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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.
Arjuna Subject : -
Articles 621 Documents
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Using a Semi-supervised Learning Model for Recognition of Human Daily Activities from Wearable Sensor Data Nguyen, Tien Manh; Motoki, Takagi
International Journal of Artificial Intelligence Research Vol 8, No 1 (2024): June 2024
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1146

Abstract

The application of Machine Learning (ML) and Artificial Intelligence (AI) is growing, and also becoming more important as the aging population increases. Smart support systems for distinguish Activities of Daily Living (ADL) can help the elders live more independently and safely. Many machine learning methods have been proposed for Human Activity Recognition (HAR), including complex networks containing convolutional, recurrent, and attentional layers. This study explores the application of ML techniques in ADL classification, leveraging wearable devices' time-series data capturing various parameters such as acceleration. The acceleration data obtained from sensors is so huge that it is difficult and expensive to accurately label every sample collected, so this study applies the Semi-supervised Learning model to unlabeled samples. Long Short-Term Memory (LSTM) has always been used for time series data such as acceleration, and recently, the Transformer model has emerged in many applications such as Natural Language Processing (NLP) or creating ChatGPT. In this study we proposed ADL classification method using the Self-Attention Transformer block and the Recurrent LSTM block and evaluated their results. After comparison, the model built with LSTM block gives better results than the model built with Transformer block.
Marketing Information Systems in the Context of Building WOM Marketing Through Service Quality, Institutional Image and Customer Satisfaction in Higher Education Yani, Tri Endang; Santoso, Aprih; Wibisono, Totok; Kuswardani, DC
International Journal of Artificial Intelligence Research Vol 7, No 1.1 (2023)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1.1080

Abstract

This study aims to construct word of mouth (WOM) marketing through service quality, institutional image, and customer satisfaction as variables influencing higher education institutions. The utility of the research is to help universities create word of mouth to support the sustainability and competitiveness of higher education. The population of this study are still active students at Semarang University. The number of samples is 100 and the selection of the sample ofis a conscious selection based on the criterion of respondents who are studying at least in the 4th semester. The analysis technique used is multiple linear regression and trajectory analysis.The results of the study indicate that the quality of the service and the image of the facility have a partially positive effect on customer satisfaction. The journey analysis, on the other hand, shows that customer satisfaction can neither reflect the relationship between service quality and PTO nor the relationship between image and PTO
Hyperparameter Tuning in Machine Learning to Predicting Student Academic Achievement Arifin, Muhammad; Adiyono, Soni
International Journal of Artificial Intelligence Research Vol 8, No 1.1 (2024)
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1.1214

Abstract

Prediction of student academic achievement is a very important research area; this can be seen from the many researchers who conduct research in this area. To make predictions, a machine learning model is needed. Along with their parameters, the majority of machine learning models have associated hyperparameters. However, knowing the right mix of hyperparameters is essential for robust model performance. A methodical procedure called hyperparameter optimization (HPO) aids in determining the appropriate values for them. In this study we compared four hyperparameters tuning techniques, namely HyperOpt, Random Search, Optuna and Grid Search. The results of the hyperparameters from each of these techniques are then used in machine learning algorithms to predict student academic achievement. Validation uses the 5-fold cross validation method while performance testing uses Mean absolute error. From the experimental results it was found that the hyperparameter technique The best method for predicting student academic achievement in machine learning models is gridsearchcv.
Information on Firm Value Determinants Based on Investment Decision and Dividend Policy Rahmadi, Zara Tania; Yulianto, Kampono Imam; Damayanty, Prisilia
International Journal of Artificial Intelligence Research Vol 7, No 1.1 (2023)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1.1041

Abstract

Due to the high level of investment that occurs today, this study aims to determine the Determinants of Investment Decisions, Dividend Policy and its Implications for Firm Value. The research method used in this research is quantitative method with the type of data used is panel data (pooled data) which is a combination of data from time series data with cross section data. The population in this study are companies listed on the Jakarta Islamic Index (JII) for the period 2019 to 2021. For sampling techniques in this study using non-random sample techniques with purposive sampling method. To answer the alleged hypothesis in this research using the panel regression model estimation method where the statistical tool that will be used is EViews 10. The output of this research will be published in the Sinta 2 indexed national journal, for the level of technology readiness (TKT) of the proposed research, namely the TKT type of social humanities and education, which is defined in the utilisation of R & D results for the improvement of policies and governance with the achievement of indicator point 3, namely the results / outputs of R & D delivered as a reference and information for related parties
The Impact Of Announcements Of Mergers And Acquisitions (M&A) On Stock Returns Sampurna, Dian Surya; Alexandri, Benny; Pragiwani, Meita; Suhardi, Yusuf; Ikaputri, Marcelina Wahyuningtyas
International Journal of Artificial Intelligence Research Vol 8, No 1.1 (2024)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1.1195

