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All Journal Riau Journal of Computer Science RABIT: Jurnal Teknologi dan Sistem Informasi Univrab ILKOM Jurnal Ilmiah INTECOMS: Journal of Information Technology and Computer Science JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Teknologi Sistem Informasi dan Aplikasi Informatika : Jurnal Informatika, Manajemen dan Komputer JOISIE (Journal Of Information Systems And Informatics Engineering) Jurnal Teknologi Informasi dan Multimedia Jurnal Informasi dan Teknologi Journal of Robotics and Control (JRC) Journal of Applied Engineering and Technological Science (JAETS) JSR : Jaringan Sistem Informasi Robotik Community Engagement and Emergence Journal (CEEJ) Jurnal Ilmu Komputer Journal of Applied Data Sciences Jurnal Pengabdian kepada Masyarakat Jurnal Ipteks Terapan : research of applied science and education Jurnal Teknik Informatika Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Telecommunication Control and Intelligent System Journal of Software Engineering and Information System (SEIS) SATIN - Sains dan Teknologi Informasi Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Jurnal Masyarakat Berdikari dan Berkarya (MARDIKA) The Indonesian Journal of Computer Science Jurnal Pengabdian Masyarakat Terapan
Refni Wahyuni
Universitas Hang Tuah Pekanbaru
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering 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 Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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IMPLEMENTASI SISTEM INFORMASI AKADEMIK DI PKBM AR ROYYAN UNTUK MENINGKATKAN EFISIENSI ADMINISTRASI DAN MONITORING Yuda Irawan; Refni Wahyuni; Abdi Muhaimin; M. Khairul Anam
Jurnal Masyarakat Berdikari dan Berkarya (Mardika) Vol 3 No 2 (2025): Jurnal Masyarakat Berdikari dan Berkarya (MARDIKA)
Publisher : Fakultas Teknik, Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/mardika.v3i2.12965

Abstract

PKBM Ar Royyan menghadapi tantangan dalam pengelolaan data akademik seiring dengan peningkatan jumlah siswa dan kompleksitas administrasi. Pengelolaan data yang masih dilakukan secara manual menyebabkan inefisiensi, risiko kehilangan data, serta keterbatasan sumber daya manusia. Oleh karena itu, adopsi sistem informasi akademik digital menjadi sangat penting untuk mengatasi masalah ini. Tujuan dari kegiatan pengabdian masyarakat ini adalah meningkatkan efisiensi pengelolaan data akademik dan administrasi di PKBM Ar Royyan melalui implementasi Sistem Informasi Akademik (SIAKAD). Selain itu, kegiatan ini bertujuan menjamin keamanan dan keberlanjutan data, serta meningkatkan kapasitas teknologi informasi di sekolah melalui pelatihan penggunaan sistem digital. Hasil kegiatan menunjukkan bahwa penerapan SIAKAD secara signifikan berhasil meningkatkan efisiensi pengelolaan data dan mempercepat proses administratif. Meskipun terdapat tantangan infrastruktur dan keterampilan teknologi, masalah tersebut berhasil diatasi melalui pelatihan dan dukungan teknis. Implementasi ini juga mendorong transparansi dan memberikan contoh bagi sekolah lain di wilayah tersebut dalam memanfaatkan teknologi untuk meningkatkan kualitas pendidikan. Secara keseluruhan, kegiatan ini membangun fondasi bagi pengembangan teknologi pendidikan yang berkelanjutan di masa depan.
Multimodal Deep Learning and IoT Sensor Fusion for Real-Time Beef Freshness Detection Kurniawan, Bambang; Wahyuni, Refni; Yulanda, Yulanda; Irawan, Yuda; Habib Yuhandri, Muhammad
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.977

