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INDONESIA
Journal of Computer Science and Engineering (JCSE)
Published by Institute of Computer Science and Engineering
ISSN : -     EISSN : 27210251     DOI : https://doi.org/10.36596/jcse
Core Subject : Science,
Computer Science & IT
Computer Architecture, Processor design, operating systems, high-performance computing, parallel processing, computer networks, embedded systems, theory of computation, design and analysis of algorithms, data structures and database systems, theory of computation, design and analysis of algorithms, data structures and database systems, artificial intelligence, machine learning, data science, Information System
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 2, No 2: August (2021)" : 5 Documents clear
IoT Based Novel Smart Blind Guidance System khera, Yashvi; Whig, Pawan
Journal of Computer Science and Engineering (JCSE) Vol 2, No 2: August (2021)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jcse.v2i2.172

Abstract

In this research paper the system which is proposed that can be used for safe walking for blinds. This system consist of wireless sensor within the stick which provide the information of the obstacle between the way. The main advantage of this system is the safe for the blind people walking on the road, and make them independent while walking. When obstacle is detected an alert will be given to user with the help of buzzer an vibration . The unique feature of the system is to detect the temperature of a person who passes within the range of 6 feet of which helps in maintaining the social distancing in COVID situation. The system contains a wireless sensor that integrates temporary networks that can be made within the navigation stick, which can provide group communication between them, where roaming information and networks can be provided. With the help of IOT the location and alert message shared with family members in case of emergency. The system proposed in this research study is 60% more efficient then conventional system. The information is included in table1 to validate  the result.
Pemanfaatan Teknologi Digital Wallet Sebagai Solusi Alternatif Pembayaran Modern: Literature Review Fadhilah, Jihan; Layyinna, Cut Aja Anis; Khatami, Rijal; Fitroh, Fitroh
Journal of Computer Science and Engineering (JCSE) Vol 2, No 2: August (2021)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jcse.v2i2.219

Abstract

Abstract: Financial technology innovation in the form of digital wallets is very interesting to the public. The efficiency offered from this payment system makes people start to switch from conventional payments to digital payments. In addition, many other factors influence multi-generational people using digital wallets as an alternative to their daily payments. The use of digital wallets is currently widely applied to online transportation transactions, purchases in e-commerce, to food and beverage delivery services. The method used in this study is a method of literature study with the goals to find out the development of digital wallet usage in the community from various journals sourced from Scopus and several websites that have been analyzed and processed by researchers into a literature review study. From the results obtained, it can be concluded that from year to year there is an increase in the number of digital wallet users, especially in Indonesia. Moreover after the Covid-19 pandemic, the number of digital wallet users is increasing because people have to avoid physical contact so that more transactions with digitally.Abstrak: Inovasi teknologi keuangan berupa digital wallet sangat manarik perhatian masyarakat. Efisiensi yang ditawarkan dari sistem pembayaran ini membuat masyarakat mulai beralih dari pembayaran konvensional ke pembayaran digital. Selain itu banyak faktor lain yang mempengaruhi para multi generasi menggunakan digital wallet sebagai alternatif pembayaran sehari-hari mereka. Penggunaan digital wallet saat ini banyak diterapkan untuk transaksi transportasi online, pembelian di e-commerce, hingga jasa pesan antar makanan dan minuman. Metode yang digunakan pada penelitian ini yaitu metode studi literatur dengan tujuan untuk mengetahui perkembangan penggunaan digital wallet di masyarakat dari berbagai jurnal yang bersumber dari Scopus dan beberapa website yang telah dianalisis dan diolah peneliti menjadi sebuah kajian literature review. Dari hasil yang didapatkan dapat disimpulkan bahwa dari tahun ke tahun terjadi peningkatan jumlah pengguna digital wallet, khususnya di Indonesia. Apalagi setelah pandemi Covid-19, jumlah pengguna digital wallet semakin meningkat karena masyarakat harus menghindari kontak fisik sehingga lebih banyak melakukan transaksi secara digital.
Punjabi Text Recognition System for Portable Devices: A Comparative Performance Analysis of Cloud Vision API with Tesseract Kaur, Ravneet; Sharma, Dharam Veer
Journal of Computer Science and Engineering (JCSE) Vol 2, No 2: August (2021)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jcse.v2i2.195

Abstract

The increasing availability of high performance, low priced, portable digital imaging devices has created an opportunity for on demand analysis of documents. In this paper, Punjabi Text Recognition System is developed for portable devices using two different approaches that is Google’s Cloud Vision APIs and LSTM based Tesseract OCR Engine. The performance of developed mobile based systems is compared in term of runtime and recognition accuracy. Both Vision API and LSTM based OCR engine provides good results for Roman Based Scripts. Particularly for Gurmukhi text document images, Cloud Vision API recognizes Punjabi with good accuracy as compared to Tesseract. We presented a detailed comparison and computed the character and word level accuracy of both the systems for same set of images.
Analysis of Tomato Leaf Disease Identification Techniques Chopra, Gaurav; Whig, Pawan
Journal of Computer Science and Engineering (JCSE) Vol 2, No 2: August (2021)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jcse.v2i2.171

Abstract

India loses thousands of metric tons of tomato crop every year due to pests and diseases. Tomato leaf disease is a major issue that causes significant losses to farmers and possess a threat to the agriculture sector. Understanding how does an algorithm learn to classify different types of tomato leaf disease will help scientist and engineers built accurate models for tomato leaf disease detection. Convolutional neural networks with backpropagation algorithms have achieved great success in diagnosing various plant diseases. However, human benchmarks in diagnosing plant disease have still not been displayed by any computer vision method. Under different conditions, the accuracy of the plant identification system is much lower than expected by algorithms. This study performs analysis on features learned by the backpropagation algorithm and studies the state-of-the-art results achieved by image-based classification methods. The analysis is shown through gradient-based visualization methods. In our analysis, the most descriptive approach to generated attention maps is Grad-CAM. Moreover, it is also shown that using a different learning algorithm than backpropagation is also possible to achieve comparable accuracy to that of deep learning models. Hence, state-of-the-art results might show that Convolutional Neural Network achieves human comparable accuracy in tomato leaf disease classification through supervised learning. But, both genetic algorithms and semi-supervised models hold the potential to built precise systems for tomato leaf detection.
A one step further approach to fraud detection Bagchi, Debjyoti; Mukherjee, Abhishek; Pal, Sarannak
Journal of Computer Science and Engineering (JCSE) Vol 2, No 2: August (2021)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jcse.v2i2.250

Abstract

This paper will discuss about the different approaches to fraud detection such as Data mining, machine learning and artificial intelligence and statistical data analysis. Then we list some of the technical and troublesome challenges to modern fraud detection techniques. A comparison study of these techniques is also done according to the metrics like precision, False Alarm Rate (FAR), Accuracy, Cost, True Positive Rate (TPR) against different categories of frauds such as internal bank fraud, credit card fraud, loan fraud. Finally, we discuss the disadvantages of the existing fraud detection systems and we attempt to recommend a specific technique or algorithm for detecting a specific type of fraud with their advantages and disadvantages.

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