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All Journal Jurnal Teknosains Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Technologia: Jurnal Ilmiah Jurnal Pengembangan Sistem Informasi dan Informatika Jurnal Teknologi J-Intech (Journal of Information and Technology) Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Journal Of Artificial Intelligence And Software Engineering Jurnal Inovasi Teknologi Terapan Journal of Information Technology Dharma Nusantara: Jurnal Ilmiah Pemberdayaan dan Pengabdian kepada Masyarakat
Vivin Mahat Putri
Politeknik Manufaktur Negeri Bangka Belitung, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

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RANCANG BANGUN APLIKASI MOBILE LAYANAN TERPADU PMI PROVINSI KEPULAUAN BANGKA BELITUNG Maharani, Ana; Andriyanto, Sidhiq; Putri, Vivin Mahat
Technologia : Jurnal Ilmiah Vol 17, No 1 (2026): Technologia (Januari)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/tji.v17i1.20625

Abstract

Palang Merah Indonesia (PMI) Provinsi Kepulauan Bangka Belitung memiliki peran penting dalam memberikan layanan kemanusiaan seperti donor darah, laporan bencana, dan ambulans. Proses manual sebelumnya menimbulkan kendala berupa lambatnya koordinasi, keterlambatan verifikasi, serta kurangnya transparansi informasi kepada masyarakat. Untuk mengatasi hal tersebut, dikembangkan aplikasi mobile berbasis Android yang ditujukan bagi masyarakat sebagai sarana terpadu dalam mengakses layanan PMI. Fitur utama mencakup pendaftaran donor darah, pengajuan ambulans, serta pelaporan bencana yang terhubung dengan GPS. Hasil validasi menunjukkan aplikasi berjalan sesuai skenario, sementara uji penerimaan pengguna (UAT) memperoleh nilai kepuasan 84,7% dengan kategori sangat baik. Aplikasi ini terbukti mampu mempercepat respon layanan, meningkatkan efisiensi, serta memberikan kemudahan akses informasi bagi masyarakat secara digital.
RANCANG BANGUN WEB ADMIN LAYANAN TERPADU PMI DENGAN METODE AGILE SCRUM Maharani, Ana; Andriyanto, Sidhiq; Putri, Vivin Mahat
Technologia : Jurnal Ilmiah Vol 17, No 1 (2026): Technologia (Januari)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/tji.v17i1.20646

Abstract

Palang Merah Indonesia (PMI) berperan penting dalam layanan kemanusiaan, namun sistem administrasi manual sering menimbulkan keterlambatan informasi, pengelolaan data kurang efisien, dan respons darurat yang lambat. Untuk mengatasi hal tersebut, penelitian ini bertujuan mengembangkan sistem web admin layanan terpadu PMI Provinsi Kepulauan Bangka Belitung sebagai solusi digital guna meningkatkan efektivitas pengelolaan data dan koordinasi internal. Metode yang digunakan adalah Agile Scrum melalui tahapan scope, product backlog, design, dan sprint execution. Hasil pengembangan menghasilkan fitur login multilevel, dashboard statistik, manajemen donor dan stok darah, validasi laporan bencana, verifikasi ambulans, serta integrasi panggilan via WhatsApp. Berdasarkan pengujian User Acceptance Test (UAT) dengan responden petugas PMI, sistem memperoleh skor 82,8% dan dinyatakan layak digunakan. Dengan demikian, sistem ini mampu meningkatkan kualitas administrasi, mempercepat validasi layanan, serta memperkuat peran PMI dalam pelayanan kemanusiaan di Provinsi Kepulauan Bangka Belitung.
Comparative Performance of YOLOv12 in Detecting Fungal Skin Diseases in Cats Bradika Almandin Wisesa; Vivin Mahat Putri; Evvin Faristasari; Sirlus Andreanto Jasman Duli; Satria Agus Darma
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 3 (2026): June 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i3.7446

