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All Journal Riau Journal of Computer Science Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INOVTEK Polbeng - Seri Informatika JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JOISIE (Journal Of Information Systems And Informatics Engineering) EDUMATIC: Jurnal Pendidikan Informatika Journal of Technopreneurship and Information System (JTIS) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Zonasi: Jurnal Sistem Informasi Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JISA (Jurnal Informatika dan Sains) Journal Zetroem Jurnal Computer Science and Information Technology (CoSciTech) Jurnal J-PEMAS Jurnal Nasional Teknik Elektro dan Teknologi Informasi JAIA - Journal of Artificial Intelligence and Applications Innovative: Journal Of Social Science Research SATIN - Sains dan Teknologi Informasi The Indonesian Journal of Computer Science
Junadhi Junadhi
STMIK Amik Riau
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Other

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Heart Failure Disease Classification Using Random Forest Algorithm with Grid Search Cross Validation Technique Septia, Rapindra; Junadhi; Susi Erlinda; Wirta Agustin
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4765

Abstract

Heart failure is one of the leading causes of death worldwide and requires early detection to reduce the risk of serious complications. However, the imbalance in medical data poses a challenge in developing accurate prediction models. This study developed a heart failure classification model using the Random Forest algorithm, optimized with Grid Search Cross Validation to find the best combination of hyperparameters. The dataset consisted of 300 observations with 12 medical features and 1 target feature. Data preprocessing included outlier removal using the Interquartile Range (IQR) and Winsorize methods. The Synthetic Minority Oversampling Technique (SMOTE) was applied to address class imbalance, resulting in a more balanced training data distribution. The dataset was split into 80% training and 20% testing data using stratified sampling to maintain class proportions. The model was evaluated using accuracy, precision, recall, and F1-score metrics, with results showing 90% accuracy, 0.94 precision for class 0, 0.80 precision for class 1, 0.91 recall for class 0, and 0.86 recall for class 1. The model was implemented in a Streamlit-based application, allowing users to input health parameters and receive interactive predictions. This study demonstrates that optimizing the Random Forest algorithm with Grid Search Cross Validation can improve heart failure classification performance, providing a practical solution for supporting heart failure classification. Keywords: Heart Failure Classification, Random Forest, Hyperparameter Optimization, SMOTE, Model Evaluation.
Analisis Sentimen Layanan Hotel Menggunakan Algoritma Extra Trees: Studi Kasus pada Ulasan Pelanggan Aprilita, Windi; Junadhi; Agustin; Hadi Asnal
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.4014

Abstract

This research aims to analyze the sentiment of hotel services based on customer reviews using the Extra Trees algorithm. This method was tested on a dataset containing customer reviews about hotel services. The evaluation is done by taking into account the accuracy, precision, recall, and F1 score of the developed model. The results showed that the Extra Trees algorithm was able to achieve an accuracy of 85.05%, with a precision of 84.46%, a recall of 97.00%, and an F1 score of 90.17%. These findings indicate that the Extra Trees algorithm has good performance in analyzing hotel service sentiment based on customer reviews. The implication of this research is to provide guidance to hotels to understand and improve their service quality based on feedback from customers. In addition, this research can also be the basis for further development in the field of sentiment analysis and customer service in the tourism industry.
Klasifikasi Emosi Terhadap Konflik Israel-Palestina Menggunakan Algoritma Gated Recurrent Unit Saputra, Eko Ikhwan; Fatdha, T.Sy. Eiva; Agustin; Junadhi; M. Khairul Anam
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4106

Abstract

The Israel-Palestine conflict intensified following the October 7, 2023, attack by Hamas on Israel, triggering various emotional reactions on social media. Emotion classification is crucial for understanding public sentiment related to this conflict. This study utilizes 9,917 tweets from platform X (Twitter) to classify emotions such as joy, sadness, anger, fear, disgust, and surprise. The deep learning algorithm used is Gated Recurrent Unit (GRU), developed with three different training and testing data splits: 70:30, 80:20, and 90:10. For text representation, Global Vector (GloVe) word embedding is employed. Given the imbalanced dataset, this study applies the Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance. The research results indicate that the GRU model with a 90:10 data split without using SMOTE achieves the highest accuracy of 75%, followed by the models with 70:30 and 80:20 splits, which each have an accuracy of 73%.
PROTOTYPE DESIGN USER INTERFACE SISTEM PRELOVED MENGGUNAKAN METODE LEAN UX Hasibuan, Fadliansyah; Setiawan, Hengki; Ali, Edwar; Junadhi
ZONAsi: Jurnal Sistem Informasi Vol. 5 No. 1 (2023): Publikasi artikel ZONAsi: Jurnal Sistem Informasi Periode Januari 2023
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v5i1.12915

