Garuda - Garba Rujukan Digital

Training on Portfolio Creation and Learning Media Using Google Sites for Teachers and Students at SMK Muhamadiyah Banjar Sunardi Sunarni; Muhammad Kunta Biddinika; Furizal Furizal; Aldi Bastiatul Fawait; Yana Mulyana
ABDIMAS: Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2022): ABDIMAS UMTAS: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM Universitas Muhammadiyah Tasikmalaya

Website is a need to be very important to create an online presence for individuals, businesses, companies, and education. By using website, everyone can be better to known and widely known on the internet. However, some users still think that having a website should prepare many things, ranging from cost to good coding skills. The presence of the Google company in the world of technology provides convenience through its products. Google Sites is one of the platforms that provides services to make it easier to create the websites that are used as objects of training activities with workshop activity partners by Master Program of Informatics Universitas Ahmad Dahlan and SMK Muhammadiyah Banjar. The purpose of this community service activity is to carry out training on the use of Google Sites in creating portfolios and learning media. The audience of service is teachers and students with a total of 27 participants from SMK Muhammadiyah Banjar West Java Province. The activity was carried out on August 24, 2022. The stages of the activity were preparation, implementation, and evaluation. Preparation is carried out by conducting a pre-test survey of trainees. The implementation is carried out with training and hands on implementation of website creation for each participant. Evaluation of activities is carried out for each stage by collecting post-test from each trainee. The result of the activity is to increase the knowledge of training participants, both students and teaching staff in overcoming problems in the world of technology so as to make it easier to adapt to the industrial world. The training carried out received a very good response with the score of 79.13% stating that they strongly agreed with the advantages of this training.concept of healthy elderly people related to the pandemic.

Integration of AHP and TOPSIS Methods for Small and Medium Industries Development Decision Making Anton Yudhana; Rusdi Umar; Aldi Bastiatul Fawait Fawait
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 5 (2022): Oktober 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Financial problems are one of the reasons why small and medium-sized industries (SMIs) in West Kutai have not developed optimally. Government assistance programs are one of the solutions. This program must be appropriate, so a decision-making tool is needed to help choose the right SMIs to be assisted later. The weight of the criteria was determined using the Analytical Hierarchy Process (AHP) technique, and the priority of the SMIs as the preferred proposal for the recipients of development assistance was determined using the Technique for Other Reference by Similarly to Ideal Solution (TOPSIS) approach. Labor, investment, production capacity, production value, and raw materials were used to determine the priorities of SMIs beneficiaries. Furthermore, TOPSIS prioritizes the development of alternative small and medium-sized industries with types of handicraft commodities. Integration of AHP and TOPSIS methods has been successfully used in the IKM Development Priority Determination Application, with 83.3% precision and 96.4% accuracy achieved by using a confusion matrix so that the IKM ranking can be known. The results of the study found that integration of the two methods was successfully used for Small and Medium Industries Development Decision Making.

IMPLEMENTASI DATA MINING DENGAN ALGORITMA REGRESI LINEAR SEDERHANA UNTUK MEMPREDIKSI NILAI EKSPOR DI KALIMANTAN TIMUR DENGAN APLIKASI RAPIDMINER Rahmah, Sitti Rahmah; Fawait, Aldi Bastiatul
DiJITAC : Digital Journal of Information Technology and Communication DiJITAC, Vol 4 No.2, April 2024
Publisher : Universitas Islam Negeri Sultan Aji Muhammad Idris Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21093/dijitac.v4i2.8963

This research aims to determine the development of export value in East Kalimantan. This research data utilizes secondary data obtained directly from the Central Statistics Agency of East Kalimantan Province. The analysis method applied is a simple linear regression algorithm data mining. Research findings reveal that the export value in East Kalimantan in January 2022 - April 2024 up to the predicted export value in May 2024 - December 2024 experienced a decline in the export value in East Kalimantan. With an accuracy in predicting the RMSE value of 3.182%, this means that the predicted percentage of East Kalimantan's export value is classified as very accurate. The hope of this research is that this research will become a reference for decision making for related parties, so that they can find the best strategy to increase export value in East Kalimantan. In order to realize economic improvement in East Kalimantan in the future.

