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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 83 Documents
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Search results for , issue "Vol 8, No 1.1 (2024)" : 83 Documents clear
CONTRIBUTION OF SOCIAL CAPITAL AND POLITICAL MARKETING TO THE FIGURE OF THE MILLENNIAL GENERATION IN LOCAL POLITICAL CONTESTS IN INDONESIA (Case Study of Muhammad Bobby Afif Nasution's Victory in the 2020 Medan City Pilkada) Fadli, Teuku Faishal; Aminuddin, M. Faishal; Mashuri, Ali
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.v8i1.1.1276

Abstract

This study aims to analyze the political marketing strategy, social capital, and millennial generation of the Bobby and Akhyar pair in the 2020 Medan City Pilkada. This study uses a qualitative case study research method. The research design in this study uses an explanatory case study. The research data consists of primary data and secondary data. The data collection techniques used by the researcher are Documentation, Interviews, and Observation. Based on the results of the study, it shows that the political marketing strategy and social capital carried out by Bobby Nasution as a millennial political actor in the 2020 Medan City Pilkada are by implementing puss marketing (direct meetings with the community), pull marketing (utilizing media in branding his image), pass marketing (utilizing the support of influential figures in campaigning for his political ideas). Bobby Nasution's social capital consists of friendships with influential figures in Medan City, being active as a member of the PDI Party, as the son-in-law of Mr. Jokowi as President of Indonesia and others. The relationship between aspects of political marketing, social capital and millennial political actors in the victory of the Bobby-Aulia pair in the 2020 Medan City Pilkada, namely the victory obtained by the Bobby Nasution pair in the 2020 Medan City Pilkada cannot be separated from the contribution of political marketing carried out, the social capital owned and their brand image as millennial political actors. The three aspects above are interconnected in their implementation, for the ideas and political promises offered will be conveyed through direct meetings with the community, uploaded on social media, forwarded by influential figures, and channeled and assisted by the social capital they have, such as being campaigned by their supporting parties, by their business relations, or by youth communities that are included in the millennial generation community.
Sahala in Digital Era: Artificial Intelligence and the Future of Batak Church Leadership Siagian, Riris Johanna; Limbong, Sukanto
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.v8i1.1.1348

Abstract

The objective of this study is to show that a deeper comprehension of Sahala, its cultural background, and Batak church leadership will provide insights into the various potential impacts of integrating sensors and algorithms into sociocultural practices. This study employed a qualitative research approach and descriptive methods. The choice of a qualitative paradigm is based on the study's aim to investigate and describe the identified issues, specifically the functions of the church leader and the church through Sahala. The purpose of qualitative research is to provide an in-depth analysis or description of a phenomenon, drawing from the significance derived from observed occurrences. This research reveals evolving church leadership dynamics in the age of artificial intelligence. As technology advances rapidly, church leaders must demonstrate adaptability and situational awareness. They need to modify their leadership approaches to strike a balance between traditional and modern methods. The study also underscores the necessity of ethically incorporating Sahala into AI systems. When considering the use of AI to integrate Sahala into genetic parenting, it is crucial to ensure that the technology respects traditions and has the potential to foster the development of genuine individuals. Moreover, community involvement is essential to incorporate their viewpoints into the technology's development process. Technologies that disregard community input pose significant moral risks, which can only be properly evaluated and mitigated through active engagement with the community
Collaborative Governance Strategy In Accelerating Vaccination Through Vaksinasi Merdeka (Independence Vaccination) Innovation Program In Jakarta City Area Rahmawati, Devie; Anindhita, Wiratri; Imran, Mohammad Fadil; Bachtiar, Youna Chatrine; Abdullah, Zulhamri Bin; Ramadhan, Muhammad Zaky; Lumakto, Giri
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.v8i1.1.1316

Abstract

Polda Metro Jaya with the Vaksinasi Merdeka (independent vaccination) innovation program has initiated a community-based and collaborative governance strategy where Polda Metro Jaya team gone directly to the community to study, innovate and implemented a better vaccination program, that proven to be more effective and efficient than any other vaccination program. The use of ethnographic study for ten months research, found that this success of the program started with the data science approach that resulted with a vaccination innovation program design that are closer and familiar to the people in the DKI Jakarta area.
Investigation of Determinants of Financial Distress in Manufacturing Companies Mulatsih, Listiana Sri; Dharmawan, Donny; Tumiwa, Ramon Arthur Ferry; Judijanto, Loso; Alfiana, Alfiana
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.v8i1.1.1323

