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All Journal International Journal of Artificial Intelligence Research JITK (Jurnal Ilmu Pengetahuan dan Komputer) Atthulab: Islamic Religion Teaching and Learning Journal Indonesian Journal of Community Services Jurnal Teknik Informatika (JUTIF) Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Ilmiah Pendidikan Citra Bakti
Firdaus, Nurul
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Religion Humanities Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Towards Smart Village : Rides Management Mobile Application As Tourism Digital Promotion And Marketing in Society 5.0 Era Hartatik, Hartatik; Firdaus, Nurul; Aziz, Abdul
International Journal of Artificial Intelligence Research Vol 6, No 1.2 (2022)
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.2.443

Abstract

In the context of developing tourism in various regions in Indonesia, many areas are developing the potential around them to be used as tourist attractions that can attract visitors or what are then referred to as "tourist villages." In its introduction, tourist villages also need promotion through digital media. One of the efforts to market to the wider community and make it easier for people who want to visit tourist villages to purchase entrance tickets for rides and find out information about what types of rides are available. By using the Agile-Scrum development method, it is possible to produce a product Implementation of the Tourism Village Mobile Application for the Ticket Management and Tourism Rides Management Module, in the form of an application where visitors can purchase tickets and tour packages through the tourist village application on their smartphone. The application does not only sell entry tickets but also sells ride tickets available in the tourist village
Literasi Data dan Pembuatan Media Pembelajaran Interaktif berbasis Artificial Intelligence bagi Pengajar SMA Negeri 2 Surakarta Supriyadi, Andy; Firdaus, Nurul; Yusfida, Fiddin; Hartatik, Hartatik
Indonesian Journal of Community Services Vol 6, No 2 (2024): November 2024
Publisher : LPPM Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/ijocs.6.2.201-208

Abstract

Teknologi Artificial intelligence (AI) dalam pembelajaran tidak bisa dihindari. Hal tersebut memerlukan peningkatan kompetensi guru dan infrastruktur digital di dalam lingkungan sekolah. Hadirnya teknologi tersebut sering kali disalah gunakan siswa dalam mengerjakan tugas-tugas sekolah. Memperhatikan situasi tersebut pengajar atau guru dituntut untuk meningkatkan kompetensi dalam menggunakan teknologi informasi dalam memanfaatkan AI secara baik dan tepat sasaran. Selain itu belum adanya skill atau background pendidikan guru yang berelasi dengan mata pelajaran yang diampu menjadikan permasalahan yang perlu diatasi dalam jangka waktu yang dekat karena siswa perlu mendapatkan pemahaman yang tepat dari materi yang diajarkan. Sehingga perlu dukungan dari insan Perguruan Tinggi untuk melaksanakan pengabdian dengan memberikan pelatihan maupun pendampingan dalam pemanfaatan teknologi AI di dalam menunjang pembelajaran, apalagi untuk mata pelajaran Teknologi Informasi dan Komunikasi (TIK) atau Informatika yang mana transformasi digital yang pergerakannya sangat cepat. Pelatihan dan Pendampingan yang dilakukan bertujuan untuk membantu pengajar SMA menyesuaikan materi pembelajaran berdasarkan pola belajar, kebutuhan, kekuatan, kelemahan masing-masing siswa, dan dapat membantu pengajar untuk memanajemen tugas-tugas administratif seperti membuat bahan ajar, RPP atau silabus, penjadwalan, dan penilaian. Pelatihan ini diharapkan dapat membantu siswa belajar secara mandiri dengan memanfaatkan AI berbasis tutor virtual sesuai dengan tema pembelajaran, serta siswa dapat menggunakan teknologi secara bertanggung jawab dan etis. Pelatihan ini juga mengenalkan teknologi untuk mendeteksi karya hasil kecerdasan buatan atau AI. Hasil dari implementasi pelatihan literasi dan pemanfaatan AI bagi pengajar SMA berupa publikasi di media online, video dan jurnal/prosiding.Artificial intelligence has already been creating an impact on education. AI's impact on education is transformative and multi-faceted. Artificial intelligence is inevitable. AI powered adaptive learning which can provide immersive experience. Therefore, Artificial intelligence tools can enhance the teachers' and students' experience by providing personalized learning materials, automating administrative tasks, and even offering tutoring assistance. AI can enhance learning outcomes and ensure students receive the support they require to succeed. Therefore, teaching training programs and training courses were held by the university to enhance teachers’ understanding in line with the technology, especially in the use of AI. The training and courses assist in automating administrative tasks, freeing up valuable time for educators. From grading assignments and providing feedback to generating reports, teachers can focus more on individualized instruction and student support. This helps create a more efficient and productive learning environment. By using technology effectively educators can make informed decisions to improve teaching methods, curriculum design, and educational policies. Educators can create educational systems that are more personalized, efficient, and responsive to the needs of students. This purpose of this study is to improve teachers' knowledge on AI. By using AI educators create educational systems that are more personalized, efficient, and responsive to the needs of students. The result of this research included the teachers' product such as books, video, journal, and proceeding by implementing AI.
MENTORA: Inovasi Digital untuk Pemberdayaan Masyarakat Berbasis Data Fiddin Yusfida; Hartatik, Hartatik; Firdaus, Nurul; Kusuma Riasti, Berliana; Supriyadi, Andy
KOMUNITA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 4 No 3 (2025): Agustus
Publisher : PELITA NUSA TENGGARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60004/komunita.v4i3.225

