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Tech : Journal of Engineering Science
Published by Yayasan Penelitian dan Pengabdian Masyarakat Sisi Indonesia
ISSN : -     EISSN : 31097790     DOI : https://doi.org/10.69836/tech
Core Subject : Engineering,
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering
Tech : Journal of Engineering Science (E-ISSN 3109-7790) is a journal published by Yayasan Penelitian dan Pengabdian Masyarakat Sisi Indonesia with the aim of developing research that focuses on the field of engineering. Focus and Scope: Civil and Infrastructure Engineering, Mechanical Engineering, Electrical and Electronics Engineering, Industrial Engineering, Informatics and Computer Engineering, Chemical and Process Engineering, Environmental Engineering, Materials and Metallurgical Engineering, Aviation and Aerospace Engineering, Marine and Shipbuilding Engineering
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 25 Documents
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Integration and Implementation of the Kanban Method in Digital Projects for Enhancing Time Efficiency: A Case Study on the Procurement of AI-Based Forensic Device Communication in a Government Security Agency Sandryones Palinggi; Juan Salao Biantong; Erich Christian Limbongan
Tech : Journal of Engineering Science Vol 2 No 1 (2026): Inovasi Teknik dan Teknologi untuk Sistem Berkelanjutan dan Efisiensi Industri
Publisher : Yayasan Penelitian dan Pengabdian Masyarakat Sisi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69836/tech.v2i1.754

Abstract

The management of digital projects involving both physical infrastructure and artificial intelligence technology in government procurement environments presents significant challenges due to rigid sequential workflows and strict regulatory requirements. This research examines the integration and implementation of the Kanban method in a digital project for the procurement of an AI-based Forensic Device Communication system within a government security agency, with the objective of enhancing time efficiency in project execution. An intrinsic case study approach was employed to compare the conventional 92-day linear project model with the Kanban-based execution model. Data were collected through participant observation, document analysis, and structured field documentation across 33 strategic installation locations. The Kanban system was implemented using a digital board with six workflow columns and Work-In-Progress limits to manage parallel task execution. Source triangulation through digital Kanban records, official completion reports, and field observations ensured data validity. The Kanban method reduced project duration from 92 days to 49 calendar days, achieving a 46% improvement in time efficiency. The pull system approach and transparent task visualization enabled early identification of administrative bottlenecks, including licensing delays and inter-team coordination issues, without compromising the technical quality of 22 new AI-based CCTV units integrated with 11 existing units. These findings demonstrate that agile visual management methodologies can be effectively adapted to complex government procurement projects while maintaining regulatory compliance. This study provides an empirical model for integrating Kanban within public sector frameworks. Future research may extend this model to multi-agency procurement contexts.
Multiscale Characterization of Two-Phase Flow in Coal Using CT Imaging and Simulation Sindi Parashayu Anugerah
Tech : Journal of Engineering Science Vol 2 No 1 (2026): Inovasi Teknik dan Teknologi untuk Sistem Berkelanjutan dan Efisiensi Industri
Publisher : Yayasan Penelitian dan Pengabdian Masyarakat Sisi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69836/tech.v2i1.785

Abstract

Coal is a porous medium with strong heterogeneity, and its pore fracture structure plays a critical role in governing fluid flow behavior relevant to coalbed methane extraction and subsurface fluid management. However, accurate characterization of this structure has been challenging due to the limitations of conventional experimental methods. In this study, high resolution X-ray computed tomography was used to investigate the pore fracture structure of coal and its influence on gas water two-phase flow behavior. Six coal samples with different degrees of metamorphism were scanned, and three-dimensional digital models were reconstructed after image denoising, segmentation, and representative volume selection. Quantitative characterization of pore structure was performed by analyzing parameters such as pore size distribution, porosity, coordination number, and throat length. Pore network models were then extracted to simulate both single-phase and two-phase flow processes. The results showed that gas displacement by water followed a non-piston like mechanism, with preferential flow through connected pathways and gas trapping in isolated pores due to capillary effects. Relative permeability exhibited strong saturation dependence and hysteresis behavior, which were closely related to pore structure heterogeneity and connectivity. These findings provided important insights into the relationship between coal microstructure and fluid displacement efficiency, offering theoretical support for improving coalbed methane recovery.
Rancang Bangun Sistem Monitoring dan Kendali Ketinggian Air Tandon Berbasis IoT Menggunakan ESP32 dan Blynk Fikko Nanda Ramadhani; Nasywa Hamna Zakiya
Tech : Journal of Engineering Science Vol 2 No 1 (2026): Inovasi Teknik dan Teknologi untuk Sistem Berkelanjutan dan Efisiensi Industri
Publisher : Yayasan Penelitian dan Pengabdian Masyarakat Sisi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69836/tech.v2i1.822

