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Computer Science
Artificial Intelligence

Utilization of artificial intelligence in education in Indonesia

Profile image of SUROSO , S.Kom., M.I.Kom., M.B.A.SUROSO , S.Kom., M.I.Kom., M.B.A.

2024, Gamar Abdullah, Suroso, Yogi Nurfauzi, La Ode Muhammad Idrus Hamid Basri, Kennedy Acheampong

https://doi.org/10.1016/J.ASR.2021.01.022
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Abstract

Study This investigate trends and focus study related intelligence artificial intelligence (AI) in education in Indonesia. With analyzing publication data, collaboration international, and visualization network, research This identify three focus main research : development system supporter decision, application of AI for increase experience Study students, and implementation chatbots in context education. Results study show enhancement interest to application deep AI technology education in Indonesia, which is reflected of an increasing publication trend. However, challenges like inward integration curriculum existing education, accessibility technology, and problems privacy and ethics still need overcome. Cooperation international, esp with Malaysia, also playing role important in development deep AI research education in Indonesia. Findings This give outlook about development latest in use of AI for support learning and teaching in Indonesia, as well highlighting direction future research in domain This.

Figures (5)
RESULTS AND DISCUSSION Based on Figure 1, research related to artificial intelligence in education in Indonesia reaches peaking in 2023, with amount publication by 70. Increase amount publication This reflect its height interest and focus study to application deep AI technology increase effectiveness learning and teaching in various level education, start from school base until college tall. With deep AI capabilities provide personalization learning, detecting learning patterns students, and provide bait fast turnaround, research This become the more important in face challenge globalization and competition in the digital era.
RESULTS AND DISCUSSION Based on Figure 1, research related to artificial intelligence in education in Indonesia reaches peaking in 2023, with amount publication by 70. Increase amount publication This reflect its height interest and focus study to application deep AI technology increase effectiveness learning and teaching in various level education, start from school base until college tall. With deep AI capabilities provide personalization learning, detecting learning patterns students, and provide bait fast turnaround, research This become the more important in face challenge globalization and competition in the digital era.
Figure 4. Distribution Geographical Indonesian Cooperation
Figure 4. Distribution Geographical Indonesian Cooperation
In figure 6, the new theme in artificial intelligence research in education in Indonesia can identified through marker color yellow on keywords certain, shows that keywords the new become focus study in a number of year final. Wrong One striking keywords in this theme is "chat gpt and chattbott. Existence color yellow on keywords the indicated that study has more intensive on aspects This in a number of year lastly, esp in context Technology in entrepreneurship. From the results research presented, can concluded that interest and focus study to application of artificial intelligence (AI) in education in Indonesia has experience significant improvement. Publication trends show peaking in 2023, reflects its height interest to deep AI technology increase effectiveness learning and teaching in various level education. However, there are a number of necessary challenges overcome, like integration AI technology to in curriculum existing education there is, accessibility technology for all layer society, as well problem privacy and ethics related student data use and retrieval decision. Apart from that, collaboration international also plays role important in development deep AI research education in Indonesia, with collaboration active especially with Malaysia, shows effort for expand understanding and exchange knowledge in this domain globaly. Analysis visualization the network also revealed three focus main research: development system supporter decision, implementation intelligence artificial for increase experience Study students, and development
In figure 6, the new theme in artificial intelligence research in education in Indonesia can identified through marker color yellow on keywords certain, shows that keywords the new become focus study in a number of year final. Wrong One striking keywords in this theme is "chat gpt and chattbott. Existence color yellow on keywords the indicated that study has more intensive on aspects This in a number of year lastly, esp in context Technology in entrepreneurship. From the results research presented, can concluded that interest and focus study to application of artificial intelligence (AI) in education in Indonesia has experience significant improvement. Publication trends show peaking in 2023, reflects its height interest to deep AI technology increase effectiveness learning and teaching in various level education. However, there are a number of necessary challenges overcome, like integration AI technology to in curriculum existing education there is, accessibility technology for all layer society, as well problem privacy and ethics related student data use and retrieval decision. Apart from that, collaboration international also plays role important in development deep AI research education in Indonesia, with collaboration active especially with Malaysia, shows effort for expand understanding and exchange knowledge in this domain globaly. Analysis visualization the network also revealed three focus main research: development system supporter decision, implementation intelligence artificial for increase experience Study students, and development

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EDUCATION IN THE ERA OF ARTIFICIAL INTELLIGENCE: AN EVIDENCE FROM DHAKA INTERNATIONAL UNIVERSITY (DIU)
Centre for Research on Islamic Banking & Finance and Business