Abstract

One of the corporate actions carried out by companies is mergers and acquisitions (M&A). This research aims to examine the impact of merger and acquisition (M&A) announcements on stock returns of banking companies listed on LQ 45 for the 2011-2021 period. This research uses the event study method, with 3 banking companies from 8 merger and acquisition (M&A) events, with an event window of 91 days, namely 45 days pre-announcement, 1 day of announcement and 45 days post-announcement. The results of this research show that the market responded positively to 8 merger and acquisition (M&A) announcement events. The benefit of this research is for policy makers to stimulate stock prices with the help of various announcements from their corporate action strategies. Investors will be helped in understanding stock market mechanisms in making wise investment decisions before reacting to corporate actions. Meanwhile, policy makers are interested in influencing stock prices and investors are interested in the composition of risk-return parameters in their portfolios. This research will act as an important investment tool for both.
NEW CONSUMER AND MARKETING PATTERNS IN THE POST-PANDEMIC SCENARIO ARE PAVING THE WAY FOR THE SDGS IMPLEMENTATION Hendra, Hendra
International Journal of Artificial Intelligence Research Vol 7, No 1.1 (2023)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1.1063

Abstract

In the post-pandemic era, this essay examines how sustainable marketing and consumption models might help advance the implementation of the Sustainable Development Goals (SDGs). The study is motivated by the need for innovative solutions to decrease the negative consequences of the COVID-19 situation on global sustainability programs. The report synthesizes current research on sustainability marketing, the circular economy, and sustainable business strategies using a systematic literature review approach. The results show that sustainable marketing techniques can significantly impact consumer behavior and promote more environmentally friendly production and consumption patterns. The circular economy concept, which emphasizes resource efficiency and waste minimization, can also aid in sustainable development by fostering new economic opportunities and halting environmental damage. In order to encourage more sustainable practices in the post-pandemic era, the paper offers ideas for businesses and policymakers on how to incorporate sustainable marketing and circular economy principles into their plans. The study adds to the growing body of knowledge on the circular economy and sustainability marketing by pointing out possible avenues for encouraging sustainable consumption and production, which are crucial for reaching the SDGs
A Model of Indonesian Consumers' Online Shopping Behavior, an Extension of TAM Wibasuri, Anggalia; Pratisti, Cahyani; Nurjanah, Indah Ike
International Journal of Artificial Intelligence Research Vol 7, No 1.1 (2023)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1.1115

Abstract

The aim of determining the online shopping behavior of Indonesian consumers was to create a model of online shopping behavior in Indonesia. The specific goal was to examine and develop a model of online shopping behavior in Indonesia using the Technology Acceptance Model, which is integrated with e-trust, security, and perceived risk as moderators. This research used a descriptive analysis method with a quantitative approach. Primary data were obtained by distributing questionnaires with 385 respondents as samples, using an online survey. The questionnaire was analyzed to determine the effect of the Technology Acceptance Model on Purchase Intention in online marketing through the moderating role of trust, security, and risk. The object of this research was online shopping users in Indonesia. The population of this study was all consumers who used the Internet to make online purchases (Blibli.com, Tokopedia.com, Bukalapak.com, Beribenka.com, Shopee.com, or other online product marketing sites) either through smartphone media or other media (PCs, and laptops). Samples were taken using the non-probability sampling technique with the purposive sampling method and analyzed using SEM. The results showed that perceived usefulness positively affected consumer attitudes, perceived ease of use positively affected consumer attitudes, perceived ease of use positively affected purchase intentions, perceived ease of use affected purchase intentions strengthened by perceived risk, consumer attitudes positively affected purchase intentions, attitudes affected purchase intentions strengthened by security, and attitudes affected purchase intentions strengthened by e-trust.
Cultural Change of Mathematics Teachers' Views on Technology: Navigating the Artificial Intelligence Revolution Utami, Niken Wahyu; Sagita, Laela; Rahmawati, Rina Dyah; Nurdianto, Heri
International Journal of Artificial Intelligence Research Vol 8, No 2 (2024): December 2024
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i2.1232

