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Herlambang Setiadi
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Faculty of Advanced Technology and Multidiscipline, Gedung Kuliah Bersama, Kampus C Mulyorejo, Universitas Airlangga Jl. Dr. Ir. H. Soekarno, Surabaya, East Java 60115, Indonesia
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Journal of Advanced Technology and Multidiscipline (JATM)
Published by Universitas Airlangga
ISSN : -     EISSN : 29646162     DOI : https://doi.org/10.20473/jatm.v1i2.40293
Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology
Journal of Advanced Technology and Multidiscipline (JATM) aims to explore global knowledge on sciences, information, and advanced technology. JATM provides a place for researchers, engineers, and scientists around the world to build research connections and collaborations as well as sharing knowledge on how addressing solutions to the (real world) problems through discoveries on cutting edge of science and technology. We encourage researchers to submit research in the following fields: ● Power System ● Control Systems ● Renewable Energy Technology ● Advanced Manufacturing ● Optimization & System Engineering ● Human Factors & Ergonomics ● Supply Chain & Logistic Management ● Waste Processing/ Waste Treatment ● Pollutant Removal ● Applied Chemistry ● Nano Medicine ● Sensor ● Artificial Intelligence ● Health Informatics ● Robotics & Mechatronics ● Computer Vision ● Data mining ● Human Computer Interaction ● Software Engineering ● Deep Learning ● Internet Of Things ● Natural Language Processing ● Learning Analytics & technologies ● Machine learning
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 4 No. 2 (2025): Journal of Advanced Technology and Multidiscipline" : 5 Documents clear
A PID - Ziegler Nichols Method for Load Frequency Control Anggraini, Dessy Dwi; Palaloi, Sudirman; Maharani, Markies Diana Desy; Sularso, Adhimas Herjuno; Manurung, Rosa Tiarmin; Habibi, Rizky Maulana Iqwan; Aditya, Putra Yoga; Harsito, Catur
Journal of Advanced Technology and Multidiscipline Vol. 4 No. 2 (2025): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jatm.v4i2.69482

Abstract

Dynamic load variations significantly impact the stability of system frequency, necessitating the implementation of Load Frequency Control (LFC) to maintain frequency stability. In this study, a PID-based control approach is applied to LFC modeling using the Ziegler-Nichols tuning method through the Reaction Curve Method. The test was conducted using the difference of load of 1 p.u. Using these parameters, the optimal PID controller was configured with Kp = 2.97, Ki = 0.78, and Kd = 2.27. The evaluation demonstrated that the system achieved a settling time of 17 seconds and a maximum overshoot of 65.35 Hz. Under various load scenarios, including increasing, decreasing, and fluctuating loads, the LFC system equipped with a PID controller based on the Ziegler-Nichols Reaction Curve Method effectively maintained frequency stability despite significant load changes. These findings confirm that the proposed approach is reliable in preserving system performance under dynamic load conditions.
Evaluating Cognitive Load of a Laundry Service Worker: A Subjective Workload Assessment Technique Approach Wulandari, Chandrawati Putri; Vincent, Adriel Maruli; Hassani, Gilang Fadly; Sunar, Muhammad Akbar; Aldhama, Shofa Aulia; Mufidah, Ilma
Journal of Advanced Technology and Multidiscipline Vol. 4 No. 2 (2025): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jatm.v4i2.70952

Abstract

Laundry service workers perform repetitive and physically demanding tasks, often under time constraints, leading to increased cognitive load. Cognitive load assessment is crucial for understanding workload distribution and optimizing task allocation in labor-intensive industries. This study evaluates the cognitive load of laundry service workers using the Subjective Workload Assessment Technique (SWAT). The analysis focuses on two primary phases: scale development and event scoring. The scale development phase involved rating three workload dimensions: time pressure, mental effort, and stress level. The event scoring phase analyzed workload variations across tasks and workers. The findings indicate that ironing is the most cognitively demanding task, followed by washing and moving to the dryer, while storing and customer retrieval generally impose lower workloads. Notably, differences in workload perception among workers highlight the need for task redistribution, process optimization, and potential ergonomic interventions. This study provides valuable insights into improving worker efficiency and well-being in service industries.
Design of an Unmanned Surface Vehicle Based on Pixhawk Autopilot for Water Sampling Masyhur, Abdullah Al; Setiawan, Muhammad Aldo; Achmad, Achmad; As’ad, Muhammad Ridwan
Journal of Advanced Technology and Multidiscipline Vol. 4 No. 2 (2025): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jatm.v4i2.71651