This study investigates the transformative impact of artificial intelligence (AI) on education, assessing both its advantages and drawbacks. Employing the random sampling survey method, data was collected from 160 participants at Dhaka International University. The respondents, predominantly aged between 18-21 years with an average age of 20.6, exhibited varying levels of awareness regarding AI tools-46 percent were familiar, 44 percent somewhat aware, and 10 percent unfamiliar. Notably, 72.5 percent of participants gained knowledge about artificial intelligence through online sources such as websites, research papers, and forums. The study identified prominent AI tools used by respondents, with ChatGPT being the most widely employed, alongside Google Translator, Microsoft Bard, Grammarly, QuillBot, and YouChat. ChatGPT, in particular, found extensive application in academic studies, research, website development, and app development. Interestingly, 17.5 percent of respondents reported being paid users of AI tools. Beyond usage patterns, the research delved into the efficacy of AI in enhancing education, addressing privacy concerns, and exploring associated challenges, benefits, impacts, ethical considerations, and potential future directions. Employing a Likert scale for assessment, the study concludes by advocating for the integration of AI in education while underscoring the imperative for safeguards to mitigate potential misuse. This comprehensive exploration provides valuable insights into the evolving landscape of AI within the educational sector.

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Impacts of Artificial Intelligence Technology on Student Learning of Selected College Students in Gumaca, Quezon
Psychology and Education

Psychology and Education: A Multidisciplinary Journal, 2025

This research aimed to describe the impacts of artificial intelligence (AI) technology, specifically ChatGPT, Google Meet, and Google Classroom, on student learning experiences in selected colleges and universities in Gumaca, Quezon. It sought to identify the demographic profile of respondents, their usage of AI technologies, the perceived impacts of AI on various aspects of student learning such as access and equity, personalized learning experience, enhance learning outcome, teacher-student interactions, and practical application, and whether these impacts vary based on demographic profiles. This applied descriptive survey method utilizing researcher-made questionnaires that were validated by experts to gather necessary data. Purposive sampling selected 100 students already integrating AI technology into their studies. Data were analyzed using percentage, frequency, and weighted mean along with One-Way ANOVA to determine significant differences. Findings revealed that the respondents are 19-20 years old (32%), females (67%), and second year college students (32%). All the students use ChatGPT (100%) but not everyone use Google Meet (75%) and Google Classroom (73%). Additionally, the respondents agree on the positive impact of using AI in student learning in terms of access and equity (mean=3.91), personalized learning experience (mean=4.02), enhance learning outcome (mean=4.00), teacher-student interactions (mean=3.87), and practical applications (4.14) but has to improve using AI for 21st century skills development, student progress monitoring, objective grade computation, efficiency in assignment submissions, and providing lifelong learning opportunities. Lastly, ANOVA results showed that there is no significant difference on the perceived impacts of artificial intelligence in students learning when respondents are group according to profiles as to age, sex, and college level. The study recommends for parents, teachers, students, and future researchers to be conscious on the positive application of AI with due guidance, exploration of trends and AI for different context, and consideration of ethical considerations in its utilization.

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AI in Education
Fati Tahiru

Journal of Cases on Information Technology

Artificial intelligence (AI) is developing and its application is spreading at an alarming rate, and AI has become part of our daily lives. As a matter of fact, AI has changed the way people learn. However, its adoption in the educational sector has been saddled with challenges and ethical issues. The purpose of this study is to analyze the opportunities, benefits, and challenges of AI in education. A review of available and relevant literature was done using the systematic review method to identify the current research focus and provide an in-depth understanding of AI technology in education for educators and future research directions. Findings showed that AI's adoption in education has advanced in the developed countries and most research became popular within the Industry 4.0 era. Other challenges, as well as recommendations, are discussed in the study.

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Artificial Intelligence (ΑΙ) in Education—Current Trends
Anastasios Fountis

Algorithms for intelligent systems, 2024

Artificial intelligence (AI) is a crucial pillar for the growth of the educational process in the Internet age. Its constant growth and incorporation into numerous aspects of life, such as education, have given rise to the need to analyze not just its benefits, but also the perspectives it can offer for all levels and types of education. The successful use of information technology in education, whether in live classes or remotely, enhances the quality of instruction and learning. Intelligent education systems are the most important AI-based application in education. With such intelligent education systems, step-by-step teaching approaches are used based on the individual’s demands and learning pace . It is divided into a domain model, a pedagogical model, and a learner model. The subject model provides the background knowledge of the subject to be taught to the learner. The learner model describes the student’s abilities, particularly his or her knowledge .

