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Short Circuit Analysis on Distribution Network 20 kV Using Etap Software Arizaldi, Afif; Salahuddin, S; Muhammad, M; Jain, Vishal; Pandey, Govinda Prashad; Watane, Manoj Jagannathrao
Journal of Renewable Energy, Electrical, and Computer Engineering Vol 1, No 2 (2021): September 2021
Publisher : Institute for Research and Community Service, Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v1i2.5232

In an electric power system, electricity is generated by the power plant and then channeled to a transmission line and then distributed to consumers, in the process of distributing electrical energy, the system does not always work in normal conditions, sometimes the system can experience disturbances such as one-phase, two-phase, and three-phase disturbances. This interference can disrupt the electrical system and can damage equipment if left unchecked, therefore it is necessary to install a protection device that can decide the interference so as not to damage other equipment when a disturbance occurs. Here the protection device used is a circuit breaker. In a fault condition, the circuit breaker must be able to separate the points of the fault so as not to damage other electrical equipment. In this case, to determine the capacity of the best protection device for the system, a short circuit fault simulation is performed. To simplify the calculation process here the author uses the help of ETAP software (Electrical Transient Analysis Program).

Hydrolysis of coffee pulp as raw material for bioethanol production: sulfuric acid variations Mawaddah, Mawaddah; Setiawan, Adi; Zulnazri, Zulnazri; Putri, Almia Permata; Khan, Naseer A.; Jain, Vishal
Journal of Renewable Energy, Electrical, and Computer Engineering Vol 2, No 1 (2022): March 2022
Publisher : Institute for Research and Community Service, Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v2i1.6382

Indonesia has enormous biomass resources due to its land territory is mostly surrounded by forests and agricultural area. One of the main agricultural commodities is Gayo Arabica coffee. Coffee agro-residue such as coffee-pulp contains glucose, organic matter, protein, nitrogen and high minerals. Therefore, coffee pulp can be a potential raw material for bioethanol production. In order to develop an effective technology for bioethanol production from coffee-pulp, it is necessary to investigate in early the way of glucose can be effectively prepared. In this preliminary investigation, glucose products ware prepared using two methods, i.e. method-I under several main-stages including extraction, delignification, and hydrolysis. While, under method-II, the sample was directly hydrolyzed at 100Â°C for 4 h. Under both methods, hydrolysis process to get glucose was performed by adding sulfuric acid (H2SO4) at various concentrations (8 wt.%, 10 wt.% and 12 wt.%). Based on analysis results, the highest glucose level, i.e. 17 % was obtained from method-II by adding 8 wt.% sulfuric acid. The less the amount of sulfuric acid added, the higher the glucose level produced. No difference in pH was found from both methods. The color of glucose produced under method-I is clearer compared to those prepared under method-II.

Policy and decision making in education during the Covid-19 Pandemic: A Case Study Sumantri, Pulung; Hasudungan, Anju Nofarof; Jain, Vishal; Mursalin, M
International Journal for Educational and Vocational Studies Vol. 4 No. 3 (2022)
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/ijevs.v0i0.5935

This study aims to describe the educational policies issued by the Ministry of Education, Culture, Research and Technology and the decisions taken by Senior High School 1 Rupat (SMAN 1 Rupat) as an effort to continue education during the Covid-19 pandemic. The research method used is descriptive qualitative research method with a case study approach. Data was collected by means of literature study, interviews, documents and observations. Data analysis was carried out by adopting an interactive model from Miles and Huberman. The results of the study show that flexibility is the goal of the issuance of policies and decisions taken by the government and schools with the aim of maintaining student safety from Covid-19 and minimizing the impact of learning loss. The challenge in the future is to find a model of resilience that can be maximized to restore Indonesian education.

Cotton Disease Prediction Using Deep Transfer Learning: Comparative Analysis of Resnet50, VGG16 and Inceptionv3 Models Gupta, Sandeep; Hamid, Abu Bakar Abdul; Nyamasvisva, Tadiwa Elisha; Jain, Vishal; Tyagi, Nitin; Mun, NG Khai; Ather, Danish
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.1116

Cotton is among the most critical crops in the world textile industry, but it is highly susceptible to a vast array of infections that have a tremendous impact on output and fiber quality. Traditional cotton disease diagnosis is mostly based on manual inspection by farmers and experts and is time consuming, labor intensive and inaccurate due to similarity of symptoms. The high rate at which artificial intelligence, especially computer vision and deep learning (DL), have advanced has provided effective alternatives to auto-detecting plant diseases. As a subdivision of the DL approach, transfer learning allows adapting existing convolutional neural networks to the agricultural domain using smaller datasets to guarantee higher performance. This work introduces comparative analysis of three popular deep transfer learning (DTL) models ResNet50, VGG16, and InceptionV3 that are used in the classification of cotton leaf diseases. The training, validation, and testing were performed on a dataset of 1,991 labelled images that included four categories of normal and diseased cotton leaves and plants. All models were optimized and assessed with standard measures, such as validation and test accuracy. The experimental results show that InceptionV3 had the highest accuracy of 95.28, VGG16 had 85.85, and ResNet50 had the lowest accuracy of 69.81. The high accuracy of InceptionV3 is also a testament to its ability in the extraction of multi-scale features, and the trade-off between accuracy and computational efficiency. The results affirm the feasibility of DTL frameworks to revolutionize precision agriculture by facilitating diagnosis of cotton diseases in a timely and reliable manner. This development can help in ensuring that farming activities are sustainable, pesticides are used efficiently and the economy does not suffer economic losses and helps in ensuring that productivity and environmental protection are maintained in cotton farming.

