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Andi Adriansyah
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Journal of Integrated and Advanced Engineering (JIAE)
Published by Asosiasi Staf Akademik Perguruan Tinggi Seluruh Indonesia
ISSN : 2774602X     EISSN : 27746038     DOI : https://dx.doi.org/10.51662/jiae
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering
Journal of Integrated and Advanced Engineering JIAE adalah jurnal ilmiah peer-review yang menerima makalah penelitian yang terkait erat dengan bidang Teknik, seperti Mekanik, Listrik, Industri, Sipil, Kimia, Material, Fisik, Komputer, Informatika, Lingkungan dan Arsitektur.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 59 Documents
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Analysis of Plant Growth and Gallic Acid Content for Cavendish Banana (Musa acuminata) Shoot Culture with Bubble Column Bioreactor Nunung Nurhayati; Rizkita Rachmi Esyanti; Khalilan Lambangsari
Journal of Integrated and Advanced Engineering (JIAE) Vol 2, No 1 (2022)
Publisher : Asosiasi Staf Akademik Perguruan Tinggi Seluruh Indonesia (ASASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51662/jiae.v2i1.37

Abstract

Cavendish banana (Musa acuminata) is one of the most important fruits in the world. Cavendish shoots tissue culture using bubble column bioreactor can be a solution to produce high yielding plantlet and gallic acid due to the aeration with minimum shear stress. In this study, the average growth rate, presence of gallic acid, and antioxidant activity (IC50) in the bubble column bioreactor (200 mL capacity) with the aeration rates of 1 mL/s and 2 mL/s using Murashige & Skoog half-strength liquid medium supplemented with 0.5 ppm gibberellic acid will be analyzed. The aeration system used was atmospheric air. The leaves and stems were extracted by maceration using 96% ethanol solvent (1:10 (w/v)). A qualitative phenolic test with FeCl3, thin layer chromatography, and antioxidant test with 2,2-diphenyl-1-picrylhydrazyl was carried out. The average growth rate in the bioreactor were 0.22 ± 0.001 g/day (1 mL/s) and 0.21 ± 0.001 g/day (2 mL/s). All the leaf and stem extracts showed positive results for the phenolic test, but the presence of gallic acid could not be detected clearly by thin-layer chromatography. The IC50 values in aeration rates of 1 mL/s and 2 mL/s of the leaves were 41.35 and 79.54 μg/mL, respectively, while the stems were 51.87 and 104.94 μg/mL, respectively. It could be concluded that the growth of the banana plantlet and the production of antioxidants in the bubble column bioreactor was higher in aeration rate of 1 mL/s than 2 mL/s.
Detection of Road Cracks Using Convolutional Neural Networks and Threshold Segmentation Arselan Ashraf; Ali Sophian; Amir Akramin Shafie; Teddy Surya Gunawan; Norfarah Nadia Ismail; Ali Aryo Bawono
Journal of Integrated and Advanced Engineering (JIAE) Vol 2, No 2 (2022)
Publisher : Asosiasi Staf Akademik Perguruan Tinggi Seluruh Indonesia (ASASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51662/jiae.v2i2.82

Abstract

Automatic road crack detection is an important transportation maintenance responsibility for ensuring driving comfort and safety. Manual inspection is considered to be a risky method because it is time consuming, costly, and dangerous for the inspectors. Automated road crack detecting techniques have been extensively researched and developed in order to overcome this issue. Despite the difficulties, most of the proposed methodologies and solutions involve machine vision and machine learning, which have lately acquired traction largely due to the increasingly more affordable processing power. Nonetheless, it remains a difficult task due to the inhomogeneity of crack intensity and the intricacy of the background.  In this paper, a convolutional neural network-based method for crack detection is proposed. The method is inspired from recent advancements in applying machine learning to computer vision. The primary goal of this work is to employ convolutional neural networks to detect the road crack. Data in the form of images has been used as input, preprocessing and threshold segmentation is applied to the input data. The processed output is feed to CNN for feature extraction and classification. The training accuracy was found to be 96.20 %, the validation accuracy to be 96.50 %, and the testing accuracy to be 94.5 %.
Effect of Alkaline 5% NaOH treatment with variations of immersion time on tensile strength and flexural strength of Betung bamboo internode Zulhanif Zulhanif; Firlli Abim Mahtata; Mohammad Badaruddin
Journal of Integrated and Advanced Engineering (JIAE) Vol 2, No 2 (2022)
Publisher : Asosiasi Staf Akademik Perguruan Tinggi Seluruh Indonesia (ASASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51662/jiae.v2i2.43

