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Makara Journal of Technology
Published by Universitas Indonesia
ISSN : 23552786     EISSN : 23564539     DOI : https://doi.org/10.7454/mjt
Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mechanical Engineering
MAKARA Journal of Technology is a peer-reviewed multidisciplinary journal committed to the advancement of scholarly knowledge and research findings of the several branches of Engineering and Technology. The Journal publishes new results, original articles, reviews, and research notes whose content and approach are of interest to a wide range of scholars. It also offers rapid dissemination. MAKARA Journal of Technology covers the recent research in several branches of engineering and technology include Electrical & Electronics Engineering, Computer Engineering, Mechanical Engineering, Chemical & Bioprocess Engineering, Material & Metallurgical Engineering, Industrial Engineering, Civil & Architecture Engineering, and Marine Engineering. Criteria used in determining acceptability of contributions include newsworthiness to a substantial part of the engineering & technology and the effect of rapid publication on the research of others. This journal, published three times each year, is where readers look for the advancement of discoveries in engineering and technology.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 4 Documents
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Search results for , issue "Vol. 30, No. 1" : 4 Documents clear
Multicriteria Analysis of Vehicle Exhausts Emission using Fuzzy Analytic Hierarchy Oke, Sunday Ayoola; Abdul, Ibraheem Adedotun; Badmus, Ismaila; Rajan, John; Jose, Swaminathan; Yekinni, Adekunle Adetayo; Olaiya, Kabiru Alani; Adeniran, Mofoluwaso Kehinde; Benrajesh, Pandiaraj
Makara Journal of Technology Vol. 30, No. 1
Publisher : UI Scholars Hub

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Abstract

This study employs the fuzzy analytic hierarchy process (FAHP) to identify the critical factors and their degree of relevance to the vehicle emission process. Its innovation lies in the potential to blend ambiguity and uncertainty with the established AHP. FAHP transforms information into a defuzzification state through signal-to-noise ratios, normalization, and pairwise comparison. The principal parameters considered are revenue, sold packing units, CAGR, packing materials, consumption, and CO2 emissions (A, B, C, D, E, and F, respectively). From the normalized defuzzified weight result, consumption (Parameter E) is the best (normalized weight, 0.8685917), while CO2 emissions (Parameter F) was the worst (normalized weight, 0.050454358). Considering the weights and ranks of the data, run order 4 ranked first with values of 0.2414, 0.0903, 0.1864, 0.1448, 0.2867, 0.0412, and 0.99078 for parameters A, B, C, D, E, and F, respectively. This work is useful for logistics managers who wish to control vehicle emissions. Manufacturers could reduce vehicle emissions by improving the combustion process designs through the data for the ranking of these prioritized parameters.
The PID-Based Three Quadcopter UAVs Formation Control under External Disturbance An, Vo Van; Mien, Trinh Luong
Makara Journal of Technology Vol. 30, No. 1
Publisher : UI Scholars Hub

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Abstract

This paper presents the design and evaluation of a formation control strategy for three quadcopter UAVs, based on a PID controller in a leader–follower structure, under the influence of external disturbances. Each UAV employs a six-degree of-freedom dynamic model and utilises a cascade PID control architecture, in which the inner control loop stabilises the attitude. In contrast, the outer control loop regulates position and maintains the formation. The PID parameters are tuned using the Ziegler–Nichols method to ensure simple implementation and low computational cost. The performance of the control system is evaluated through simulations in the MATLAB environment for two typical formation shapes (linear and triangular), both in noise-free conditions and under external disturbances. Simulation results show that in noise-free conditions, the system achieves a rise time of about 2–3 seconds, a settling time of 10–15 seconds for the linear formation, and 20–25 seconds for the triangular formation, with overshoot less than 15% on the position axes and a steady-state error of approximately 0.05 meters. When subjected to external disturbances, the UAVs still maintain the desired formation with a steady-state error of less than 0.1–0.5 meters, demonstrating an acceptable level of disturbance resistance. These results prove that, despite its simple structure, the proposed Leader–Follower PID control strategy can still ensure stable formation and effective trajectory tracking for small-scale UAV systems, while also being suitable for practical applications that require low cost and high deployability.
Global Research on Palm Oil Diseases and Infections: A Bibliometric Analysis Saputra, Fahmi Achmad; Mustika, Indria Puti; Safarida, Anna; Sriherwanto, Catur; Putra, Nicky Rahmana
Makara Journal of Technology Vol. 30, No. 1
Publisher : UI Scholars Hub

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Abstract

The sustainability of global palm oil production faces significant threats from a range of diseases and infections affecting palm oil crops. This study presents a comprehensive bibliometric analysis to map the scientific landscape and evolution of research related to palm oil diseases over the past decade. Using data from the Scopus database, 366 relevant documents were analyzed using R and VOSviewer to uncover trends in publication volume, citation impact, prolific authors, country contributions, and keyword co-occurrence networks. The findings reveal a strong research concentration on G. boninense, highlighting its critical role as a persistent pathogen in oil palm plantations. Emerging themes, such as bioactive compound research, comparative biology, and plant–microbiome interactions, reflect the growing interdisciplinary interest in sustainable disease management. This study identified key research gaps and proposed future directions, including molecular breeding, biocontrol strategies, and valorization of bioactive compounds from oil palm by-products. The results offer strategic insights to guide future scientific inquiry and inform sustainable solutions for global palm oil production.
A Deep Learning-Based Approach for Bot Detection in Trending Hashtags on X Hussain, Mehboob; Rana, Muhammad Rizwan Rashid; Imran, Muhammad; Shoaib, Muhammad; Mujtaba, Muhammad Hasaan
Makara Journal of Technology Vol. 30, No. 1
Publisher : UI Scholars Hub

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Abstract

The widespread presence of bots on social media platforms, such as X (formerly Twitter), poses a significant threat to the integrity of online information by facilitating the dissemination of misinformation and manipulating public discourse. This study proposes a robust deep learning-based framework, DeepBot, to detect bot participation in trending hashtags and discussions on X. The approach uses a dataset sourced from Kaggle, comprising user profile metadata, including follower count, tweet frequency, account verification status, and engagement metrics. The data were subjected to comprehensive preprocessing, including noise removal, part-of-speech (POS) tagging, and word embedding using the pre-trained GloVe model. RoBERTa is employed for feature extraction to capture deep contextual semantics, followed by classification through a deep neural network (DNN) to effectively distinguish between human users and bots. The proposed model is evaluated against established baselines using standard performance metrics. Experimental results demonstrate that DeepBot achieves superior performance with an accuracy of 92.82%, precision of 91.24%, and recall of 91.78%, confirming its effectiveness in enhancing the reliability of bot detection in social media trend analysis.

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