SSShaumiwaty Shaumiwaty

Shaumiwaty Shaumiwaty

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Shaumiwaty Shaumiwaty has a total of 6 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Enhancing Personalized Learning Using Artificial Intelligence and Machine Learning Approaches

    by Shaumiwaty Shaumiwaty, Mochamad Heru Riza Chakim, Heni Nurhaeni, Victorianda

    The convergence of artificial intelligence (AI) and machine learning (ML) technologies has revolutionized the education landscape, shifting paradigms toward individualized and optimized learning environments. By harnessing AI predictive power and ML adaptive capabilities, educational outcomes are enhanced while equipping teachers with data driven insights for informed decision making. The primary objective of this research is to explore how customized learning environments, ML models, performance measurement, and AI algorithms improve educational outcomes and learning experiences. Despite the rapid advancements in AI driven education, a gap exists in the integration of AI powered personalization with statistical validation techniques like SmartPLS, particularly in evaluating its direct impact on student engagement and performance. The novelty of this study lies in its emphasis on AI driven customization in learning, utilizing advanced statistical validation techniques to provide empirical support for personalized education models. The method involves a survey based approach combined with SmartPLS statistical modeling to analyze correlations between AI driven learning adaptations and educational outcomes. The findings from the result and discussion indicate a positive impact of AI algorithms and ML models on academic success, individualized learning, and improved performance measures, with most hypotheses yielding significant results. These insights align with emerging trends in personalized and adaptable learning and technological advancements, such as immersive experiences and the integration of virtual reality. By addressing the research gap and validating AI driven learning models through SmartPLS, this study contributes to the growing body of knowledge in AI enhanced education, demonstrating the effectiveness of intelligent, data-driven learning environments in fostering better academic performance and engagement.


  • Open Access

    THE ANALYSIS OF GRAMATICAL AND LEXICAL ERRORS ON THE STUDENTS' THESES OF IAIN TAKENGON

    by Shaumiwaty Shaumiwaty, Imam Munandar

    This research used the Error Analysis (EA) method to examine the grammatical mistakes made by English department students of the State Institute of Islamic Studies (IAIN) Takengon. The thesis works produced by those students were the focus of this study. Six students' theses were mined for information, specifically chapters four and five. The authors collected data from students, recognized grammatical faults, categorized errors in students' theses to estimate the frequency of errors, and then converted the data into percentages for analysis. Evidence suggests eleven distinct categories of writing mistakes made by students. There are 6% cases of improper subject-verb agreement, 3% cases of wrong word order, 10% cases of improper preposition, 17% cases of improper article use, 3% cases of improper pluralization, 16% cases of improper punctuation, 6% cases of improper auxiliary use, 24% cases of obscene, unnecessary words, 6% cases of wrong word choice, 6% cases of improper parallel structure, and 3% cases of redundant expression. In addition, the author counted 175 different typos. Punctuation, introductory phrase, and adverbial errors predominate. According to the findings, students' grammatical mistakes are fueled by their inability to master the rules of the target language and their limited familiarity with its vocabulary and structures.


  • Open Access

    HERMENEUTIKA DAN KHAZANAH KEILMUAN ISLAM

    by Shaumiwaty Shaumiwaty, Evanirosa Evanirosa, Rahmat Hidayat

    Hermeneutika as an art include three component. There are text, interpreter, and listener. The role of hermeuneutika explain the text about the writer think. In the process has some problem between the writer and the interpreter byself. The interpreter must known the massage and try to understand the text meaning. According to Muhammad Arkoun and Nasr Hamid Abu Zayd that hermeuneutika can applied in Quran. Alquran was formed by reality, culture and make Quran as a language text. Meanwhile reality, culture and language not loose from the history, because alquran was a history text.Abstrack: Hermeneutika sebagai seni menafsirkan mengharuskan tiga komponen, yakni teks, penafsir dan penyampaian kepada pendengar. Hermeneutika berperan menjelaskan teks seperti apa yang diinginkan oleh si pembuat teks tersebut. Dalam proses tersebut, terdapat pertentanggan antara pikiran yang diarahkan pada objek dan pikiran penafsir sendiri. Orang yang melakukan interpretasi harus mengenal pesan dan kecondongan sebuah teks, lalu meresapi isi teks dan mengusainya. Mohammad Arkoun dan Nasr Hamid Abu Zayd yang keduanya sama berpendapat bahwa hermeneutika dapat diterapkan pada Al Qur’an. Al-Quran yang terbentuk melalui realitas, budaya dan terungkapkan dalam bahasa menjadikan al-Quran sebagai teks bahasa. Sedang realitas, budaya dan bahasa itu sendiri tak lepas dari sisi historis yang melingkupinya, karena itu al-Quran juga merupakan teks historis. Kata Kunci: Hermeneutika, Khazanah, Keilmuan, Islam.