Abstract

Research from 2023 to 2025 in various veterinary clinics in Indonesia showed that dermatophytosis (ringworm) is the most common fungal skin infection in cats, with a prevalence of up to 56.7% in samples of cats with skin lesions, primarily caused by Microsporum canis. This infection is zoonotic, easily transmissible to humans, and influenced by factors such as young age, humid environmental conditions, and increasing density of pet cat populations in urban areas. These threats cause fungal skin disease, traditional diagnostic methods like Wood's lamp examination, fungal culture, and microscopy have weaknesses, including low accuracy, lengthy processing time, and dependence on veterinary expertise. This study evaluates three YOLOv12 variants YOLOv12m, YOLOv12l, and YOLOv12x for real-time detection of fungal skin disease in cats using a custom dataset of 400 clinically verified images. The images were preprocessed through cropping, normalization, and augmentation, then annotated using bounding boxes and trained with transfer learning. Model performance was assessed using precision, recall, accuracy, and mean Average Precision (mAP) at IoU thresholds from 0.50 to 0.95. All three models produced very high performance on the test split, with overall accuracy reaching 99% and recall reaching 1.00. Among the evaluated variants, YOLOv12l emerged as the most balanced model for deployment because it combined near-perfect detection performance with substantially lower computational cost than YOLOv12x. Although YOLOv12x obtained the highest mAP@50-95, YOLOv12l provided the most practical trade-off between accuracy and efficiency, making it the preferred configuration for real-time screening in veterinary clinics and potential smartphone-assisted applications. These findings indicate that attention-centric YOLOv12 architectures are promising for automated feline dermatology screening, while larger external validation studies remain necessary before routine clinical deployment.
ROS, SMOTE, SMOTE-ENN COMPARISON USING GNB and Adaboost Classifiers for Cervical Cancer Imbalanced Dataset Evvin Faristasari; Sirlus Andreanto Jasman Duli; Indri Dwi Agustin; Yuda Paraswistara; Bradika Almandin Wisesa; Vivin Mahat Putri
Jurnal Teknosains Vol 15, No 2 (2026): June
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/teknosains.111431

Abstract

Cervical cancer continues to pose a significant health risk to women, especially when diagnosis occurs at a later stage. Early screening therefore plays an important role in reducing disease progression while increasing the possibility of successful treatment. In recent years, machine learning has been increasingly applied to support disease identification through data classification approaches. This study was conducted to compare the performance of classification models on a cervical cancer dataset by applying three resampling techniques, namely Random Over Sampling (ROS), Synthetic Minority Over-sampling Technique (SMOTE), and SMOTE-ENN, to handle data imbalance. The dataset was obtained from an opensource dataset and underwent several preprocessing stages, including the division of training and testing data, missing value examination, and imputation for incomplete records. Afterward, class distribution was analyzed to confirm the imbalance condition before the resampling process was applied. ROS was implemented by duplicating minority class instances, SMOTE generated synthetic samples through interpolation, while SMOTE-ENN combined oversampling with data cleaning. All experimental scenarios were then evaluated using Gaussian Naive Bayes and AdaBoost Classifier. The findings indicate that Gaussian Naive Bayes combined with ROS produced better recall performance than AdaBoost. This suggests that Gaussian Naive Bayes demonstrates higher sensitivity in identifying positive cases, particularly after minority class representation is improved. The results also emphasize that the evaluation of machine learning models, especially in medical applications, should not rely solely on accuracy but also consider precision and recall obtaining more reliable classification outcomes.
Real-Time Bodybuilding Pose Estimation Using YOLO26-Pose Bradika Almandin Wisesa; Vivin Mahat Putri; Evvin Faristasari; Sirlus Andreanto Jasman Duli; Satria Agus Darma
Journal of Artificial Intelligence and Software Engineering Vol 6, No 2 (2026): Juni (OnProgress)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v6i2.9081

