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Journal of Applied Science and Technology in Engineering
Published by PT Arete Mahardika Saqhi
ISSN : -     EISSN : 31645739     DOI : -
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Journal of Applied Science and Technology in Engineering (JASTE) is a peer-reviewed, open-access scientific journal that aims to disseminate original research and scholarly studies contributing to the development and application of engineering science and technology. The journal covers electrical engineering, telecommunications engineering, computer and informatics engineering, industrial and manufacturing engineering, mechanical engineering, civil and environmental engineering, as well as interdisciplinary research in engineering and applied technology. JASTE is published twice a year, in February and August, by Arete Litera under PT Arete Mahardika Saqhi, Indonesia.
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Articles 5 Documents
 1 
Machine Learning-Based Sentiment Classification for Detecting Financial Misinformation on Social Media Robert Situmorang; Yunus Yulianus
Arete Litera: Multidisciplinary Journal of Research ( AMJR ) Vol 1 No 1 (2026): February 2026
Publisher : Arete Litera

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Abstract

Financial misinformation on social media is difficult to identify because misleading posts often combine emotionally charged language, incomplete evidence, promotional claims, and technically plausible financial terminology. This conceptual technical review examines how machine-learning sentiment classification can be incorporated into a broader detection pipeline for financial misinformation. The review synthesizes literature on financial-domain language models, deception detection, sentiment analysis, feature engineering, and human-in-the-loop verification. It proposes a modular architecture consisting of data acquisition, text normalization, financial sentiment representation, misinformation-risk classification, explanation, and reviewer escalation. The analysis shows that sentiment is useful as a contextual signal but is insufficient as a stand-alone indicator because legitimate financial communication may also be strongly positive or negative. Robust systems should combine contextual embeddings, source and propagation features, claim-evidence consistency, calibration, and explainable outputs. Evaluation should report precision, recall, F1-score, area under the curve, calibration error, and performance across topics and time periods. The proposed architecture provides an engineering-oriented foundation for developing transparent financial misinformation screening systems without treating automated classification as a substitute for professional verification.  
DeepFake Voice Resilient System berbasis Otentikasi Spektrum Frekuensi Non-Linier pada Asisten Digital Pasien Lansia Asep Suhendar
Arete Litera: Multidisciplinary Journal of Research ( AMJR ) Vol 1 No 1 (2026): February 2026
Publisher : Arete Litera

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Abstract

Voice-based digital assistants for elderly patients with mild dementia are increasingly deployed but face serious threats from deepfake voice attacks that can impersonate family members. This research aimed to develop a system resilient to deepfake voice attacks by utilizing nonlinear frequency spectrum authentication derived from digital hearing aids already worn by the elderly. The methods employed included nonlinear feature extraction from acoustic feedback signals of hearing aids and Siamese Neural Network training with contrastive loss. The study involved 30 elderly individuals with mild dementia (MMSE scores 20-24) who used digital hearing aids. The results demonstrated that deepfake detection accuracy reached 96.7%, with a false rejection rate of 3.8%, a false acceptance rate of 2.4%, and an average authentication latency of 412 ms. This system required no active interaction from the elderly, thereby imposing no burden on their cognitive functions. This study concluded that hearing aid-based nonlinear frequency spectrum authentication effectively serves as a passive defense mechanism against deepfake voice attacks on elderly digital assistants.
Digital Image Forensics for Authenticating WhatsApp Screenshots Using Metadata and Error-Level Analysis Margareth Simanjuntak
Arete Litera: Multidisciplinary Journal of Research ( AMJR ) Vol 1 No 1 (2026): February 2026
Publisher : Arete Litera

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Abstract

WhatsApp screenshots are widely used to communicate records of conversations, yet a screenshot is a rendered image that can be edited, recomposed, or generated without preserving the original message database. This technical review examines a layered forensic workflow for assessing screenshot authenticity using acquisition records, cryptographic hashes, metadata examination, error-level analysis, clone detection, compression artifacts, optical character recognition, and interface-consistency checks. The analysis emphasizes that no single method can prove authenticity. Metadata may be absent after screenshot capture or platform transfer, while error-level analysis is sensitive to recompression and should not be interpreted as definitive evidence of manipulation. A defensible workflow begins with preservation of the submitted file and device context, followed by reproducible image analysis and comparison with native WhatsApp artifacts when legally and technically available. The article proposes a confidence-based reporting framework that separates observations, analytical indications, and conclusions. Technical validation should use controlled genuine and manipulated screenshot datasets, report sensitivity and specificity by manipulation type, and test robustness across devices, operating systems, themes, resolutions, and compression levels. The resulting framework positions screenshot analysis as a digital-forensics triage process rather than a stand-alone legal determination.
Design and Usability Evaluation Framework for an Augmented Reality-Based Civic Education Application Ahmad Sugianto; Suryono Suryono
Arete Litera: Multidisciplinary Journal of Research ( AMJR ) Vol 1 No 1 (2026): February 2026
Publisher : Arete Litera

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Abstract

Augmented reality can support civic education by connecting abstract concepts with contextual three-dimensional objects, interactive scenarios, and location-aware learning activities. However, educational relevance does not by itself demonstrate that an augmented reality application is technically usable, reliable, or deployable. This conceptual design article develops an engineering and usability-evaluation framework for an augmented reality-based civic education application. The framework covers requirements analysis, content-object mapping, interaction design, marker or markerless tracking, asset optimization, device compatibility, privacy, functional testing, and user evaluation. It recommends measuring task completion, learnability, efficiency, error rate, interface consistency, tracking stability, rendering performance, and perceived usability. Educational outcomes may be evaluated as secondary evidence, while the primary contribution remains the design and validation of the technological system. The analysis identifies major risks including low-end device limitations, unstable tracking, excessive cognitive load, inaccessible interaction patterns, and inadequate protection of student data. A staged evaluation process is proposed, beginning with expert inspection and laboratory testing, followed by small-scale usability testing and field validation. The framework enables future researchers to report augmented reality educational applications with clearer technical specifications, reproducible procedures, and measurable performance criteria.
Design Requirements for an IoT-Based Remote Pain Monitoring System for Older Adults with Osteoarthritis Taufik Suroto
Arete Litera: Multidisciplinary Journal of Research ( AMJR ) Vol 1 No 1 (2026): February 2026
Publisher : Arete Litera

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Abstract

Pain in osteoarthritis varies across time, activity, sleep, and environmental context, while conventional clinic-based recall may not capture short-term fluctuations. Internet of Things technology offers a means to combine repeated self-reported pain assessments with mobility and physiological measurements from wearable devices. This conceptual technical review defines design requirements for an IoT-based remote pain monitoring system for older adults with osteoarthritis. The proposed architecture includes wearable and mobile sensing, ecological momentary assessment, secure data transmission, quality control, event detection, visualization, and clinician review. The synthesis emphasizes that pain remains a subjective experience and should not be inferred solely from sensor data. Wearable measures can contextualize patient reports and identify changes that warrant review, but they should not automatically diagnose or alter treatment. Key engineering requirements include low-burden interaction, large and accessible controls, intermittent-connectivity support, timestamp synchronization, missing-data detection, encryption, role-based access, and transparent alert thresholds. Evaluation should include usability, adherence, battery performance, transmission reliability, data completeness, false-alert rate, and agreement between device records and reference measures. The framework provides a responsible pathway for developing remote monitoring systems that support clinical decision-making while preserving patient autonomy and safety.

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