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INDONESIA
Journal of Business, Social and Technology
Published by Politeknik Siber Cerdika Internasional
ISSN : 28072928     EISSN : 28076362     DOI : 10.59261
Core Subject : Economy, Social, Engineering,
Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences
This journal publishes research articles covering all aspects of information technology, information systems, agricultural technology, computer social and political sciences, and economics that belong to the business, social, and technological context.
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 176 Documents
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Comparative Analysis of Supervised Learning and Unsupervised Anomaly Detection in Security Log Analysis for Post-Incident Digital Forensic Investigation Indramana, Iwan; Purwanto, Asto
Journal of Business, Social and Technology Vol. 7 No. 2 (2026): Journal of Business, Social and Technology
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jbt.v7i2.605

Abstract

Background: Attempts to perform post-incident digital forensic investigation on large-scale security logs generated by enterprise firewalls and servers introduce a range of challenges. As data grows larger and more complex, it is no longer feasible to conduct manual analysis. Methodologically, there has been only limited empirical work directly comparing supervised and unsupervised paradigms for use in a post-incident forensic framework on operational-scale, real-world logs. Objective: This paper compares the classification performance of supervised and unsupervised machine learning methods for forensic analysis of security logs, as well as the prioritization of various security anomalies using both approaches. Methods: Analysis of a dataset containing more than 359,000 firewall and server logs obtained over a 30-day period. Labeled events were used to implement a supervised model, Logistic Regression; Isolation Forest is an unsupervised anomaly detection method, which performs best among the models trained on normal baseline logs. Evaluation metrics included accuracy, precision, recall, ROC-AUC, and ranking-based anomaly assessment. Results: Logistic Regression — accuracy (0.99), ROC-AUC (0.9998), precision/recall for suspicious events (1.00, 0.99) — demonstrated near-perfect discriminability of labeled behavioral features within a 24-hour period. Isolation Forest: 86% overall accuracy, 93% precision, 59% recall; excellent forensic triage property: confirmed suspicious events among the top 200 anomaly-ranked entries: 197 of 200 (92.5%). Sensitivity analysis of the contamination parameter showed that ranking precision at the top 200 remained stable within the 0.05 to 0.30 range (Fig. 7A, 7B), demonstrating the robustness of rank-based prioritization despite variability in global recall across contamination values. Conclusion: Our results demonstrate high predictive performance for supervised classification and efficient forensic triage through low false-positive rates in unsupervised anomaly detection of both time-series logs and free-text security event logs.
The Influence of Social Media Marketing and Electronic Word of Mouth (E-WOM) on Purchase Intention Through Trust in Indibiz Products in the Telkom Yogyakarta and Southern Central Java Area Kusumadewi, Afifah Nuraghnia; Widowati, Retno
Journal of Business, Social and Technology Vol. 7 No. 2 (2026): Journal of Business, Social and Technology
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jbt.v7i2.606

Abstract

Background: The digitalization of business services in Indonesia has boosted social media marketing (SMM) and e-WOM adoption among SMEs in the B2B telecommunications sector. However, trust as a link between SMM, e-WOM, and purchase intention for products like Indibiz remains underexplored. Objective: This study examines the impact of SMM and e-WOM on purchase intention for Indibiz through consumer trust, focusing on SMEs in the Telkom Yogyakarta Jateng Selatan area that use social media, are aware of Indibiz, but have not subscribed. Methods: This study uses a quantitative explanatory approach with purposive sampling, collecting 208 valid responses from 283 questionnaires via Google Forms. Data were analyzed using SEM-PLS with SmartPLS 4.0, including outer model tests (validity, reliability) and inner model analysis (path coefficients, bootstrapping, R²). Results: All seven hypotheses were supported. SMM positively influenced trust (β = 0.287, t = 3.42, p < 0.01) and purchase intention (β = 0.198, t = 2.21, p < 0.05). e-WOM positively influenced trust (β = 0.602, t = 7.15, p < 0.001) and purchase intention (β = 0.231, t = 2.64, p < 0.01). Trust significantly mediated both relationships (SMM→Trust→PI: β = 0.130; e-WOM→Trust→PI: β = 0.272). The model explained 73.1% of purchase intention variance (R² = 0.731). Conclusion: Trust mediates the relationship between digital marketing signals and B2B purchase intention in Indonesian telecommunications SMEs. Practitioners should focus on trust-building content strategies and manage e-WOM credibility to convert prospects into Indibiz subscribers. Future research should explore other regions and platforms.
Yeo-Johnson Transformation Usage in Data Preprocessing for Well Production Prediction Using Deep Neural Networks (DNN) Rizky, Alringga; Yuniarti, Anny
Journal of Business, Social and Technology Vol. 7 No. 2 (2026): Journal of Business, Social and Technology
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jbt.v7i2.607

