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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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Aspect Based Sentiment Analysis: A Systematic Literature Review Suhariyanto Suhariyanto; Riyanarto Sarno; Chastine Fatihah; Edi Faisal
Journal of Applied Intelligent System Vol 5, No 1 (2020): 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.v5i1.3807

Abstract

Aspect based sentiments can provide more detailed information about the sentiment (positive, negative, and neutral) based on an aspect in a review. It can provide better recommendations to users in decision making process. A number of previous studies have been conducted on aspect-based sentiment analysis indicating that survey is needed to provide an overview of the method available in aspect-based sentiment analysis. The survey method has been implemented since the last 5 years to obtain novelty from existing methods. The Systematic Literature Review (SLR) method is used to review a collection of 34 papers from various academic databases which focus on the aspect of extraction, sentiment analysis, and aspect aggregation. The papers will be sorted based on the focus of the method used. For each analysis, a detailed analysis is described on the contribution of the method to the aspect-based sentiment analysis alongside a comparison with other methods as well as advantages and disadvantages. The last section discusses the method commonly used in this study as well as future challenges in the study focusing on aspect-based sentiment analysis.
IMPLEMENTATION OF DIVIDE AND CONQUER IN THE HANOI TOWER GAME Bonifacius Vicky Indriyono; Zudha Pratama
Journal of Applied Intelligent System Vol 5, No 2 (2020): 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.v5i2.4291

Abstract

Artificial Intelligence (AI) is a technology in the field of computer science that simulates human intelligence into computers to solve various problems and jobs as well as humans do. Games / games are an implementation of the field of computer science which also embraces the concept of AI. In the midst of the rampant types of games available, the author chose the Hanoi Tower which is a mathematical game / puzzle that requires logic. Players are challenged to complete in a short time with a certain number of discs. The benefit of this game is that it can train how to think with certain patterns so as to improve the memory of players. To make it easier to solve it, the Divide and Conquer Algorithm can be used which can solve problems in the Tower of Hanoi game by breaking them down into sub-problems which will later be able to help speed up finding solutions. From the results of testing the application of the Divide and Conquer Algorithm in the hanoi tower game application by solving the disk arrangement problem. Players can finish the game in a large number of plates in a short time. Keywords – Artificial Intelligence, Divide and Conquer Algorithm, Games, Tower of Hanoi.
Keyphrase Extraction on Covid-19 Tweets Based on Doc2Vec and YAKE Fahri Firdausillah; Erika Devi Udayanti
Journal of Applied Intelligent System Vol 6, No 1 (2021): 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.v6i1.4454

Abstract

Keyword and keyphrase extraction are one of the initial foundations for performing several text processing operations such as summarization and document clustering. YAKE is one of the techniques used for unsupervised and independent keyphrase extraction, it does not require a corpus for linguistic tools such as NER and POS-tag. However, the use of YAKE in microblogging documents such as Twitter often results in a keyphrase that is less representative because of the lack of words used for ranking. This paper offers a solution to this problem by looking for similar tweets in the keyphrase extraction process using Doc2Vec so that the number of words used in the YAKE ranking process can be greater. Covid-19 tweets related are used as dataset as the topic is currently widely discussed on social media to prove that the proposed approach could improve keyphrase extraction performance
Sequential Model for Mapping Compound Emotions in Indonesian Sentences - Aripin; Wisnu Agastya; Hanny Haryanto
Journal of Applied Intelligent System Vol 5, No 1 (2020): 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.v5i1.4264

Abstract

This research proposes mapping Indonesian sentences with single and multiple structures into emotion classes based on a multi-label classification process. The result of this research can apply in various fields, including the development of facial expressions in virtual character animation. Applications in other fields are facial expression analysis, human-computer interaction systems, and other virtual facial character system applications. In previous research, the classification process used for emotion mapping was usually based only on the frequency of occurrence of adjectives. The resulting emotion classes are less representative of sentence semantics. In this research, the proposed sequential model can take into account the semantics of the sentence so that the results of the classification process are more natural and representative of the semantics of the sentence. The method used for the emotion mapping process is multi-label text classification with continuous values between 0-1. This research produces the tolerant-method that utilizes the error value to deliver accuracy in the model evaluation process. The tolerant-method converts the predicted-label, which has an error value less than or equal to the error-tolerant value, to the actual-label for better accuracy. The model used in the classification process is a sequential model, including one-dimensional Convolution Neural Networks (CNN) and bidirectional Long Short-Term Memory (LSTM). The CNN model generates feature maps of each input in a partial way. Meanwhile, bidirectional LSTM captures information from input data in two directions. Experiments were performed using test data on Indonesian sentences. Based on the experimental results, bidirectional LSTM can produce an accuracy of 91% in the 8: 2 data portion and error-tolerant of 0.09.Keywords : Sequential Model, Mapping Compound Emotions, Sentence Semantics, Indonesian Sentences
Whale Optimization Algorithm Bat Chaotic Map Multi Frekuensi for Finding Optimum Value Nur Wahyu Hidayat; . Purwanto; Fikri Budiman
Journal of Applied Intelligent System Vol 5, No 2 (2020): 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.v5i2.4432