Abstract

Water is an important element in the life of living creatures, both for consumption and other purposes. Therefore clean water is crucial for human health and environmental protection. To determine the quality of water, whether it is safe for consumption or not, testing in a laboratory is required by testing the chemical elements and physical elements. This is because there are differences in determining whether water is suitable for use or not, the depth of the water also influences the differences in water quality, therefore we need the process of taking the water to be tested. Currently this process is carried out manually using manned vessels, this causes inefficiencies if carried out continuously. To overcome this problem, we need a tool that can collect water automatically. Unmanned Surface Vehicle (USV) is a vehicle that can walk on the surface of the water without passengers and can run manually using a Radio Control (RC) transmitter or automatically using the Pixhawk autopilot and Global Positioning System (GPS) as a localization system. This research aims to design an Unmanned Surface Vehicle (USV) that can take water samples automatically using the Pixhawk autopilot at a certain point and at a certain depth.
Sentiment and Social Network Analysis of X Social Media on the Implementation of the Merdeka Belajar Curriculum in Indonesia Herra, Nafisahika Putri; Ramadhani, Olga Kabsyah; Mumtaz, Nabila; Zakaria, Ditha Meiga; Maryamah
Journal of Advanced Technology and Multidiscipline Vol. 4 No. 2 (2025): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jatm.v4i2.71938

Abstract

Indonesian Ministry of Education, Culture, Research, and Technology introduced the Merdeka Curriculum to overcome post-pandemics COVID-19 challenges with a transformative education policy. However, the effectiveness of education policy requires the contribution of public opinion. Exploring sentiment public opinions, and structural dimensions of interaction or network behavior are needed. This paper proposed sentiment and social network analysis of X social media on the implementation of the Merdeka Curriculum in Indonesia. The methodology consists of preprocessing, vectorizer with TF-IDF, sentiment and social network analysis. Sentiment classification was performed using four machine learning models, Support Vector Machine (SVM), Random Forest, XGBoost, and LightGBM. Based on the experimental results, Random Forest achieved the best performance with 70% accuracy. The analysis revealed that public sentiment was dominated by neutral and negative responses, indicating persistent criticism and limited support throughout the curriculum’s rollout. Social network analysis identified central accounts in the discourse, including @nadiemmakarim and @Kemdikbud_RI, while other accounts, for example @adekumala, served as key bridges within the network despite receiving fewer mentions. This paper integrates a data-driven approach to understanding public opinion and shows influence dynamics on social media providing valuable insights for policy communication and refinement in the digital era.
A Lean Warehousing Approach for Waste Reduction: A Case-Based Analysis Using VSM and VALSAT Kartika Nur 'Anisa'; Desak Made Adya Pramesti
Journal of Advanced Technology and Multidiscipline Vol. 4 No. 2 (2025): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jatm.v4i2.76518

Abstract

This study aims to identify and reduce waste in the loading and unloading processes at PT XYZ’s motorcycle distribution warehouse to improve operational efficiency. A Lean Warehousing approach was adopted, beginning with Value Stream Mapping (VSM) to visualize the current workflow and identify non-value-added activities. Waste types were quantified using the Waste Assessment Model (WAM), and improvement priorities were determined through the VALSAT tool. Further analysis with Process Activity Mapping provided a detailed evaluation of each process step, facilitating the elimination of inefficiencies. The assessment revealed that the most dominant wastes were motion (22.43%), waiting (17.70%), and processing waste (12.87%). To address these issues, root cause analysis was conducted using the Why-Why method, followed by the development of corrective actions based on 5W1H framework. Improvement strategies included workflow optimization and the implementation of standardized operational procedures. Unloading time was reduced by 22.12% (from 104 to 81 minutes), and loading time decreased by 37.65% (from 85 to 53 minutes). Moreover, Process Cycle Efficiency (PCE) significantly improved, i.e. 28.40% for unloading and 17.81% for loading. The study confirms that the structured application of lean tools can effectively eliminate non-value-added activities, improve process flow, and enhance overall warehouse performance. These findings provide practical insights for warehouse and logistics managers in implementing lean-based improvements to achieve higher operational efficiency.

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