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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 5 Documents
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Search results for , issue "Vol 5, No 1 (2020): Journal of Applied Intelligent System" : 5 Documents clear
Automatic Power-up Items Placement on Shooter Game using Convolutional Neural Network Alvin Satria Nugraha; Abas Setiawan; Wijanarto Wijanarto
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.v5i1.4213

Abstract

- A shooter game is a popular game genre with various components. To make a shooter game more attractive, some power-ups items can support players to achieve their goals. Power-ups items provide more power to players, some of which include ammo, extra lives, and invulnerability. The location of power-ups items should be in a special place so that it neither too easy to find nor too difficult to find. Item placement could be done manually by a human or a technical artist. It will need a relatively long time and high cost. In this paper, we try to mimic technical artist vision when placing an item. Visual images have been collected by scanning spatially the forest terrain by using a virtual camera on top. Each image data comply with the item placement rules according to the Tomb Raider and Uncharted 4 games. Convolutional Neural Network (CNN) is used to find out which images can be occupied by power-up items or not. From several experimental scenarios, the use of the Global Average Pooling layer is proven to produce a model that is not overfitting. The best CNN models are developed and got an accuracy of 90.5% with an architecture that includes the Global Average Pooling layer. That model is applied to the new forest terrain so that power-up items can automatically be placed in an appropriate location.
5th Hyphotesis Consideration of UTAUT for IOT By Exploiting ACO based Classification Rudy Ariyanto; Vivin Ayu Lestari; Septian Enggar Sukmana
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.v5i1.3523

Abstract

Internet of things (IoT) application needs to be evaluated to gain better improvement and innovation. The evaluation can be examined from user acceptance. The unified theory of acceptance and use of technology (UTAUT) can be used as a model to identify user acceptance in using technology, including IoT application. However, the ease of use of technology must be included, so the determining of easy of use from negative aspects must be included, so the 5th hypothesis of UTAUT (hindering condition) must be included. Before this hypothesis is formulated and included in evaluation by the user, obtaining data to identify the real condition of the user is performed using forensic analysis and ACO based classification. To evaluate this activity, this 5th hypothesis is measured by reliability and validity test, also hypothesis testing itself.
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.
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
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    

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