Abstract

Beef freshness quality is one of the important indicators in ensuring food safety and suitability. However, conventional methods such as manual visual inspection and laboratory testing cannot be widely applied in real-time and mass scale. To overcome these challenges, this study proposes a meat freshness detection system based on a multimodal approach that combines visual imagery and gas sensor data in a single IoT-based framework. This system is designed by utilizing the YOLOv11 architecture that has been optimized using the Adam optimizer. The dataset consisted of 540 original beef images, expanded into 1,296 images after augmentation. The model is trained on these augmented images and is able to achieve detection performance with a mAP@0.5 value of 99.4% and mAP@0.5:0.95 of 95.7%. As a further improvement, the cropped image features from the YOLOv11 model are processed through a combination of the ViT model and CNN to classify the level of meat freshness into three classes: Fresh, Medium, and Rotten with an accuracy of 99%. On the other hand, chemical data was obtained from the MQ136 and MQ137 gas sensors to detect H₂S and NH₃ levels which are indicators of meat spoilage. Data from visual and chemical data were then combined through a multimodal fusion method and classified using the Random Forest algorithm, producing a final prediction of Fit for Consumption, Need to Check, and Not Fit for Consumption. This multimodal model achieved a classification accuracy of 98% with a ROC-AUC score approaching 1.00 across all classes. While the proposed system achieved very high accuracy, further validation across diverse real-world environments is recommended to establish its generalizability.
Aplikasi Pengarsipan Surat Masuk dan Surat Keluar Berbasis Web pada SMP Negeri 32 Pekanbaru Yulisman, Yulisman; Wahyuni, Refni; Irawan, Yuda
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 3 No. 4 (2020): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Archiving incoming and outgoing mail is very important in an organization, especially for institutions such as SMP Negeri 32 Pekanbaru. The filing of letters at SMP Negeri 32 Pekanbaru is still done by writing incoming and outgoing letters on the agenda book and storing letters in filing cabinets, making it difficult to find old letter archives and often losing letters. The purpose of this research is to find the right solution so that the archiving of incoming and outgoing mail at SMP Negeri 32 Pekanbaru is more effective and efficient by making an application for archiving incoming and outgoing mail. The method used in this research is the system development model method, namely the Waterfall Model. The application design and analysis model uses the UML (Unified Modeling Language) model which is an object-oriented language or OOP (Object Oriented Programming). Application development and development uses a static programming language, namely PHP (Hypertext Pre-processor) and MySQL as application database. The results of the research on the making of incoming and outgoing mail archiving applications are very helpful and easier for SMP Negeri 32 Pekanbaru in filing incoming and outgoing mail, especially the Administration (School Administration) section because letter archiving is already stored in the database. The conclusion is that the application is very easy and helpful in archiving incoming mail and this letter is evident from the user's assessment of the application with a value of 92% more effective and efficient.
Penyuluhan Cyberbullying dan Etika Digital bagi Siswa Sekolah Dasar di SDIT Ar Royyan Pekanbaru Riau berbasis Teknologi Interaktif Wahyuni, Refni; Irawan, Yuda
Jurnal Pengabdian Masyarakat Terapan Vol 2 No 3 (2025): JUPITER Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jupiter.2.3.92

Abstract

Penggunaan teknologi digital yang semakin meluas di kalangan siswa sekolah dasar memberikan peluang besar dalam proses pembelajaran, namun juga menghadirkan risiko serius berupa cyberbullying dan perilaku bermedia yang tidak etis. Permasalahan yang ditemukan di SDIT Ar Royyan Pekanbaru menunjukkan bahwa banyak siswa terlibat dalam tindakan seperti ejekan di media sosial, komentar kasar, penggunaan bahasa tidak sopan saat bermain game daring, hingga tindakan lain seperti penyebaran pesan bernada merendahkan dan pelecehan verbal digital. Minimnya literasi digital, rendahnya etika berinternet, serta kurangnya edukasi formal mengenai keamanan digital menjadikan siswa rentan menjadi pelaku maupun korban perundungan siber. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pemahaman siswa mengenai bahaya cyberbullying dan menanamkan etika digital melalui pendekatan edukatif dan interaktif berbasis teknologi. Metode kegiatan meliputi presentasi visual, video edukatif, diskusi kelompok, kuis digital, serta roleplay yang menggambarkan kasus nyata seperti flaming, harassment, trolling, impersonation, dan outing. Kegiatan diikuti oleh 30 siswa kelas IV dan V, diawali dengan pre-test yang menunjukkan hanya 45% siswa mampu mengidentifikasi bentuk-bentuk cyberbullying beserta dampaknya. Setelah penyuluhan, hasil post-test meningkat signifikan menjadi 87%. Selain peningkatan kognitif, observasi lapangan menunjukkan perubahan sikap positif, seperti meningkatnya kehati-hatian siswa dalam berkomentar, menurunnya penggunaan bahasa kasar saat bermain daring, serta tumbuhnya empati terhadap korban cyberbullying. Guru pendamping juga melaporkan bahwa siswa mulai lebih terbuka dalam membicarakan pengalaman digital mereka dan meminta bimbingan dalam menggunakan media sosial dengan bijak. Kegiatan ini membuktikan bahwa pendekatan edukatif berbasis teknologi, dipadukan dengan metode partisipatif seperti roleplay dan gamifikasi, sangat efektif dalam meningkatkan literasi digital, kesadaran etika bermedia, dan kemampuan siswa dalam mengenali serta mencegah berbagai bentuk cyberbullying.
An Integrated Machine Learning and Deep Learning Approach for Multiclass Flood Risk Classification with Feature Selection and Imbalanced Data Handling Irawan, Yuda; Refni Wahyuni; Herianto
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.4639