Abstract

Financial distress refers to a continuous decline in a company's financial performance, necessitating prediction and mitigation. It typically begins with the company’s inability to meet its short-term obligations, signaling a deterioration in financial condition. This study aims to examine the effects of Return on Assets (ROA), Current Ratio (CR), and Debt to Equity Ratio (DER) on financial distress, with company size serving as a moderating variable. The research employs regression analysis and quantitative methods, focusing on manufacturing firms listed on the Indonesia Stock Exchange that consistently published financial reports from 2020 to 2023. Using purposive sampling, the study selected 40 samples from 10 companies, with data analyzed through Partial Least Squares-Structural Equation Modeling (PLS-SEM). The findings reveal that ROA significantly impacts financial distress, while CR and DER have no such effect during the observed period. Furthermore, company size moderates the relationship between ROA and CR with financial distress but does not moderate the influence of DER on financial distress. These results provide managerial implications, serving as indicators for corrective actions to prevent financial distress or potential bankruptcy in manufacturing companies
Interest Rate Policy Moderate The Performance Impact On Banking Stock Price In Indonesia Sari, Laynita; Assagaf, Aminullah; Lusiana, Lusiana; Elfiswandi, Elfiswandi; Zefriyeni, Zefriyeni
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.v8i1.1.1352

Abstract

The stock price is a factor that investors must consider in investing. The stock price is an indicator of the successful management of the company. An increase in share price will reflect an increase in shareholder wealth as an investor. There is a phenomenon in banking stock prices in Indonesia from 2020-2021, where share prices have decreased yearly. This study aimed to investigate the effect of company performance on stock prices by using interest policy as a moderating variable. The method used in this research is panel data regression. The results show that performance positively affects stock prices, and interest policy moderates the relationship between performance and stock prices.
Understanding Tourism Behaviour Through Exploratory Data Analysis with Machine Learning on Search Engine Data: Case Study in Bangka Belitung Islands, Indonesia Divo Dharma Silalahi; Nidia Mindiyarti
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.v8i1.1.1372

Abstract

Analyzing tourist behaviour through Google search data offers a dynamic, real-time approach to understanding travel preferences. This study employs Exploratory Data Analysis (EDA) alongside machine learning techniques such as hierarchical clustering, Principal Component Analysis (PCA), Strength Variables Index (SVI), heat map generation, and correlation matrix analysis to explore the key tourism drivers in Bangka Belitung. These drivers are categorized into demand-side factors—including tourist preferences, curiosity, seasonality, and economic conditions—and supply-side factors, such as transportation, accommodation, activities, pricing, culinary tourism, and local attractions. The findings reveal that transportation and accommodation consistently emerge as the most influential drivers in both regions, highlighting the importance of accessibility and lodging availability. Bangka emphasizes culinary experiences and price sensitivity, while Belitung is more influenced by economic conditions and seasonality. Peak tourism periods are identified during Chinese New Year in February, New Year, and mid-year school holidays in June to July. In Belitung, culinary tourism and seasonal activities see increased interest during February and October, while Bangka shows steady interest in beach-related activities and culinary offerings throughout the year. . Misalignment between supply-side factors, such as limited affordable accommodation or transportation options, can impact tourism performance during these periods. These insights offer practical recommendations for local governments, tourism boards, and businesses to refine marketing strategies, enhance tourist experiences, and optimize tourism infrastructure. . Focusing on affordable travel and culinary experiences for Bangka seasonal tourism and economic preferences for Belitung can help maximize tourism potential and drive sustainable growth in the region
Bearing Capacity in Reinforced Soil: A Systematic Review of Modern Assesment Methods Putri, Lusi Dwi
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.v8i1.1.1301

Abstract

This systematic literature review  aims to thoroughly analyze the probabilistic methods used to assess the bearing capacity of reinforced soil , with a focus on identifying research trends, gaps, and evaluating various techniques such as Monte Carlo simulation, reliability-based design, and the stochastic finite element method (SFEM). The review follows established SLR protocols, employing purposive sampling from scientific databases such as Scopus to select peer-reviewed articles and conference papers. The dataset includes 113 full-text articles, 9 books, and 420 non-full-text entries, totaling 542 sources. Data collection was guided by predetermined inclusion and exclusion criteria, and a coding framework was utilized to categorize and compare key variables, including probabilistic methods and research outcomes. Qualitative synthesis was used for theme extraction, while quantitative assessment evaluated the effectiveness of the methods. The main contribution of this study lies in highlighting the strengths, limitations, and practical applicability of various probabilistic approaches, while advocating for the further integration of probabilistic and deterministic methods to enhance the reliability of soil reinforcement design. This review provides valuable insights for geotechnical engineers and researchers, advancing the understanding of probabilistic methods in improving the performance of reinforced soil.
ENHANCING COMMUNITY HEALTH CENTER PERFORMANCE THROUGH PUBLIC SERVICE INNOVATION AND DIGITAL TRANSFORMATION STRATEGIES Prianto, Arif; Rahayu, Agus; Gaffar, Vanessa; Adiwibowo, Lili
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.v8i1.1.1380