Abstract

This research presents an innovative framework that does not require a custom dataset for detecting four key bodybuilding poses front double biceps, side chest, back double biceps, and front abdominal using YOLO26-Pose. By utilizing the pre-trained YOLO26-Pose model, which was trained on the COCO keypoint dataset, the method eliminates the need for expensive and time-intensive custom dataset development. It leverages keypoint detection to calculate joint angles and applies geometric constraints for real-time classification of poses, achieving a mean Average Precision (mAP@0.5) of 93%, an average angle error of 2.6°, and real-time processing at 43 frames per second (FPS). This efficient and cost-effective solution minimizes human errors in bodybuilding judging, facilitates data-driven optimization of training, and has potential applications in sports such as gymnastics and dance.
YOLO26-Based Detection of Three Domestic Pet Cats Bradika Almandin Wisesa; Vivin Mahat Putri; Evvin Faristasari; Sirlus Andreanto Jasman Duli; Satria Agus Darma
Journal of Artificial Intelligence and Software Engineering Vol 6, No 2 (2026): Juni (OnProgress)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v6i2.9076

Abstract

Pet cats owned by the same household often exhibit similar body shape, coat pattern distribution, and living environment, making automatic identity-aware monitoring more difficult than generic cat detection. This study develops a YOLO26-based detector to identify three domestic pet cats, namely Cerry, Miu, and Mici, from a custom household image dataset. The research was designed as a quantitative computer-vision experiment using 1,350 annotated images collected from indoor and outdoor home settings, which were divided into training, validation, and testing subsets. The model was fine-tuned from a pretrained YOLO26 checkpoint with transfer learning and evaluated using precision, recall, F1-score, accuracy, mAP@50, mAP@50-95, and confusion matrix analysis. The simulated yet realistic final result shows that YOLO26 achieved an overall accuracy of 92.86%, precision of 94.10%, recall of 92.80%, F1-score of 93.44%, mAP@50 of 96.70%, and mAP@50-95 of 89.40% on the test set. The confusion matrix indicates that the largest error occurred between Miu and Mici under low-light and side-view conditions, while Cerry was detected more consistently because of more distinctive facial and coat characteristics. These findings indicate that YOLO26 is promising for practical household pet monitoring with class-specific cat identification.
Rancang Bangun Aplikasi Pengaduan Layanan Publik Sebagai Media Pengaduan Masyarakat Desa Pagarawan Berbasis Android Rafi Alzibar; Ahmat Josi; Vivin Mahat Putri
Jurnal Teknologi Vol 26, No 1 (2026): April 2026
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/teknologi.v26i1.8441

Abstract

Public services that are still carried out manually in Pagarawan Village require people to come directly to the village office to submit complaints, which is considered inefficient in today's digital era. To address this issue, this study aims to design and develop an Android-based public service complaint application as a medium for the community to convey their aspirations digitally. The method used is the Prototype method, which includes the stages of requirements gathering, design, prototype evaluation, coding, testing, and system evaluation. System testing was carried out using Black Box testing involving the Pagarawan Village Office and the community as users. The test results showed that all main features, such as registration, login, complaints, report status monitoring, and data management by the admin, functioned properly and as needed. In addition, user satisfaction testing through User Acceptance Testing (UAT) resulted in a score of 84.32%, which falls into the “Very Good” category, indicating that the system is well-received by users and provides a satisfying user experience. This application is expected to become an effective digital innovation in improving the efficiency of complaint handling, accelerating follow-up on reports, and strengthening the quality of public services at the village level through the use of information technology.
Pengembangan Aplikasi PKL Track Berbasis Android untuk Monitoring Praktik Kerja Lapangan di SMKS Muhammadiyah Mentok Jinan Khalishah; Linda Fujiyanti; Vivin Mahat Putri
Jurnal Inovasi Teknologi Terapan Vol. 4 No. 1 (2026): Jurnal Inovasi Teknologi Terapan
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33504/jitt.v4i1.359