Abstract

Floods are hydrometeorological disasters that often occur in tropical regions such as Indonesia and can have significant impacts on infrastructure, economy, and public health. This study aims to build and compare the performance of 21 artificial intelligence models, consisting of 15 Machine Learning algorithms and 6 Deep Learning architectures, in classifying flood risk levels based on multivariate tabular data. The dataset used includes 22 relevant environmental and social variables, with classification targets in four classes: Low, Moderate, High, and Very High. To improve data quality, feature selection was carried out using the LASSO method and class balancing with the SMOTEENN technique. The evaluation results showed that the C4.5, MLP, Random Forest, and Logistic Regression models obtained the highest accuracy (>94%), followed by deep learning models such as BiLSTM, CNN, and BiGRU with competitive accuracy (≥90%). Confusion matrix analysis confirmed the consistency of predictions across classes with a balanced distribution, especially in the decision tree and deep neural network models. This study emphasizes the importance of selecting a model that suits the characteristics of the data to achieve optimal predictions. The pipeline developed in this study is expected to be the basis for a more accurate and adaptive AI-based early warning system in mitigating flood risks in the future.
COMPARISON OF DEEP LEARNING MODELS LSTM AND BILSTM IN DIABETES PREDICTION: COMPARISON OF DEEP LEARNING MODELS LSTM AND BILSTM IN DIABETES PREDICTION Wahyuni, Refni; Irawan, Yuda
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.4904

Abstract

Diabetes mellitus remains a major global health concern, requiring early detection to prevent severe complications and reduce mortality. This study developed and evaluated two deep learning architectures, Long Short-Term Memory (LSTM) and Bidirectional LSTM (BiLSTM), for diabetes prediction using the Pima Indians Diabetes Dataset. The research methodology involved systematic preprocessing, including outlier handling with median imputation, data normalization, and training–testing data splitting (80:20). Both models were trained using 614 samples for training and 154 samples for testing, with 50 epochs and a batch size of 32. The evaluation was performed using accuracy, precision, recall, F1-score, and AUC metrics. Results indicated that LSTM achieved an accuracy of 74.03%, while BiLSTM slightly outperformed it with 74.68%. Confusion matrix analysis further revealed that BiLSTM reduced false negatives and provided more consistent learning stability compared to LSTM. Accuracy and loss curves confirmed BiLSTM’s superior convergence and generalization capability. These findings demonstrate that BiLSTM is more effective and reliable for diabetes prediction tasks. The study concludes that BiLSTM offers better potential for integration into decision-support systems, and future research could enhance performance through larger datasets, advanced optimization, and real-world clinical validation.
Co-Authors -, Herianto A.A. Ketut Agung Cahyawan W Achmad Deddy Kurniawan Aditya Rickyta Ahmad Fauzan Azim Anam, M Khairul Anita Febriani Areta Sonya Rahajeng Aulia Putri Bambang Kurniawan Cindy Syaficha Hardiana Daniel Luis Kristian Sirait Desi Rahmawati Destina Destina Devis, Yesica Edriyansyah Eka Sabna Elma Novfuja Farida Try Puspa Siregar Fonda, Hendry Habib Yuhandri, Muhammad Harun Mukhtar Hasnor Khotimah Herianto Herianto Herianto Herianto - Herianto Herianto Ikhtiaruddin Ikhtiaruddin Ilzi Adrolis SNR Ismail Wiyono Jeri Trio Sentana Kurniawan, Bambang Mardeni, Mardeni Marwati, Leha Matthijs B Punt Maulita Yulia Sari Mbunwe Muncho Josephine Mbunwe Muncho Josephine Melyanti, Rika Mohd Rinaldi Amartha Muhaimin, Abdi Muhamadiah, Muhamadiah Muhardi Muhardi - Muhardi Muhardi Muhardi Muhardi Mutiara Sari, Ria Naima Belarbi Naima Belarbi Nur Syari’ah Nurhadi Nurhazimah Rafiah O.K Saddam Hussein Perkasa, Reza Rahmaddeni Rahmaddeni Rahmalisa, Uci Renaldi, Reno Reza Perkasa Rian Ordila Richi Andrianto Rickyta, Aditya Riri Maharani Sabna, Eka Saputra, Haris Tri Sentana, Jeri Trio Siti Aisyah Siti Aisyah Suherman Suherman Sukron Nasution Suriandi Suriandi Syamsul Arifin Taman Yani Uci Rahmalisa Vita Rahmatiah Syakirah Yesica Devis Yuda Irawan Yulanda Yulanda Yulanda Yulanda, Yulanda Yulia Fatma YULISMAN Yulisman, Yulisman Yunior Fernando Zufi Pratama Noviardi