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Journal of Applied Science and Advanced Engineering
Published by Universitas Gunadarma
ISSN : -     EISSN : 29857252     DOI : https://doi.org/10.59097/jasae.v2i2
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering Mechanical Engineering Physics
JASAE | Journal of Applied Science and Advanced Engineering (ISSN: 2985-7252) is an international, multidiscipline, open access, peer-reviewed scholarly Journal published biannually for researchers, developers, technical managers, and educators in the field of science and engineering. The Journal aims to become an international forum for the research and development community to publish articles of the highest quality in all science and engineering disciplines. We invite you to submit your work to the Journal. Papers relating directly or indirectly to all aspects of these fields are also welcome to submit. JASAE intended to provide a forum for expressing new ideas and a place to expound on these areas of knowledge that can further understand science and Engineering issues and concerns.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 43 Documents
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Design and Implementation of a Smart Automated Chess Board thabet, Abdelrahman; Prasetyo, Judhi
Journal of Applied Science and Advanced Engineering Vol. 3 No. 2 (2025): JASAE: September 2025
Publisher : Master Program in Mechanical Engineering, Gunadarma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59097/jasae.v3i2.52

Abstract

This research presents the design and implementation of an innovative automated chessboard. The system autonomously moves chess pieces using a CoreXY motion system with an electromagnet end-effector, while real-time move detection is achieved through Hall Effect sensors. Powered by the Robot Operating System (ROS) on a Raspberry Pi running a competent chess engine, the board allows users to play against an intelligent opponent with varying difficulty levels. This project bridges the gap between traditional and digital chess, offering an innovative and interactive platform for entertainment and education.
Optimizing ICT Infrastructure for Enhanced Agricultural Productivity in Lampung Province, Indonesia: Challenges and Opportunities Muhida, Riza
Journal of Applied Science and Advanced Engineering Vol. 3 No. 2 (2025): JASAE: September 2025
Publisher : Master Program in Mechanical Engineering, Gunadarma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59097/jasae.v3i2.57

Abstract

Lampung Province, one of Indonesia's key agrarian regions, plays a critical role in national food security. However, the agricultural sector faces significant challenges, including low productivity, resource inefficiency, and the adverse effects of climate change. The integration of Information and Communication Technology (ICT), such as the Internet of Things (IoT), precision agriculture, and big data analytics, offers innovative solutions to these challenges. This paper explores the potential of ICT to enhance agricultural productivity in Lampung Province by analyzing case studies from Indonesia and globally. The study identifies key challenges, including limited internet infrastructure, low digital literacy among farmers, high technology costs, and insufficient technical support. Strategic recommendations are proposed, such as strengthening ICT infrastructure in rural areas, providing subsidies and incentives for farmers, increasing digital literacy through training programs, and developing IoT-based pilot projects. The findings highlight the importance of ICT in modernizing agriculture, improving farmers' welfare, and ensuring sustainable development. By addressing these challenges and leveraging ICT, Lampung Province can transform its agricultural sector, contributing to both regional and national food security
Measurement of Benzo [a]pyrene concentration in motor vehicle emissions using STM32F103-based TGS822 sensor Hawa, Anjani Anil; Wardoyo, Arinto Yudi Ponco; Anggraeni, Dewi; A, Renetha Salma Myesha; Efendi, Yahya
Journal of Applied Science and Advanced Engineering Vol. 3 No. 2 (2025): JASAE: September 2025
Publisher : Master Program in Mechanical Engineering, Gunadarma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59097/jasae.v3i2.59

Abstract

Benzo[a]pyrene is one of the PAHs (Polycyclic Aromatic Hydrocarbons) pollutants originating from incomplete combustion or pyrolysis of organic materials. Benzo[a]pyrene is classified in GRUB 1 materials that have a carcinogenic impact on humans. Benzo [a]pyrene sources can be found in air, surface water, and soil. Benzo[a]pyrene can be sourced from motor vehicle emissions as a pollutant in the air. The incomplete combustion of fossil fuels used as motor vehicle fuel can be a source of Benzo[a]pyrene in the air. Therefore, research is needed to quantify the Benzo[a]pyrene concentration. This study aims to measure the concentration of Benzo[a]pyrene gas produced from motor vehicle emissions. The vehicle to be measured is two-wheeled vehicles with pertalite fuel. Vehicle smoke flows into the collection chamber through a hose with three different injection time durations. The measurement was conducted using a system based on the calibrated sensor of TG822. The average total concentration of B [a] P in the chamber depends on the injection time. The concentration is 63.572 ppb for 20s, 64.822 ppb for t40s, and 95.284 ppb for 60s.
Performance Optimization of Battery Balancing System Based on Multiwinding Transformer and Single Inductor with Fuzzy Logic Control Method Yusiran, Yusiran; Leksono, Edi; Haq, Irsyad Nashirul; Ayumurti, Andini Jinggan
Journal of Applied Science and Advanced Engineering Vol. 3 No. 2 (2025): JASAE: September 2025
Publisher : Master Program in Mechanical Engineering, Gunadarma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59097/jasae.v3i2.60

