Antonius Alijoyo | Parahyangan Catholic University (original) (raw)

Papers by Antonius Alijoyo

Ilmu Komputer, Manajemen dan Sosial Swabumi : Suara Wawasan Sukabumi/Swabumi (Suara Wawasan Sukabumi), Mar 15, 2024

Jurnal Teknologi Dan Sistem Informasi Bisnis/Jurnal Teknologi dan Sistem Informasi Bisnis, Apr 30, 2024

Coopetition, Apr 16, 2024

Jurnal Ilmiah Penelitian dan Pembelajaran Informatika, Feb 23, 2024

Jurnal Indonesia Sosial Teknologi, Mar 27, 2024

Alexandria Engineering Journal /Alexandria Engineering Journal, Jul 1, 2024

Alexandria Engineering Journal, Nov 30, 2023

The growth of IoT (Internet of Things) devices has revolutionized several industries and brought ... more The growth of IoT (Internet of Things) devices has revolutionized several industries and brought about novel security threats. Recognizing network anomalies that may point to malicious activity or system flaws is a major issue. Traditional anomalous identification methods frequently need to catch up when dealing with the special traits of IoT environments, including resource limitations and changing network behavior. This paper introduces an innovative approach, the Bat-optimized CNN-BiLSTM model, to enhance the security and efficiency of IoT environments. This model combines the strengths of Convolutional Neural Networks (CNNs) for spatial analysis and Bidirectional Long Short-Term Memory (BiLSTM) networks for capturing temporal patterns, thus effectively representing time and space trends in IoT data. To optimize its performance further, researchers have leveraged the Bat algorithm, inspired by natural behaviors, to fine-tune the model. This program effectively searches for the best network anomaly detection parameters by imitating the echo activity of bats. Researchers want to increase detection accuracy by lowering false positives and false negatives using the Bat algorithm to enhance the CNN-BiLSTM model. The experimental findings show that the Bat-optimised CNN-BiLSTM model beats the state-ofthe-art anomaly detection methods with 99.43% accuracy and efficiency.

International Journal of Advanced Computer Science and Applications, Dec 31, 2022

Journal of Social Science, Nov 21, 2022

The objective of the study was analyzing the Business Transformation Strategy of PT. Krakatau Ste... more The objective of the study was analyzing the Business Transformation Strategy of PT. Krakatau Steel (Persero) Tbk Towards a Sustainable Company. The research followed a qualitative descriptive method. The results of the analysis show that the business transformation strategy carried out by PT. Krakatau Steel (Persero) Tbk towards a sustainable firm is done through debt restructuring and cost efficiency to increase labor productivity to lead the company to profitability. As a business entity that grows and develops in the community, this company also always strives to maintain harmonious relations with the surrounding community through corporate social responsibility (CSR) or partnerships and the Community Development Program (PKBL), which is held regularly every year. In addition, PT. Krakatau Steel (Persero) Tbk also consistently takes part in the Company Performance Assessment (PROPER) program conducted by the Republic of Indonesia's Ministry of Environment and Forestry.

JPPI (Jurnal Penelitian Pendidikan Indonesia), May 28, 2023

This study aims to understand how a pioneer Bus Rapid Transit (BRT) company in Indonesia strength... more This study aims to understand how a pioneer Bus Rapid Transit (BRT) company in Indonesia strengthens its business resilience when facing uncertainty due to the COVID-19 pandemic. A qualitative research approach with the case study method is used where the primary data source is respondents, who are determined based on the purposive sampling method. Data collection and analysis were conducted using triangulation techniques by distributing questionnaires, structured interviews, and focus group discussions, which have helped discover that the pioneer BRT company is not fully prepared for the COVID-19 pandemic. The company then decided to strengthen risk management capabilities by increasing risk management competencies that support decision-making in responding to the impact of the COVID-19 pandemic. Risk leaders believe that strengthening risk capabilities can boost the company's resilience in the face of the COVID-19 pandemic and help it succeed in the new-normal era later. However, it is recommended that companies implement a business continuity management system based on the ISO 22301:2019 Business Continuity Management System (BCMS) standard as a systematic and comprehensive approach. The implication of implementing this standard is strengthening the company's readiness to deal effectively with risks of resilience and business continuity in the future.

