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Journal of Moeslim Research Technik
Published by Yayasan Adra Karima Hubbi
ISSN : 30476704     EISSN : 30476690     DOI : 10.70177/technik
Core Subject : Engineering,
Aerospace Engineering Automotive Engineering Control & Systems Engineering Electrical & Electronics Engineering Engineering
Journal of Moeslim Research Technik is is a Bimonthly, open-access, peer-reviewed publication that publishes both original research articles and reviews in all fields of Engineering including Civil, Mechanical, Industrial, Electrical, Computer, Chemical, Petroleum, Aerospace, Architectural, etc. It uses an entirely open-access publishing methodology that permits free, open, and universal access to its published information. Scientists are urged to disclose their theoretical and experimental work along with all pertinent methodological information. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 73 Documents
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OPTIMIZING MAXIMUM POWER POINT TRACKER (MPPT) USING HYBRID CUCKOO SEARCH-PSO ALGORITHM ON SOLAR ENERGY CONVERSION SYSTEM UNDER PARTIAL SHADING CONDITIONS Sahiri, Erpan
Journal of Moeslim Research Technik Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v3i1.3459

Abstract

The efficiency of solar energy systems is highly dependent on the accurate tracking of the maximum power point (MPP), especially under partial shading conditions, which are common in real-world environments. Traditional Maximum Power Point Tracking (MPPT) algorithms such as Perturb and Observe (P&O) and Incremental Conductance (IncCond) often fail to track the global MPP under such conditions, resulting in significant energy loss. This study presents a hybrid optimization approach using the Cuckoo Search (CS) and Particle Swarm Optimization (PSO) algorithms to improve the accuracy and speed of MPP tracking in solar energy systems under partial shading. The primary objective is to evaluate the effectiveness of the hybrid Cuckoo Search-PSO (CS-PSO) algorithm compared to conventional MPPT methods. A simulation-based approach was employed to model the solar energy conversion system and assess the performance of the MPPT algorithms. The results show that the CS-PSO algorithm outperforms traditional methods, achieving a tracking accuracy of 98.4%, with a reduced time to reach the MPP (8.7 seconds). In contrast, P&O and IncCond exhibited lower accuracy and slower convergence times. The study concludes that the hybrid CS-PSO algorithm provides a more efficient solution for optimizing MPPT under partial shading conditions, offering significant improvements in energy efficiency and tracking performance.
ARCHITECTURAL ENGINEERING IN THE DIGITAL ERA: PARAMETRIC DESIGN AND STRUCTURAL RATIONALIZATION Prabawasari, Veronika Widi; Takahashi, Haruto; Baharuddin, Faizal; Schneider, Anna
Journal of Moeslim Research Technik Vol. 3 No. 2 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v3i2.3624

Abstract

Architectural engineering in the digital era is increasingly shaped by parametric design methodologies that enable complex form generation and performance-driven optimization. Rapid advancements in computational tools have transformed design processes, yet a persistent gap remains between architectural exploration and structural rationalization, often resulting in inefficiencies and post-design adjustments. This study aims to develop an integrated computational framework that aligns parametric design with structural performance, ensuring that architectural forms are both innovative and structurally feasible. A computational design-based methodology was employed, combining parametric modeling, finite element analysis, and algorithmic optimization across representative architectural typologies. Iterative workflows were implemented to establish continuous feedback between geometric parameters and structural responses. Results indicate that integrated parametric-structural models achieve higher structural efficiency, reduced material consumption, and improved deformation control compared to conventional and non-integrated approaches. Statistical analysis confirms significant performance improvements, while case-based validation demonstrates strong alignment between simulated and expected structural behavior. Findings further reveal that real-time integration enhances design adaptability and decision-making efficiency. This study concludes that the integration of parametric design and structural rationalization represents a robust and scalable paradigm for contemporary architectural engineering, offering significant implications for sustainability, performance optimization, and interdisciplinary collaboration.
BEYOND DETERMINISTIC MODELS: PROBABILISTIC APPROACHES TO RISK-AWARE CIVIL ENGINEERING SYSTEMS Sitopu, Joni Wilson; Purba, Virgo Erlando; Damanik , Dermina Roni Santika; Williams, Sarah
Journal of Moeslim Research Technik Vol. 3 No. 2 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v3i2.3625

Abstract

Civil engineering systems increasingly operate under conditions of uncertainty, variability, and exposure to extreme events, challenging the adequacy of deterministic modeling approaches that rely on fixed assumptions and simplified safety margins. Probabilistic methods offer a more realistic representation by explicitly incorporating uncertainty into analysis and decision-making processes. This study aims to develop a risk-aware probabilistic framework that enhances reliability assessment and supports more informed engineering decisions. A mixed-methods computational design was employed, integrating stochastic modeling, Monte Carlo simulation, Bayesian updating, and reliability analysis across representative infrastructure systems. Results indicate that probabilistic and hybrid models achieve higher reliability indices, lower probabilities of failure, and reduced expected losses compared to deterministic approaches. Statistical analysis confirms significant differences in performance, while case-based validation demonstrates strong agreement between probabilistic predictions and observed system behavior. Findings further reveal that adaptive integration of data-driven techniques improves model accuracy and responsiveness under dynamic conditions. This study concludes that probabilistic approaches provide a robust and scalable paradigm for risk-aware civil engineering, offering substantial implications for infrastructure design, maintenance, and resilience planning.

Page 8 of 8 | Total Record : 73

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