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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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PUSPINDES E-Performance Information System for Monitoring the Performance Teguh Tamrin; Akhmad Khanif Zyen
Journal of Applied Intelligent System Vol 7, No 2 (2022): 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.v7i2.6492

Abstract

Puspindes is a government institution built by the Pemalang government to provide competence in the field of Information and Communication Technology (ICT) development. The rural informatics empowerment center, hereinafter referred to as PUSPINDES, Pemalang Regency is a flagship program under the supervision and responsibility of BAPERMASDES (Community Empowerment Agency Village) Pemalang Regency this institution focuses on village development, especially in the field of Computer Information Technology and also Intern networks for villages. A system was created to assist in the administrative process carried out by PUSPINDES employees using the PHP Programming Language CodeIgniter package and data storage using a MySQL database.
Development of Android-Based 3d Animation Learning Applications to Support Distance Learning for the D4 Animation Study Program, Udinus Semarang Nur Rokhman; Novi Hendriyanto
Journal of Applied Intelligent System Vol 7, No 2 (2022): 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.v7i2.6814

Abstract

The existence of the COVID-19 pandemic has become a big problem in practicum courses, especially the 3D1 Animation course at the Dian Nuswantoro University animation study program, Semarang. Lecturers cannot guide students directly when experiencing obstacles in the learning process such as during face-to-face learning. The purpose of this research is to create an android application for learning media 3d1 animation. In this application there are several menus including the semester learning plan menu, video tutorials, task collection, consultation with lecturers, remote desktop requests and othersRemote desktop features to make it easier for lecturers to guide students remotely. This study uses the waterfall method, namely software requirements analysis, design, development, testing, and maintenance with testing using the black box method. The test results show that each aspect has results that can be concluded as successful and feasible. This research succeeded in developing android-based 3d1 animation learning media.
GLCM Based Locally Feature Extraction On Natural Image Edi Faisal; Agung Nugroho; Ruri Suko Basuki; Suharnawi Suharnawi
Journal of Applied Intelligent System Vol 7, No 2 (2022): 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.v7i2.6569

Abstract

GLCM is a feature extraction method that uses statistical analysis using a gray scale. Contrast, correlation, energy and entropy are feature features whose value will be sought as the basis for finding the threshold which can then be used to find the threshold value in image segmentation. In this study, a local-based GLCM method is used where the image that has been made into grayscale will be divided into 16 parts of the same size. Each section will look for the value of its GLCM features, namely Contrast, correlation, energy and entropy. The calculation of these four features will be applied to 16 parts of the grayscale image, which can then be used to find the threshold value. The results of the four features in the calculation with an angle of 0o are the contrast value = 0.0080, correlation = 0.619, energy : 0.00160 and entropy : 0.05591.
Visitor Prediction Decision Support System at Dieng Tourism Objects Using the K-Nearest Neighbor Method Eko Hari Rachmawanto; Christy Atika Sari; Heru Pramono; Wellia Shinta Sari
Journal of Applied Intelligent System Vol 7, No 2 (2022): 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.v7i2.6821

Abstract

A tourist target is anything that attracts a visitor or tourist to come to visit a place or area. Tourism goods play an important role in a country or region, becoming a source of national foreign exchange, increasing human resources, and improving the economy of surrounding communities. The problem posed in this study is how to implement a decision support system in predicting visitor numbers for Dieng tourists using the k-nearest neighbor method. The purpose of this study is to help the local government and surrounding communities to improve facilities such as restaurants, places of worship, parking lots, clean toilets so that tourists can feel safe and comfortable when visiting Dieng. Helps manage tourism targets. is what you give. These attractions using a decision support system as a process to predict visitors. The number of visitors who visited in December 2017 was 421,394, which serves as a reference for predicting the number of visitors who will visit Dieng in the following year. The predicted result is 29569.25 visitors with a parameter value of k = 8 and a minimum RMSE value of k = 1/0.
Sentiment Analyst on Twitter Using the K-Nearest Neighbors (KNN) Algorithm Against Covid-19 Vaccination Suprayogi Suprayogi; Christy Atika Sari; Eko Hari Rachmawanto
Journal of Applied Intelligent System Vol 7, No 2 (2022): 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.v7i2.6734