Abstract

In this study, a modular battery balancing topology based on a single inductor and multi-winding transformer is proposed. In particular, the voltage equalization topology based on this modular balancer consists of cell-level equalization based on a multi-winding transformer and module-level equalization based on a single inductor. A control algorithm based on fuzzy logic (FLC) is applied to the module-level balancer with the difference between the module voltage and the module average voltage being used as the input variable and the duty cycle as the output variable. Meanwhile, the cell-level equalization utilizes a fixed duty cycle (FDC) control mechanism. The balancing process between cell and module level is done alternately so that this control method can be used on non-uniform transformers. The balancing model and FLC design was created in Matlab/Simulink 2021a and experiments using 4 cells LG HG2 18560 3000 mAh battery were carried out to verify the performance of the balancing system. The experimental results show that the FLC method can save the balancing time between modules by 31.26% compared to the FDC method. Furthermore, the proposed control system is proven to optimize the energy transfer which can reach zero voltage gap (ZVG) below 5 mV with a relatively high efficiency around 86.95%..
Spatial Mapping Based on The Settlement Carrying Capacity Value in Banjarmasin Utara Sub District, Indonesia Hadi, Inu Kencana; Efendi, Muhammad; Kumalawati, Rosalina; Pamuja, Indra Agung; Riduan, M.; Ramadhani, M. Ilham
Journal of Applied Science and Advanced Engineering Vol. 3 No. 2 (2025): JASAE: September 2025
Publisher : Master Program in Mechanical Engineering, Gunadarma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59097/jasae.v3i2.62

Abstract

Land Capability Unit refers to the process of evaluating the suitability and performance of land for specific purpose. In this context, it involves the assessment of land to determine the carrying capacity for residential land in the North Banjarmasin Sub-district. There are many potentials that can be used as attractions for residents outside the city of Banjarmasin to the study area, such as trade and service activities, education, and even health, which can have an impact on increasing the population. The increase in population is directly proportional to the increase in the need for residential. This study aims to analyze the carrying capacity of residential land in North Banjarmasin Sub-district. The results of the study showed that all villages in the study area had a DDPm value > 1, which indicates that the carrying capacity of residential land is relatively high. This value is an indicator that the area has the capacity for residents to settle.
Dynamic Force Analysis of Single Acting Compressor Based on Angular Velocity Hartono, Budi; Sutoyo, Edy; Sutisna, Satya Permana; Al-Kindi, Hablinur; Suhada, Rohman
Journal of Applied Science and Advanced Engineering Vol. 3 No. 2 (2025): JASAE: September 2025
Publisher : Master Program in Mechanical Engineering, Gunadarma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59097/jasae.v3i2.65

Abstract

This paper presents a dynamic force analysis of a single-action piston compressor operating at various crankshaft angular velocities. The analysis was performed using Scilab and CADCAM software tools to evaluate the inertia forces acting on the crankshaft, connecting rod, and piston head. At a crankshaft speed of 1500 rpm, the inertia force on the crankshaft was calculated as 0.03 N, increasing to 0.055 N at 2000 rpm and 0.066 N at 2200 rpm. For the connecting rod, the corresponding forces were 17.51 N, 31.12 N, and 37.66 N, respectively. At the piston head, the inertia force rose from 0.063 N at 1500 rpm to 0.11 N at 2000 rpm, and 0.14 N at 2200 rpm. The results indicate that variatioins in angular velocity significantly affect the magnitude of dynamic forces within the compressor components.
Application-based Simulations to Understand the Management Concepts of Electrical Load-shedding: A Case Study of the Electricity System on Offshore Platforms Goeritno, Arief; Syamsudin, Tangtang; Azama, Irham Muhammad; Waluyo, Roy; Fitriani, Fitriani
Journal of Applied Science and Advanced Engineering Vol. 4 No. 1 (2026): JASAE: March 2026
Publisher : Master Program in Mechanical Engineering, Gunadarma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59097/jasae.v4i1.69