Abstract

Background: The accurate prediction of infill well production is one of the major bottlenecks for hydrocarbon reservoir development. Traditional reservoir simulation tools are computationally expensive, taking weeks to months per scenario. Objective: This paper presents the development of a Deep Neural Network (DNN) model for prediction with hyperparameter optimization using the Tree-structured Parzen Estimator (TPE) to predict pay porosity (PORPAYX) in infill wells of the Pertamina Hulu Sanga Sanga field. Methods: A DNN model was developed to predict oil well production based on subsurface and production features from a comprehensive dataset of Pertamina Hulu Sanga Sanga reservoir characteristics and production data. Details of our method include: training the model on a robust dataset, hyperparameter tuning using the Tree-structured Parzen Estimator (TPE), and K-fold cross-validation for performance validation. Results: Scaling normalized the data in such a way that every feature had equal influence during model training, enabling better learning and accurate prediction. In contrast, fitting the model using unscaled data resulted in an R² of less than zero (a negative score), meaning that the model could not explain the variability in the data. The mean R² score of the unscaled data model was −0.08496, along with a higher MSE = 0.009057 and RMSE = 0.095148. This was due to the model's failure to process features with varying scales, which prevented proper learning and prediction. Conclusion: Residual plots confirmed that the model trained with scaled data met the assumptions of linearity and normality.
Social Capital Construction in Informal Strategic Alliances in Micro Enterprises: The Role of MSME (Micro, Small, and Medium Enterprises) Companions as External Facilitators Widyawan, Bisma; Salman, Dhani; Maesarini, Indah Wahyu
Journal of Business, Social and Technology Vol. 7 No. 2 (2026): Journal of Business, Social and Technology
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jbt.v7i2.610

Abstract

Background: Micro businesses have been recognised globally for their contribution to wealth and job creation, but they continue to face sustainability challenges due to limited resources, networks, and managerial capacity. An approach to overcome these limitations is to create informal strategic alliances through collaborative efforts. Most studies, however, assume that social capital in business networks evolves naturally, thus overlooking the role of external facilitation in intentionally constructing social capital, especially in the context of developing countries with the proliferation of micro-enterprises. Objective: The purpose of this study is to examine the social construction process of social capital in informal strategic alliances in microenterprises, with particular attention to the role of MSME companions as external facilitators. Methods: A qualitative approach with a case study design focusing on the Gerai Jajanan Turki (GJT) community in Depok City. A combination of methods was used to collect data, including semi-structured interviews with business actors and customers, a survey, and document analysis. NVivo 15 was used for thematic analysis. Results: This research found that informal alliances and social capital were constructed in GJT through the facilitation of MSME companions. Companions aided in establishing connections between business actors and assisted in communication, role allocation, and dispute resolution, resulting in partnerships replete with trust and stable business alliances. Conclusion: The construction of collaborative networks can be facilitated by external facilitators. This study builds upon the social capital construction framework by proposing that trust and cooperative norms may be purposefully created through facilitative means.
The Effect of ESG Risk Rating on Corporate Profitability: The Role of Firm Size and Leverage as Moderating Variables Syurmita, Syurmita; Welkom, Syahfitri Suryaningsi; Rayesha, Khansa Chikita
Journal of Business, Social and Technology Vol. 7 No. 2 (2026): Journal of Business, Social and Technology
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jbt.v7i2.613

Abstract

Background: Sustainalytics ESG Risk Rating has been identified as a determinant of corporate financial performance. However, its effect on profitability—particularly for developing markets like Indonesia—remains underexplored. This study examines how ESG risk relates to profitability and whether firm size or leverage moderates their relationship. Objective: This study seeks to determine the influence of ESG risk on profitability, with firm size and leverage as moderating variables. Methods: A quantitative study employing Moderated Regression Analysis (MRA) was conducted using 76 firms listed on the Indonesia Stock Exchange (IDX) in 2024. The proxy for profitability was Net Profit Margin (NPM), and ESG Risk Ratings were obtained from Sustainalytics. Results: ESG Risk Ratings negatively affect profitability (B = −2.418; p = 0.005), whereby higher sustainability risk impairs net profit margins. This negative effect is moderated by firm size (B = 0.094; p = 0.001), as larger firms are better equipped to manage ESG risks. Conversely, higher leverage strengthens the negative effect of ESG risk on profitability (B = −0.839; p = 0.001), as highly leveraged firms are less capable of addressing sustainability pressures. Conclusion: The results underscore the need for both ESG risk disclosure and governance. Larger firms cope with ESG risk more effectively than highly leveraged firms. Further research is warranted with a longer observation period and additional measures of profitability.
The Single Presence Policy for Rural Banks Marbun, Bachtiar
Journal of Business, Social and Technology Vol. 7 No. 2 (2026): Journal of Business, Social and Technology
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jbt.v7i2.621

Abstract

Background: Indonesian banking regulation has undergone significant structural transformation with the enactment of OJK Regulation No. 12/POJK.03/2020. This regulatory shift raises critical legal questions about its implications for Rural Bank institutions. Objective: This research aims to understand and examine the single presence policy for Rural Banks, which is predicted to be implemented, and to determine the consequences of the single presence policy regulation after the issuance of the Commercial Bank Consolidation POJK. Methods: The research methods applied include qualitative research with normative legal methods, employing statute and conceptual approaches to analyze primary legal materials, including Bank Indonesia Regulations, OJK Regulations, and the P2SK Law (Law No. 4/2023). Results: The single presence policy for Rural Banks is predicted to be implemented with the aim of increasing banking stability, resilience, and competitiveness at the national level, as well as facilitating digital revitalization in the financial industry. Regarding the harmonization of bank control regulations through controlling shareholders, the Commercial Bank Consolidation POJK also regulates changes related to the minimum capital requirements for bank tier thresholds. The current core capital requirements are as regulated in Article 147, paragraph (1) of the Republic of Indonesia Financial Services Authority Regulation Number 12/POJK.03/2021 concerning Commercial Banks, which are grouped into 4 (four) KBMI. Conclusion: The emergence of the single presence policy is unsuitable and irrelevant for banking, especially for BPR, considering that the history of the formation of BPR, which aimed to help people in rural areas, is contrary to the single presence policy.

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