The Influence of Social Media in Increasing Student Motivation in Mathematics Lessons for Elementary Schools Nursyam, Aisyah; Widyatiningtyas, Reviandari; Palayukan, Hersiyati; Fawait, Aldi Bastiatul
Journal of Social Science Utilizing Technology Vol. 2 No. 1 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v2i1.855

Background. Mathematics learning in elementary schools (SD) often requires innovative approaches to increase student engagement. With the development of technology, the use of social media as a learning tool is starting to become the focus of research to increase students' learning motivation in mathematics. Purpose. The research aims to measure how much influence the use of social media has in increasing students' motivation in learning mathematics in elementary school, as well as providing a concrete understanding of the relationship between social media and motivation to learn mathematics. Method. A quantitative approach using a survey model is used to examine the impact of social media on student motivation. Questionnaires were distributed to elementary school teachers and mathematics education students via Google Form and WhatsApp (WA) groups. Research ethical principles were upheld, and data were analyzed using Miles and Huberman's qualitative data analysis techniques. Results. The majority of respondents gave a positive view of the influence of social media in mathematics learning. However, there are a small number who feel that social media can interfere with studying concentration. The integration of social media needs to be considered wisely to minimize risks and maximize its benefits in mathematics learning. Conclusion. The research results show that social media has great potential in increasing students' motivation in learning mathematics in elementary school. However, its use needs to be managed wisely and responsive to student needs and preferences. Social media integration can be an interesting and effective learning alternative in the context of mathematics learning at school.

Analysis of Student Acceptance of SPADA E-Learning Using UTAUT Method Syekh Budi Syam; Muh. Jamil; Aldi Bastiatul Fawait
Jurnal Informasi dan Teknologi 2024, Vol. 6, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v6i3.590

SPADA UWGM is an e-learning platform used by Widyagama Mahakam University Samarinda (UWGM). This platform has been used since 2020 for the teaching and learning process, both to provide materials, assignments, and quizzes and to take attendance. The use of e-learning is certainly a technological innovation in the field of education. This progress is something that cannot be avoided because it is also strongly supported by the advancement of science, so there needs to be a measurement of the extent to which this e-learning can be accepted from the perception of its users. This study uses the UTAUT method with six variables, namely performance expectancy, effort expectancy, social influence, facilitating condition, use behavior, and Behavioral Intention to measure the level of student acceptance of SPADA UWGM. The questionnaire used was a questionnaire with answer choices in the form of a Likert scale and was processed using the smart PLS application to see the reliability and validity of the questionnaire items and prove the hypothesis between variables with an error tolerance limit of 10%. The results of this study indicate that performance expectancy does not affect behavior intention. While effort expectancy and social influence influence behavior intention. Other things such as facilitation conditions and behavioral intentions influence use behavior. So based on the research conducted, it can be concluded that the performance of the SPADA UWGM e-learning system does not influence students' interest in using and utilizing the existing e-learning system. Meanwhile, social influence and a sense of trust that the existing system is easy to use have a significant influence on students' efforts and intentions in using the SPADA UWGM e-learning system. Other things such as the condition of campus facilities in supporting the use of the system have an influence on students' seriousness in using the e-learning system, which means that the better the facilities, the more students' motivation will increase in utilizing SPADA UWGM sustainably.

Long Short-Term Memory vs Gated Recurrent Unit: A Literature Review on the Performance of Deep Learning Methods in Temperature Time Series Forecasting Furizal, Furizal; Fawait, Aldi Bastiatul; Maghfiroh, Hari; Maâ€™arif, Alfian; Firdaus, Asno Azzawagama; Suwarno, Iswanto
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1546

Temperature forecasting is a crucial aspect of meteorology and climate change studies, but challenges arise due to the complexity of time series data involving seasonal patterns and long-term trends. Traditional methods often fall short in handling this variability, necessitating more advanced solutions to enhance prediction accuracy. LSTM and GRU models have emerged as promising alternatives for modeling temperature data. This study is a literature review comparing the effectiveness of LSTM and GRU based on previous research in temperature forecasting. The goal of this review is to evaluate the performance of both models using various evaluation metrics such as MSE, RMSE, and MAE to identify gaps in previous research and suggest improvements for future studies. The method involves a comprehensive analysis of previous studies using LSTM and GRU for temperature forecasting. Assessment is based on RMSE values and other metrics to compare the accuracy and consistency of both models across different conditions and temperature datasets. The analysis results show that LSTM has an RMSE range of 0.37 to 2.28. While LSTM demonstrates good performance in handling long-term dependencies, GRU provides more stable and accurate performance with an RMSE range of 0.03 to 2.00. This review underscores the importance of selecting the appropriate model based on data characteristics to improve the reliability of temperature forecasting.