Abstract

Optimization is one of the most interesting things in life. Metaheuristic is a method of optimization that tries to balance randomization and local search. Whale Optimization Algorithm (WOA) is a metaheuristic method that is inspired by the hunting behavior of humpback whales. WOA is very competitive compared to other metaheuristic algorithms, but WOA is easily trapped in a local optimum due to the use of encircling mechanism in its search space resulting in low performance. In this research, the WOA algorithm is combined with the BAT chaotic map multi-frequency (BCM) algorithm. This method is done by inserting the BCM algorithm in the WOA search phase. The experiment was carried out with 23 benchmarks test functions which were run 30 times continuously with the help of Matlab R2012a. The experimental results show that the WOABCM algorithm is able to outperform the WOA and WOABAT algorithms in most of the benchmark test functions. The increase of performance in the average of optimum value of WOABCM when compared to WOA is 2.27x10 ^ 3.
Application of the K-Nearest Neighbors (K-NN) Algorithm for Classification of Heart Failure Ryan Yunus; Uli Ulfa; Melinna Dwi Safitri
Journal of Applied Intelligent System Vol 6, No 1 (2021): 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.v6i1.4513

Abstract

Heart failure is a type of disease that has the largest number of patients in the world. Based on information from the data center, there were 229,696 people with heart failure in 2013. Lack of public knowledge about what indications of a person having heart failure make the main cause not handled properly by heart failure patients. In this study, data classification was carried out using KNN algorithm because it has a simple calculation and has a fast time. This study only uses 12 attributes, while the previous study compared 6 algorithms with 13 attributes from 299 data. The highest algorithm with 94.31% accuracy by Random Forest while KNN had an accuracy rate of 86.95% with the same data. In this study, the accuracy of the sample data was compared between 20 data and 299 total data. Both of them have different accuracy. 20 sample data has an accuracy rate of 89.29% while 299 data has an accuracy rate of 96.66%.
Developing Smart City 5.0 Framework To Produce Competency Indra Gamayanto; Aris Nurhindarto
Journal of Applied Intelligent System Vol 5, No 1 (2020): 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.v5i1.4228

Abstract

Abstract - Smart cities are essential things that must be applied in the face of globalization and competition. In smart city 5.0, three important things discussed are human resource development, smart marketing, and information technology. These three things cannot be separated from each other because they are related. Furthermore, the smart city 5.0 article is a development from the previous article, namely smart city 1.0-3.0. Smart City 5.0 provides four important formulas for developing a smart city and a framework to guide its implementation. The four formulas and the resulting framework will develop in the next article, namely intelligent intelligence. It will continue to make prototypes and smart city intelligence applications. The result of this article is a framework that is a concept and strategy in developing a smart region that is part of a smart city. This article is still under development and research will continue. Furthermore, the development of this research will certainly require several more stages in reaching the top of the research, namely a big picture of a smart city and performance measurement for each process contained in a smart city. Therefore, it takes the right steps and formulas to produce a smart city 5.0 framework Keywords - Smart city, Human resource, Marketing, Technology, Innovation    
A Video Quality Testing : Review of Human Visual Aspect Andi Danang Krismawan; Lekso Budi Handoko
Journal of Applied Intelligent System Vol 6, No 2 (2021): 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.v6i2.4613

Abstract

Various types of video player applications have been widely used by the community. The emergence of the latest version and a variety of features make people need to make a choice to use a video player application with a good visual level. The type of video that is often played is a file with an MP4 extension. This file type is not heavy but is usually intended for long file durations such as movies. In this paper, we will use a dataset in the form of a movie file with an MP4 extension. The video player applications used include VLC, Quick time, Potplayer, KMPLayer, Media Player Classic (MPC), DivX Player, ACG Player, Kodi, MediaMonkey. Through various empirical calculations, such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Structutral Similarity Index Measurement (SSIM), Threshold F-ratio, Visual Signal to Noise Ratio (VSNR), Visual Quality Metric (VQM), and Multiscale - Structutral Similarity Index Measurement (MS-SSIM) has analyzed the visual capabilities of each video player application. Experimental results prove that the KMPlayer application gets the best visual results compared to other selected applications.
Improvement of Accuracy and Handling of Missing Value Data in the Naive Bayes Kernel Algorithm Bijanto Bijanto; Ryan Yunus
Journal of Applied Intelligent System Vol 6, No 2 (2021): 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.v6i2.5288

Abstract

The lost impact on the research process, can be serious in classifying results leading to biased parameter estimates, statistical information, decreased quality, increased standard error, and weak generalization of the findings. In this paper, we discuss the problems that exist in one of the algorithms, namely the Naive Bayes Kernel algorithm. The Naive Bayes kernel algorithm has the disadvantage of not being able to process data with the mission value. Therefore, in order to process missing value data, there is one method that we propose to overcome, namely using the mean imputation method. The data we use is public data from UCI, namely the HCV (Hepatisis C Virus) dataset. The input method used to correct the missing data so that it can be filled with the average value of the existing data. Before the imputation process means, the dataset uses yahoo bootstrap first. The data that has been corrected using the mean imputation method has just been processed using the Naive Bayes Kernel Algorithm. From the results of the research tests that have been carried out, it can be obtained an accuracy value of 96.05% and the speed of the data computing process with 1 second.
Securitary Text on Images with RC-128 Bit Synthric Key Encryption Muslih Muslih; Abdussalam Abdussalam; Elkaf Rahmawan Pramudya
Journal of Applied Intelligent System Vol 6, No 2 (2021): 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.v6i2.4620

Abstract

The main purpose of using cryptography is to provide the following four basic information security services. One of the purposes of cryptography is secrecy. Confidentiality is the fundamental security service provided by cryptography. This is a security service that stores information from unauthorized persons. Confidentiality can be achieved through a variety of ways ranging from physical security to the use of mathematical algorithms for data encryption. Vernam cipher is a stream cipher where the original data or plain with 8x8 block operation. Experimental results prove that RC4 can perform encryption and decryption with a fast execution process. In this study used a processor with 8GB of RAM. The encryption result of the text used yields the average encryption time and decryption average of 2 second.

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