Abstract

The development of technology related to Artificial Intelligence is growing rapidly, and one of its implications is the teaching of mathematics in the classroom. Therefore, it is necessary to conduct research on the perspective of mathematics teachers in addressing the development of artificial intelligence (AI) used in mathematics learning. This study examines the role of AI technology in facilitating pedagogical reform in mathematics education from the perspective of teachers. Through a questionnaire distributed to mathematics teachers, this paper identifies teachers' perspectives on the development of AI and its use in their classrooms. A total of 56 mathematics teachers participated in this study. In addition to the five-item questionnaire, an open-ended questionnaire was also provided. A number of AI that teachers use in their teaching are also mentioned in this paper. The paper also discusses the challenges that mathematics teachers face when using AI in mathematics lesson planning in their classrooms. It concludes that mathematics learning using AI has significant potential to improve students' competencies by equipping them with essential skills for the digital age
ECONOMIC EMPOWERMENT STRATEGY MODEL FOR COASTAL WOMEN ON THE BASIS OF BLUE ECONOMY AND LOCAL POTENTIAL IN SURABAYA Rahmiyati, Nekky -; Rachmawati, Titiek
International Journal of Artificial Intelligence Research Vol 7, No 1.1 (2023)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1.1043

Abstract

This study aimed to determine the role of coastal women in improving the economy of fishermen family, the role of coastal women in implementing blue economy, and the right empowerment strategy model for coastal women. The type of this research was quantitative, the number of samples was 50 and the sampling technique was purpose sampling. This study used SWOT analysis. This research found that coastal women have not played a role in the application of the blue economy, obstacles in the application of the blue economy include: from the side of fishermen (producers) there were still many fishermen's wives who have low knowledge, especially about the blue economy. Practices that were not environmentally friendly, for example the use of plastic in every activity, throwing garbage / waste into the sea / drying the fish on the highway, this showed a low level of understanding the minimize waste, which means that in the production process must produce clean products (clean production) with no waste (zero waste). The role of coastal women in utilizing local potential at tourist beaches was still not optimal because KPPI members did not have skills, especially no innovation and no product variations from fishermen's catches, and weak marketing strategies. The results of the SWOT analysis showed that the main strategy generated was the SO strategy with the highest score of 3.9 in position 1, namely using strengths to seize and take advantage of the maximum opportunities
Piercing the Corporate Veil on the Responsibilities of Limited Liability Company Directors in Nominee Agreements which have the Potential Risk of Lawsuits Rizka Rahadiyani Aisyah; Arman Nefi
International Journal of Artificial Intelligence Research Vol 7, No 1.1 (2023)
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i2.1032

Abstract

Companies are also an important business component and are widely available in the world, including in Indonesia where they are legal entities. The integrity of a member of the company's board of directors and board of commissioners to maintain their loyalty as the party entrusted with managing the company properly and correctly as a responsibility to stakeholders. This action is known as the Piercing the Corporate Veil doctrine, which in this paper is at issue if it turns out that there is a nominee agreement between the directors and shareholders of a third party who is actually the party who is one of the shareholders and what is the potential risk of legal action? If a dispute occurs in the company due to the nominee agreement, the company will experience the risk of loss. The author researches with normative legal research, which involves studying documents or written data, research on legal systematics, legal theory. In the initial stage the author conducted research on documents related to the subject of this discussion. Apart from that, use is based on the internet, newspapers and electronic media. In this case, the action of Piercing the Corporate Veil Shareholders in a Limited Liability Company turns out to be the discovery of a nominee agreement between the directors and shareholders from a third party who is actually the party who is one of the shareholders, so in this case the Nominee Agreement can be null and void by law and an attempt to smuggle the law because the Nominee Agreement has violated several regulations in Indonesia, namely Article 33 of the Investment Law and Article 1320 of the Civil Code and is not valid. The potential risk of a company lawsuit if a dispute occurs is due to the nominee agreement which results in the company experiencing a risk of loss because seen from the position of the Piercing the Corporate Veil Doctrine, it cannot be implemented properly because the agreement between shareholders and directors has been violated. regulations in Indonesia, namely Article 33 of the Investment Law and Article 1320 of the Civil Code. So there is less accountability.

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