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JAIS (Journal of Applied Intelligent System)
Published by Universitas Dian Nuswantoro
ISSN : 25020493     EISSN : 25029401     DOI : -
Core Subject :
Journal of Applied Intelligent System (JAIS) is published by LPPM Universitas Dian Nuswantoro Semarang in collaboration with CORIS and IndoCEISS, that focuses on research in Intelligent System. Topics of interest include, but are not limited to: Biometric, image processing, computer vision, knowledge discovery in database, information retrieval, computational intelligence, fuzzy logic, signal processing, speech recognition, speech synthesis, natural language processing, data mining, adaptive game AI.
Arjuna Subject : -
Articles 15 Documents
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Search results for , issue "Vol. 8 No. 2 (2023): Journal of Applied Intelligent System" : 15 Documents clear
Compression Run Length Encoding On Watermarking Using a Combination of DCT, DWT and SVD Abdussalam, Abdussalam; Pramudya, Elkaf Rahmawan
Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i2.7524

Abstract

This study focus on identifying medical images by proposing the Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) transformation watermarking technique and prove an increase the quality of watermarked images is good in terms of imperceptibility. Due to reduce the need for data memory compression is applied to the host image, where the compression technique chosen is lossless so that the compressed host image experiences a decrease in file size while maintaining data integrity, to maintain image degradation perceptions and diagnostic quality standards during the watermarking process. Here, we use DWT-DCT-SVD and Run Length Encoding (RLE). A good Peak Signal to Noise Ratio (PSNR) more than 30 dB using over than 200 compression size. The extracted watermark image is quite good with a fairly high PSNR value. The highest compression result size is in 32.2511.
Opinion Mining on Chat GPT based on Twitter Users Nashrulloh, Muhammad Rikza; Julianto, Indri Tri; Muzaky, Rifky Khoerul
Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i2.8399

Abstract

The presence of Chatbots can assist humans in their everyday lives. Chat GPT is one of the commonly used Chatbots that humans rely on to support their work, serve as an assistant, or even create artistic works or writings. The purpose of this research is to investigate opinions regarding the presence of Chat GPT. This Opinion Mining method is conducted by crawling data from Twitter, which can be categorized into three opinions: Positive, Negative, or Neutral. To calculate the accuracy level of the model created, two algorithms, Naïve Bayes and K-Nearest Neighbour, are compared. The model validation process utilizes K-Fold Cross Validation by varying the value of k (k=2, k=4, k=6, k=8, and k=10) and different sampling methods, namely Linear, Shuffled, and Stratified, to obtain optimal accuracy values. The research results indicate that the K-Nearest Neighbour Algorithm achieves the highest accuracy value of 92.40%. Based on this comparison, the K-Nearest Neighbour Algorithm is deemed suitable for modeling Opinion Mining of Chat GPT. The distribution of Twitter users' opinion percentages regarding Chat GPT is as follows: Positive 9.4%, Negative 1.4%, and Neutral 89%. Neutral opinions dominate the results of the conducted Opinion Mining.Keyword : chat GPT, opinion mining, twitter
Measuring User Experience Of Traveloka Hotel Using User Experience Questionnaire Aminurdin, Majid; Maulana, Donny; Wiyatno, Tri Ngudi
Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i2.8608

Abstract

Nowadays, there are many online travel agencies (OTAs) in Indonesia that provide various options for their customers. Before choosing which OTA to use, customers usually check each platform to ensure that they offer the best service. Traveloka is the most preferred OTA app by 67.5% of respondents. Google Play Store reviews show that users are still confused with information such as pricing and proper payment. Some features do not work properly when making hotel reservations. User Experience Questionnaire is used to quickly measure the user experience level of the product. Attractiveness, perspiculty, efficiency, accuracy, stimulation, and novelty were the six UEQ scales used. A random sample of one hundred app users was selected. The results showed that each scale was overall excellent. The criteria of attractiveness 2.485 ? 1.750, perspiculty 2.290 ? 1.900, efficiency 2.448 ? 1.780, dependability 2.338 ? 1.650, stimulation 2.393 ? 1.550, and novelty 2.293 ? 1.400. This research achieves the objectives or features of the application in terms of design, systems, and services. the result is that the Traveloka application can improve perspiculty with existing functions, so that the hotel booking process becomes easier to understand, easy to learn, simple, and clear.
Data Security Using Color Image Based on Beaufort Cipher, Column Transposition and Least Significant Bit (LSB) Handoko, Lekso Budi; Umam, Chaerul
Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i2.7863

Abstract

One of cryptography algorithm which used is beaufort cipher. Beaufort cipher has simple encryption procedure, but this algorithm has good enough endurance to attack. Unauthorized people cannot break up decrypt without know matrix key used. This algorithm used to encrypt data in the form of text called plaintext. The result of this algorithm is string called ciphertext which difficult to understood that can causing suspicious by other people. Beaufort cipher encryption tested with avalanche effect algorithm with modified one, two, three and all key matrix which resulting maximum 31.25% with all key modification so another algorithm is needed to get more secure. Least Significant Bit (LSB) used to insert ciphertext created to form of image. LSB chosen because easy to use and simple, just alter one of last bit image with bit from message. LSB tested with RGB, CMYK, CMY and YUV color modes inserted 6142 characters resulting highest PSNR value 51.2546 on YUV color mode. Applying steganography technique has much advantage in imperceptibility, for example the image product very similar with original cover image so the difference can not differentiate image with human eye vision. Image that tested as much ten images, that consist of five 512 x 512 and five 16 x 16 image. While string message that used is 240, 480 and 960 character to test 512 x 512 image and 24, 48 and 88 character to test 16 x 16 image. The result of experiment measured with Mean Square Error (MSE) and Peak Signal Ratio (PSNR) which has minimum PSNR 51.2907 dB it means stego image that produced hood enough. Computation time calculation using tic toc in matlab resulting fastest value 0.041636 to encrypt 2000 character and the longest time is 4.10699 second to encrypt 6000 character and inserting to image. Amount of character and amount of multi algorithm can affecting computation time calculation.
Time Series Forecasting of Top 3 Ranking Cryptocurrencies Setiawan, Ridwan; Julianto, Indri Tri; Roji, Fikri Fahru
Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i2.8435

Abstract

Cryptocurrency has become a phenomenon worldwide. Although not all countries have legalized it, it is considered a promising investment asset. Currently, there are three top-ranking cryptocurrencies: Bitcoin, Ethereum, and Tether. This research aims to compare the performance of five forecasting algorithms, namely Autoregressive Integrated Moving Average (ARIMA), Neural Network, Support Vector Machine, Linear Regression, and Generalized Linear Model, using the dataset of Bitcoin, Ethereum, and Tether cryptocurrencies. The research methodology employed is Knowledge Discovery In Databases (KDD). The technique involves assessing the performance based on the Root Mean Square Error (RMSE) and comparing the results to find the most optimal model performance. The research findings indicate that for Bitcoin cryptocurrency, the Neural Network algorithm produced the most optimal results with an RMSE of 9180.534. For Ethereum cryptocurrency, the Neural Network algorithm demonstrated the best performance with an RMSE value of 537.528. Furthermore, for Tether cryptocurrency, the ARIMA algorithm yielded the best performance with an RMSE value of 0.003. Keywords – bitcoin, cryptocurrency, ethereum, forecasting, tether

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