Abstract

Kegiatan Pelatihan dan Serah Terima Aplikasi MENTORA dilaksanakan oleh Grup Riset Applied Data Science and AI (DSAI) Universitas Sebelas Maret (UNS) Surakarta melalui skema Pengabdian Kepada Masyarakat Hibah Grup Riset (PKM HGR-UNS) pada 10 Juli 2025 di D3 Teknik Informatika, Sekolah Vokasi UNS. Kegiatan ini bertujuan meningkatkan efektivitas pengelolaan data pendampingan komunitas dengan memanfaatkan teknologi informasi. MENTORA adalah aplikasi digital inovatif yang dirancang untuk mendukung pemberdayaan masyarakat berbasis wilayah dengan fitur unggulan seperti Admin Center, Fasilitator Hub, Group Management, Community Management, Activity Management, Activity Insights Dashboard, dan Data Exporter. Pelatihan diikuti oleh admin dan fasilitator yang akan mengoperasikan aplikasi di lapangan untuk memastikan implementasi optimal. Acara ini juga menjadi momentum inisiasi kerja sama tridharma perguruan tinggi antara UNS dan Majelis Pemberdayaan Masyarakat PP Muhammadiyah. Diharapkan dengan hadirnya MENTORA, pengelolaan data pendampingan masyarakat menjadi lebih terstruktur, transparan, dan mendukung transformasi digital di komunitas.
Optimizing Alternating Least Squares for Recommender Systems Using Particle Swarm Optimization Yusfida A'la, Fiddin; Firdaus, Nurul; Supriyadi, Andy
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5154

Abstract

Recommender systems play a crucial role in various digital platforms by assisting users in discovering relevant items. The research problem addressed in this study is the limited predictive accuracy of ALS-based recommender systems due to suboptimal parameter selection. This study explores how Particle Swarm Optimization (PSO) can be leveraged for parameter optimization to address this limitation. The dataset used is MovieLens 1M, which contains over one million user ratings for thousands of movies. The research process includes data preprocessing, data splitting, model training, and evaluation using Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) as the primary metrics. The evaluation results indicate a significant improvement in model performance after optimization, with RMSE decreasing from 0.895 to 0.860 and MAE from 0.704 to 0.680. These findings demonstrate that optimization algorithms can effectively improve the prediction accuracy of recommendation systems. This research contributes to the application of swarm-based optimization techniques in enhancing matrix factorization-based recommender systems.
Teacher's Understanding of Elementary School Teacher Quality Components in Education Unit Accreditation Instruments Firdaus, Nurul; Nurhakim, Riki Rahman; Sunandar, Yoga; Latifah, Wifa Fakhriyah
Atthulab: Islamic Religion Teaching and Learning Journal Vol. 8 No. 1 (2023): Atthulab: Islamic Religion Teaching and Learning Journal
Publisher : Laboratory of Islamic Religious Education Faculty of Tarbiyah and Teacher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/ath.v8i1.17881

