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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) AKSIOMA: Jurnal Program Studi Pendidikan Matematika International Journal of Artificial Intelligence Research Jurnal CoreIT JITK (Jurnal Ilmu Pengetahuan dan Komputer) Dinamisia: Jurnal Pengabdian Kepada Masyarakat JURNAL TEKNOLOGI DAN OPEN SOURCE Digital Zone: Jurnal Teknologi Informasi dan Komunikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH Zonasi: Jurnal Sistem Informasi Journal of Applied Engineering and Technological Science (JAETS) Jurnal Pengabdian Masyarakat Multidisiplin JPMB: Jurnal Pemberdayaan Masyarakat Berkarakter Jurnal Teknik Informatika (JUTIF) IJISTECH Jutsi: Jurnal Teknologi dan Sistem Informasi J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat J-COSCIS : Journal of Computer Science Community Service Edumatica: Jurnal Pendidikan Matematika Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat SATIN - Sains dan Teknologi Informasi JURNAL KARYA ILMIAH MULTIDISIPLIN Jurnal Pengabdian Masyarakat dan Riset Pendidikan INOVTEK Polbeng - Seri Informatika Edu Komputika Journal IndoAI: Journal of Artificial Intelligence and Computational Logic
Ahmad Zamsuri, Ahmad
Universitas Lancang Kuning
Aerospace Engineering Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Synthetic Minority Oversampling Technique for Efforts to Improve Imbalanced Data in Classification of Lettuce Plant Diseases Nurliana Nasution; Feldiansyah Feldiansyah; Ahmad Zamsuri; Mhd Arief Hasan
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 6 No. 1 (2023): Jurnal Teknologi dan Open Source, June 2023
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v6i1.2883

Abstract

In this study we classified lettuce plant diseases. These plant diseases are available in the form of images that have been converted in .csv format to be classified. These plant diseases are available in the form of images that have been converted in .csv format to be classified. Image These plant diseases have been divided into several classes or categories. Then we determine the features of each row and column of the dataset. Each line in the CSV file represents one image, and each column represents one feature Each line in the CSV file represents one image, and each column represents one feature. Then a label is made for each line in the CSV file, namely the class or category where the images are grouped. Thus, so that we get datasets that are ready to be processed with machine learning. However, in processing the dataset, we get imbalanced data. So we added the Synthetic Minority Over-sampling Technique (SMOTE) method to overcome the imbalance that occurs. So that the data can be classified using several algorithms to find the best accuracy.
PRO DAN KONTRA PENGGUNAAN AI PADA DUNIA PENDIDIKAN Ahmad Zamsuri; Wenni Syafitri; Guntoro Guntoro; Idel Waldelmi; Novia Putri Bimby
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol. 5 No. 2 (2025): Desember 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i2.5414

Abstract

Abstract: The Community Service (PkM) activity aims to enhance the knowledge of teachers at MI AL FATTAAH regarding the utilization of Generative Artificial Intelligence (Gen-AI) in education. Currently, student assessment is still conducted conventionally, meaning the utilization of Gen-AI technology is not yet optimal. Non-involvement in this technological development could negatively impact the quality of education in the future. Through socialization and education activities, this PkM introduced the concepts, usage, and result analysis of Gen-AI in the educational context, highlighting the pros and cons of its implementation. Effectiveness assessment was conducted using pre-tests and post-tests with the Coefficient of Reproducibility (CR) and Coefficient of Scalability (CS). CR and CS results of 1 indicate that the knowledge transfer was effective and the activity was executed well. This PkM not only improved the teachers' understanding of AI but also has the potential to become a learning model for similar educational institutions.            Keywords: Gen-AI, Socialization, Utilization, Education  Abstrak: Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan meningkatkan pengetahuan guru MI AL FATTAAH mengenai pemanfaatan Generative Artificial Intelligence (Gen-AI) dalam pendidikan. Selama ini, penilaian murid masih dilakukan secara konvensional, sehingga pemanfaatan teknologi Gen-AI belum optimal. Ketidakterlibatan dalam perkembangan teknologi ini dapat berdampak negatif terhadap kualitas pendidikan di masa depan. Melalui kegiatan sosialisasi dan edukasi, PkM ini memperkenalkan konsep, penggunaan, serta analisis hasil Gen-AI dalam konteks pendidikan, dengan menyoroti aspek pro dan kontra penerapannya. Penilaian efektivitas dilakukan melalui pre-test dan post-test menggunakan koefisien Reprodusibilitas (CR) dan Skalabilitas (CS). Hasil CR dan CS sebesar 1 menunjukkan bahwa transfer pengetahuan berlangsung efektif dan kegiatan terlaksana dengan baik. PkM ini tidak hanya meningkatkan pemahaman guru terhadap AI, tetapi juga berpotensi menjadi model pembelajaran bagi lembaga pendidikan sejenis. Kata kunci: Gen-AI, Sosialisasi, Pemanfaatan, Edukasi
Geodetically-Enhanced Hybrid GRU with Adaptive Dropout and Dynamic L2 Regularization for Earthquake Parameter Prediction in Indonesia Mubarak MR, Najmuddin; Susandri, Susandri; Zamsuri, Ahmad
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5478

