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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 191 Documents
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Learning Vector Quantization for Robusta and Arabica Coffee Classification Jatmoko, Cahaya; Sinaga, Daurat; Lestiawan, Heru; Hadi, Heru Pramono
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.v8i2.7343

Abstract

ANN or artificial neural network is a way to solve various kinds of problems to make decisions based on training. One of the methods of JSt which contains competitive and supervised learning. Where this layer will automatically learn the classification of the closest input distances and will be distributed to the same class. there are 2 types of coffee beans that are famous in the world, namely arabica and robusta, for some people or the layman it will be very difficult to distinguish these 2 types of coffee beans apart from the fact that the shape is almost the same the color looks almost the same but there are a number of differences in the two coffee beans which we can see from the shape of the seed. Robusta has a shape that tends to be round and smaller in size, and has a rougher texture. Arabica, on the other hand, is slightly flatter and longer in shape. The size is slightly bigger than Robusta but the texture of Arabica is smoother than Robusta. This is the basis of this study where the images of the two coffee beans will be extracted using the first-order texture feature extraction method based on MU parameters, standard deviation, skewness, energy, entropy, and smoothness. The method for collecting data was in the form of a quantitative method using images from each coffee bean, both Arabica and Robusta, with a total of 130 images. The comparison between training_data and test_data is 80:20. Through research conducted in the form of performance parameters with the best accuracy, including: Learning rate 0.01, max epoch or maximum iteration of 10 and 30%, the amount of training data used is 39 training images and 26 test images resulting in an accuracy presentation of 71% for the training process and error with a percentage of 96% for the test process.
Goods Inventory System Using Visual Basic.Net at PT. Mitra New Grain with Waterfall Method Ferawati, Eva; Maulana, Donny; Nawangsih, Ismasari
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.v8i2.8753

Abstract

This research is motivated by the process of making raw material inventory stocks that still use paper and have not been connected to the database. The problems that arise in the company are regarding the stock of goods, the process of reporting incoming and outgoing goods is still by handwriting which results in calculation errors and differences between physical data and record data. The design of this raw material information system uses the Visual Basic.Net programming language and SQL Server as a database. The system development model used is the waterfall model, analysis and design using diagrams contained in UML. While data collection techniques use research methods by means of observation, interviews, and literature studies. The purpose of this research is to design a raw material inventory information system that can support all incoming and outgoing inventory activities in the company. The result of this research is a desktop-based inventory system application that can assist in processing inventory data and reporting data.
Harnessing Item Features to Enhance Recommendation Quality of Collaborative Filtering Isinkaye, Folasade Olubusola
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.v8i2.7915

Abstract

Recommendation systems provide ways of directing users to items that may be relevant to them by guiding them to relevant items that will be suitable to the users according to their profiles. Collaborative filtering is one of the most successful and mature techniques of recommender system because of its domain independent ability. Bayesian Personalized Ranking Smart Linear Model (BPRSLIM) is model-based collaborative filtering (CF) recommendation algorithm that usually reconstructs a scanty user-item matrix directly; also, using only user-rating matrix usually prevents the algorithm from accessing relevant information that could enhance its recommendation accuracy. Therefore, this work reconstructs BPRSLIM user-item rating matrix via item feature information in order to improve its performance accuracy. Comprehensive experiments were carried out on a real-world dataset using different evaluation metrics.  The performance of the model showed significant improvement in recommendation accuracy when compared with other top-N collaborative filtering-based recommendation algorithms, especially in precision and nDCG with 30.6% and 22.1% respectively.
Crypto-Stegano Color Image Based on Rivest Cipher 4 (RC4) and Least Significant Bit (LSB) Rachmawanto, Eko Hari; Hasbi, Hanif Maulana; Sari, Christy Atika; Irawan, Candra; Inzaghi, Reza Bayu Ahmad; Akbar, Ilham Januar
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.v8i2.8497