Abstract

Clean water management often faces obstacles such as overflowing water reservoirs or pump damage due to limited manual monitoring. This study aims to design and implement an automatic water reservoir monitoring and control system based on the Internet of Things (IoT). The method used is a prototype method that includes the identification, design, and repeated testing stages. The hardware architecture consists of an ESP32 microcontroller, an HC-SR04 ultrasonic sensor, a relay, a buzzer, and a manual drain tap connected to a 300 ml reservoir, integrated with the blynk cloud platform. The sensor measures the distance to the water surface which is converted into volume using the formula V = ((H - d)/H) x Vmax. The test results show that the system successfully classifies water levels into three categories: "Low", "Medium", and "Full" with good accuracy. The pump operates automatically when the water is low and reaches a stable off state at a threshold of 6 cm to prevent overflow, while the manual drain tap allows users to drain excess water as needed. Additionally, the system provides real-time monitoring and manual control through a low-latency smartphone interface. In conclusion, the implemented IoT system effectively overcomes manual monitoring challenges, improves water efficiency, and provides users with reliable remote control access.
Cognitive Scaffolding in AI-Assisted Writing: An Empirical Study of Human Creativity and Content Authenticity Sheik Mohamed S H; M Nirmala; S Makesh
Tech : Journal of Engineering Science Vol 2 No 1 (2026): Inovasi Teknik dan Teknologi untuk Sistem Berkelanjutan dan Efisiensi Industri
Publisher : Yayasan Penelitian dan Pengabdian Masyarakat Sisi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69836/tech.v2i1.838

Abstract

Artificial Intelligence (AI) has significantly transformed the landscape of academic and professional writing by offering intelligent support in idea generation, content organization, language refinement, and editing. AI-assisted writing tools such as ChatGPT, Gemini, Perplexity, and QuillBot are increasingly used as cognitive support systems that reduce mental effort and improve writing productivity. However, concerns regarding originality, plagiarism, misinformation, and overdependence on AI-generated content continue to raise ethical and academic challenges. The present study examines the influence of AI-assisted writing on writing cognition and content authenticity through the concept of Human–AI Synergy. The study adopted a quantitative research design using a structured questionnaire distributed among 30 respondents, including students, teachers, and content writers familiar with AI writing tools. Statistical techniques such as Percentage Analysis, Chi-Square Test, Correlation Analysis, One-Way ANOVA, and exploratory Structural Equation Modeling (SEM) were employed for data analysis. The findings reveal that AI tools positively influence writing cognition by enhancing brainstorming, idea organization, productivity, and language quality. SEM results confirmed significant relationships between Human–AI Synergy, Writing Cognition, and Content Authenticity. The study also emphasizes that while AI improves writing efficiency, human creativity, ethical judgment, and critical evaluation remain essential to ensure originality and authenticity in writing practices. The study concludes that AI should be viewed as a collaborative cognitive partner rather than a replacement for human intellectual effort. Effective integration of AI in writing requires ethical awareness, institutional guidelines, and responsible human supervision to balance technological assistance with creativity and academic integrity.
Sistem Kendali Lampu Otomatis ESP8266 Berbasis Sensor PIR dan Monitoring Aplikasi Blynk Adit Ramadan; Muhammad Ridwan Martana; Naaq Shal Ramadanu
Tech : Journal of Engineering Science Vol 2 No 1 (2026): IOT is a Future? Nice.....
Publisher : Yayasan Penelitian dan Pengabdian Masyarakat Sisi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69836/tech.v2i1.830

Abstract

Energy efficiency issues in building lighting sectors often stem from human negligence in turning off electronic devices, resulting in significant operational electricity costs. This research aims to design and implement a smart light control system based on the Internet of Things (IoT) using the ESP8266 microcontroller, HC-SR501 PIR sensor, and Blynk platform. The method used is experimental with a hardware design approach separating low and high current paths, alongside software development using non-blocking logic in Arduino IDE. Integration with the IoT platform allows dual control: automation based on motion detection and remote manual control via mobile application. Test results show the PIR sensor has a 100% detection accuracy rate at an optimal distance of up to 4 meters. Furthermore, efficiency analysis shows that this system implementation can reduce unnecessary active lamp duration, resulting in an average energy saving of ± 45.8% compared to manual systems. This study concludes that the combination of physical sensors and cloud-based control is a reliable and responsive solution to support energy conservation in modern buildings.

Page 3 of 3 | Total Record : 25

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