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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Pendidikan Bahasa dan Sastra Indonesia TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JSI: Jurnal Sistem Informasi (E-Journal) Register: Jurnal Ilmiah Teknologi Sistem Informasi Proceeding of the Electrical Engineering Computer Science and Informatics Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer JURNAL REKAYASA TEKNOLOGI INFORMASI Query : Jurnal Sistem Informasi Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) EDUKATIF : JURNAL ILMU PENDIDIKAN Jurnal Basataka (JBT) JISKa (Jurnal Informatika Sunan Kalijaga) Indonesian Journal of Electrical Engineering and Computer Science EARR TEPIAN Jurnal Tinta: Jurnal Ilmu Keguruan dan Pendidikan Buletin Poltanesa Daengku: Journal of Humanities and Social Sciences Innovation DIKSI: Jurnal Kajian Pendidikan dan Sosial JUrnal Riset Ilmu Pendidikan AKADEMIK: Jurnal Mahasiswa Humanis Journal of Innovation Research and Knowledge Jurnal Sistem Informasi Jurnal INFOTEL Jurnal Informatika Polinema (JIP)
Ramadiani -
Universitas Mulawarman
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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Relasi Manusia dan Lingkungan dalam Sastra Indonesia: Studi Literatur Berbasis Ekologi Budaya Halimatusya'diyah; Ramadiani, Ramadiani
Jurnal Tinta Vol. 7 No. 2 (2025): Jurnal Tinta
Publisher : Universitas Al-Qolam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35897/jurnaltinta.v7i2.1877

Abstract

Penelitian ini mengkaji relasi manusia dan alam dalam perspektif ekologi budaya melalui analisis terhadap enam karya sastra Indonesia, baik dalam bentuk cerpen, novel, maupun puisi. Pendekatan ekologi budaya yang dikembangkan oleh Julian H. Steward menjadi kerangka teoretis untuk menelaah bagaimana budaya, sistem kepercayaan, teknologi, dan kekuasaan membentuk hubungan manusia dengan lingkungannya. Setiap karya menunjukkan wajah relasi yang berbeda: dari harmoni spiritual masyarakat tradisional, eksploitasi kapitalistik oleh kekuasaan, hingga praktik kultural yang menjaga kelestarian alam. Metode yang digunakan dalam penelitian ini adalah metode SLR (Systematic Literature Review). Hasil kajian ini menunjukkan bahwa karya sastra dapat menjadi medium reflektif dan kritis terhadap transformasi relasi ekologis manusia, serta berperan penting dalam membangun kesadaran ekologi berbasis budaya lokal.
Evaluasi Kualitas Website SMK Negeri 1 Lhoknga Metode Webqual 4.0 Wulandari, Yuli; Anita, Anita; Puspitasari, Ni Luh Gede Dian; Ramadiani, Ramadiani
AKADEMIK: Jurnal Mahasiswa Humanis Vol. 5 No. 3 (2025): AKADEMIK: Jurnal Mahasiswa Humanis
Publisher : Perhimpunan Sarjana Ekonomi dan Bisnis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37481/jmh.v5i3.1645

Abstract

The rapid advancement of information and communication technology has encouraged educational institutions to optimize their digital platforms, particularly school websites, to support academic and administrative activities. However, ensuring that these websites meet the needs and expectations of their users requires regular evaluation. This study aims to assess the quality of the SMK Negeri 1 Lhoknga website using the Webqual 4.0 method, which evaluates three main dimensions: usability, information quality, and service interaction quality. A descriptive quantitative approach was employed through a survey involving 61 active users, including students, teachers, and administrative staff, selected using purposive sampling. Data were collected via an online questionnaire based on the Webqual 4.0 indicators, utilizing a five-point Likert scale, and analyzed using descriptive statistics. The findings show that all three dimensions are categorized as “good,” with service interaction quality scoring the highest (3.81), followed by usability (3.79) and information quality (3.78). The dominant factor influencing user satisfaction was service interaction quality, highlighting the importance of system stability, accessibility, and security. Recommendations include regularly updating content, implementing a more modern and responsive design, and adding interactive features such as live chat and digital suggestion boxes to enhance user experience. These results provide practical insights for improving the school’s digital services and contribute to the broader discussion on educational website quality assessment.
Evaluasi Kualitas Sistem Informasi Akademik Menggunakan Metode System Usability Scale di SMK Negeri 2 Sangatta Utara Hariyanti, Titik; Ilma, Okta Usrifatin; Ramadiani, Ramadiani
DIKSI: Jurnal Kajian Pendidikan dan Sosial Vol. 6 No. 4 (2025): Diksi: Jurnal Kajian Pendidikan dan Sosial
Publisher : Yayasan Pendidikan Bima Berilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53299/diksi.v6i4.2426

