment, with Bima exhibiting the highest commitment scores (mean = 4.18), followed by Sumbawa (mean = 3.92). In contrast, transactional leadership, more common in Dompu, correlates with lower commitment (mean = 3.09). Self-efficacy also plays a crucial role, with higher scores associated with increased job satisfaction and commitment, particularly in Sumbawa (mean = 3.75) and Bima (mean = 3.38). Job satisfaction mediates the relationship between leadership styles and organizational commitment, underscoring its importance in fostering a dedicated workforce. The study reveals significant contextual differences, emphasizing the need for tailored leadership development programs that address specific socio-cultural and demographic factors. Key contributions include empirical evidence supporting transformational leadership in rural administration and the integration of self-efficacy into leadership theories. Recommendations for future research include longitudinal studies and multi-source assessments, while practical applications suggest focusing on transformational leadership training, enhancing self-efficacy, and improving job satisfaction through better working conditions and career advancement opportunities. By addressing these factors, rural administrations can enhance organizational commitment and improve governance outcomes, ultimately contributing to sustainable rural development.
Applied Random Forest Algorithm for News and Article Features on The Stock Price Movement: An Empirical Study of The Banking Sector in Vietnam Nhat, Nguyen Minh
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.338

Abstract

In 2023, in the context of the world economic and political situation continuing to experience many difficulties and challenges, the global stock market has suffered many unfavorable impacts. In that general context, Vietnam's stock market faces many problems, challenges, and strong fluctuations due to unexpected changes in the world's macro economy and geopolitics. Therefore, the study's goal is to investigate the impact of news articles on the stock price movement of commercial banks in Vietnam. Using a dataset of 94,784 news articles from January 2023 to April 2024 and applying the Random Forest algorithm, the author analyzes the significance of various news features. The study identifies that the proportion of news sources with positive evaluations and the proportion of news sources mentioning commercial banks are the most influential features of the stock price movement. The findings reveal that positive news boosts investor confidence, increasing stock prices, while high media attention significantly influences trading activity. Other notable features include the number of news sources and the total sentiment score of articles, which also play crucial roles. This research provides valuable insights for investors and analysts to understand the effect of news articles on stock prices, enhancing their decision-making process in the banking sector. Finally, the research results are scientific proof that helps the Vietnamese stock market to have more positive and robust changes, continue to be an attractive destination for domestic and foreign investment capital flows, and a channel for medium and long-term capital important term for the economy, making an increasingly more outstanding contribution to the country's socio-economic development in the new era.
Spatial Estimation for Tuberculosis Relative Risk in Aceh Province, Indonesia: A Bayesian Conditional Autoregressive Approach with the Besag-York-Mollie (BYM) Model Sasmita, Novi Reandy; Arifin, Mauzatul; Kesuma, Zurnila Marli; Rahayu, Latifah; Mardalena, Selvi; Kruba, Rumaisa
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.185

Abstract

Tuberculosis (TB) remains a significant public health challenge globally, with Indonesia being the second-highest country in TB cases worldwide. Aceh Province has one of the highest TB incidence rates in Indonesia. This study aims to estimate and map the spatial distribution patterns of TB relative risk across districts in Aceh Province, Indonesia, to reveal significant variations. The study employed an ecological time-series study design, utilizing the Bayesian Conditional Autoregressive (CAR) approach with the Besag-York-Mollie (BYM) model for spatial estimation and mapping of TB relative risk. TB case data and population data for 23 districts/cities in Aceh Province from 2016 to 2022 were analyzed. Spatial analysis was used to estimate and map TB's relative risk, aiding in identifying areas with higher transmission risks. The results showed that the relative risk of TB varied across districts/cities in Aceh Province over the study period. However, Lhokseumawe and Banda Aceh consistently exhibited high to very high relative risks over the years. In 2022, Lhokseumawe City and Banda Aceh City had the highest relative risks by 2.26 and 2.17, respectively, while Sabang City and Bener Meriah District had the lowest by 0.43 and 0.32, respectively. This study provides valuable insights into the heterogeneous landscape of TB risk in Aceh Province, which can inform targeted interventions and planning strategies for effective TB control. Using the Bayesian CAR BYM model proved effective in estimating and mapping TB's relative risk, highlighting areas requiring prioritized attention in TB prevention and control efforts.
Urban Heat Island Spatial Model for Climate Village Program Planning Munsyi, Munsyi; Nugroho, Agung; Jauhari, Ahmad; Faisal, Moh Reza
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.223

Abstract

Global warming and climate change are critical issues impacting ecosystems, human habitats, and the overall environment. Urban Heat Island (UHI) is a significant phenomenon resulting from increased urban temperatures due to dense urban development, the use of heat-absorbing materials, and reduced vegetation. This study focuses on analyzing the UHI effect in Banjarmasin, Indonesia, using spatial regression and descriptive spatial analysis methods. By employing Land Surface Temperature (LST) data from Landsat 9 and Sentinel-2 satellite imagery, combined with data from wireless sensor networks (WSN), this research aims to develop a comprehensive UHI spatial model to inform climate village program planning. The results reveal substantial temperature variations within Banjarmasin, with urban areas showing significantly higher LST values compared to vegetated outskirts. The integration of satellite data with real-time WSN measurements provides a robust validation method, ensuring accurate environmental monitoring. This study underscores the importance of enhancing green spaces and implementing sustainable spatial planning to mitigate UHI effects. The proposed UHI spatial model offers a valuable tool for urban planners and policymakers in developing strategies to improve urban environmental quality and resilience to climate change.
Assessing the Performance and Competitive Strategies of Bamboo Weaving MSMEs in Bali Using Quantitative Associative Causal Design Kartika, I Made; Sumada, I Made; Suwandana, I Made Adi; Adnyana, Yudistira; Sedana, I Dewa Gede Putra; Meryawan, I Wayan
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.320