Abstract

The corona virus (2019-nCoV), commonly known as COVID-19 has been officially designated as a global pandemic by the WHO. Twitter, is one of the social media used by many people and is popular among internet users in expressing opinions. One of the problems related to Covid-19 and causing a stir is the procurement of the Covid-19 vaccine. The procurement of the vaccine caused various opinions in Indonesian society, where the uproar was also quite busy being discussed on Twitter and even became a Trending Topic. The opinions that appear on Twitter will then be used as data for the Sentiment Analysis process. One of the members of the House of Representatives (DPR), namely RibkaTjiptaning was also included in the Trending Topic list on Twitter for refusing to receive the Covid-19 vaccine. Sentiment analysis itself is a computational study of opinions, sentiments and emotions expressed textually. Sentiment analysis is also a technique to extract information in the form of a person's attitude towards an issue or event by classifying the polarity of a text. Research related to Sentiment Analysis will be examined by dividing public opinion on Twitter social media into positive and negative sentiments, and using the K-Nearest Neighbor (KNN) algorithm to classify public opinion about COVID-19 vaccination. In the testing section, the Confusion Matrix method is used which then results in an accuracy of 85%, precision of 100%, and recall of 78.94%.
Predicting News Article Popularity with Multi Layer Perceptron Algorithm Arie Rachmad Syulistyo; Vira Meliana Agustin; Dwi Puspitasari
Journal of Applied Intelligent System Vol 7, No 2 (2022): 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.v7i2.6826

Abstract

Nowadays, news media seems to have been digitized. One of them is printed news which has now turned into online news. The increasing use of social media has made people interested in reading news online. News needs to attract readers with their headlines. Various online news media businesses want to know the future demand of readers, as well as whether the released news can reach more readers so that the news becomes popular. Therefore, with the increasing interest in online news today, this paper will analyze the performance of the Neural Network Algorithm and other artificial intelligence techniques in predicting the popularity of news articles that can help the media to know whether their news will become popular. The news article popularity prediction system can increase its revenue if there are advertisements in the news. The test results show that the accuracy of the Multi Layer Perceptron is 76% and Random Forest gives an accuracy of 70%.
Integration of Augmented Reality and Voice Recognition in Learning English for Children Dimas Wahyu Wibowo; Ika Kusumaning Putri; Leni Saputri
Journal of Applied Intelligent System Vol 7, No 2 (2022): 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.v7i2.6119

Abstract

Application development by combining two technologies, namely Augmented Reality and Voice Recognition, can make learning media regarding object recognition at home interact directly with 3D virtual objects. The technology can also help the pronunciation or pronunciation of sentences in English. Natural Language Processing (NLP) is used to understand human language so that machines can understand and process it. This ability supports Voice Recognition to have intelligence and interact like humans. wit.ai is an open-source NLP platform that can support speech-to-text application development. The merging of the two technologies in this development using the wit.ai platform. With the wit.ai platform that is used to understand voice commands and perform tasks as needed for applications regarding object recognition at home, users will be able to interact with objects at home through the given voice commands. In the Black Box testing, each functionality got the results that all the features had functioned properly. User Acceptance Test was also carried out and the average test results were 95.77% and 93.26% on a Likert scale with test results on 13 respondents aged 6-9 years old who have tried the application and 14 respondents as observers when 13 respondents aged 6-9 years tried the application. These results show that the application can be accepted and used as a tool in learning media.
IMAGE CLASSIFICATION OF LOCAL ROBUSTA AND ARABICA COFFEE SEEDS IN MALANG REGENCY USING GRAY LEVEL CO-OCCURRENCE MATRIX AND K-NEAREST METHODS Devita Widiawati; Muhammad Rijalun Shodaqu; Gilang Priambodo; Maulana Fajar Anas; Titien Suhartini Sukamto; Aris Nurhindarto
Journal of Applied Intelligent System Vol 7, No 3 (2022): 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.v7i3.7214