Abstract

Jual beli barang preloved mulai banyak diminati sebagian masyarakat karena memiliki harga yang lebih terjangkau dibandingkan barang yang kondisinya baru, namun masih layak untuk digunakan kembali. Penjual yang kesulitan memperluas jangkauan pemasaran dan konsumen yang kesulitan menemukan barang preloved yang diinginkan, menjadi permasalahan pada bisnis barang preloved. Pada penelitian ini dibuat sistem preloved melalui web online menggunakan pendekatan metode Lean UX sebagai proses perancangan prototype user interface. Sistem ini dirancang untuk mempermudah penjual dan pembeli barang preloved. Pengumpulan data melibatkan 100 responden yang terdiri dari masyarakat yang pernah berbelanja barang preloved, menggunakan kuesioner USE untuk mendapat umpan balik dari pengguna agar mempercepat perancangan dan mengetahui nilai usability nya. Hasil pengujian menunjukkan persentase usablity sebesar 86% yang berarti dalam kategori sangat layak. Maka dapat disimpulkan bahwa prototipe sistem preloved memiliki User Experience yang sangat baik dan dapat diterima dengan mudah oleh pengguna web.
Implementasi Deep Learning untuk Pengenalan Plat Nomor Kendaraan Ginting, Alex Elanta; Azdar, Qowiyyu; Jabbar, Fiqri Abdul; Ramadhani, Yurifa; Junadhi
Innovative: Journal Of Social Science Research Vol. 5 No. 4 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i4.20358

Abstract

Automatic license plate recognition is a vital component in the development of intelligent transportation systems and security management based on digital imagery. This study examines the implementation of deep learning using algorithm to detect and recognize vehicle license plates from visual images. Using 472 sample images of license plates taken under varying lighting conditions, camera angles, and background complexities, the research involved manual data labeling and trained an end-to-end object detection model. Google Colab was employed to train the model, allowing efficient and cost-free GPU computation. After training, the system was tested for its ability to detect license plate regions, followed by character extraction using Optical Character Recognition (OCR). Experimental results show that the model accurately detects license plate regions with a detection accuracy exceeding 90%, and successfully reads most alphanumeric characters, despite challenges such as image blur and partial occlusion. These findings demonstrate that the a reliable solution for license plate recognition systems powered by artificial intelligence. Furthermore, this research offers potential for integration into automated edge devices and intelligent traffic management systems.
Optimalisasi Penggunaan Microsoft Powerpoint Guna Mendukung Keahlian Siswa Magang Di Stmik Amik Riau Junadhi; Agustin; Edwar Ali; Susanti; Herwin
J-PEMAS - Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2023): Jurnal Pengabdian Masyarakat J_PEMAS
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/j-pemas.v4i2.938

Abstract

Pengabdian kepada masyarakat (PKM) ini bertujuan melatih para siswa untuk membuat media pembelajaran berbasis powerpoint. Sehingga dapat dimanfaatkan dalam proses presentasi laporan di sekolah. Metode yang digunakan adalah action research (Penelitian tindakan) yang terdiri dari 4 (empat) langkah, yaitu: analisa awal, proses persiapan, proses pelaksanaan dan penutup. Adapun mitra dari kegiatan PKM ini adalah para siswa/siswi yang melaksanakan kerja praktik di STMIK Amik Riau sebanyak 20 orang dan kegiatan pengabdian ini dilaksanakan selama 2 (dua) hari. Adapun topik materi yang diberikan kepada siswa meliputi cara mengaktifkan/membuka dan menutup aplikasi Ms. PowerPoint; membuat file baru, teknik penggunaan warna, mengubah warna background, menambahkan tabel, gambar, video, sound dan menggunakan efek dalam presentasi; serta mencetak slide, note page, dan handout. Hasil yang diperoleh dari kegiatan PKM ini yaitu sebanyak 83% dari jumlah siswa sebagai peserta telah mampu membuat media presentasi berbasis powerpoint secara tuntas. Dengan demikian bisa ditarik kesimpulan bahwa kegiatan ini dapat memberikan dampak yang baik karena peserta (siswa) telah mampu meningkatkan hardskill untuk mengoperasikan laptop atau komputer diantaranya bisa membuat media pembelajaran berbasis powerpoint. Sehingga media pembelajaran yang telah dibuat tersebut dapat digunakan dalam kegiatan keperluan di sekolah.
Workshop Desain Sistem UI/UX Untuk Membangun Ekosistem Kreatif Junadhi; Agustin; Rahmiati; Susanti; M. Jamaris
J-PEMAS - Jurnal Pengabdian Masyarakat Vol. 5 No. 1 (2024): Jurnal Pengabdian Masyarakat J_PEMAS
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/j-pemas.v5i1.1081