Abstract

Earthquake prediction remains challenging due to the nonlinear behavior and uncertainty of seismic activity. This study introduces a geodetically-enhanced hybrid GRU model integrating adaptive dropout and dynamic L2 regularization to improve robustness and accuracy in earthquake magnitude prediction. In addition to seismic sequence data, slip-rate values derived from scalar moment distribution were incorporated as a domain-informed feature to represent tectonic strain accumulation across Indonesia. The dataset consisted of BMKG records from 2010–2025 and was processed through outlier removal, normalization, temporal reshaping, and feature integration. The proposed model was evaluated against multiple deep learning baselines including CNN-1D, LSTM, standard GRU, Transformer-based models, and Neural ODE architectures. Performance assessment used RMSE, MAE, and R² metrics. The resulting hybrid GRU achieved improved predictive accuracy with an RMSE of 0.5176, MAE of 0.3973, and an R² score of 0.5997, outperforming both CNN-1D and standard GRU baselines. The integration of slip-rate features contributed to reduced prediction variance across tectonically active zones. These findings demonstrate that combining geodetic information with adaptive regularization strategies improves generalization and model stability for seismic forecasting. The approach offers potential applicability for rapid early-warning scenarios requiring low latency and reliable prediction accuracy.
TRANSFORMASI PEMBELAJARAN STATISTIKA MELALUI PENGEMBANGAN E-MODULE INTERAKTIF UNTUK PENINGKATAN LITERASI STATISTIS MAHASISWA Sari Herlina; Yaya S Kusumah; Dadang Juandi; Ahmad Zamsuri; Dola Julianti
AKSIOMA: Jurnal Program Studi Pendidikan Matematika Vol. 14 No. 4 (2025)
Publisher : UNIVERSITAS MUHAMMADIYAH METRO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/ajpm.v14i4.13308

Abstract

Di era digital, kemampuan untuk memahami dan menganalisis data statistik semakin penting. Kemahiran dalam statistik atau literasi statistis memungkinkan individu untuk memahami data yang digambarkan melalui grafik, tabel, dan ilustrasi, membantu mereka untuk membuat keputusan yang tepat berdasarkan data. Penelitian ini bertujuan untuk mengembangkan e-module menggunakan  Kvisoft Flipbook Maker untuk meningkatkan Literasi Statistis calon guru matematika. Dalam penelitian ini didesain bahan ajar berupa E-Module yang didesain menggunakan Kvisoft Flipbook Maker digunakan dalam pembelajaran Statistika Pendidikan. E-Module ini dikembangkan dengan menggunakan software Kvisoft Flipbook Maker yang menyajikan materi Statistika Pendidikan dengan visualisasi yang menarik serta kaya dengan fitur multimedia. Metode penelitian ini merupakan penelitian pengembangan dengan mengadaptasi model ADDIE. Subjek penelitiannya adalah mahasiswa calon guru matematika di Program Studi Pendidikan Matematika, Universitas Islam Riau. Jumlah subjek penelitian sebanyak 42 orang mahasiswa. Instrumen yang digunakan terdiri dari lembar validasi, tes literasi statistis, lembar observasi dan lembar wawancara. Data dikumpulkan melalui tes literasi statistis, observasi, dan respons mahasiswa melalui wawancara. Hasil penelitian menunjukkan bahwa: 1) Hasil desain E-Module menggunakan  Kvisoft Flipbook Maker telah diuji kelayakannya. Dari segi validitas, kelayakan desain ini berada dalam kategori valid, sedangkan kepraktisannya berada pada kategori praktis. Desainnya juga efektif, karena ada peningkatan literasi statistik yang mencapai 76,19%. Dengan demikian, penelitian ini menghasilkan desain E-Module digital menggunakan  Kvisoft Flipbook Maker yang efektif dan layak digunakan untuk meningkatkan Literasi Statistis mahasiswa calon guru matematika. Kesimpulan penelitian ini, E-Module dapat diaplikasikan dalam matakuliah statistika, serta e-modul dapa digunakan dilingkup yang lebih luas diberbagai program studi di Indonesia.In the digital age, the ability to understand and analyze statistical data is increasingly important. Proficiency in statistics or statistical literacy allows individuals to understand the data depicted through graphs, tables, and illustrations, helping them to make informed decisions based on data. This research aims to develop an e-module using Kvisoft Flipbook Maker to improve the Statistical Literacy of prospective mathematics teachers. In this study, teaching materials in the form of E-Modules were designed using Kvisoft Flipbook Maker to be used in learning Educational Statistics. This digital module was developed using Kvisoft Flipbook Maker software which presents educational statistics material with interesting visualizations and rich multimedia features. This research method is a development research by adapting the ADDIE model. The subject of the research is a prospective mathematics teacher student at the Mathematics Education Study Program, Universitas Islam Riau. The number of research subjects was 42 students. The instruments used consisted of validation sheets, statistical literacy tests, observation sheets and interview sheets. Data were collected through statistical literacy tests, observations, and student responses through interviews. The results of research show that 1) The design results of the Digital E-Module using Kvisoft Flipbook Maker have been tested for feasibility. In terms of validity, the feasibility of this design is in the valid category, while the practicality is in the practical category. The design is also effective, because there is an increase in statistical literacy which reaches 76.19%. Thus, this study produced a digital E-Module design using Kvisoft Flipbook Maker that is effective and suitable to be used to improve the Statistical Literacy of prospective mathematics teacher students. The conclusion  of this research is that e-modules can be applied in statistics courses, and e-modules can be used in a wider scope in various study programs in Indonesia.
Evaluation of the Effect Of Regularization on Neural Networks for Regression Prediction: A Case Study of MLLP, CNN, and FNN Models Susandri; Ahmad Zamsuri; Nurliana Nasution; Maya Ramadhani
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/m2rcsf96