Abstract

Penelitian ini bertujuan mengukur seberapa baik sistem informasi akademik yang digunakan di SMK Negeri 2 Sangatta Utara. Pengukuran dilakukan dengan menggunakan metode System Usability Scale (SUS). Sistem informasi akademik ini berperan penting dalam membantu mengurus berbagai kegiatan pendidikan, seperti mendaftarkan siswa, memberi nilai, serta membuat laporan akademik. Namun, kemudahan penggunaan dan tingkat kepuasan pengguna sangat memengaruhi efektivitas sistem tersebut. Dengan pendekatan kuantitatif, data dikumpulkan melalui pemberian kuesioner SUS kepada pengguna sistem, yaitu guru dan staf administrasi. Hasil evaluasi menunjukkan bahwa sistem informasi akademik yang digunakan berada dalam kategori marginal, sehingga perlu ditingkatkan agar lebih mudah digunakan, dengan skor SUS rata-rata sebesar 51.344, temuan ini memberikan gambaran yang jelas tentang tingkat kemudahan penggunaan sistem. Hasil ini menjadi dasar untuk memberikan saran pengembangan selanjutnya agar sistem lebih efisien dan nyaman digunakan di lingkungan sekolah.
Efektitivitas Aplikasi Exam Browser dalam Evaluasi Ujian Online di Sekolah Menengah Atas Gore, Krisantus Gore; Soraya, Nova Intan; Ramadiani, Ramadiani
EDUKATIF : JURNAL ILMU PENDIDIKAN Vol 7, No 4 (2025): Agustus
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/edukatif.v7i4.8535

Abstract

Sistem evaluasi yang baik dan aman diperlukan untuk digitalisasi pendidikan, terutama untuk ujian yang dilakukan secara online di sekolah menengah. Tujuan dari penelitian ini adalah untuk mengetahui seberapa baik aplikasi Exam Browser mendukung ujian sumatif ganjil dan genap di SMA Negeri 1 Sangatta Utara. Penelitian menggunakan pendekatan deskriptif kuantitatif dan mengumpulkan data melalui observasi, kuesioner, wawancara, dan dokumentasi. Selain itu, data dianalisis menggunakan model Miles dan Huberman. Hasil penelitian menunjukkan bahwa Exam Browser dapat meningkatkan integritas ujian dengan membatasi akses perangkat, memberikan kemampuan reshuffle soal, dan memungkinkan guru untuk mempercepat proses koreksi dan rekap nilai. Karena aplikasi ini mendorong kemandirian belajar dan mengurangi praktik kecurangan, respons guru dan siswa biasanya positif. Namun, masih ada kendala teknis, terutama terkait dengan keterbatasan perangkat siswa dan masalah jaringan, tetapi masalah ini diatasi dengan bantuan tim IT sekolah dan fasilitas komputer siswa. Meskipun demikian, Exam Browser masih berfungsi dengan baik sebagai sarana evaluasi ujian online, dan perlu terus mengoptimalkan fiturnya untuk mengikuti perkembangan teknologi dan memenuhi kebutuhan siswa
LQ45 Stock Recommendations with Fundamental Analysis Using the Simple Additive Weighting Method Ramadiani, Ramadiani; Idrus, S. Saleh Al; Jundillah, Muhammad Labib
TEPIAN Vol. 5 No. 4 (2024): December 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i4.3200