Abstract

This article describes the management concepts of electrical load-shedding in the electricity system of the offshore platforms environments for drilling to produce gases and oils. Stable and efficient electrical systems are essential for offshore platforms to ensure safety, productivity, and operational continuity. Load-shedding is a critical function that maintains the balance between power generation and demand during contingency events. This study employs an application-based simulation methodology to evaluate management strategies for electrical load-shedding in offshore electricity systems. Eight simulation scenarios assessed various operational conditions, including generator capacity, transformer performance, cable characteristics, and load prioritization. The results identify the feasibility and limitations of each scenario, illustrating the effects of different shedding strategies on power flow distribution, voltage stability, and system losses. The analysis shows that some configurations maintain stability margins, while others result in operational infeasibility due to voltage drops and overloading. The findings emphasize the necessity of structured load prioritization and the integration of automation using programmable logic controller (PLC)-assisted systems to improve system resilience. These results offer practical guidance for offshore operators, supporting enhanced planning and decision-making for reliable load-shedding strategies.
Aerodynamic Performance of the NACA 0012 Airfoil: Lift and Drag Characteristic Across a Range of Angles of Attack Septiawan, Dedy; Yuliaji, Dwi; Waluyo, Roy
Journal of Applied Science and Advanced Engineering Vol. 4 No. 1 (2026): JASAE: March 2026
Publisher : Master Program in Mechanical Engineering, Gunadarma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59097/jasae.v4i1.79

Abstract

The wing is one of the most critical components in an aircraft structure, as it directly contributes to the generation of lift, which enables flight. Without wings, an aircraft would be unable to produce lift or counter aerodynamic drag effectively. This study aims to analyze the lift and drag forces acting on a NACA 0012 airfoil under varying angles of attack and flow velocities. Two approaches were employed: numerical simulations using ANSYS Fluent to investigate airflow patterns and pressure distribution on the upper and lower surfaces of the airfoil, and experimental testing in a wind tunnel to validate and complement the findings. The experiments considered angles of attack of 0°, 3°, 6°, and 9°, with freestream velocities of 1 m/s and 3 m/s. The quantitative data collected include lift coefficient (CL), drag coefficient (CD), the relationships between CL–α, CD–α, and CL–CD, as well as pressure and velocity distributions from the CFD simulations. Both computational and experimental results indicate that increasing the angle of attack produces a significant change in the lift and drag characteristics of the airfoil. In conclusion, variations in the angle of attack have a substantial impact on the aerodynamic flow behavior around the airfoil and on the magnitude of the resulting lift and drag forces.
Analysis Of Prediction Of Electrical Power Use Outside Peak Load Of Apartment Building X Using The Long Short Term Memory (LSTM) Method Nazara, Meiman Zaro; Rofii, Ahmad; Muliadi, Jemie
Journal of Applied Science and Advanced Engineering Vol. 4 No. 1 (2026): JASAE: March 2026
Publisher : Master Program in Mechanical Engineering, Gunadarma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59097/jasae.v4i1.80

Abstract

Energy efficiency in residential high-rise buildings has become a critical issue in modern power management, particularly during off-peak periods (LWBP), which contribute significantly to daily electricity consumption. However, most existing studies have primarily focused on peak load forecasting, leaving limited exploration of electricity usage during off-peak hours. This study proposes a daily electricity consumption forecasting model for the off-peak period using the Long Short-Term Memory (LSTM) architecture, designed to capture long-term dependencies in time-series data. The dataset consists of one year of historical daily electricity consumption records from Apartment X. Data preprocessing included Min-Max normalization, time windowing, and partitioning into 80% training and 20% testing sets. Hyperparameter optimization was performed using Optuna, while model performance was evaluated using RMSE, MAE, MSE, and R² metrics. Experimental results demonstrate that the LSTM model effectively captured the temporal patterns of LWBP electricity consumption, achieving RMSE = 0.140, MAE = 0.109, MSE = 0.020, and R² = 0.537. These findings highlight the potential of LSTM as a decision-support tool for building energy management systems, enabling optimization of electricity usage during non-peak hours. Furthermore, this work provides opportunities for future research by integrating hybrid deep learning architectures (e.g., CNN-LSTM or Bi-LSTM) and incorporating external factors such as temperature, weather conditions, and occupant behavior to improve predictive accuracy in real-world applications.
Prediction of Peak Load Electricity Consumption in Apartment X Building Using Deep Learning with GRU Method Yusuf, Yusuf; Rofii, Ahmad; Muliadi, Jemie
Journal of Applied Science and Advanced Engineering Vol. 4 No. 1 (2026): JASAE: March 2026
Publisher : Master Program in Mechanical Engineering, Gunadarma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59097/jasae.v4i1.81

Abstract

This study presents a predictive framework for daily electricity consumption forecasting in Apartment X using a Recurrent Neural Network (RNN) model with the Gated Recurrent Unit (GRU) method. The dataset consists of daily electricity log sheets containing two main variables: Peak Load Time (WBP) and Off-Peak Load Time (LWBP). The preprocessing stage includes data cleaning, normalization using Min–Max Scaling, and sequence formation through a sliding window approach. The GRU architecture comprises two hidden layers, a dropout layer, and optimization using the Adam optimizer. The model’s performance was evaluated using MAE, RMSE, and R². The results show that the GRU model achieved an R² value of 0.623, indicating a good capability in capturing consumption patterns. This study contributes to energy forecasting studies in developing countries, emphasizing smart building energy management applications

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