Abstract

This study explores the factors influencing the competitiveness and performance of bamboo weaving Micro, Small, and Medium Enterprises (MSMEs) in Bali, using a quantitative associative causal design. Bamboo weaving, an integral part of Balinese culture, faces significant challenges post-COVID-19. This research aims to analyze key factors such as business capabilities, product quality, infrastructure, technology, resources, government policies, and external support, and their impact on the competitiveness and performance of these MSMEs. Data were collected from 100 bamboo weaving MSMEs in Buleleng and Bangli using structured surveys. The collected data were analyzed using Partial Least Squares (PLS) structural equation modeling to validate the proposed hypotheses. The study reveals that product quality (path coefficient = 0.275, t-statistic = 3.048, p-value = 0.003), infrastructure (path coefficient = 0.187, t-statistic = 2.176, p-value = 0.032), technology (path coefficient = 0.239, t-statistic = 3.231, p-value = 0.002), resources (path coefficient = 0.179, t-statistic = 2.048, p-value = 0.043), and external support (path coefficient = 0.185, t-statistic = 2.387, p-value = 0.019) significantly influence the competitiveness of bamboo weaving MSMEs. In contrast, business capabilities (path coefficient = 0.169, t-statistic = 1.856, p-value = 0.066) and government policies (path coefficient = - 0.031, t-statistic = 0.283, p-value = 0.778) were found to be insignificant in this context. The findings indicate that improvements in product quality, better infrastructure, adoption of modern technologies, effective resource management, and robust external support systems are critical in enhancing competitiveness. However, the expected positive impact of competitiveness on MSME performance (path coefficient = 0.182, tstatistic = 1.269, p-value = 0.207) was not statistically significant. This suggests that factors beyond competitiveness, such as market conditions and internal business processes, play a more substantial role in determining performance outcomes. This study provides practical recommendations for MSMEs to enhance competitiveness, emphasizing the need for improved product quality, infrastructure, technology adoption, resource management, and leveraging external support. Additionally, the research highlights the necessity for stronger, more effective government policies tailored to the unique challenges of bamboo weaving MSMEs. These insights are valuable for MSME owners, policymakers, and stakeholders aiming to support the bamboo weaving industry in Bali, ensuring its sustainability and growth in the post-pandemic era.
Research Gaps in Radio Frequency Identification Technology Implementation in Warehouses Haswika, Haswika; Qurtubi, Qurtubi; Setiawan, Danang; Supriyadi, Supriyadi
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.245

Abstract

Warehouses are important in enabling and supporting the efficient execution of logistical activities. Integrating radio frequency identification (RFID) technology can catalyze innovation in warehouse operations by reducing the tracking and management of items. This study aims to identify novel research prospects for integrating RFID technology within warehouse operations. The researchers conducted a comprehensive literature evaluation by examining articles indexed by Scopus. This study has comprehensively analyzed the critical elements of each paper reviewed, including the research aims, findings, outputs, and gaps. These characteristics contribute to identifying innovative research directions in the context of RFID technology and its application in warehouse environments. This study provides a significant result, as no recent literature review on a similar topic exists. Furthermore, this literature review aims to address the existing theoretical void by building upon prior research and offering scientific contributions by presenting a complete and comprehensive literature review.
Performance Fuzzy Decision Model for Evaluating Employees’ Work-from-Home Performance Immanuel, Christiawan; Utama, Ditdit Nugeraha
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.269

Abstract

This study aims to identify key workplace environmental parameters and develop a Decision Support Model (DSM) to evaluate the performance of work-from-home (WFH). The methods utilized include Tsukamoto Fuzzy Logic and conventional techniques. Key parameters incorporated into the DSM-WFHP model include room temperature, internet speed, number of children, virtual office setup, and physical activity (sport). The research culminates in the DSM-WFHP model, which provides accurate assessments of WFH employee performance. Findings indicate that variations in these parameters significantly impact performance, with specific quantitative results demonstrating that optimal room temperature, high internet speed, fewer children present, an effective virtual office setup, and regular physical activity correlate with higher performance scores. Thus, this research concludes that the DSM-WFHP model effectively offers precise performance evaluation guidance for remote employees, making a valuable contribution to remote work management. With regards to the novelty of this study, this is the first time that the synergetic effect of multiple environmental factors has been incorporated into a comprehensive DSM.

Page 14 of 52 | Total Record : 518

 12   13   14   15   16 

Filter by Year

2020 2026


Reset
Filter By Issues
All Issue Vol 7, No 1: January 2026 Vol 6, No 4: December 2025 Vol 6, No 3: September 2025 Vol 6, No 2: MAY 2025 Vol 6, No 1: JANUARY 2025 Vol 5, No 4: DECEMBER 2024 Vol 5, No 3: SEPTEMBER 2024 Vol 5, No 2: MAY 2024 Vol 5, No 1: JANUARY 2024 Vol 4, No 4: DECEMBER 2023 Vol 4, No 3: SEPTEMBER 2023 Vol 4, No 2: MAY 2023 Vol 4, No 1: JANUARY 2023 Vol 3, No 4: DECEMBER 2022 Vol 3, No 3: SEPTEMBER 2022 Vol 3, No 2: MAY 2022 Vol 3, No 1: JANUARY 2022 Vol 2, No 4: DECEMBER 2021 Vol 2, No 3: SEPTEMBER 2021 Vol 2, No 2: MAY 2021 Vol 2, No 1: JANUARY 2021 Vol 1, No 2: DECEMBER 2020 Vol 1, No 1: SEPTEMBER 2020 More Issue