Abstract

Shares are a sign of ownership of a person or entity in a company or limited liability company. Shares are in the form of a piece of paper that explains that the paper's owner is the owner of the company that issued the securities. In the Indonesia Stock Exchange (IDX) there are several kinds of stock indices, one of which is LQ45. It is known that until 2020 there were 2.48 million investors in the capital market. However, it should be noted that of the large number of investors, 85% to 90% of investors experience failure or loss. This happens because investors do not have adequate skills and knowledge in investing in stocks. Therefore, a system is needed that can assist in determining the selection of LQ45 stocks, namely a decision support system (DSS). This system was built web-based using the Simple Additive Weighting (SAW) method to determine the order of the most recommended stocks in the garden. This study uses 45 stocks as alternative data and 5 selection criteria, namely Return on Assets (ROA), Price to price-to-earnings ratio (PER), Price to Book Value (PBV), Net Profit Margin (NPM), and Debt to Equity Ratio (DER). The implementation of the SAW method on the system produces a sequence of LQ45 stock recommendations, namely Adaro Energy Indonesia as the best alternative with the highest preference value of 0.925.
Representasi Bahasa Ritual Mantra dan Doa Nelayan Bajau: Tinjauan Literatur Review Ira, Taqdiraa; Ramadiani, Ramadiani
Jurnal Pendidikan Bahasa dan Sastra Indonesia Vol 14, No 3 (2025)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/133872-019883

Abstract

 Language in traditional societies serves a broader function than mere communication; it acts as a representation of culture, spirituality, and collective identity. This study focuses on ritual language in the form of prayers and mantras used by the Bajau fishing community, a maritime group deeply connected to the sea as the center of their livelihood and belief system. Employing an interdisciplinary approach that integrates anthropological linguistics, semiotics, and maritime cultural studies, this research aims to explore the symbolic and performative representations of language in Bajau ritual practices. A mixed-method approach is applied, with bibliometric data collected through Publish or Perish and analyzed using VOSviewer software. The analysis reveals a growing academic interest in the semantics and symbolism of Bajau prayers and mantras, with a dominant focus on their linguistic-performative function as a medium of communication with supernatural entities. This study underscores the importance of documenting and analyzing ritual language as a means of preserving oral cultural heritage and strengthening local identity amid the pressures of modernization. Keywords: ritual language, Bajau community, mantra, prayer, semiotics, maritime culture
IMPLIKASI PENGGUNAAN AI DALAM PEMBELAJARAN TEKS BAHASA INDONESIA PADA JENJANG SMP: SEBUAH KAJIAN SLR Harman Harman; Yunia Hardiani; Desy Sitti Kahdijah; Ramadiani Ramadiani; Yusak Hudiyono
Jurnal Basataka (JBT) Vol. 8 No. 2 (2025): Desember 2025
Publisher : Prodi Pendidikan Bahasa dan Sastra Indonesia, Universitas Balikpapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36277/basataka.v8i2.1254

Abstract

AI kini digunakan sebagai alat bantu pembelajaran yang mampu menyediakan umpan balik otomatis, memfasilitasi analisis teks, meningkatkan motivasi belajar, serta mendukung proses menulis dan membaca secara lebih efektif. Penelitian ini bertujuan untuk menganalisis implikasi penggunaan teknologi AI dalam pembelajaran teks Bahasa Indonesia melalui pendekatan Systematic Literature Review (SLR). Pengumpulan data dilakukan dengan menelusuri berbagai artikel ilmiah pada Google Scholar, Garuda, dan ResearchGate dengan rentang waktu 2023–2025, menggunakan kata kunci yang relevan dengan pemanfaatan AI dalam pembelajaran teks. Artikel yang ditemukan kemudian diseleksi melalui proses peninjauan judul, abstrak, serta ketersediaan teks lengkap untuk menentukan relevansi. Data yang diperoleh dianalisis menggunakan metode analisis tematik untuk mengidentifikasi pola, temuan, dan isu-isu yang muncul dari masing-masing penelitian. Berdasarkan hasil analisis, ditemukan bahwa penggunaan AI memberikan dampak positif terhadap peningkatan kemampuan literasi siswa, terutama dalam hal penyusunan teks, pemahaman struktur teks, serta pengembangan kemampuan berpikir kritis melalui fitur-fitur AI seperti feedback otomatis, koreksi tata bahasa, dan analisis bahasa alami. Namun, terdapat pula tantangan berupa risiko plagiarisme, ketergantungan siswa terhadap teknologi, keterbatasan kompetensi digital guru, serta isu etika dalam penggunaan AI. Penelitian ini diharapkan dapat memberikan wawasan bagi pendidik dalam mengoptimalkan pemanfaatan AI secara tepat, etis, dan berkelanjutan dalam pembelajaran teks Bahasa Indonesia.
Analisis Manajemen Risiko Menggunakan ISO 31000 : 2018 pada Website Academic Integrated System Universitas XYZ Labib Jundillah; Elfrida Simanjuntak; Vina Zahrotun Kamila; Ramadiani Ramadiani
Jurnal Informatika Polinema Vol. 12 No. 3 (2026): Vol. 12 No. 3 (2026)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v12i3.9599