Abstract

Betung bamboo has a bigger stem diameter, thicker walls, and shorter internodes than other species of bamboo, making it ideal for building materials such as bridges and interior furnishings that may also be turned into works of art. Alkaline NaOH treatment was introduced to Betung bamboo to increase its mechanical properties. The alkaline treatment used a solution consisting of 5 %NaOH. Specimens with alkaline treatment were immersed into 5%NaOH solution for one hour, two hours, and three hours, followed by two hours of drying in a furnace at 60 °C. Tensile tests (ASTM D638) and flexural tests (ASTM D790) were carried out using servo hydraulics MTS Landmark 100 kN under static loading. The tensile strength, modulus of rupture (MOR) and modulus of elasticity (MOE) were analyzed from the results tests. The average maximum tensile strength of the Betung bamboo internode immersed for two hours into 5%NaOH solution is about 195.95 MPa, whereas the average values of MOR and MOE are about 207.35 MPa and 4.56 GPa, respectively. The faults and surface conditions in the Betung bamboo internode were observed using fractographic and morphological observations.
Design & Fabrication of Automatic Color & Weight-Based Sorting System on Conveyor Belt Tasnuva Jahan Nuva; Md. Imteaz Ahmed; Sarker Safat Mahmud
Journal of Integrated and Advanced Engineering (JIAE) Vol 2, No 2 (2022)
Publisher : Asosiasi Staf Akademik Perguruan Tinggi Seluruh Indonesia (ASASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51662/jiae.v2i2.87

Abstract

Object sorting is a basic process that is employed in a variety of disciplines in our daily lives for our convenience. Previously, the sorting operation was done by hand using labor justification. Because product quality does not remain consistent during the typical sorting process, it adds complexity to the segregation of products based on their height, color, size, and weight. This method is also time-consuming and slows down output. To overcome these problems, Low-Cost Automation (LCA) has been implemented in the sorting system, which aims to reduce production time, labor cost, and processing complexity, improve product quality, increase production rate, etc. So, in this project, an effective method has been developed for automatically sorting the object based on color and weight. This method uses a conveyor belt, strain gauge load cell, DC motor, servo motor, TCS 34725 RGB color sensor, LCD, LED, and LDR to identify, separate, and collect the objects according to their color and weight. Arduino is used to controlling all the processes. This work has sorted three types of colors -red, , green, and blue, and the weight of different ranges. Firstly, the weights have been sorted by load cell, and then the desired colors have been sorted by color sensor. A bucket at the end of the conveyor belt can be rotated depending on the signal sent from the Arduino to collect the box. The collecting box has a specific portion in a particular color. Hence, it could be rotated at a specific angle for an exact weight for red, blue, and green colors. 
Hydrodynamic study of drying on Qisthi Hindi using a Fluidized Bed Dryer Nanang Ruhyat; Haris Ilman Fiqih; Jessi Ray Mardhatilla; Firman Maulana; Fajar Anggara; Dewi Murniati
Journal of Integrated and Advanced Engineering (JIAE) Vol 2, No 2 (2022)
Publisher : Asosiasi Staf Akademik Perguruan Tinggi Seluruh Indonesia (ASASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51662/jiae.v2i2.67

Abstract

A Fluidized Bed Dryer (FBD) is one of the most efficient and prominent moisture-reducing dryers in the food, chemical, and pharmaceutical industries. This work investigates changes in moisture content and drying rate in the FBD with a dense bed as a perforated plate and uses an indirect heating medium. Here the air flows by the blower and acts as a dryer after passing through the heater to reduce the moisture content contained in the material. Qisthi Hindi can be used as herbal medicine for several diseases such as asthma, cough, diabetes, and liver and stomach problems. It can even be consumed during the COVID-19 pandemic. The Qisthi Hindi root has a fairly high calcium and protein content, so drying must be carried out at moderate temperatures because it is a heat-sensitive material. Drying using FBD is carried out at temperatures ranging from 50-100 °C. On air drying at 50 °C, the protein content increased by 3.13%, calcium content increased by 29% from the levels before drying, and water content decreased by 5.3%. At the drying air temperature of 100 °C, the protein content decreased to 3.87%, and the calcium content decreased by 15% from drying at 50 °C. FBD reduced the moisture content significantly in Qisthi Hindi, which is heat sensitive. 
Chatbot System for Mental Health in Bahasa Malaysia Muhammad Imran Ismael; Nik Nur Wahidah Nik Hashim; Nur Syahirah Mohd Shah; Nur Syuhada Mohd Munir
Journal of Integrated and Advanced Engineering (JIAE) Vol 2, No 2 (2022)
Publisher : Asosiasi Staf Akademik Perguruan Tinggi Seluruh Indonesia (ASASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51662/jiae.v2i2.83

Abstract

Chatbot has been the driving force of modern communication for business, customer service and even mental healthcare. At the same time, there are not many research and project regarding mental health chatbots in Bahasa Malaysia. This project focuses on developing a chatbot application for mental healthcare in Bahasa Malaysia. This chatbot system is integrated with artificial intelligence and natural language processing. This chatbot utilize the feedforward neural network model to train the datasets. Apart from the backend of the application, Kivy and KivyMD are used to create the app's graphical user interface.
Generating images for Supervised Hyperspectral Image Classification with Generative Adversarial Nets Hassan Abdalla Abdelkarim Osman; Norsinnira Zainul Azlan
Journal of Integrated and Advanced Engineering (JIAE) Vol 2, No 2 (2022)
Publisher : Asosiasi Staf Akademik Perguruan Tinggi Seluruh Indonesia (ASASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51662/jiae.v2i2.80

