JAIS (Journal of Applied Intelligent System)
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.
Articles
191 Documents
<![CDATA[Classification Email Spam using Naive Bayes Algorithm and Chi-Squared Feature Selection ]]>
<![CDATA[Ningsih, Maylinna Rahayu]]>;
<![CDATA[Unjung, Jumanto]]>;
<![CDATA[Farih, Habib al]]>;
<![CDATA[Muslim, Much Aziz]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.62411/jais.v9i1.9695
<![CDATA[Spam email is a problem that disturbs and harms the recipient. Machine learning is widely used in overcoming email spam because of its ability to classify emails into spam or non-spam. In this research, the Naïve Bayes algorithm is initiated with the Chi-Squared selection feature to classify spam emails. So that the implementation is able to increase accuracy for better performance in classification. The feature selection method is used to direct the model's attention to features that are related to the target variable. In this study, the chi squared feature uses a value of K = 2500, with an accuracy of 98.83% which shows an increase in model performance compared to previous research. So that the Naïve Bayes model with the Chi-Squared selection feature is proven to provide better performance. ]]>
<![CDATA[Completing Sudoku Games Using the Depth First Search Algorithm ]]>
<![CDATA[Alfany, Fauzan Maulana]]>;
<![CDATA[Sari, Christy Atika]]>;
<![CDATA[Jatmoko, Cahaya]]>;
<![CDATA[Laksana, Deddy Award Widya]]>;
<![CDATA[Irawan, Candra]]>;
<![CDATA[Huda, Solichul]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.62411/jais.v9i1.10017
<![CDATA[Sudoku is a digital game that is included in the type of logic-based puzzle game where the goal is to fill in the puzzle with random numbers. Therefore, in this research it is proposed to use Artificial Intelligence which contains the Depth First Search Algorithm to track the number of possible solutions that lead to only one so that it becomes efficient. This game has different levels of difficulty such as easy, medium and difficult. The time and complexity of execution will vary depending on the difficulty so it is proposed to use Android Studio software. The experimental results prove that there is an increase in playing the Sudoku game quickly and accurately by applying the Depth First Search Algorithm method. This is proven by the ability to complete this game using the Depth First Search Algorithm using the Android Studio programming language. The average time at the easy level is 11:04 minutes, at the normal level is 10:52 minutes, at the hard level is 25:46 minutes, and at the extreme level is 38 minutes.]]>
<![CDATA[Analysis of Inter-Subject and Session Variability using Brain Topographic Map ]]>
<![CDATA[Setiawan, Fachruddin Ari]]>;
<![CDATA[Pradana, Dio Alif]]>;
<![CDATA[Nandang, Iim]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.62411/jais.v9i1.10051
<![CDATA[The study described investigates the application of Brain-Computer Interface (BCI) technology, focusing on Motor Imagery (MI) signals which enable individuals to control movements through mental visualization. A major challenge in this field is accurately distinguishing between different movements, particularly when dealing with data from multiple subjects and recording sessions, known as inter-subject and inter-session variability. To address this, the authors employ the Wavelet Packet Transform-Common Spatial Patterns (WPT-CSP) method to enhance the resolution of MI signals. They visualize the results using Brain Topographic Maps (Topomaps) to depict brain activity during MI tasks, facilitating the analysis of variability across subjects and sessions. Utilizing dataset 2a from the Brain-Computer Interface Competition (BCIC) IV, the study demonstrates the efficacy of this approach in identifying variability patterns. This research holds promise for improving BCI technology applications in various domains, and future work could explore refining signal processing techniques and validation on larger datasets. Topomap.]]>
<![CDATA[Counselor Application Frontend with Personality- matching Using Android-Based K-Means Clustering Algorithm ]]>
<![CDATA[Putra, Ifan Perdana]]>;
<![CDATA[Rachmawanto, Eko Hari]]>;
<![CDATA[Sari, Wellia Shinta]]>;
<![CDATA[Rahayuningtyas, Tri Esti]]>;
<![CDATA[Umam, Choerul]]>;
<![CDATA[Himawan, Mahadika Pradipta]]>;
<![CDATA[Yaacob, Noorayisahbe Bt Mohd]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.62411/jais.v9i1.10217
<![CDATA[Education is one of the most important things for people to have. Many people are competing for education to increase their abilities. Technology plays a big role in developing access to education to make it easier with many online applications and online classes education becomes easier. However, there are still many unresolved problems in this field of education, namely the emergence of the phenomenon of incompatibility between educators and students so that student interest decreases dramatically because of this. And also, the lack of learning materials taught that are not school subjects such as programming. Therefore, the author and team designed an application where this application can find students a learning mentor outside of school so that they can increase their knowledge. The application also provides a matching feature based on the student's personality so that the student can find a suitable tutor.]]>
