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International Journal of Artificial Intelligence Research
Published by STMIK Dharma Wacana
ISSN : -     EISSN : 25797298     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal Of Artificial Intelligence Research (IJAIR) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics of Artificial intelligent Research which covers four (4) majors areas of research that includes 1) Machine Learning and Soft Computing, 2) Data Mining & Big Data Analytics, 3) Computer Vision and Pattern Recognition, and 4) Automated reasoning. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.
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Articles 13 Documents
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Search results for , issue "Vol 7, No 2 (2023): December 2023" : 13 Documents clear
Expert System for Diagnosis of Lung Disease from X-Ray Using CNN and SVM Zulkifli, Zulkifli; Soeprihatini, Retno Ariza; Sfenrianto, Sfenrianto; Wiyanti, Zulvi; Bintoro, Panji; Fitriana, Fitriana; Sukarni, Sukarni; Putri, Nopi Anggista; Andini, Dwi Yana Ayu
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.870

Abstract

The lung disease diagnosis expert system utilizes human knowledge to diagnose various conditions affecting the lung. Diseases caused by fungal or bacterial infection in the organ can cause inflammation as well as death when it is not detected on time. A standard method to diagnose these conditions is the use of a chest X-ray (CXR), which requires careful examination of the image by an expert. In this study, several CNN and SVM architectural models were proposed to classify CXR images to diagnose whether a person has COVID-19, Viral Pneumonia, Bacterial Pneumonia, Tuberculosis (TB), and Normal. The experiment showed that InceptionV3 had the best results compared to other CNN architectures and SVM. Classification accuracy, precision, recall, and f1-score of CXR images for COVID-19, Viral Pneumonia, Bacterial Pneumonia, TB, and Normal were 0.86, 0.91, 0.91, and 0.91, respectively. This study was based on a deep learning system with different CNN and SVM architectures that can work well on the CXR images dataset for diagnosing lung disease.
Development of Augmented Reality Learning Media in Chemistry Subject High School Priyanto, Priyanto; Sumarwan, Sumarwan
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i2.912

Abstract

This study aims to develop chemical bond Augmented Reality (AR) learning media based on Android applications and determine their feasibility. AR media is used in Chemistry class X SMA. Topics developed in this medium are covalent bonding materials and molecular shapes. This Research and Development research was conducted using the multimedia development life cycle (MDLC) model with the stages of concept, design, material collecting, assembly, testing, and distribution. At the testing stage, a feasibility test is carried out through two stages of the validation test, namely the alpha test and beta test. The results of this study indicate that: (1) AR learning media products in chemistry class X were successfully developed with covalent bonds and molecular shapes; (2) the results of testing AR learning media in chemistry Class X obtained very decent results with a percentage of 89.58% in media testing, 91.25% in material testing, and 80.20% in testing prospective users; and (3) this AR learning media received a positive response both from students as potential users and from the subject teacher concerned regarding the easy-to-understand material due to clear visualization and examples as well as an attractive appearance.
Design of Auxiliary Facilities to Reduce Potential Musculoskeletal Disorders in the Product Packaging Process Dewa, Parama Kartika; Dewi, Novita
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.2.984

Abstract

The manufacturing sector continues to grow after the Covid-19 pandemic. One of the competitiveness that supports the development of this sector is a business engaged in the packaging process. Several research studies show that packaging has a major influence on product marketability. However, not all packaging processes are managed by the product manufacturers themselves, but are left to other organizational partners. PBX is one of the organizations engaged in product packaging management. When carrying out the production process, operators experience complaints of musculoskeletal disorders, which have an impact on decreased performance and the risk of injury to operators. This is certainly a bad impact for the PBX. The REBA method is used to carry out analysis and efforts to improve work methods. This method was chosen because this method can help analyze potential injuries based on the operator's body when carrying out a work operation. The results obtained in the initial conditions of the worker's way of working, the operator's way of working is currently in the high risk category. This is indicated by the REBA value of 9. Improvement efforts to reduce this risk are carried out by using tools that can be used by operators. The results of the design improvement of assistive facilities can reduce high risk to low risk.
The Performance Analysis of SIKITO LLDIKTI Region II System using COBIT 2019 Framework: A Case Study Wulandari, Intan Fitriana; Herdiansyah, Muhammad Izman; Kunang, Yesi Novaria; Cholil, Widya; Ariandi, Muhamad; Ependi, Usman
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i2.832

