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JAIS (Journal of Applied Intelligent System)
ISSN : 25020493     EISSN : 25029401     DOI : -
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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.
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Articles 15 Documents
Search results for , issue "Vol. 8 No. 2 (2023): Journal of Applied Intelligent System" : 15 Documents clear
Decision Support System For Determining The Best Employee Using The Visekriterijumsko Kompromisno Rangiranje Method (Case Study At Distribution Center Guardian) Auliyah, Risma; Maulana, Donny; Afriantoro, Irfan
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.v8i2.8637

Abstract

The quality of human resources is one of the supporting factors to increase the performance productivity of a corporate agency. Highly competent human resources can support the level of performance, with performance appraisal, the achievements of each employee will be obtained. To obtain fast and accurate information on employee performance that meets the expected criteria. To find out this, with a multi-criteria decision-making method by solving complex and unstructured situations into parts and compiling them using the Visekriterijumsko Kompromisno Rangiranje (VIKOR) method on Decision Support Systems (SPK), the determination of the best employee can be calculated based on the calculation of the weight their respective criteria, so that they can quickly select the best employees in the company. From the final results of the VIKOR method, ranking 1 is Sukron, with a value of 0.
File Cryptography Optimization Based on Vigenere Cipher and Advanced Encryption Standard (AES) Muslih, Muslih; Handoko, L. Budi; Rizqy, Aditya
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.v8i2.7899

Abstract

The rapid The main problem in the misuse of data used in crime is the result of a lack of file security. This study proposes a data security method to protect document files using the Advanced Encryption Standard (AES) algorithm combined with the Vigenere Cipher. This research carried out 2 processes, namely the encryption process and the decryption process. The encryption process will be carried out by the AES algorithm and then encrypted again with the Vigenere Cipher algorithm. The experiments show that the proposed method can encrypt files properly, where there are changes in the value of the document file and the encrypted file cannot be opened and the description results do not cause changes to the original file. The results of this study are that the system is able to work properly so as to produce file encryption and decryption using the AES method combined with the Vigenere Cipher. In document files, the largest difference in encryption and decryption time is 8 seconds, while in image files the difference in encryption and decryption time is 17 seconds. This longest time difference is generated by large files.
The Involvement of Local Binary Pattern to Improve the Accuracy of Multi Support Vector-Based Javanese Handwriting Character Recognition Sari, Christy Atika; Sari, Wellia Shinta; Shelomita, Viki Ari; Kusuma, Mohammad Roni; Puspa, Silfi Andriana; Gusta, Muhammad Bima
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.v8i2.8450

Abstract

Indonesia is a country that is rich in cultural diversity. An example of one such variety is the Javanese language. The letters that are usually used in Javanese are non-Latin letters or are usually known as Javanese script. However, along with advances in technology, the Javanese language is increasingly being forgotten. In the past, the Javanese script was used as a subject in schools, aiming for Indonesian students to continue to gain knowledge about the Javanese script. The initial step in the introduction of the Javanese script starts with the preprocessing process by changing the image of the Javanese script from the RGB image to a grayscale image which is then performed feature extraction, where the feature extraction used in this script recognition is texture extraction with the Local Binary Pattern (LBP) algorithm. The results of this processing are obtained information that can be used as a parameter in the Multi Support Vector Machine (SVM) classification to predict Javanese script images. In this study using the LBP method with the Multi SVM Algorithm as a classification algorithm produces a high accuracy of 90% in the recognition of Javanese script, better than using only Multi SVM with an accuracy of 80%.
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.

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