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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.
Pengembangan Aplikasi PKL Track Berbasis Android untuk Monitoring Praktik Kerja Lapangan di SMKS Muhammadiyah Mentok Khalishah, Jinan; Fujiyanti, Linda; Putri, Vivin Mahat
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 Ramadhan, Muhammad Hilal; Rindri, Yang Agita; Putri, Vivin Mahat
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 Pengaduan Layanan Publik Sebagai Media Pengaduan Masyarakat Desa Pagarawan Berbasis Android Alzibar, Rafi; Josi, Ahmat; Putri, Vivin Mahat
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.
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): Juni 2026 (in progress)
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.