Short Circuit Analysis on Distribution Network 20 kV Using Etap Software Arizaldi, Afif; Salahuddin, S; Muhammad, M; Jain, Vishal; Pandey, Govinda Prashad; Watane, Manoj Jagannathrao
Journal of Renewable Energy, Electrical, and Computer Engineering Vol. 1 No. 2 (2021): September 2021
Publisher : Institute for Research and Community Service (LPPM), Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v1i2.5232

In an electric power system, electricity is generated by the power plant and then channeled to a transmission line and then distributed to consumers, in the process of distributing electrical energy, the system does not always work in normal conditions, sometimes the system can experience disturbances such as one-phase, two-phase, and three-phase disturbances. This interference can disrupt the electrical system and can damage equipment if left unchecked, therefore it is necessary to install a protection device that can decide the interference so as not to damage other equipment when a disturbance occurs. Here the protection device used is a circuit breaker. In a fault condition, the circuit breaker must be able to separate the points of the fault so as not to damage other electrical equipment. In this case, to determine the capacity of the best protection device for the system, a short circuit fault simulation is performed. To simplify the calculation process here the author uses the help of ETAP software (Electrical Transient Analysis Program).

Hydrolysis of coffee pulp as raw material for bioethanol production: sulfuric acid variations Mawaddah, Mawaddah; Setiawan, Adi; Zulnazri, Zulnazri; Putri, Almia Permata; Khan, Naseer A.; Jain, Vishal
Journal of Renewable Energy, Electrical, and Computer Engineering Vol. 2 No. 1 (2022): March 2022
Publisher : Institute for Research and Community Service (LPPM), Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v2i1.6382

Indonesia has enormous biomass resources due to its land territory is mostly surrounded by forests and agricultural area. One of the main agricultural commodities is Gayo Arabica coffee. Coffee agro-residue such as coffee-pulp contains glucose, organic matter, protein, nitrogen and high minerals. Therefore, coffee pulp can be a potential raw material for bioethanol production. In order to develop an effective technology for bioethanol production from coffee-pulp, it is necessary to investigate in early the way of glucose can be effectively prepared. In this preliminary investigation, glucose products ware prepared using two methods, i.e. method-I under several main-stages including extraction, delignification, and hydrolysis. While, under method-II, the sample was directly hydrolyzed at 100°C for 4 h. Under both methods, hydrolysis process to get glucose was performed by adding sulfuric acid (H2SO4) at various concentrations (8 wt.%, 10 wt.% and 12 wt.%). Based on analysis results, the highest glucose level, i.e. 17 % was obtained from method-II by adding 8 wt.% sulfuric acid. The less the amount of sulfuric acid added, the higher the glucose level produced. No difference in pH was found from both methods. The color of glucose produced under method-I is clearer compared to those prepared under method-II.

Electromechanical Devices of Adaptive and Control-Tracking Systems G.S., Kerimzade; Jain, Vishal; Mahjabeen, Farhana; Ahmad, Munir; Patil, Dipak P.; Garba, Auwal; Mahajan, Vinod Shantaram
Journal of Renewable Energy, Electrical, and Computer Engineering Vol. 3 No. 2 (2023): September 2023
Publisher : Institute for Research and Community Service (LPPM), Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v3i2.11537

In the presented work, some characteristics of devices of adaptive and control-tracking control systems are considered. The characteristic features of angle sensors, methods of converting analog signals with high accuracy (for example, sine-cosine transformers) occupies a leading position among the development and research of tracking systems. The modern electronic element base opens up new possibilities - the creation of tracking digital angle converters (TDAC) using the principles of digital tracking and adaptive control in them. Stability, efficiency, load form determines the reliability, accuracy, economy, service life of electromechanical automation devices, test equipment, etc. Determining the characteristics, establishing analytical relationships between the initial data and output parameters is one of the stages of the algorithm for solving the problems of designing equipment parameters for monitoring and tracking control systems, which in turn contributes to the development of a mathematical model from a system of equations, the joint solution of which allows you to establish analytical relationships between the initial data and settings.

Enhanced Agricultural Decision-Making: Machine Learning Approaches for Crop Prediction and Analysis in India Gupta, Sandeep; Hamid, Abu Bakar Abdul; Nyamasvisva, Tadiwa Elisha; Tyagi, Nitin; Jain, Vishal; Mun, Ng Khai; Ather, Danish
JOIN (Jurnal Online Informatika) Vol 10 No 2 (2025)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v10i2.1610

This paper addresses the critical aspects of agriculture in the Indian economy and the challenges faced by this sector, including soil quality decline, unpredictable weather, and the need for efficient decision-making. It presents machine learning as a transformative approach for improved agricultural decision-making, enabling enhanced crop prediction and productivity. Machine learning (ML) algorithms are shown to effectively analyze vast datasets to generate predictive models that aid in crop selection optimization, disease outbreak prediction, and market fluctuation anticipation, thus leading to increased yields and profitability. Focusing on crop prediction, the paper discusses models leveraging historical data and advanced algorithms to forecast crop yields. Additionally, the application of machine learning in precision farming, such as optimizing fertilizer application, is explored. The paper uses a mixed-method approach on a dataset encompassing various crops and environmental parameters. In this paper the various techniques such as K-Nearest Neighbor (KNN), Support Vector Machines (SVM), Decision Tree (DT) and Random Forest (RF) algorithms have been employed to demonstrate the utility of ML in the agricultural fields. The KNN at the value of K=4 and SVM with polynomial kernel resulted the accuracy of 0.982 and 0.989 respectively. Whereas DT and RT gave the results in terms of accuracy of 0.987 and 0.970 respectively. Overall, it can be said that all these techniques used in the present work showed the better accuracy for agricultural sustainability.

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