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    First results of undersea muography with the Tokyo-Bay Seafloor Hyper-Kilometric Submarine Deep Detector
    Marko Holma

    Scientific Reports

    Tidal measurements are of great significance since they may provide us with essential data to apply towards protection of coastal communities and sea traffic. Currently, tide gauge stations and laser altimetry are commonly used for these measurements. On the other hand, muography sensors can be located underneath the seafloor inside an undersea tunnel where electric and telecommunication infrastructures are more readily available. In this work, the world’s first under-seafloor particle detector array called the Tokyo-bay Seafloor Hyper-Kilometric Submarine Deep Detector (TS-HKMSDD) was deployed underneath the Tokyo-Bay seafloor for conducting submarine muography. The resultant 80-day consecutive time-sequential muographic data were converted to the tidal levels based on the parameters determined from the first-day astronomical tide height (ATH) data. The standard deviation between ATH and muographic results for the rest of a 79-day measurement period was 12.85 cm. We anticipate that...

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    Interannual Variability of Water Level in Two Largest Lakes of Europe
    Andrey Kostianoy

    Remote Sensing

    Regional climate change affects the state of inland water bodies and their water balance, which is determined by a number of hydrometeorological and hydrogeological factors. An integral characteristic of changes in the water balance is the behavior of the level of lakes and reservoirs, which not only largely determines the physical and ecological state of water bodies, but also significantly affects the coastal infrastructure and socio-economic development of the region. This paper investigates the interannual variability of the level of the Ladoga and Onega lakes, the largest lakes in Europe located in the northwest of Russia, according to satellite altimetry data for 1993–2020. For this purpose, we used three specialized altimetry databases: DAHITI, G-REALM, and HYDROWEB. Water level data from these altimetry databases were compared with in-situ records at water level gauge stations. Information on air temperature (1945–2019) and precipitation (1966–2019) acquired at three meteost...

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    Terrestrial or oceanic forcing? Water level variations in coastal lagoons constrained by river inflow and ocean tides
    Zacharie Sohou

    Advances in Water Resources

    The study concerns the water level (WL) evolution in lagoons under the influence of tides and river fluxes. We derive new approximate analytical solutions of the Stigebrandt (1980) equations and apply them to the Nokoué Lagoon (Benin), a large tropical coastal lagoon fed by substantial river input.

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    GENESIS: co-location of geodetic techniques in space
    Javier Ventura-traveset

    Earth, Planets and Space, 2023

    Improving and homogenizing time and space reference systems on Earth and, more specifically, realizing the Terrestrial Reference Frame (TRF) with an accuracy of 1 mm and a long-term stability of 0.1 mm/year are relevant for many scientific and societal endeavors. The knowledge of the TRF is fundamental for Earth and navigation sciences. For instance, quantifying sea level change strongly depends on an accurate determination of the geocenter motion but also of the positions of continental and island reference stations, such as those located at tide gauges, as well as the ground stations of tracking networks. Also, numerous applications in geophysics require absolute millimeter precision from the reference frame, as for example monitoring tectonic motion or crustal deformation, contributing to a better understanding of natural hazards. The TRF accuracy to be achieved represents the consensus of various authorities, including the International Association of Geodesy (IAG), which has enunciated geodesy requirements for Earth sciences. Moreover, the United Nations Resolution 69/266 states that the full societal benefits in developing satellite missions for positioning and Remote Sensing of the Earth are realized only if they are referenced to a common global geodetic reference frame at the national, regional and global levels. Today we are still far from these ambitious accuracy and stability goals for the realization of the TRF. However, a combination and co-location of all four space geodetic techniques on one satellite platform can significantly contribute to achieving these goals. This is the purpose of the GENESIS mission, a component of the FutureNAV program of the European Space Agency. The GENESIS platform will be a dynamic space geodetic observatory carrying all the geodetic instruments referenced to one another through carefully calibrated space ties. The co-location of the techniques in space will solve the inconsistencies and biases between the different geodetic techniques in order to reach the TRF accuracy and stability goals endorsed by the various international authorities and the scientific community. The purpose of this paper is to review the state-of-the-art and explain the benefits of the GENESIS mission in Earth sciences, navigation sciences and metrology. This paper has been written and supported by a large community of scientists from many countries and working

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    Satellite Remote Sensing of Surface Winds, Waves, and Currents: Where are we Now?
    Samantha Lavender

    Surveys in Geophysics, 2023

    This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/ sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind-and wave-induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields.

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