Abstract

With the advancement of remote sensing technologies, hyperspectral imagery has garnered significant interest in the remote sensing community. These developments have inspired improvement in various hyperspectral images (HSI) classification applications, such as land cover mapping, amongst other earth observation applications. Deep Neural Networks have revolutionized image classification tasks in areas of computer vision. However, in the domain of hyperspectral images, insufficient training samples have been earmarked as a significant bottleneck for supervised HSI classification. Moreover, acquiring HSI from satellites and other remote sensors is expensive. Thus, researchers have turned to generative models to leverage the existing data to increase training samples, such as particularly generative adversarial networks (GAN). This paper explores the use of a vanilla GAN to generate synthetic data. The network employed in this paper was built using a deep learning python package, PyTorch and tested on a popular HSI dataset called Indian Pines dataset. The network achieved an overall accuracy of 64%. While promising, there is still room for improvement.
Improvement of output voltage from shading interference on solar cell using a reflector system Muhammad Iqbal; Eko Ihsanto; Agab Bakheet Mohammednour
Journal of Integrated and Advanced Engineering (JIAE) Vol 2, No 2 (2022)
Publisher : Asosiasi Staf Akademik Perguruan Tinggi Seluruh Indonesia (ASASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51662/jiae.v2i2.39

Abstract

One of the factors that affect the performance of photovoltaic cells is shading. Shading can reduce the intensity of solar radiation on the cells. This study aims to design a system that can improve the amount of voltage from shading disturbances to optimise the output voltage on the solar cell by using a reflector. The reflector is designed in a flat mirror measuring. It is expected that there will be an increase in the output voltage of the existing solar cell system. The more reflected light that hits the surface of the solar panel and illuminates the shading area, the more significant the increase in output voltage, current and power, and vice versa.
Axis manipulation to solve Inverse Kinematics of Hyper-Redundant Robot in 3D Space Sheldon Ijau Winston; Annisa Jamali
Journal of Integrated and Advanced Engineering (JIAE) Vol 2, No 2 (2022)
Publisher : Asosiasi Staf Akademik Perguruan Tinggi Seluruh Indonesia (ASASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51662/jiae.v2i2.81

Abstract

A solution based on inverse kinematics is required for the robot's end effector, also known as its tip, to reach a target. Current methods for solving the inverse kinematics solution for a hyper-redundant robot in three 3D are generally complex, difficult to visualize, and time-intensive. This requires the development of new algorithms for solving inverse kinematics in a quicker and more efficient manner. In this study, an axis manipulation using a geometrical approach is used. Initially, a general algorithm for a 2 m-link hyper-redundant robot in 3D is generated. The method employed a repetitive basic inverse kinematics solution of a two-link robot on virtual links. The virtual links are generated using a specific geometric proposition. Finally, the 3D solution is generated by rotating about the global z-axis. This method reduces the mathematical complexity required to solve the inverse kinematics solution for a 2-m-link robot. In addition, this method can manage variable link manipulators, thereby eliminating singularity. To demonstrate the effectiveness of the model, numerical simulations of hyper redundant models in 3D are presented. This new geometric approach is anticipated to enhance the performance of hyper-redundant robots, enabling them to be of greater assistance in fields such as medicine, the military, and search and rescue. 
Monitoring chicken livestock process using Vento Application at a farm Firman Andika; Rachmat Muwardi; Mirna Yunita; Mhd Adanan Purba
Journal of Integrated and Advanced Engineering (JIAE) Vol 2, No 2 (2022)
Publisher : Asosiasi Staf Akademik Perguruan Tinggi Seluruh Indonesia (ASASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51662/jiae.v2i2.42

Abstract

Regular temperature monitoring in the poultry industry is necessary to produce high-quality products. However, the traditional methods of these activities are still massively applied. Therefore, a modest process on poultry farms requires temperature monitoring and control. Vento is a climate controller developed by Big Dutchman that is easy to understand and user-friendly. Further, the module provides a handy installation and operation on the farm. Therefore, Vento is suitable to use in hot climates area. Vento performs temperature control by reading the input collected from the DOL114 sensor and the DOL12 sensor. The DOL114 sensor performs temperature and humidity detection in the front area of the cage. At the same time, the DOL12 was installed to obtain temperature information behind the cage. Both functions as input to operate the Heater, but only the DOL114 sensor is used to activate the cooling pad. The temperature value gathered by the DOL114 sensor and the DOL12 sensor will be processed by Vento, resulting in average temperature data. Thus, the data obtained from the sensor will be transferred to the Vento system to operate the output in the form of an exhaust fan. The exhaust fan serves as a tool that removes air and ammonia in the cage so that the cage temperature complies with a predetermined setpoint. 

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