Abstract

Website Academic Integrated System (AIS) Universitas XYZ merupakan media untuk mendukung aktivitas administrasi akademik secara online, seperti pendaftaran mahasiswa baru, pengelolaan kurikulum, pengisian Kartu Rencana Studi (KRS), hingga pengolahan data wisuda. Sesuai fungsinya, AIS pastinya menyimpan berbagai data sensitif, mulai dari riwayat akademik hingga dokumen penting mahasiswa. Namun, dalam operasionalnya AIS berhadapan dengan sejumlah risiko, seperti perubahan kebijakan Kementerian, bug pada fitur KRS, server down, serta human error. Risiko-risiko tersebut dapat mengganggu keberlangsungan layanan dan menurunkan kualitas pelayanan akademik. Penelitian ini bertujuan untuk menganalisis manajemen risiko pada Website AIS dengan menggunakan kerangka kerja ISO 31000:2018. Metode penelitian dilakukan melalui tahapan komunikasi dan konsultasi, penentuan cakupan, konteks, dan kriteria, identifikasi risiko, analisis risiko, evaluasi risiko, hingga penyusunan perlakuan risiko. Berdasarkan hasil penelitian, teridentifikasi 16 risiko yang dikelompokkan ke dalam tiga tingkatan, yaitu 3 risiko kategori tinggi (listrik padam, gangguan Internet Service Provider, dan server down), 9 risiko kategori menengah (antara lain kebakaran, korsleting listrik, human error, backup failure, bug KRS, overload, dan update gagal), serta 4 risiko kategori rendah (pencurian hardware, akses data ilegal, kerusakan hardware, dan ketidaksesuaian sistem dengan peraturan baru). Rekomendasi perlakuan risiko disusun berdasarkan tingkatan risiko. Dengan demikian, penerapan manajemen risiko berbasis ISO 31000:2018 terbukti mampu membantu mengidentifikasi serta memberikan perlakuan risiko yang tepat dalam meningkatkan keandalan dan keamanan Website AIS.
Artificial Intelligence–Driven Learning Analytics for Enhancing Student Engagement and Academic Performance in Digital Learning Environments Dendi Pratama; Eka Maya S.S. Ciptaningsih; Ramadiani Ramadiani; Achmad Fawaid; Winci Firdaus; Bambang Sudarsono
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 2 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4835

Abstract

The quick development of digital learning ecosystems after educational reform in the post-pandemic era requires an increase in intelligent monitoring systems that assess student engagement and predict academic performance. Traditional learning assessment techniques frequently have flaws when detecting early disengagement signals and initiating corrective actions for at-risk students. This research proposes an Artificial Intelligence (AI)-Driven Learning Analytics method that aims to improve student engagement monitoring and academic performance prediction in digital learning environments. A fabricated LMS-based educational dataset was used, which includes behavior analysis, engagement factors, academic factors, interaction factors, and temporal learning behavior obtained from LMSs like Moodle, Google Classroom, and Canvas. Several machine learning models, including Random Forest, XGBoost, Support Vector Machine, Artificial Neural Network, and Long Short-Term Memory (LSTM), were tested. The results revealed that the LSTM model had the best performance with an accuracy rate of 95% and a ROC-AUC value of 0.98, highlighting the importance of temporal learning behavior in educational prediction systems. Some of the essential engagement factors found to be most effective were assignment submission, quiz score, inactivity period, session length, and login number. The findings make a theoretical contribution to Artificial Intelligence in Education and Learning Analytics by combining multidimensional engagement analysis, temporal behavior modeling, and explainable AI into a unified framework. In practice, the suggested framework can aid adaptive learning, early warning, individualized intervention, and evidence-based education decisions in intelligent digital learning ecosystems.
Designing an Intelligent Decision Support System for Evaluating Teaching Effectiveness in Technology-Enhanced Classrooms Ramadiani Ramadiani; Azainil Azainil; Kenya Permata Kusumadewi; Guellica Agnesia Claudia Thanos; Toong Hai Sam
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 2 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4848