<![CDATA[Mobile-Based Interactive Learning Media Design Using Augmented Reality Concepts ]]>
<![CDATA[Pamungkas, Natalinda]]>;
<![CDATA[Indriyono, Bonifacius Vicky]]>;
<![CDATA[Mahmud, Wildan]]>;
<![CDATA[Zahari, Iqlima]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.62411/jais.v9i1.10225
<![CDATA[One of the natural disasters that currently occurs frequently in Indonesia is earthquakes. An earthquake is a situation where the earth shakes due to volcanic activity, or collisions due to the movement of the earth's plates. Earthquake activity causes many problems. One of them is liquefaction. Liquefaction is an event that shows a loss of soil shear strength caused by an increase in pore water pressure. This occurs because the earthquake load occurred so quickly and briefly. Liquefaction is a description of the effects of an earthquake so that the soil layer loses its strength. Not many people know the process of earth movement which is the precursor to earthquakes. Especially people who have hearing limitations. For this reason, education is needed to be conveyed to the public. Educational techniques in virtual form will be a special attraction for people, especially deaf people. Augmented Reality (AR) technology is a technology where virtual objects and real objects are combined. In this research, an application was produced in the form of learning media that utilizes Augmented Reality (AR) technology with the Marker Based Tracking method. To make learning media more interactive, the technology was developed using the MDLC (Multimedia Development Life Cycle) method. The results of the tests carried out concluded that the application could be used as an interactive learning medium to increase knowledge about the occurrence of earthquakes and the effects of liquefaction for the community]]>
<![CDATA[Optimization Of Neural Network Method Using Chi-Square Feature Selection In Poverty Data Classification ]]>
<![CDATA[Aprilia, Tresi Aprilia]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.62411/jais.v9i1.10227
<![CDATA[Poverty is a fundamental problem that has become the center of attention in several aspects, for example from the government. The government needs poverty data and analyzes it to determine which poverty alleviation programs should be delivered to the right target or the poor. The aim of this study is to determine the accuracy of the classification of poverty in Batang District using the Neural Network method using the chi square feature selection. The dataset used in this study uses poverty data sourced from the Batang district BPS based on the results of the Susenas survey (National Economic Survey) for the 2022 time period. The results of this study indicate that the accuracy obtained for poverty classification using a neural network is 96.38% , with a precision value of 100%, and a recall value of 89.38%. Whereas when using a neural network with feature selection chi square, it gets an accuracy value of 93.68%, with a precision value of 91.07%, and a recall value of 90.26%. The contribution of this research is to develop a neural network method using feature selection chi square to improve the results of the accuracy of the classification is not poor or poor. ]]>
<![CDATA[Predicting Gold Price Movement Using Long Short-Term Memory Model ]]>
<![CDATA[Nagata, Azaria Beryl]]>;
<![CDATA[Hidajat, Moch Sjamsul]]>;
<![CDATA[Wibowo, Dibyo Adi]]>;
<![CDATA[Widyatmoko, Widyatmoko]]>;
<![CDATA[Yaacob, Noorayisahbe Bt Mohd]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.62411/jais.v9i1.10305
<![CDATA[Gold, as a valuable commodity, has been a primary focus in the global financial market. It is often utilized as an investment instrument due to the belief in its potential price appreciation. However, the unpredictable and complex movement of gold prices poses a significant challenge in investment decision-making. Therefore, this research aims to address this issue by proposing the use of the Long Short-Term Memory (LSTM) model in time series analysis. LSTM is a robust approach to understanding patterns and trends in gold price data over time. In the context of time series analysis, historical gold price data includes daily, weekly, and monthly datasets. Each model with its respective dataset is useful for identifying patterns in gold prices. The daily model achieves an MSE of 452.2284140627481 and an RMSE of 21.26566279387379. The weekly model achieves an MSE of 1346.1816584357384 and an RMSE of 36.69034830082345. The monthly model achieves an MSE of 11649.597907584808 and an RMSE of 107.93330305139747. With these RMSE results, the LSTM model can predict gold prices effectively. Based on the trained models, it can also be concluded that gold prices exhibit long-term temporal dependence.]]>
<![CDATA[Data Mining Application Analyzing Customer Purchase Patterns Using The Apriori Algorithm ]]>
<![CDATA[Prayugo, Moh. Lambang]]>;
<![CDATA[Wibowo, Dibyo Adi]]>;