Abstract

Workshop Desain Sistem UI/UX Untuk Membangun Ekosistem Kreatif bertujuan memberikan pemahaman mendalam tentang desain sistem antarmuka pengguna (UI/UX) sebagai kunci dalam pengembangan ekosistem kreatif yang berkelanjutan. Kegiatan dilakukan selama dua hari dengan melibatkan dosen sebagai narasumber dan mahasiswa komunitas UI/UX desain yang berjumlah sebanyak 30 orang. Rangkaian kegiatan dimulai dari tahapan pengantar dan pemahaman dasar desain UI/UX, peserta diperkenalkan pada prinsip-prinsip penting dan tren terkini dalam desain. Studi kasus dan analisis mendalam memberikan contoh aplikasi praktis dari konsep-konsep tersebut dalam situasi dunia nyata. Sesi praktis dan hands-on memberikan peserta kesempatan untuk menerapkan pengetahuan yang telah mereka pelajari melalui proyek-proyek desain yang relevan. Workshop kelompok dan kolaborasi meningkatkan interaksi antar peserta, memfasilitasi diskusi, dan mendukung pertukaran ide. Sesi konsultasi dan feedback memastikan bahwa peserta mendapatkan panduan dan perbaikan langsung terhadap desain mereka. Pameran dan diskusi hasil karya mengakhiri workshop dengan merayakan kreativitas peserta dan memberikan kesempatan untuk mendiskusikan solusi desain. Evaluasi dan umpan balik sesudahnya membantu memperbaiki workshop untuk masa depan. Hasil akhir kegiatan workshop menunjukkan bahwa 87% peserta berhasil memperoleh kemampuan dalam merancang sistem UI/UX untuk membangun ekosistem kreatif, sedangkan 13% lainnya belum mencapai kriteria tuntas.
Co-Authors Adhitya Karel Maulaya Agustin Agustin Agustin -, Agustin Agustin Agustin Ahmad Nazri aisyah manurung Alexsander Anam, M Khairul Aprilita, Windi Aprillian Kartino Azdar, Qowiyyu Benino Giordiola Millenio Bias Arbi Fauzan Chakra Wibawanto Devi Efriadi Dwiansyah, Zovanli Edwar Ali Efrizoni, Lusiana Erlin Fatdha, T.Sy. Eiva Fathur Rahman Fransiskus Zoromi Fransiskus Zoromi Friadi, Roby Ginting, Alex Elanta Hadi Asnal, Hadi Handoko Harianto, Helfin Hasibuan, Fadliansyah Helda Yenni, Helda Helfin Harianto Heru Satria Surya Herwin Herwin Herwin, Herwin Irfansyah Irfansyah Jabbar, Fiqri Abdul Jamaris, Muhamad Jasmarizal Laili Suryati Lusiana M. Agustian Reyza Novris M. Jamaris M. Jamaris Mahesya, Abdan Fitra Mardainis Marlim, Yulvia Nora Mi`rajul Rifqi Muhammad Muadin Muhammad Oase Ansharullah Muhammad Oase Ansharullah Muhammad Syaifullah Nanang Susanto Naufal Khairi Nelianli Yan Jaya Nova Agustina Nu'man Nu'man Rahmaddeni Rahmaddeni Rahmiati Rahmiati Ramadhani, Yurifa Rio Agus Panbudi Rivaldi Dwi Andhika Rizaldinata, Wahyu Roby Friadi Said, Shodiq Mufadhol Saputra, Eko Ikhwan Septia, Rapindra Setiawan, Hengki Shodiq Mufadhol Said Silvyana Dwi Putri SUSANTI Susanti, Susanti Susi Erlinda SUSI ERLINDA T. Sy. Eiva Fatdha Tashid Tashid Triyani Arita Fitri Wirta Agustin Yansyah Saputra Wijaya Yuda Irawan