Abstract

The rapid digital transformation of education has significantly increased the adoption of technology-enhanced classrooms, generating substantial educational data that can support intelligent instructional evaluation. However, conventional teacher assessment systems remain limited by subjectivity, inconsistent evaluation standards, and the inability to analyze multidimensional learning analytics data effectively. This study aims to design an Intelligent Decision Support System (IDSS) for evaluating teaching effectiveness in smart classroom environments using the ELECTRE (Elimination and Choice Translating Reality) method integrated with Artificial Intelligence (AI)-based educational analytics. The proposed framework combines learning analytics indicators, machine learning models, and outranking-based multi-criteria decision-making to support transparent and data-driven educational governance. The evaluation criteria include student engagement, attendance rate, assignment completion, student satisfaction, learning outcomes, classroom interaction, technology integration, and instructor responsiveness. The computational process involved decision matrix construction, normalization, weighted normalization, concordance-discordance analysis, and aggregate dominance evaluation. The results demonstrated that the ELECTRE method effectively identified dominant teaching alternatives and handled conflicting instructional criteria systematically. Teacher 3 achieved the highest performance ranking due to superior instructional performance across all evaluation indicators. Additionally, AI-based predictive analysis improved evaluation accuracy and instructional pattern identification within technology-enhanced classrooms. The study contributes theoretically by extending the application of ELECTRE within intelligent educational DSS frameworks and practically by providing educational institutions with a scalable and transparent mechanism for evaluating teaching effectiveness. The proposed system supports smart educational governance, data-driven decision-making, and sustainable classroom quality assurance in digital learning ecosystems.
Co-Authors A., Amelia Achmad Fawaid Achmad Nizar Hidayanto Addy Septyawan Agus, Fahrul Aini, Nur Amelia A. Anita Anita Apriyanti Nurliyah Arief Hidayat Ariffin, Zainal AW., Sawung Awang Harsa Kridalaksana Azainil Azainil Bayu Ramadhani Damayanti, Elok Dendi Pratama Desy Sitti Kahdijah Dharma Widada Dian Wardiana Sjuchro Dyna Marisa Khairina Dyna Marissa Khairina Eka Maya S.S. Ciptaningsih Eko Junirianto Eko Wiji Setio Budianto Elfrida Simanjuntak Fahrul Agus Fahrul Agus Fahrul Agus Fazari, Alawiyah Nur Gore, Krisantus Gore Guellica Agnesia Claudia Thanos Halimatusya'diyah Hamdani Hamdani Hariyanti, Titik Harman Harman Hatta, Heliza Rahmania Heliza Rahmania Hatta, Heliza Rahmania Idrus, S. Saleh Al Ilma, Okta Usrifatin Imanda, Galih Dapa Indah Fitri Astuti, Indah Fitri Ira, Taqdiraa Jundillah, Muhammad Labib Kenya Permata Kusumadewi kusnandar kusnandar Kusnandar Kusnandar Labib Jundillah Labib Jundillah, Muhammad Luthfi Fahrozi, Muhammad Masayu Widiastuti Mohd. Hasan Selamat Mohd. Hasan Selamat Muhamad Azhari Muhamad Azhari Muhammad Fadli Muhammad Labib Jundillah Nadia Christin Borneo S Nina Queena Hadi Noraini Che Pa Noraini Che Pa Nur Aini Nur Aini Nurbasar Nurbasar Prastyo, Teguh Priantono, Ahmad Agung Puspitasari, Ni Luh Gede Dian Putut Pamilih Widagdo Putut Pamilih Widagdo, Putut Pamilih Rahmah, Auliana Rahmah, Auliana Reza Andrea Rodziah binti Atan Rodziah binti Atan Rusli Abdullah S Sujito S., Wardana Sawung AW. Septya Maharani, Septya Setyadi, Hario Jati Siti Lailiyah Soraya, Nova Intan Sri Rahayu Sudarsono, Bambang Surya Adithama Swasti Maharani Toong Hai Sam Tunggal, Anggunan Vina Zahrotun Kamila Wardana S. Winci Firdaus Yuli Wulandari, Yuli Yulianto Yulianto Yunia Hardiani Yusak Hudiyono, Yusak Zainal Ariffin Zainal Arifin