Abstract

Regularization is an important technique for developing deep learning models to improve generalization and reduce overfitting. This study evaluated the effect of regularization on the performance of neural network models in regression prediction tasks using earthquake data. We compare Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), and Feedforward Neural Network (FNN) architectures with L2 and Dropout regularization. The experimental results show that MLP without regularization achieved the best performance (RMSE: 0.500, MAE: 0.380, R²: 0.625), although prone to overfitting. CNN performed poorly on tabular data, while FNN showed marginal improvement with deeper layers. The novelty of this study lies in a comparative evaluation of regularization strategies across multiple architectures for earthquake regression prediction, highlighting practical implications for early warning systems.
Co-Authors Abini, Eka Yestira Nita Alkhairi, Putrama Alwan, Hiba Basim Anam, M Khairul Andi Zahran Budiman Andre Armada Aprilia Milanda Putri Arini Arita Fitri, Triyani Arpan Asparizal, Asparizal Astri Wahyuni Baehaqi Bayu Febriadi, Bayu Bimby, Novia Putri Dadang Juandi Dafwen Toresa Deni Iskandar Diyah Ayu Rizqiani Dola Julianti Eddis Syahputra Pane, Eddis Syahputra Eko Sediyono Elvira Asril, Elvira Elvira Elvira Fadly Suandi Fajar, Muhammad Al Fajrizal Fajrizal Fajrizal, Fajrizal Febrizal Alfarasy Syam Febrizal Alfarasy Syam Febrizal As-Syam Feldiansyah Feldiansyah Feldiansyah, Feldiansyah Fitri Juliani Gunadi Widi Nurcahyo Guntoro, Guntoro Hamdani Hamdani Hazira, Nadila Hendrawan, Riki Hiba Basim Alwan Idel Waldelmi idel waldelmi, idel Indriati, Mefa Julianti, Dola Keumala Anggraini Khairani Djahara, Khairani Lisnawita Lisnawita Loneli Costaner Mariza Devega Maya Ramadhani Mhd. Arief Hasan, Mhd. Arief Mubarak MR, Najmuddin Muhamad Sadar, Muhamad Muzdalifah, Indah Novia Putri Bimby Nurfika Sari Nurliana Nasution Nurliana Nasution, Nurliana Nuroini, Indi Pandu Pratama Putra, Pandu Pratama Pardede, Akim Manaor Hara Poningsih Rahmiati Rahmiati Ramadani, Indah Ramadhani, Maya Roki Hardianto Sahrul Saputra Saputra, Eko Ikhwan Sari Herlina Sari Herlina Sari Herlina Sarjon Defit Shelydia Martha Suhendra Sumijan , Sumijan Susandri Susandri, Susandri Susi Handayani Sutejo Sutejo Syahtriatna D Syahtriatna Djusar Syahtriatna Djusar Syam, Salmaini Safitri Taufiq Hidayah Tintien Koerniawati Triyani Arita Fitri Turnandes, Yogo Vebby Vebby Vebby Walhidayat Walhidayat Walhidayat Wenni Syafitri Wirta Agustin Yaya S Kusumah Yaya S. Kusumah Yenni, Heda Yogi Yunefri, Yogi Yogo Turnandes Yogo Turnandes Yoyon Efendi Yuhelmi Yuhelmi Yuvi Darmayunata Zamzami, Zamzami