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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JURNAL MEDIA INFORMATIKA BUDIDARMA PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JMM (Jurnal Masyarakat Mandiri) Sebatik JURNAL PENDIDIKAN TAMBUSAI Jurnal Ilmiah Media Sisfo Journal of Information Technology and Computer Engineering JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF SCIENCE AND SOCIAL RESEARCH EXPLORE Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Teknologi Informasi dan Pendidikan Jusikom: Jurnal Sistem Informasi Ilmu Komputer bit-Tech Jurnal Sistem Informasi dan Informatika (SIMIKA) JATI (Jurnal Mahasiswa Teknik Informatika) Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Infortech Jurnal Pendidikan Guru (JPG) Journal of Applied Data Sciences Jurnal Computer Science and Information Technology (CoSciTech) Majalah Ilmiah UPI YPTK Journal of Computer Scine and Information Technology Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Ipteks Terapan : research of applied science and education Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence EXPLORE Jurnal Komtekinfo Journal of Computers and Digital Business SmartComp JOURNAL OF COMMUNITY SERVICE AND APPLICATION SCIENCE (JCSAS) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Pustaka Robot Sister
Sovia, Rini
Universitas Putra Indonesia YPTK Padang, Padang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering 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 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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Perancangan Sistem Peminjaman Papan Surfing Menggunakan Rfid, Barcode Scanner Dan Delphi 7 Riska Amelia; Rini Sovia; Ruri Hartika Zain
Journal of Computer Scine and Information Technology Volume 10 Issue 1 (2024): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

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

Abstract

Water surfing has become a tourism industry worth billions, where millions of surfers travel around the world to several water surfing destinations in search of the 'perfect wave'. It is now estimated that there are more than 10 million water surfers in the world and this continues to increase at 12-16% per year. These surfers also visit places in the world that they feel are in harmony with what they are looking for. In one place they visited there were surfboard rental kiosks.Surfboard rental service sellers will serve visitors to rent their surfboards. Because there are too many surfboard enthusiasts, it is too difficult for surfboard rental service sellers to serve visitors. From these problems, a system is needed that can simplify the process and data collection of surfboard borrowing.
Implementasi Metode Yolov10 Untuk Mendeteksi Penyakit Melalui Analisis Citra Daun Pada Tanaman Padi Encik Yoega Renaldi; Sumijan Sumijan; Rini Sovia
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 14, No 4 (2025): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v14i4.8486

Abstract

Padi menjadi makanan pokok bagi hampir 80% untuk diseluruh Indonesia, yang penghidupannya sangat bergantung pada hasil panen. Sektor pertanian padi menghadapi tantangan berupa penyakit pada daun tanaman, dengan mayoritas petani masih menggunakan metode konvensional dalam deteksi penyakit, menyebabkan keterlambatan penanganan. Penelitian ini mengembangkan sistem deteksi dini penyakit tanaman padi menggunakan kecerdasan buatan dan computer vision dengan deep learning. Implementasi metode YOLOv10 yang efektif dengan menghilangkan penekanan Non-Maximum Suppression untuk mengurangi komputasi secara signifikan. Data penelitian yang dikumpulkan di Dinas Pertanian Kota Padang mencakup 1.446 citra dari tiga jenis penyakit: hawar daun bakteri, cendawan bercak, dan virus tungro. Pre-processing melalui augmentasi data, dataset diperbesar menjadi 10.122 citra. Pelatihan model selama 100 epoch menghasilkan tingkat kepercayaan untuk penyakit daun bakteri hawar (90%), cendawan bercak (91%), dan virus tungro (98%). Sistem mencapai tingkat kepercayaan mAP 93%, Skor F1 88%, dengan waktu komputasi 0,9 detik per citra. Sistem ini menjadi solusi efektif dan efisien bagi para ahli pertanian dan petani dalam menganalisis tingkat keparahan penyakit daun pada tanaman padi.
An Analysis of Public Satisfaction with Government Services: A Multi-Method Approach Using PCA, K-Means Clustering, and Linear Regression Abuzar Gafari; Sarjon Defit; Rini Sovia
Sebatik Vol. 30 No. 1 (2026): June 2026
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/pcdj8z43