Abstract

In today's organizational landscape, information technology plays a critical role in supporting ongoing activities. Therefore, it is essential to conduct an analysis to determine the advantages and disadvantages of IT implementation. This research focuses on the Higher Education Service Institute (LLDIKTI) Region II, a government agency responsible for improving the quality of higher education in its working area. LLDIKTI Region II uses an information technology system that aligns with the Institute's vision and mission. However, the governance level of the Online Functional Position Information System known as SIKITO has never been assessed, highlighting the need for a maturity framework to measure SIKITO's level and align it with LLDIKTI's vision and mission goals. COBIT 2019 is a framework that aligns with the vision and mission of LLDIKTI and demonstrates how each stakeholder's differences affect the use of information technology based on the maturity level of the implemented system. This research applied the COBIT 2019 framework in LLDIKTI Region II, utilizing the APO07, BAI08, and MEA03 domains. The results indicate that SIKITO's maturity level is below the expected value of -2.33, indicating a need for further development. This research contributes to the field by providing insights into the importance of aligning IT governance with an organization's vision and mission, and the role of maturity frameworks such as COBIT 2019 in achieving this alignment.
Implementation of Digital Marketing Strategy with Chatbot Technology Ramadhan, Farhan Fathur; Sitanggang, Andri Sahata; Wibawa, Julian Chandra; Radliya, Nizar Rabbi
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i2.1006

Abstract

Chatbots are a rapidly growing technology in the field of digital marketing. They are computer programs designed to simulate conversation with human users. Chatbots can be integrated into websites, mobile apps, and messaging platforms to provide instant customer service and support, as well as personalized recommendations and promotions. By using natural language processing (NLP) and machine learning (ML) techniques, chatbots can understand and respond to user input in a human-like manner. They can also be programmed to respond to specific keywords, trigger events, and customer behavior. Chatbot implementation in digital marketing can help companies to improve customer engagement, increase sales and reduce costs. However, the key to successful chatbot implementation is to ensure that the chatbot is designed to meet the specific needs of the target audience and that it is integrated into the overall marketing strategy. This thesis explains the beneficial role of chatbots and shows how chatbots can be integrated into digital marketing strategies.
Comparison of Ensemble Learning Methods for Mining the Implementation of the 7 Ps Marketing Mix on TripAdvisor Restaurant Customer Review Data Sunarko, Budi; Hasanah, Uswatun; Hidayat, Syahroni
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i2.1096

Abstract

The 7P marketing mix encompasses various business facets, notably the Process element governing internal operations from production to customer service. With the surge in online customer feedback, assessing machine learning efficacy, especially ensemble learning, in classifying 7P-related customer review data has gained prominence. This research aims to fill a gap in existing literature by evaluating ensemble learning’s performance on 7P classification, an area not extensively explored despite prior sentiment analysis studies. Employing a methodology merging Natural Language Processing (NLP) with ensemble learning, the study processes restaurant reviews using NLP techniques and employs ensemble learning for precision and accuracy. Findings demonstrate that DESMI yielded the highest performance metrics with accuracy at 0.697, precision at 0.699, recall at 0.697, and an F1-score of 0.684. These outcomes underscore ensemble learning's potential in handling complex datasets, signifying its relevance for marketers and researchers seeking comprehensive insights from customer reviews within the 7P marketing mix domain. This study sheds light on how ensemble learning outperforms its foundational methods, indicating its prowess in extracting meaningful insights from diverse and intricate customer feedback.
Automatic water level controlling and monitoring system using IoT application muliadi, muliadi; Isminarti, Isminarti
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1.1044

