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All Journal JDM (Jurnal Dinamika Manajemen) Aptisi Transactions on Management Aptisi Transactions on Technopreneurship (ATT) Startupreneur Business Digital (SABDA Journal) International Transactions on Artificial Intelligence (ITALIC)
Bist, Ankur Singh
Unknown Affiliation
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science Social Sciences

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 1 
The Importance of Building a Digital Business Startup in College Bist, Ankur Singh
Startupreneur Business Digital (SABDA Journal) Vol. 2 No. 1 (2023): Startupreneur Business Digital (SABDA)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v2i1.265

Abstract

Indonesia has enough established startups for them to become popular in business incubators that accept college or university students. This is because aspiring entrepreneurs who have business ideas are given access to the incubation concept and program. As a result, study was done to find out how business incubators help colleges create firms. However, there are barriers to developing businesses, including limited technology, management, and leadership. A qualitative methodology was used to carry out the study at Raharja University's Alphabet Incubator. Utilizing an observational research approach and a literature review to gather data with the goal of streamlining the procedure, It is clear that the government supports business incubators in creating startups and utilizing technology to expand businesses. The goal of the research is to boost creativity or innovation in creating successful new companies in higher education. seen from students making use of the Alphabet Incubator's resources to create small enterprises in the digital sector and expand the workforce.
The Future of Work: How Digital Tools are Transforming Human Resource Management Bist, Ankur Singh; Zakaria, Noor Azura; Anwar, Nizirwan; Jacqueline, Greisy; Ming, Li Wei
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2355

Abstract

This study examines the transformative role of digital tools in reshaping key functions of Human Resource Management (HRM), including recruitment, training, performance management, and employee engagement. Employing a mixed-method approach, it integrates quantitative survey data with qualitative insights from HR professionals to assess the impact of digital technologies on HR functions. The results indicate a 35% improvement in recruitment effi ciency, enhanced employee development, and significant advances in perfor- mance management through the adoption of digital tools. Moreover, digital engagement platforms have reduced employee turnover, particularly in remote work environments. Despite these benefits, challenges such as resistance to change and digital skill gaps persist, requiring attention for successful imple- mentation. The study contributes to academic literature by addressing these challenges and offering practical guidance for organizations. Future research should explore the long-term effects of digital transformation and the role of emerging technologies like blockchain in further revolutionizing HRM prac- tices.
Examining The Interplay of Technology Readiness and Behavioural Intentions in Health Detection Safe Entry Station Rahardja, Untung; Aini, Qurotul; Bist, Ankur Singh; Maulana, Sabda; Millah, Shofiyul
JDM (Jurnal Dinamika Manajemen) Vol 15, No 1 (2024): March 2024
Publisher : Department of Management, Faculty of Economics and Business, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jdm.v15i1.48914

Abstract

This research aims to determine the factors that influence the adoption of safe entry station (SES) as a health detection technology. There are six main constructs that will be studied, namely Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions and Technology Readiness, towards Behavioural Intention. Data collection was carried out using a survey distributed to 824 participants by analysis was carried out using the Structural Equation Model. The research findings show a significant relationship between technology readiness and behavioral intention regarding the use of safe entry station. The results of this research specifically show that the application of artificial intelligence in safe entry station health detection technology has a significant positive impact on increasing accuracy in the health examination process. Furthermore, this research provides insight into substantial practical implications in various business sectors, highlighting the importance of integrating safe entry station with organizational systems. The academic implications contained in this research will make a positive contribution to the development of knowledge and theory in the field of safe entry station technology adoption and can provide a strong basis for further research, while the managerial implications of this research lie in the ability to further design effective implementation strategies in various sectors.
A Novel Approach for Facial Attendance:AttendXNet Arora, Kawal; Bist, Ankur Singh; Prakash, Roshan; Chaurasia, Saksham
Aptisi Transactions On Technopreneurship (ATT) Vol 2 No 2 (2020): September
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v2i2.86

Abstract

Recent advancements in the area of facial recognition and verification introduced the possibility of facial attendance for various use cases. In this paper we present a system named as AttendXNet. Our method uses the ResNet and Multi-layer feed forward network to achieve the state of art results. Extensive analysis of various deep learning and machine learning techniques is described. Face anti-spoofing is a major challenge in facial attendance. Extended-MobileNet is used to resolve the same issue. We also introduced the end to end pipeline to implement an attendance system for various use cases.
Custom OCR for Identity Documents:OCRXNet Arora, Kawal; Bist, Ankur Singh; Prakash, Roshan; Chaurasia, Saksham
Aptisi Transactions On Technopreneurship (ATT) Vol 2 No 2 (2020): September
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v2i2.87

