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All Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JISICOM (Journal of Information System, Infomatics and Computing) Jurnal Informatika dan Rekayasa Elektronik Jurnal Varian Jurnal Bumigora Information Technology (BITe) SOLID Jurnal Teknimedia: Teknologi Informasi dan Multimedia Jurnal Kependidikan: Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran dan Pembelajaran Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Bakti Sekawan : Jurnal Pengabdian Masyarakat Prosiding Seminar Nasional CORISINDO
Azhar, Raisul
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Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Peningkatan Kompetensi Guru SMAN 7 Mataram dalam Melaksanakan Pembelajaran dengan Pendekatan Deep Learning Azwar, Muhamad; Hariyadi, I Putu; Azhar, Raisul; Priyanto, Dadang; Adil, Ahmat; Santoso, Heroe; Syahrir, Moch.; Augustin, Kartarina; Zulkipli, Zulkipli; Darma, I Made Yadi; Asroni, Ondi; Qulub, Mudawil; Azhar, Lalu Zazuli; Widyawati, Lilik; Anas, Andi Sofyan
Bakti Sekawan : Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2025): Desember
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/bakwan.v5i2.852

Abstract

The capability of educators to respond to the dynamics of 21st-century education is a primary determinant in establishing a high-quality learning environment. Based on initial findings at SMAN 7 Mataram, a disparity was identified between the urgency of applying varied learning models and the reality in the field, which still relies heavily on conventional, teacher-centered approaches. This situation implies minimal active student participation and suboptimal stimulation of critical thinking skills or Higher Order Thinking Skills (HOTS). This community service program was initiated to escalate teacher capacity at SMAN 7 Mataram, specifically in designing Deep Learning-based schemes. The implementation approach adopted the Participatory Action Research (PAR) method, involving the full attention of 70 teachers through a series of phases, ranging from preparation and implementation to evaluation and mentoring. Key interventions included training on compiling Deep Learning-oriented Lesson Plans and teaching simulations. Program effectiveness was measured through questionnaires, lesson plan document reviews, and observations. Evaluation data showed a substantial positive impact, marked by an increase in conceptual understanding of Deep Learning indicators (40%), 6C principles (40%), the teacher's function as a facilitator (32%), and the application of authentic assessment (40%). In terms of implementation, the quality of lesson plans accommodating student-centered activities surged significantly from 30% in the pre-activity phase to 100% after the activity. It can be concluded that this program effectively boosts teachers' pedagogical competence comprehensively and encourages the transformation of teaching practices in the classroom to become more dynamic.
PEMILIHAN BAHAN PUPUK ORGANIK UNGGULAN DALAM SISTEM PENDUKUNG KEPUTUSAN MENGGUNAKAN METODE WEIGHTED PRODUCT Heroe Santoso; Raisul Azhar; Suriyati Suriyati; Melati Rosanensi; I Made Yadi Dharma; Husain Husain; Fathurrahman Fathurrahman
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 5 No. 2 (2024): Desember 2024
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v5i2.208

Abstract

Organic fertilizer is a type of fertilizer that comes from natural ingredients that contain organic materials, such as plant, animal or other organic waste. Organic fertilizer naturally contains essential nutrients for plants, such as nitrogen, phosphorus, potassium, micronutrients and beneficial organic materials. Organic fertilizers have experienced significant development in recent years. Increased awareness of the importance of sustainable and environmentally friendly agriculture has encouraged the use and development of organic fertilizers. Meanwhile, organic fertilizer can be produced through composting, fermentation or decomposition of organic materials. To be able to produce superior and quality fertilizer products, of course you must choose superior or quality product ingredients. Sources of organic material can be goat kohe, effective microorganism 4 (EM4), bamboo leaf waste, chicken manure waste, burnt husks, cocopeat, coconut fiber. This research aims to create a decision support system using the weighted product (WP) method. WP is a popular multi-criteria analysis decision and is a multi-criteria decision making method. The choice of the weighted product (WP) method is also based on its ability to provide optimal solutions in the ranking system. The choice of this method is also based on the computational complexity which is not too difficult so that the time required to produce calculations is relatively short
ANALISIS SENTIMENT KEUANGAN MENGGUNAKAN FINE-TUNED FINBERT Heroe Santoso; Raisul Azhar; Suryati Suryati; Melati Rosanensi; I Made Yadi Dharma; Husain Husain; Ahmat Adil; Muhamad Azwar; I Putu Hariyadi
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 6 No. 2 (2025): Desember 2025
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v6i2.316

Abstract

Financial information is a critical type of data for analysis. However, because much of it is unstructured and widely dispersed, an appropriate analytical method is required, one of which is sentiment analysis. In the financial context, sentiment analysis is employed by the industry to assess public perceptions of companies or market conditions. This study implements a fine-tuned FinBERT model to perform sentiment analysis in the financial sector. The dataset used is a combination of FiQA (Financial Question Answering) and The Financial PhraseBank, consisting of English sentences labeled with negative, neutral, and positive sentiments. The research process involved data preprocessing, tokenization, data splitting, model training, and evaluation using accuracy, precision, recall, F1-score, and confusion matrix metrics. The results show that the model achieved 82% accuracy, with its best performance in the positive class (F1-score 0.88) and the neutral class (F1-score 0.85), but weaker performance in detecting the negative class (F1-score 0.49). These findings indicate that the fine-tuned FinBERT is effective for financial sentiment analysis, particularly for positive and neutral sentiments, though improvements are needed in negative sentiment detection, potentially through expanding training data diversity or applying data augmentation techniques
Co-Authors Afriandi, Mahsus Ahmat Adil Al-Mu’min, Al-Mu’min Alfiansyah, Githa Andi Sofyan Anas Anthony Anggrawan Apriani Apriani Augustin, Kartarina Azhar, Lalu Zazuli Dadang Priyanto Daniel Happy Putra Darma, I Made Yadi Edy Satriawan Engelbertus Mite Faisal Faisal Fathurrahman Fathurrahman Hammad, Rifqi Hariyadi, I Putu Hendra Husain Husain Husain Husain Husain I Gede Bagus Arthana I Made Yadi Dharma I Made Yadi Dharma I Putu Hariyadi Ikrom, Paizul Khairan marzuki Khirullah, Zidan Kurniadin Abd Latif Kurniawan Kurniawan Lilik Widyawati Mayadi Mayadi Mayadi Mayadi Mayadi, Mayadi Melati Rosanensi Mia Mubiatma Muhamad Azwar Muhamad Azwar Muhamad Azwar, Muhamad Muhammad Azwar Muhammad Munawir Gazali Muliadi Muliadi Ni GustiAyu Dastriani Ondi Asroni Qulub, Mudawil Rana, Dwi Sadam Husen Santoso, Heroe Sirojul Hadi Sukma, I Gusti Ayu Yunita Suriyati Suriyati Suriyati, Suriyati Suryati Suryati Syahrir, Moch. Triwijoyo, Bambang Krismono Yayan Suganda Zulfikri, Muhammad Zulkipli Zulkipli Zulkipli Zulkipli