Evolution of the Use of Artificial Intelligence in Mobile Applications to Improve the Efficiency of Public Service Loso Judijanto; Arief Yanto Rukmana; Aldi Bastiatul Fawait; Sitti Rahmah; Sugiarto Sugiarto
West Science Social and Humanities Studies Vol. 2 No. 11 (2024): West Science Social and Humanities Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsshs.v2i11.1457

The integration of artificial intelligence (AI) into mobile applications has transformed public service delivery by enhancing efficiency, accessibility, and responsiveness. This study employs a bibliometric approach to analyze the evolution of AI applications in public service, focusing on research trends, key contributors, and thematic developments from 2000 to 2024. The findings reveal a rapid increase in research output since 2018, driven by advancements in enabling technologies such as IoT, 5G, and machine learning, as well as global challenges like the COVID-19 pandemic. Key application areas identified include healthcare, smart cities, and governance, with AI-powered mobile apps demonstrating significant potential in addressing societal needs. However, challenges related to data privacy, algorithmic bias, and technical infrastructure persist. This study underscores the importance of ethical frameworks, interdisciplinary collaboration, and localized solutions to maximize the impact of AI in public service delivery. The findings offer valuable insights for researchers, practitioners, and policymakers seeking to leverage AI for smarter and more equitable public services.

The Influence of Social Media in Increasing Student Motivation in Mathematics Lessons for Elementary Schools Nursyam, Aisyah; Widyatiningtyas, Reviandari; Palayukan, Hersiyati; Fawait, Aldi Bastiatul
Journal of Social Science Utilizing Technology Vol. 2 No. 1 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v2i1.855

Background. Mathematics learning in elementary schools (SD) often requires innovative approaches to increase student engagement. With the development of technology, the use of social media as a learning tool is starting to become the focus of research to increase students' learning motivation in mathematics. Purpose. The research aims to measure how much influence the use of social media has in increasing students' motivation in learning mathematics in elementary school, as well as providing a concrete understanding of the relationship between social media and motivation to learn mathematics. Method. A quantitative approach using a survey model is used to examine the impact of social media on student motivation. Questionnaires were distributed to elementary school teachers and mathematics education students via Google Form and WhatsApp (WA) groups. Research ethical principles were upheld, and data were analyzed using Miles and Huberman's qualitative data analysis techniques. Results. The majority of respondents gave a positive view of the influence of social media in mathematics learning. However, there are a small number who feel that social media can interfere with studying concentration. The integration of social media needs to be considered wisely to minimize risks and maximize its benefits in mathematics learning. Conclusion. The research results show that social media has great potential in increasing students' motivation in learning mathematics in elementary school. However, its use needs to be managed wisely and responsive to student needs and preferences. Social media integration can be an interesting and effective learning alternative in the context of mathematics learning at school.

Concerns of Ethical and Privacy in the Rapid Advancement of Artificial Intelligence: Directions, Challenges, and Solutions Furizal, Furizal; Ramelan, Agus; Adriyanto, Feri; Maghfiroh, Hari; Ma'arif, Alfian; Kariyamin, Kariyamin; Masitha, Alya; Fawait, Aldi Bastiatul
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.24090

AI is a transformative technology that emulates human cognitive abilities and processes large volumes of data to offer efficient solutions across various sectors of life. Although AI significantly enhances efficiency in many areas, it also presents substantial challenges, particularly regarding ethics and user privacy. These challenges are exacerbated by the inadequacy of global regulations, which may lead to potential abuse and privacy violations. This study provides an in-depth review of current AI applications, identifies future needs, and addresses emerging ethical and privacy issues. The research explores the important roles of AI technologies, including multimodal AI, natural language processing, generative AI, and deepfakes. While these technologies have the potential to revolutionize industries such as content creation and digital interactions, they also face significant privacy and ethical challenges, including the risks of deepfake abuse and the need for improved data protection through platforms like PrivAI. The study emphasizes the necessity for stricter regulations and global efforts to ensure ethical AI use and effective privacy protection. By conducting a comprehensive literature review, this research aims to provide a clear perspective on the future direction of AI and propose strategies to overcome barriers in ethical and privacy practices.

Penerapan Artificial Intelligence untuk Analisis Risiko Proyek Green bonds di Indonesia Judijanto, Loso; Fawait, Aldi Bastiatul
Sanskara Akuntansi dan Keuangan Vol. 3 No. 02 (2025): Sanskara Akuntansi dan Keuangan (SAK)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/sak.v3i02.521

The growing need for sustainable financing has positioned Green bonds as an important instrument to fund environmentally friendly projects. However, these projects face various risks, including financial, environmental, and regulatory challenges, especially in emerging markets such as Indonesia. This study explores the application of Artificial Intelligence (AI) in mitigating these risks through qualitative research involving five interviewees from the fields of finance, environment, and technology. Using NVIVO for thematic analysis, the findings highlight the potential of AI in predictive analysis, environmental monitoring, and risk scenario simulation, while overcoming challenges such as data quality, cost, and regulatory inconsistency. This study underscores the transformative role of AI in improving transparency, efficiency, and scalability in green bond risk management, and provides recommendations to stakeholders to foster sustainable finance practices in Indonesia.

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