This paper discusses a conceptual review on how Enterprise Risk Management (ERM) plays a role in ... more This paper discusses a conceptual review on how Enterprise Risk Management (ERM) plays a role in the competitiveness of companies that adopts the Value Chain (VC) model and Life Cycle Cost (LCC) approach. A literature review was conducted over some selected papers. The result shows that ERM is critically and fundamentally required to have an effective VC model and the practice of the LCC approach. Further, some discussions with practitioners in Indonesian listed companies gave a result that affirmed such conceptual review in a practical environment. The results lead to the recommendation that ERM should be a prerequisite before the value adoption chain model and LCC approach by a company. This paper, however, is without the field research, and therefore, an empirical study is strongly recommended to confirm the conclusion of this conceptual review and to understand the critical key success factors in building or establishing an effective interlink between ERM, VC, and LCC.

International Journal of Environmental, Sustainability and Social Science, Mar 31, 2022

Toll road operators need to implement effective risk management. This study focuses on how a Stat... more Toll road operators need to implement effective risk management. This study focuses on how a State-Owned Enterprise (SOE) toll road operator assesses the maturity of their ISO 31000-based risk management practices by using an ISO 31000-based risk management maturity model, ERMA ISO31000 RM3. The study is predominantly based on a qualitative approach through document reviews, questionnaires, and interviews. The assessment result shows that the company's risk management maturity score reaches 3.62 (a scale of 0.00-5.00) or at the DEFINED level of the risk management maturity. The study also shows that the company's risk management process gets the highest score, 4.45, while the lowest score, 3.22, is for the company's performance management. By using the maturity assessment result, the company's management can develop a risk management improvement road map to assist their efforts in increasing the effectiveness of their existing risk management practices. Referring to the assessment result, the management can prioritize the improvement on low-score maturity attributes, such as their performance management, risk culture, resilience and sustainability, risk management framework, and management process, while maintaining their current practices of the risk management process, which has already reached a considerably high maturity level.

Effective detection has been extremely difficult due to plagiarism's pervasiveness throughout a v... more Effective detection has been extremely difficult due to plagiarism's pervasiveness throughout a variety of fields, including academia and research. Increasingly complex plagiarism detection strategies are being used by people, making traditional approaches ineffective. The assessment of plagiarism involves a comprehensive examination encompassing syntactic, lexical, semantic, and structural facets. In contrast to traditional string-matching techniques, this investigation adopts a sophisticated Natural Language Processing (NLP) framework. The preprocessing phase entails a series of intricate steps ultimately refining the raw text data. The crux of this methodology lies in the integration of two distinct metrics within the Encoder Representation from Transformers (E-BERT) approach, effectively facilitating a granular exploration of textual similarity. Within the realm of NLP, the amalgamation of Deep and Shallow approaches serves as a lens to delve into the intricate nuances of the text, uncovering underlying layers of meaning. The discerning outcomes of this research unveil the remarkable proficiency of Deep NLP in promptly identifying substantial revisions. Integral to this innovation is the novel utilization of the Waterman algorithm and an English-Spanish dictionary, which contribute to the selection of optimal attributes. Comparative evaluations against alternative models employing distinct encoding methodologies, along with logistic regression as a classifier underscore the potency of the proposed implementation. The culmination of extensive experimentation substantiates the system's prowess, boasting an impressive 99.5% accuracy rate in extracting instances of plagiarism. This research serves as a pivotal advancement in the domain of plagiarism detection, ushering in effective and sophisticated methods to combat the growing spectre of unoriginal content.