cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Sugeng Hadi Susilo
Contact Email
shadis172.gh@gmail.com
Phone
+6281334519340
Journal Mail Official
evrimata.engineering.physics@gmail.com
Editorial Address
Jl, Margobasuki VII no 19, Mulyoagung, Dau-Malang, Jawa Timur 65151
Location
Kota malang,
Jawa timur
INDONESIA
Journal of Evrimata: Engineering and Physics
Published by PT. ELSHAD TECHNOLOGY INDONESIA
ISSN : -     EISSN : 30251265     DOI : https://doi.org/10.70822/journalofevrmata.vi
Core Subject : Science, Engineering,
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT
- Engineering (miscellaneous) - Civil and Structural Engineering - Electrical and Electronic Engineering - Mechanical Engineering - Chemical Engineering - Physics - Computer Science - Energy
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 4 Documents
 1 
Search results for , issue "vol. 04 no. 01, 2026" : 4 Documents clear
Development of an Information System to Enhance Supply Chain Efficiency of Gentle Living: Demand Forecasting, Buffer Stock, and Stock Verification Muhammad Khasbul Hadi; Farid Angga Pribadi; Rakhmat Arianto
Journal of Evrímata: Engineering and Physics Vol. 04 No. 01, 2026
Publisher : PT. ELSHAD TECHNOLOGY INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70822/journalofevrmata.vi.137

Abstract

The rapid growth of e-commerce has considerably amplified the complexity of supply chain management, particularly for small and medium enterprises (SMEs) that sell fast-moving consumer goods. Gentle Living, a web-based baby product retailer, faces persistent operational challenges rooted in inaccurate raw material recording, the absence of demand forecasting, unstructured buffer stock management, and unsystematic stock verification. These deficiencies result in stockouts, overstock, and disrupted production continuity. Digital transformation of supply chain operations has emerged as a critical success factor for SMEs competing in dynamic e-commerce environments, where operational inefficiencies directly translate into customer attrition and revenue loss. This study develops a web-based information system that integrates three core supply chain modules: demand forecasting using the Autoregressive Integrated Moving Average (ARIMA) method, buffer stock calculation using the probabilistic safety stock model, and stock verification (stock opname) supported by inventory reconciliation workflows. System development follows the Agile methodology, with Laravel as the primary backend framework and Python for time-series processing. Functional testing employs Black-Box Testing, while user acceptance is evaluated through User Acceptance Testing (UAT). The ARIMA model demonstrated practically acceptable forecasting accuracy with MAPE values within industry-standard thresholds (<20%), and the probabilistic buffer stock formula successfully calibrated safety inventory thresholds to service-level requirements. Results indicate that the system accurately predicts demand trends, maintains appropriate buffer stock levels, and significantly reduces inventory discrepancy rates, thereby improving the overall efficiency and resilience of Gentle Living's supply chain.
Analysis of Work Safety Behavior Among Workers in the Development Project at PT Bahagia Selalu Bersinar Housing Aura Park in Pondok Bestari Indah, Langdungsari, Malang Regency, East Java Fifi Damayanti; Kiki Frida Sulistyani; Hilarius Hudi Prayoga
Journal of Evrímata: Engineering and Physics Vol. 04 No. 01, 2026
Publisher : PT. ELSHAD TECHNOLOGY INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70822/journalofevrmata.vi.139