Abstract

Recent advancements in the area of Optical Character Recognition (OCR) using deep learning techniques made it possible to use for real world applications with good accuracy. In this paper we present a system named as OCRXNet. OCRXNetv1, OCRXNetv2 and OCRXNetv3 are proposed and compared on different identity documents. Image processing methods and various text detectors have been used to identify best fitted process for custom ocr of identity documents. We also introduced the end to end pipeline to implement OCR for various use cases.
Artificial Intelligence Based Drug Discovery Techniques for COVID-19 Detection Arora, Kawal; Bist, Ankur Singh
Aptisi Transactions On Technopreneurship (ATT) Vol 2 No 2 (2020): September
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v2i2.88

Abstract

Recent advancements in the area of drug discovery using artificial intelligence made it possible to speed up the hunt for new pharmaceuticals. Drugs like arbidol, atazanavir, remdesivir & favipiravir are under testing phase to cure COVID-19. In this paper, we present systematic study of AI based drug discovery techniques suitable for COVID-19 detection.
Passion to Profession: A review of Passion fruit Processing Biswas, Srishti; Mishra, Ritesh; Bist, Ankur Singh
Aptisi Transactions On Technopreneurship (ATT) Vol 3 No 1 (2021): March
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v3i1.143

Abstract

Passion fruit (Passiflora edulis) is a nutritious tropical fruit belongs to the family Passifloraceae. The purple passion fruit is local from southern Brazil through Paraguay to northern Argentina. India, for a long time, has appreciated a moderate collect of purple passion fruit in the Nilgiris in the south and in various parts of northern India. The Passion fruit has good amount of antioxidants, flavanoids, anti- inflammatory, anti- bacterial, anti- fungal and anti- ageing properties. This fruit has huge economical importance as all the parts of this fruit (seed, peel, flower, pulp) are rich in medicinal and therapeutic properties. The fruit is a fantastic wellspring of dietary fiber, nutrient, Vitamin C and Vitamin A. Being a decent laxative, it likewise secures the colon mucosa by diminishing openness time to harmful substances in the colon and clearing off the malignant growth causing poisonous substances from the colon. Passion fruit has several medical advantages and hence require diverse processing and preservation methods. Here we are going to review portion of these methods.
Convolutional Neural Networks in Medical Image Understanding Upreti, Megha; Pandey, Chitra; Bist, Ankur Singh; Rawat, Buphest; Hardini, Marviola
Aptisi Transactions On Technopreneurship (ATT) Vol 3 No 2 (2021): September
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v3i2.188

Abstract

In the era of social media images/pictures play a vital role. Facebook, whatsapp, instagram everywhere we see a lot of pictures nowadays. Along with social media, the pictures play a very important role in medical science. Medical Image can help in diagnosis, clinical treatment and teaching tasks. Traditional classification of images has reached an end because of its time taking nature and efforts made to extract, select and classify . This problem is solved with the help of CNN(Convolutional neural network).In medical science we have treatment for body anomalies that were not there before .Using the deep learning models of CNN we can detect the disease like Cancer ,Lung Infection and treat it. This article aims to provide a comprehensive survey of applications of CNNs in medical image understanding.
Designing an AI-Based Expert System to Enhance Standard Language Use on Social Media Aini, Qurotul; Naurah, Syahla; Bist, Ankur Singh; Sunarjo, Richard Andre; Novitasari, Dewiana; Sasono, Ipang; Apriliasari, Dwi
International Transactions on Artificial Intelligence Vol. 3 No. 2 (2025): May
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v3i2.788

Abstract

The widespread use of social media has significantly transformed the way people communicate, often leading to informal, shortened, and mixed-language expressions that deviate from standard linguistic norms. This phenomenon raises concerns about the erosion of proper language usage, particularly among younger generations. This study aims to design an AI-based expert system to support and improve the use of standard Indonesian on digital communication platforms. By integrating language rules into a decision-support model, the system can provide real-time feedback on grammar, spelling, and appropriate word usage during online interactions. This research adopts a qualitative approach through literature review and system design framework, emphasizing the need for intelligent linguistic assistance tools. The proposed expert system will be capable of analyzing user-generated content, detecting deviations from formal language standards, and offering suggestions or corrections. The findings contribute to ongoing efforts to preserve national language identity in the digital age and promote linguistic awareness through technology. Ultimately, this study offers an innovative solution to bridge the gap between informal digital trends and the preservation of standard language, encouraging responsible and high-quality communication in the modern digital ecosystem.
Co-Authors Apriliasari, Dwi Arora, Kawal Biswas, Srishti Chaurasia, Saksham Jacqueline, Greisy Marviola Hardini Maulana, Sabda Millah, Shofiyul Ming, Li Wei Mishra, Ritesh Naurah, Syahla Nizirwan Anwar Novitasari, Dewiana Pandey, Chitra Prakash, Roshan Qurotul Aini Rawat, Buphest Sasono, Ipang Sunarjo, Richard Andre Untung Rahardja Upreti, Megha Zakaria, Noor Azura