Abstract

Flawless performance evaluation results across all service dimensions may potentially obscure the identification of areas for improvement and diminish objectivity in decision-making. This study aims to identify the specific service attributes influencing public satisfaction and to segment respondents based on their satisfaction levels at the Office of the Ministry of Religious Affairs in Payakumbuh City. The research integrates Principal Component Analysis (PCA), K-means clustering, and linear regression. PCA was employed to reduce data dimensionality and establish principal components; K-means clustering was utilized to group respondents based on perceptual similarities regarding service quality; and linear regression was applied to identify the most significant factors influencing public satisfaction within each segment. The data were sourced from the Public Service Survey Information System (SISULAP) application of the Payakumbuh Ministry of Religious Affairs, spanning June 2024 to October 2025, with a total of 1,950 respondents. The findings reveal that service process and efficiency are the primary factors influencing all respondent segments, with the low-satisfaction segment identified as the top priority for service improvement. The regression models demonstrate robust performance across all segments. These findings provide an empirical foundation for data-driven policymaking to enhance public service quality.
Sentiment Analysis of Public Comments on YouTube Content Using Principal Component Analysis and Naive Bayes Dede Pratama; Sumijan Sumijan; Rini Sovia
Sebatik Vol. 30 No. 1 (2026): June 2026
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/ra6yvz19

Abstract

The rapid acceleration of digital media development compels public broadcasting institutions to adapt to shifting public information consumption patterns, which are now centered on online platforms. TVRI Sumatera Barat has responded to these dynamics by leveraging YouTube as a channel for content distribution and audience engagement. However, this interaction generates a massive volume of unstructured comment text, rendering manual sentiment analysis inefficient, time-consuming, and prone to subjectivity. This study aims to address these challenges by automatically and objectively classifying user sentiment using a machine learning approach. The applied methodology integrates Principal Component Analysis (PCA) and the Gaussian Naive Bayes algorithm. PCA serves as a dimensionality reduction technique to simplify TF-IDF weighted text features without losing vital information, while Gaussian Naive Bayes was selected for classification due to its efficiency in rapidly processing the continuous numerical data resulting from the PCA transformation. The research dataset comprises 10 comments from the TVRI Sumatera Barat YouTube channel in 2024, collected via the YouTube Data API, which underwent preprocessing and labeling for positive and negative sentiments. Model validation was conducted using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The test results demonstrate that the combination of PCA and Gaussian Naive Bayes effectively enhances computational efficiency and delivers precise classification performance. This research makes a significant contribution by providing a measurable method for public opinion analysis, which is essential as a basis for evaluating audience perception to improve the quality of digital broadcasting strategies in public institutions.
Optimalisasi Strategi Pembelajaran Siswa Melalui Identifikasi Gaya Belajar Menggunakan Klasterisasi K-Means dan Klasifikasi K Nearest Neighbor Ilsa Hidayat; Musli Yanto; Rini Sovia
Journal of Information System Research (JOSH) Vol 7 No 3 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i3.9322