Abstract

The construction sector in Indonesia continues to show a high risk of work accidents, largely due to human behavioral factors that have the potential to cause accidents. This study aims to analyze the work safety behaviors implemented by workers on the Aura Park Housing development project by PT Bahagia Selalu Bersinar in Malang Regency, East Java. The main focus of the analysis is on the level of Compliance in the application of Personal Protective Equipment (PPE) as the main indicator of Attitude towards safety. The research approach applied is quantitative with data collection methods using surveys and direct observations in the field over a period of one month. Data on daily PPE use compliance were collected from 77 project workers. The research data shows that worker compliance with PPE use standards reaches a very low level, which is only 20%, far below the minimum standard of 60%. Gloves are the most frequently used PPE, while the use of other vital PPE such as helmets, safety shoes, and vests is still very minimal. This low level of compliance indicates that work safety behavior at the project site has not been optimally implemented and a safety culture has not been well established.
Ensuring Data Integrity in Healthcare Records through Hybrid Storage and Blockchain-Backed Audit Trails Azmiansyah Azmiansyah; Yan Watequlis Syaifudin; Cahya Rahmad; Josafat Pratama Susilo; Triana Fatmawati; Yuri Ariyanto; Pramana Yoga Saputra; Indrazno Siradjuddin; Chandrasena Setiadi
Journal of Evrímata: Engineering and Physics Vol. 04 No. 01, 2026
Publisher : PT. ELSHAD TECHNOLOGY INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70822/journalofevrmata.vi.140

Abstract

Ensuring the integrity and auditability of Electronic Health Records (EHRs) is critical for patient safety, regulatory compliance, and trust in digital healthcare. Conventional audit mechanisms such as database logs, are inherently mutable and vulnerable to insider tampering, failing to meet stringent requirements for tamper-proof, independently verifiable data provenance. To address this, this paper proposes and implements a hybrid EHR integrity system that combines PostgreSQL for sensitive clinical data storage with a private Hyperledger Fabric blockchain for immutable audit logging. Only lightweight metadata and SHA-256 hashes of records (not full EHRs) are written to the blockchain, preserving privacy while enabling cryptographic verification. Deployed on modest, heterogeneous hardware and featuring a user-friendly web interface with batched audit workflows, the system achieves 100% tamper detection accuracy, 210 ms average write latency, and 45 TPS throughput that demonstrates feasibility for real-world, resource-constrained clinical environments. Our approach delivers strong, scalable data integrity without prohibitive overhead, bridging the gap between regulatory demands and practical healthcare IT deployment.
Beyond Aggregate Metrics: Item-Level Performance Variability in SBERT-Based Automated Short Answer Scoring for Programming Education Pramana Yoga Saputra; Yan Watequlis Syaifudin; Dika Rizky Yunianto; Triana Fatmawati; Rossa Akmalia; Farida Ariany; Yuri Ariyanto
Journal of Evrímata: Engineering and Physics Vol. 04 No. 01, 2026
Publisher : PT. ELSHAD TECHNOLOGY INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70822/journalofevrmata.vi.142

Abstract

Automated short answer scoring (ASAG) systems based on Sentence-BERT (SBERT) and cosine similarity are commonly evaluated using aggregate metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and Pearson correlation, averaged across an entire item set. Aggregate reporting can conceal substantial variability at the level of individual items, masking failure patterns relevant to instructional reliability. This study re-examines item-level scoring data from a deployed SBERT-cosine similarity ASAG module within the BAJAPRO Basic Java Programming platform, comparing a single-reference synonym-expansion strategy against a multi-reference text-preprocessing strategy across 21 short explanatory items. Rather than reporting averages alone, performance is decomposed per item, revealing MAE ranging from 0.0007 to 0.070 and Pearson correlation ranging from 0.20 to 0.96 within a single evaluation condition, a range invisible in prior aggregate-only reporting. A qualitative failure case further shows SBERT-based similarity failing to distinguish semantically opposite mathematical operations expressed in near-identical sentence structures. The study explicitly reports its inability to verify item-to-concept mappings due to undocumented original evaluation scripts, treating this as a methodological finding on reproducibility practice in ASAG research rather than a limitation to be concealed. The findings argue for routine item-level reporting and improved experimental documentation in future SBERT-based ASAG studies.

Page 1 of 1 | Total Record : 4

 1 

Filter by Year

2026 2026


Reset
Filter By Issues
All Issue Vol. 04 No. 01, 2026 Vol. 03 No. 02, 2025 Vol. 03 No. 01, 2025 Vol. 02 No. 02, 2024 Vol. 02 No. 01, 2024 Vol. 01 No. 02, 2023 Vol. 01 No. 01, 2023