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All Journal BUDGETING : Journal of Business, Management and Accounting International Journal Software Engineering and Computer Science (IJSECS) Jurnal Sistim Informasi dan Teknologi
Cut Susan Octiva
Universitas Amir Hamzah
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Social Sciences

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Analisis Pengaruh Paket Remunerasi dan Stres Kerja terhadap Turnover Intention dengan Kepuasan Kerja sebagai Variabel Mediasi pada Karyawan I Nyoman Tri Sutagana; Rihfenti Ernayani; Festus Evly R.I. Liow; Cut Susan Octiva; Rianti Setyawasih
BUDGETING : Journal of Business, Management and Accounting Vol 4 No 1 (2022): BUDGETING : Journal of Business, Management and Accounting
Publisher : Institut Penelitian Matematika Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/budgeting.v4i1.4687

Abstract

This study explains the effect of work stress and remuneration packages on turnover intention, using job satisfaction as a mediator. The object of research is one of the companies engaged in the palm oil sector in Jakarta, PT Kruing Lestari Jaya. This study discusses the theory of the four research variables, namely work stress, remuneration packages, turnover intention, and job satisfaction. This study used quantitative methods through the distribution of questionnaires via Google Form to 48 respondents, which were then processed using the SPSS version 25.0 program using saturated sampling techniques for sampling data. The results showed that work stress has a significant effect on turnover intentions. Remuneration packages have a significant effect on turnover intention. Job satisfaction does not mediate work stress and turnover intention. Job satisfaction does not act as a buffer between the remuneration package and the turnover intention. From the results of the study, it can be concluded that direct influence has a greater value than indirect influence. The job satisfaction does not mediate the effect of the remuneration package on turnover intention at PT Kruing Lestari Jaya. Keywords : Job Satisfaction, Remuneration Package, Work Stress and Turnover Intention
Improving Student Text Writing Ability by Utilizing the Use of Augmented Reality Feature Fitria Meisarah; Cut Susan Octiva; Purwo Agus Sucipto; Ika Rahayu Satyaninrum; Asri Ady Bakri
Jurnal Sistim Informasi dan Teknologi 2023, Vol. 5, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v5i1.213

Abstract

This study used a quantitative methodology. Experimental research is used, with a post-test-only control design as the study design. There were 100 students in the study's population, and students from classes A (the experimental type) and C (the control class) made up the sample. This study uses assemblers as a learning medium applied to those classes. Two variables are used in this study: the independent variable (the augmented reality feature in the assembler application) and the dependent variable (the ability to write descriptive texts for class students). Data collection techniques used are interview techniques, documentation, and observation. The application used to process research data is SPSS. This study's results show an influence between using augmented reality features and students' writing abilities. This is evident from the average value of the experimental class and control class.
Measurement Analysis of the Level of E-Commerce Adoption Readiness in SMEs Using Technology Readiness Index Method Sulistyowati; Haniwijaya Pahlawansah; Chevy Herli Sumerli A; Cut Susan Octiva; Humaidah Muafiqie
Jurnal Sistim Informasi dan Teknologi 2023, Vol. 5, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jsisfotek.v5i2.263

Abstract

The purpose of this study is to determine the extent of readiness for adoption and what factors influence readiness for e-commerce adoption. This study uses the Technology Readiness Index (TRI) model and the Information Technology Adoption Model by adding the variables of customer readiness, competitive pressure, and IT adoption. The population in this study is SMEs. The sample used from this population is 150 respondents with the purposive sampling technique. This study used quantitative methods with analysis techniques using PLS-SEM and data analysis using SmartPLS version 3.0. The results of this study indicate that six out of ten hypotheses are accepted. So that the factors that influence the readiness of e-commerce adoption are the optimism variable for the customer readiness variable, the optimism variable for the competitive pressure variable, innovativeness for the customer readiness variable, innovativeness for competitive pressure, discomfort for customer readiness, and competitive pressure for IT adoption.
Application of The Speed-Up Robust Features Method To Identify Signature Image Patterns On Single Board Computer Nursalim; Cut Susan Octiva; Suluh Sri Wahyuningsih; Muhammad Lukman Hakim; Novrini Hasti
Jurnal Sistim Informasi dan Teknologi 2023, Vol. 5, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jsisfotek.v5i4.312