Abstract

Accuracy in adjusting teaching strategies to student learning characteristics is important because it can determine the effectiveness of the learning process. One of the key factors in improving the quality of learning is the suitability between teachers' teaching strategies and students' learning styles. The mismatch between the two aspects can reduce the effectiveness of the learning process and have an impact on low learning outcomes. Based on this, this study aims to optimize students' learning strategies through the application of the K-Means clustering model and the K-Nearest Neighbor classification. The performance of the K-Means Algorithm is able to classify learning styles and determine the labeling of learning styles, K-Nearest Neighbor is used to classify data that has been labeled by the K-Means algorithm. This research dataset amounted to 200 student data sourced from SMP Negeri 1 Panyabungan from the results of 20 questions answered by students. The results showed that the combination of the K-Means and K-Nearest Neighbor algorithms produced good performance with an accuracy value of 0.92, precision of 0.92, recall of 0.92, and F1-score of 0.91. The contribution of this research is expected to enrich the literature related to the application of the K-Means and K-Nearest Neighbor models in optimizing learning strategies, as well as assisting teachers at SMP Negeri 1 Panyabungan in designing and implementing learning strategies that are more effective and in accordance with the needs of students.
Co-Authors Abuzar Gafari Adiddo Restiady Adinda Syalsabila Aditra Agus Salim, David Ahsan Firdaus Al-arrafi, Muhammad Ikhsan Amin Amirul Mukminin, Andi Anam, M Khairul Anggy Wahyudi ANIP FEBTRIKO Aulia Fitrul Hadi Aulia Fitrul Hadi Awal, Hasri Borianto, B Chairunnissa Deliva Akbar, Syifa Dede Pratama Deny Suyandi Deval Gusrion Devia Kartika Devita, Retno Dila, Rahmah Dwi Andhara Valkyrie Dwiki Aulia Fakhri Edo Rinaldi Rais Effendy, Geraldo Revanska Eka Praja Wiyata Mandala Elmi Rahmawati Elmi Rahmawati, Elmi Encik Yoega Renaldi Erlanda, Hadrian Fana, Wulan Stau Fatimah, Noor Firdaus Gema, Rima Liana Gunadi Widi Nurcahyo Guslendra Guslendra Guslendra Guslendra Gusriva, Revi Hadi, Aulia Fitrul Hadiyanto, Tegas Hanippa Prima Putra Harnaranda, Jefri Hartika Zain, Ruri Hartika Hendri Irawan Hendrik, Billy Heriyanto Hoka Muhgrah Sandawa Huda, Ramzil Ika Melinia Sapitri Fitriyanti Ilsa Hidayat Irzal Arief Wisky Islam, Md Ataul Jimmy Febio Julsapargi Nursam Khomsi, Ahmad Lidya Adriani Darma Lony Armawati Tambunan Lubis, Fitri Amelia Sari maha rani Maha Rani Mardhiah, Sitty Mhd Wedo Muhammad Aidil Rahman Muhammad Reza Putra Muhammad, Abulwafa Musli Yanto Musli Yanto Musli Yanto Mutiana Pratiwi Niken Rindiana Noviardi, Refli Nugraha, Fajri Nurdiansyah, Ali Nursam, Julsapargi Nursyahrina Permana, Randi Permana, Randy Prihandoko Putra, Kharisma Utama Putri Melati Putri Melati Rahmad Rahmad Rahman, Muhammad Aidil Rahman, Zumardi Rahmi, Nadya Alinda Raja Ayu Mahessya Ramadani, Sela Ramadhanu, Agung - Randa Mahardika Randy Permana Randy Permana Revi Gusriva Ricki Ardiansyah ricki ardiansyah Ricki Ardiansyah Ricki Ardiansyah, Ricki Ridwan Sutri Rinaldi Chan, Fajri Rindhani Aditia, Mellya Riska Amelia Riyan Saputra Riyan Saputra, Riyan Roza, Yesi Betriana Rozakh, Muhammad Ruri Hartika Zain Ruri Hartika Zain Ruri Hartika Zain S, Sumijan Sandawa, Hoka Muhgrah Saputra, Charisman Fajri Saputra, Oriza Rama Saputra, Randy Sarjo Defit Sarjon Defit Sarjon Defit Selfi Melisa Selvia, Dina Shally Amna Shary Armonitha Lusinia Shary Armonitha Lusinia Silky Safira Siregar, Diffri Sulastri Sulastri Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sutri, Ridwan Syafri Arlis Syafril Syafril Syaiffullah, Afif Tika Christy Tri Rahayuningsih Tuti Nabila Wahyudi, Anggy Widya Nursanty Wifra Safitri Wirdawati, Wira Yanti, Rahma Yanto, Musli Yasmin, Nabilla Yenila, Firna Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri, Yuhandri Yuhandri, Y