Abstract

The education process can run smoothly if it has a competent teacher quality. Schools must ensure the quality of teachers in order to produce quality teachers. This study aims to determine the understanding of educators in the Education Unit Accreditation Instrument (IASP) 2020 in order to improve the quality of education at SD/MI Serangpanjang, Subang, Indonesia by using the mechanism of the accreditation component. The method used is descriptive qualitative with data from interviews, distributing research questionnaires, and document studies. The results showed that the IASP 2020 could be understood well by teachers at SD/MI, Serangpanjang District, Subang Regency. Teachers at SD/MI, Serangpanjang Sub-district, Subang Regency can understand the statements in the 2020 Education Unit Accreditation Instrument. The conclusion is that the understanding of Islamic Religious Education and Teachers of Non-Islamic Religious Education regarding the quality components of elementary school teachers is well understood. The research is completed with the hope that it can be taken into consideration in improving the quality of teachers. Proses pendidikan dapat berjalan dengan mulus jika mempunyai mutu guru yang berkompeten. Sekolah harus melakukan proses penjaminan mutu guru setiap saat agar dapat menghasilkan guru yang berkualitas. Penelitian ini bertujuan untuk mengetahui serta mendeskripsikan pemahaman pendidik dalam Instrument Akreditasi Satuan Pendidikan (IASP) 2020 guna meningkatkan mutu pendidikan di SD/MI Serangpanjang, Subang, Indonesia dengan menggunakan mekanisme komponen-komponen akreditasi. Metode yang digunakan yaitu kualitatif deskriptif dengan data hasil wawancara, penyebaran angket peneltian, dan studi dokumen. Hasil penelitian menunjukkan bahwa IASP 2020 dapat di pahami dengan baik oleh guru di SD/MI Kecamatan Serangpanjang Kabupaten Subang. Hasil pemahaman pendidik di SD/MI Kecamatan Serangpanjang Kabupaten Subang dengan hasil akhir guru dapat memahami pernyataan-pernyataan dalam Instrument Akreditasi Satuan Pendidikan 2020. Oleh karena itu dapat dikatakan bahwa pemahaman guru Pendidikan Agama Islam dan Non Pendidikan Agama Islam mengenai komponen mutu guru tingkat SD sudah dipahami dengan baik. Penelitian ini diselesaikan dengan harapan dapat menjadi bahan pertimbangan dalam peningkatan kualitas guru.
RELEVANSI MATERI BUKU TEKS BAHASA INDONESIA TERHADAP KURIKULUM 2013 Azizah, Aida; Firdaus, Nurul
Jurnal Ilmiah Pendidikan Citra Bakti Vol. 9 No. 1 (2022)
Publisher : STKIP Citra Bakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38048/jipcb.v9i1.607

Abstract

Penelitian ini bertujuan untuk mengetahui apakah buku teks Bahasa Indonesia kelas XII SMA ini sesuai dengan standar aspek materi yang meliputi akurat atau tepat, terbaru, serta sesuai dengan konteks dan kemampuan berpikir siswa yang terdapat dalam kurikulum 2013. Penelitian ini termasuk deskriptif kualitatif . subjek dari penelitian ini adalah buku teks Bahasa Indonesia kelas XII SMA edisi revisi tahun 2018. Metode penelitian ini yakni metode dokumentasi yang diwujudkan dalam bentuk kata-kata, kalimat, dan materi dalam buku teks Bahasa Indoensia kelas XII SMA edisi revisi tahun 2018 terhadap kurikulum 2013. Dalam buku teks tersajikan sebanyak 6 materi yang relevan dan 2 pokok pembahasan mengenai ke akuratan, keterbaruan buku yang disesuaikan dengan kurikulum 2013. Hasil dari analisis data penelitian ini yaitu menghasilkan kerelevansian atau kesesuaian dan standart pada kurikulum 2013 yang meliputi kompetensi inti dan kompetenai standar, kompetensi ini yang diambil adalah pada point 3, dan kompetensi dasar pada masing-masing materi yang meliputi surat lamaran pekerjaan, cerita sejarah/novel sejarah, teks editorial, novel, artikel, dan kritik atau esai.Kata Kunci: materi buku teks, kurikulum 2013
COMPARATIVE STUDY OF TRANSFORMER-BASED MODELS FOR AUTOMATED RESUME CLASSIFICATION Firdaus, Nurul; Kusuma Riasti, Berliana; Asri Safi'ie, Muhammad
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.7453

Abstract

This study presents a comparative evaluation of transformer-based models and traditional machine learning approaches for automated resume classification—a key task in optimizing recruitment workflows. While traditional approaches like Support Vector Machines (SVM) with TF-IDF demonstrated the highest performance (93.26% accuracy and 95% F1-score), transformer models such as DistilBERT and RoBERTa showed competitive results with 93.27% and 91.34% accuracy, respectively, and fine-tuned BERT achieved 84.35% accuracy and an F1-score of 81.54%, indicating strong semantic understanding. In contrast, Word2Vec + LSTM performed poorly across all metrics, highlighting limitations in sequential modelling for resume data. The models were evaluated on a curated resume dataset available in both text and PDF formats using accuracy, precision, recall, and F1-score, with preprocessing steps including tokenization, stop-word removal, and lemmatization. To address class imbalance, we applied stratified sampling, macro-averaged evaluation metrics, early stopping, and simple data augmentation for underrepresented categories. Model training was conducted in a PyTorch environment using Hugging Face’s Transformers library. These findings highlight the continued relevance of traditional models in specific NLP tasks and underscore the importance of model selection based on task complexity and data characteristics
Co-Authors Abdul Aziz Aida Azizah, Aida Andy Supriyadi Asri Safi'ie, Muhammad Berliana Kusuma Riasti Evi Chamalah Fachry Abda El Rahman Fiddin Yusfida Latifah, Wifa Fakhriyah Nurhakim, Riki Rahman Sunandar, Yoga Yusfida A'la, Fiddin Yusfida, Fiddin