Abstract

Through the development of a signature pattern recognition program on SBC Beagle-bone Black, this research seeks to determine how to differentiate between real and false signatures. Three techniques of gathering data were employed in this study: interviews, observations, and a review of the literature. The quick application development method is the approach that is applied. The rapid, efficient, and brief development cycle (RAD) is emphasized. This study uses a use-case diagram to illustrate the application's logic and data flow. In this study, OpenCV is used as a digital image processing library along with the C++ programming language and QT creator as an integrated development environment (IDE). This application was subjected to both accuracy and functional testing. The following conclusions are drawn from the findings of the investigation and testing that was done: Using the fast library approach for approximate nearest neighbors (FLANN) and the speeded-up robust features (SURF) feature extraction method, the signature pattern recognition program on the Beagle-bone black SBC can differentiate between real and fraudulent signatures. Through the processes of generating image scale space, feature localization, and feature description, the SURF approach extracts feature from signature images. This signature pattern recognition application is one of the digital image processing apps that can be run on the Beagle-bone Black single board computer. This indicates that the specifications of the SBC Beagle-bone Black for digital image processing are good.
The Application of Artificial Intelligence for Anomaly Detection in Big Data Systems for Decision-Making Cut Susan Octiva; Dikky Suryadi; Loso Judijanto; Mitranikasih Laia; Dedy Irwan
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3358

Abstract

The development of big data technology has generated huge volumes of diverse data, creating challenges in detecting anomalies that could potentially affect decision-making. This research aims to examine the application of artificial intelligence (AI) in detecting anomalies in big data systems to support faster, more accurate and effective decision-making. The approach used includes the integration of machine learning algorithms, such as classification-based detection, clustering, and deep learning, in identifying abnormal patterns in large datasets. The research method involves real-time dataset-based simulations by measuring the performance of AI models using accuracy, precision, recall, and F1-score metrics. The results show that the application of AI can significantly improve the anomaly detection capability compared to conventional methods, with an average accuracy of 92%.
Analysis of Household Electricity Consumption Patterns Using K-Nearest Neighbor (KNN) Method Cut Susan Octiva; Sultan Hady; Dedy Irwan; T. Irfan Fajri; Novrini Hasti
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3877

Abstract

The increasing demand for electricity in the household sector poses significant challenges to energy efficiency initiatives and environmental conservation efforts. Examining electricity usage patterns offers a pathway to uncover key determinants that influence consumption levels while formulating more effective strategies for energy management. This study attempts to evaluate electricity consumption patterns in the household sector using the K-Nearest Neighbor (KNN) algorithm. This approach is used to categorize consumption data based on attribute similarities among household units. The findings are expected to encourage more rational electricity usage practices, thereby reducing energy inefficiencies and strengthening efforts to conserve natural resources. Furthermore, the analysis aims to provide actionable insights for households to adopt sustainable habits and for policymakers to design targeted interventions that address peak demand periods and promote the use of energy-efficient technologies. By identifying specific behavioral and technological factors that contribute to high consumption, the results can serve as a basis for tailored programs aimed at minimizing waste and promoting long-term environmental management.
Integrating Zero Trust Architecture with Blockchain Technology to Maintain Data Security in the Cloud T. Irfan Fajri; Handry Eldo; Cut Susan Octiva; Dikky Suryadi; Muhammad Lukman Hakim
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5481

Abstract

Data security concerns have increasingly become a challenge to cloud computing services due to rising incidents of cyberattacks, identity theft, and data manipulation. The perimeter-based security model is ineffective because of vulnerabilities in authentication and access control, thus necessitating an adaptive layered approach. This paper presents attempts to merge Zero Trust Architecture (ZTA) with Blockchain technology as one possible way to ensure confidentiality, integrity, and availability of data in cloud environments. Research methodology comprises a detailed review of related literature, system architecture analysis, and simulation of the conceptual merger using encryption protocols and smart contracts. Results revealed that ZTA significantly reduces the opportunities for unauthorized access through multi-layered verification and least privilege principles while Blockchain provides a decentralized transparent immutable method for recording transactions on data. The hybrid will enhance security substantially against breaches from external attackers and insiders with an already established verifiable audit trail. This paper concludes that such a merger could create a stronger model—one that is more measurable—and sustainable for securing today's cloud infrastructure.
Co-Authors Asri Ady Bakri Chevy Herli Sumerli Dedy Irwan Dikky Suryadi Dikky Suryadi Festus Evly R.I. Liow Fitria Meisarah Handry Eldo Haniwijaya Pahlawansah Humaidah Muafiqie I Nyoman Tri Sutagana Ika Rahayu Satyaninrum Loso Judijanto Mitranikasih Laia Muhammad Lukman Hakim Muhammad Lukman Hakim Mutasar Novrini Hasti Nursalim Rianti Setyawasih Rihfenti Ernayani Sucipto, Purwo Agus Sulistyowati Sultan Hady Suluh Sri Wahyuningsih