Abstract

The performance of the Community Health Center (Puskesmas) has been in the spotlight of all parties concerned with its ability to adopt the right innovation strategy and implement appropriate digital transformation. This research aims to uncover (1) how public service innovation strategies impact digital transformation implementation; (2) their effect on Puskesmas performance; (3) the impact of digital transformation implementation on Puskesmas performance; and (4) the mediating role of digital transformation in this relationship within West Java, viewed from a strategic management perspective. This quantitative study was conducted across 285 from 1,098 Puskesmas in West Java Province, utilizing proportional random sampling. The sample consisted of Puskesmas distributed across cities and districts in the region, ensuring representation from each area. A questionnaire with a 5-point rating scale was the primary research instrument, validated for accuracy and reliability. Data analysis included descriptive categorization and inferential analysis using Partial Least Square (PLS) via SmartPLS. The study found that public service innovation strategies positively impacted digital transformation implementation and Puskesmas performance. Additionally, digital transformation implementation positively influenced Puskesmas performance, with digital transformation partially mediating the relationship between innovation strategies and performance.
Public Service: Digital Transformation Building Smart City In Makassar City Maldun, Syamsuddin; Juharni, Juharni; Ridho, Muhmmad; Anas, Ali; Afrisal, Ade ferry
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.v8i1.1.1379

Abstract

The demands of the era of globalization of modern government systems require the management of changes in district/city governments to improve so that stakeholders can access maximum service. For this, an applicable work mechanism is needed through the design of a prototype model of Digital Transformation of Public Services e-Government. The type of research used is phenomenological and qualitative descriptive approach. The data collection method used is triangulation, namely: survey, interview, and document analysis. Data analysis uses data collection, data condensation, data presentation, verification and drawing conclusions. Research results: focus (1) The reality of the institutional structure and human resources of the Communication and Information Service still experiences various challenges and weaknesses that must be anticipated immediately, (2) Determinant factors in capacity development originating from internal sources, namely publication, polling up, and decision-making and external opportunities supported by the local government. Meanwhile, internal obstacles are the still strong interests of political parties and external challenges are that public participation is still lacking, and (3) Prototype model of Digital Transformation of Public Services e-Government, is actually a public right and at the same time an obligation of the government, Management of existing public services system, separately accommodates data exchange between institutions, and Management of public services according to regulations, which are guided by Law 37/2008, Law 25/2009 and Regulation of the Minister of State Apparatus Empowerment and Bureaucratic Reform 27/2014 is a combination of complementary nomenclature.
Sentiment Analysis And Topic Extraction Related To The 2024 Indonesian Presidential And Vice Presisdential Election Using Deep Learning Methods Tatulus, Raffael Lucas; Wulandhari, Lili Ayu
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.v8i1.1.1378

Abstract

This research examines public sentiment and discourse surrounding the 2024 Indonesian Presidential and Vice Presidential Election through analysis of YouTube comments. Using a combination of deep learning techniques, specifically Long Short-Term Memory (LSTM) networks for sentiment analysis and Latent Dirichlet Allocation (LDA) for topic extraction, we analyzed public responses to the three presidential candidates. The LSTM model achieved varying accuracy rates across candidates: 58% for Anies Baswedan, 61% for Prabowo Subianto, and 71% for Ganjar Pranowo, with consistently high recall rates of 100% across all candidates. Topic extraction through LDA revealed distinct themes in public discourse, including leadership qualities, policy implementations, and campaign promises. The research methodology involved web scraping YouTube comments from January to October 2023, followed by comprehensive text preprocessing and analysis. Our findings provide valuable insights into public opinion dynamics and key discussion topics during the election period, contributing to the understanding of social media's role in Indonesian political discourse. This study demonstrates the effectiveness of combining deep learning approaches for analyzing large-scale social media data in the context of political communications

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