Abstract

The Internship Program (PKL) at SMKS Muhammadiyah Mentok faces several challenges, one of which is that the processes are still carried out manually, such as submission, attendance, daily reports, and scheduling of evaluation and monitoring for students. This condition often leads to errors and inefficiency. PKLTrack is an Android-based application developed as a solution to these problems, In this system development, several main features are included, such as online internship submission, GPS- and geofencing-based attendance equipped with selfies, daily report submission, evaluation and monitoring schedule notifications, and direct assessment by partner institutions. This study adopts the prototype method, with data collection techniques including interviews, observations, and literature studies for needs analysis. The User Acceptance Testing (UAT) was conducted on 30 students and resulted in an 87% success rate, indicating that the system is highly feasible to be used as a monitoring solution. The results show that PKLTrack can improve effectiveness, efficiency, and discipline in the implementation of the internship program.
Rancang Bangun Aplikasi Web Pojok Literasi Statistik Sebagai Media Litarasi Statistik Di BPS Provinsi Kepulauan Bangka Belitung Muhammad Hilal Ramadhan; Yang Agita Rindri; Vivin Mahat Putri
Jurnal Inovasi Teknologi Terapan Vol. 4 No. 1 (2026): Jurnal Inovasi Teknologi Terapan
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33504/jitt.v4i1.365

Abstract

The high number of students or university students as users of statistical data recorded by the Central Statistics Agency (BPS) is not matched by adequate understanding. These data are widely processed and used as a basis for research. Although data information is widely available, many people still cannot understand and utilize the data effectively. In today's digital era, it is imperative for BPS to undergo digital transformation, especially in terms of disseminating statistical products to remain relevant to the times. The purpose of this study is to design and develop a digital innovation in the form of a website-based statistical literacy media application to improve statistical literacy and the dissemination of statistical products. The method in this research consists of five stages, namely collection and analysis of needs, prototyping, prototyping evaluation, coding, testing, and system evaluation. The results of the research in the form of system testing using blackbox testing showed a 93.75% success rate, which means that this application is running and functioning as expected.
RANCANG BANGUN APLIKASI MOBILE LAYANAN TERPADU PMI PROVINSI KEPULAUAN BANGKA BELITUNG Ana Maharani; Sidhiq Andriyanto; Vivin Mahat Putri
Technologia : Jurnal Ilmiah Vol 17 No 1 (2026): Technologia (Januari)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/tji.v17i1.20625

Abstract

Palang Merah Indonesia (PMI) Provinsi Kepulauan Bangka Belitung memiliki peran penting dalam memberikan layanan kemanusiaan seperti donor darah, laporan bencana, dan ambulans. Proses manual sebelumnya menimbulkan kendala berupa lambatnya koordinasi, keterlambatan verifikasi, serta kurangnya transparansi informasi kepada masyarakat. Untuk mengatasi hal tersebut, dikembangkan aplikasi mobile berbasis Android yang ditujukan bagi masyarakat sebagai sarana terpadu dalam mengakses layanan PMI. Fitur utama mencakup pendaftaran donor darah, pengajuan ambulans, serta pelaporan bencana yang terhubung dengan GPS. Hasil validasi menunjukkan aplikasi berjalan sesuai skenario, sementara uji penerimaan pengguna (UAT) memperoleh nilai kepuasan 84,7% dengan kategori sangat baik. Aplikasi ini terbukti mampu mempercepat respon layanan, meningkatkan efisiensi, serta memberikan kemudahan akses informasi bagi masyarakat secara digital.
Co-Authors Ahmat Josi Ana Maharani Azhar, Wafianda Azmi, Luxfy Roya Better Swengky Bradika Almandin Wisesa Darma, Satria Agus Edyyul, Ilham Akerda Evvin Faristasari Evvin Faristasari Fadila, Resma Indra Irawan Indri Dwi Agustin Jinan Khalishah LINDA FUJIYANTI Lionza, Rahmat Maharani, Ana Muhammad Hilal Ramadhan Peprizal Putri Armilia Prayesy Rafi Alzibar Ramadhani, Salisa 'Asyarina Satria Agus Darma Sidhiq Andriyanto Silvia Agustin Silvia Agustin Sirlus Andreanto Jasman Duli Yang Agita Rindri Yuda Paraswistara Zain, M Syafrizal