<![CDATA[Hidajat, Moch. Sjamsul]]>;
<![CDATA[Mintorini, Ery]]>;
<![CDATA[Ali, Rabei Raad]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.62411/jais.v9i1.10308
<![CDATA[The study aims to implement Data Mining with Apriori Algorithm and Association Methods (shop cart analysis) to analyze the sales pattern of Kaffa Beauty Shop stores as a case study. Sales information obtained from stores is used to find out the repeated buying habits of cosmetic products. This analysis provides store owners with valuable information to make more useful decisions about product inventory management, marketing strategies, and other aspects of their business. The Apriori Algorithm implementation follows steps including data preprocessing, subsetting, frequent dataset search, and strong association rules (strong Association Rules). The results of the analysis show that there are important purchasing patterns among some cosmetic products that can be the basis of a more effective sales strategy. The study helps understand how data mining and Apriori Algorithms can be applied in business contexts such as Kaffa Beauty Shop stores. Therefore, the results of this analysis are expected to contribute greatly to improving business efficiency and optimizing marketing strategies for store owners and stakeholders. The research is also expected to show the enormous potential of data analysis to support optimal business decision making.]]>
<![CDATA[Naive Bayes Sentiment Analysis Study On Street Boba And Gildak Kediri Consumer Reviews ]]>
<![CDATA[Prasentya, Cindy Aprilia Wijaya]]>;
<![CDATA[Hermanto, Didik]]>;
<![CDATA[Negar, Wana Pramudyawardana Kusuma]]>;
<![CDATA[Isinkaye, Folasade Olubusola]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.62411/jais.v9i1.10309
<![CDATA[Streetboba & Gildak Kediri outlet is a restaurant that serves a variety of Korean food menus and various kinds of drinks with boba and jelly toppings that are sold at low prices that suit the student's budget. This restaurant is located in East Java province which is precisely on Jalan Yos Sudarso No.43, Kediri City. With technological advances that continue to grow to affect various aspects, especially in the business and industrial world. Sentiment analysis is a technology that extracts or manages text to be expressed using text that can also be classified into positive and negative polarity. Consumer reviews are a form of communication that occurs in the sales process, the stage where potential buyers receive an explanation of the product posted and buyers receive reviews that explain the advantages or disadvantages of purchasing the product. In this study, sentiment analysis was conducted based on consumer opinions regarding social media accounts. The study aimed to use social media data to assess the service, cleanliness and quality of products offered by categorizing companies as having positive and negative reviews. To classify sentiment, the Naive Bayes method is used, which combines survey data collection methods, questionnaires, and observation data.]]>
<![CDATA[Implementation Of The Base64 Algorithm For Text Encryption And Decryption Using The Python Programming Language ]]>
<![CDATA[Pamungkas, Caroko Aji]]>;
<![CDATA[Pratama, Zudha]]>;
<![CDATA[Setiarso, Ichwan]]>;
<![CDATA[Doheir, Mohamed]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.62411/jais.v9i1.10310
<![CDATA[The exchange of information on the Internet requires increased protection to avoid potential threats to privacy and security. This study identified the main issues in this regard: the need for simple and effective tools for encoding and decoding messages, and the need to understand Base64 encoding algorithms and concepts. However, to overcome this problem the author developed an application to encode and decode messages/text using the Base64 algorithm and the Python programming language. This application allows users to send secret messages/text securely via and convert the data into Base64 format for secure transmission via text media. It also covers the basics of cryptography, Base64 algorithms, and how to use the Python programming language to develop secure applications. The result of this research is a simple and effective encryption and decryption application. This application provides a solution for users to protect messages or text when they want to change confidential information by converting it to Base64 format. With this application, you can send secret messages or texts with the confidence that only authorized parties can read them. Implementing message encryption and decryption using the Base64 algorithm using Python is an important step in maintaining message privacy and security in the current digital era. This research succeeded in developing an application suitable for this purpose. Therefore, the next step is to improve the security of your application by implementing stronger encryption algorithms. Additionally, we provide a more comprehensive user guide to help users better understand cryptographic concepts. Further research may focus on integrating applications with broader Internet security protocols to address increasingly complex security threats.]]>