Abstract

Coffee is one type results current plantation  this favored by some among. Indonesia is in the order to four Becomes Robusta coffee export and producer in the world. Appearance communities coffee lovers make coffee as provider field profession for part big resident. In Indonesia, especially in the Regency of Trunk, a lot very Public around who has coffee plantations including namely Robusta coffee and Arabica coffee (coffea arabica) local. For some new people Do you know and love coffee yet? can differentiate type of coffee visually. In the era of increasingly digitalization, advanced like this. There are several method for differentiate something object among them that is processing digital image. Frequent problems occur that is many less consumers in determine Robusta and Arabica coffee types. From trouble that, then researcher designing a system classification on robusta and Arabica coffee beans could obtained with implementation algorithm K-Nearest Lightweight Classification (K-NN). [1] combined with extraction feature Gray Level Co-Occurrence Matrix (GLCM). Digital image dataset used that is a total of 194 pictures where inside it there is type image coffee beans. Image dataset Robusta and Arabica coffee beans each local number of 97 images. Image dataset shared into 20 test data and 174 training data. Testing conducted using Matlab software produce score accuracy highest at distance pixels=1 and the value of K=1 with respect to angle of 45° by 95%.
Expert System of Facial Skin Type Diagnosis and Skincare Recommendation Based on Certainty Factor Dadan Saepul Ramdan; Castaka Agus Sugianto; Rizqy Dimas Monica
Journal of Applied Intelligent System Vol 7, No 3 (2022): 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.v7i3.7150

Abstract

Facial treatment is an important need for everyone because the first sight of meeting someone is to see their face. Generally, facial skin type is just normal skin. However, several factors such as the environment, air, food, facial hygiene, and so on can affect the type of human facial skin. In this experiment, there were 5 types of facial skin, namely normal skin, dry skin, oily skin, combination skin, and sensitive skin. With the existence of various skin types, it makes some people confused in determining the type of facial skin. This also affects the selection of skincare or facial care according to the indications of each facial skin. Therefore an expert system was created to diagnose facial skin types. An expert system is a man-made system that is used to solve problems like an expert with knowledge from human to computer, although it does not give 100% absolute results, but expert systems are still helpful.
Testing the Budhara Digital Book Application (Borobudur Dalam Cerita) Sri Mulatsih; Raden Arief Nugroho; Valentina Widya Suryaningtyas; Aloysius Soerjowardhana; Ali Muqoddas; Erika Devi Udayanti
Journal of Applied Intelligent System Vol 7, No 3 (2022): 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.v7i3.7286

Abstract

Borobudur Temple is one of the icons of Indonesian tourism in the world. Unfortunately, tourists, domestic and foreign, do not have knowledge of the importance of the existence of Borobudur Temple as a cultural heritage. Evidence of the lack of knowledge of domestic tourists about the conservation of Borobudur Temple is reflected in the vandalism of thousands of people who left stains on the Borobudur stone. This has the potential to damage the rock layers of the temple. Foreign tourists themselves are also seen as lacking comprehensive knowledge about Borobudur Temple. They know a lot about the history of Borobudur, but do not understand the history of the villages surrounding the supporters of Borobudur Temple. The history of the villages around Borobudur is an important element in supporting Borobudur as a cultural heritage. In addition, efforts are needed to maintain tourist interest in visiting Borobudur Temple and the surrounding villages during the limited number of visitors. For this reason, a way is needed to educate the general public about the history and conservation efforts of the Borobudur Temple and the surrounding villages which have historical and geographical links. Based on these problems, the researchers developed a digital book called Buddhara (Borobudur Dalam Cerita) and has been testing using questionnaire.

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