Abstract

Rivest Cipher 4 (RC4) has the main factors that make this algorithm widely used, namely its speed and simplicity, so it is known to be easy for efficient implementation. The nature of the key in the RC4 algorithm is symmetrical and performs a plain per digit or byte per byte encryption process with binary operations (usually XOR) with a semirandom number. To improve the visual image after the encryption process, in this article we use the Least Significant Bit (LSB). In this study, the quality of the stego image and the original image has been calculated using MSE, PSNR and Entropy. Experiments were carried out by images with a size of 128x128 pixels to 2048x2048 pixels. Experiments using imperceptibility prove that the stego image quality is very good. This is evidenced by the image quality which has an average PSNR value above 53 dB, while the lowest PSNR value is 48 dB with a minimum dimension of 128x128 pixels.
Helmet Detection Based on Cascade Classifier and Adaptive Boosting Susanto, Ajib; Kusumawati, Yupie
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.v8i2.7392

Abstract

The increasing number of traffic accidents caused by motorcyclists not wearing helmets has led to an increase in the number of studies related to road safety surveillance. The research system used is an automatic system to detect whether the motorcyclist is wearing a helmet or not. Many studies use image processing systems, deep learning and computer vision. In this research, Cascade Classifier and Adaptive Boosting have been implemented for the process of identifying motorcycle riders with helmets and without helmets. The number of datasets used is 500 datasets with labels on the image of the driver with a helmet and the image of the driver without a helmet. Based on the test results, an accuracy of 90% has been obtained
Poverty Modeling in East Java Province Using the Spatial Seemingly Unrelated Regression (Sur) Method Wibowo, Dibyo Adi; Hidajat, Moch Sjamsul; Widyatmoko, Widyatmoko
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.v8i2.8178

Abstract

Poverty is a complex problem because it relates to various aspects of human life. In Indonesia, there is one province that has a very high percentage of poverty, namely East Java Province. Although from year to year the poverty rate has decreased, when viewed from the national level it is still very far from the government's expectations of reducing the poverty rate. Cases of poverty can be modeled by Econometrics. Econometric models are often applied to problems involving one or more related equations. One method that can be used to solve several interrelated equations because there is a correlation error regression between one another, namely Seemingly Unrelated Regression which is usually abbreviated as SUR, in this case Spatial Seemingly Unrelated Regression (SUR-Spatial) is development that takes into account the spatial influence between locations. From the results of tests conducted in the SUR-Spatial Lagrange Multiplier model, the poverty data generated by the East Java Province is the SUR-Spatial Autoregressive Model (SUR-SAR). So with the SUR-SAR model it can be seen that the variable that has a significant effect on the percentage of poor people is the growth rate of Gross Regional Domestic Product based on the constant price of the minimum wage for each district, as well as the average length of school years. Meanwhile, the Poverty Depth Index has an effect because of the growth rate of Gross Regional Domestic Product on the basis of constant prices and the average length of schooling. The Poverty Severity Index is influenced by the growth rate of Gross Regional Domestic Product at constant prices and average years of schooling.
Dijkstra-based Official Motorcycle Repair Shop Application for Determining the Shortest Route Sucipto, Adi; Doheir, Mohamed
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.v8i2.8593

Abstract

Servicing on 2-wheeled vehicles is needed so that the condition remains prime and minimizes the symptoms of component damage. Motorcycle service activities have an impact on the automotive world, especially in the City of Kudus. There are also many motorized vehicle users who do not know the closest route to the nearest Authorized Motorcycle Workshop in the holy city and choose Engine Fuel (BBM) that is in accordance with the type of vehicle they have. shorter service life because the RON (Research Octane Number) or octane number for each motorized vehicle is different, the octane number represents the resistance of the fuel to engine compression. With the development of information science in the current era, an Android-based application was created to search for the closest route to an official motorcycle repair shop in the Kudus City using the Djikstra Algorithm and having a BBM recommendation feature that is suitable for motorbike users' vehicles in the Kudus City.
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.

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