Abstract

Water tanks have recently been widely used in many applications in households or industry. It is essential to control the water level of a tank to regulate the filling process so that the tank does not overflow or empty without being noticed. This study aims to design an automatic water level control system using an IoT application to monitor and control processes. The sensor used in this study is a water level sensor, which detects the height of the water level. It works by the principle that the more water hitting the sensor, the smaller the resistance. The sensor can see whether the reservoir has reached a certain level or is complete. The sensor will inform the Wmos R1 board ESP8266 module to turn off the water pump engine and activate it again when the water level sensor reaches a certain level. The results show that the sensor worked correctly and accurately. When the water level sensor shows a whole height level in the filling process, which is 80% filled with water, the water level sensor will inform the Wmos R1 board ESP8266 module to change the relay to the OFF condition so that the water pump engine is also OFF. Upon detecting a specific height, when 50% of the tank has been filled with water, the pump engine restarts. The real-time ON/OFF status of the water pump monitoring the water using Telegram on a smartphone
Integrating Sentiment Analysis and Quality Function Deployment for Product Development 'Azzam, Abdullah; Mahardiningtyas, Syafira; Qurtubi, Qurtubi
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i2.1100

Abstract

The development of technology and media has made online data reviews a promising data source. Through machine learning utilizing text processing, data analysis of Ventela Public Low product reviews can be carried out—sentiment analysis is used to find class groups from each data. The classification algorithm is Naïve Bayes and Support Vector Machine (SVM). A classification model with the best performance and accuracy values will be selected. Word association is then applied to obtain information from the required class. Quality Function Deployment (QFD) is a tool used to assist designers in developing products. The results of the integration of sentiment analysis into QFD show that sentiment analysis produces information by the provisions of the QFD method and can support the product development process in terms of the amount of data various data topics and reduces the subjectivity of designers at the stage of determining Voice of Customer (VOC) and performance values of products and competitors
A Proposed Framework for ERP System Implementation in SMEs Setiawan, Danang; Fahrezha, Muhammad; Prakoso, Nur Abdillah Bagus; Qurtubi, Qurtubi
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i2.1102

Abstract

SMEs face numerous challenges and opportunities due to their pivotal roles in the economic development of a country. Adopting an ERP system is believed to be the catalyst to cope with the challenges and grab the opportunities faced by SMEs. However, implementing ERP led to potential risks caused by implementation failure, even for big companies. SMEs have a unique characteristic due to being receptive to adopting new technologies but having limited resources. Most previous research related to designing frameworks for ERP implementation was focused on big companies, although the fact that SMEs have distinct characteristics compared to big companies. Therefore, this study aims to design a framework for SMEs' ERP implementation. The framework phase consists of (1) measuring the business maturity, information communication and technology (ICT) maturity, proposed business process improvement, and (2) implementing an ERP system. The author has also provided a case study of ERP adoption in an SME in this paper by compiling both steps. This research will contribute to research on ERP in SMEs and practice as guidance for ERP implementors and SMEs in adopting the ERP system
Identifying Improvement Strategic from User Application Reviews Group Using K-Means Clustering and TF-IDF Weighting Istiqomah, Khairunnisa Nurul; Widodo, Imam Djati; Mufid, Nisrina Faiza; Qurtubi, Qurtubi
International Journal of Artificial Intelligence Research Vol 7, No 2 (2023): December 2023
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i2.1062

Abstract

PT ABC is one of the companies that provide online ticket-purchasing facilities amidst the rise of the digitalization era. So, companies need to see how application users complain as a form of evaluation and improvement. The rating results given by application users show a score of 3.3 from 172,000 reviews. The review results that will be examined are user reviews from January 2022 to April 1, 2023, which is more or less the last year of user comments. This research aims to form a review group using K-Means Clustering, the Elbow method, TF-IDF weighting, and analysis of review improvement strategies. The Elbow method is used to determine the optimal number of clusters so as not just to use assumptions. The success of the Elbow method in processing categorical data can be supported by assigning weights based on word frequency sequences using TF-IDF. The research analysis results show the formation of 4 clusters, with two tending to have negative sentiment, one neutral sentiment, and one positive sentiment. Mapping is carried out on each cluster to find out the characteristics of each cluster and possible causes of reviews, as well as providing solutions and strategies as a form of improvement. The problem of negative reviews appearing in each review group is different. It can be corrected with the proposed strategies, such as improving the appearance of features at the registration, ordering, and payment stages, adding payment methods, and carrying out regular system maintenance.

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