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All Journal TEKNIK INFORMATIKA BAREKENG: Jurnal Ilmu Matematika dan Terapan Warta Pengabdian Unnes Journal of Mathematics Education Research Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Jurnal Ilmiah Farmako Bahari Community Development Journal: Jurnal Pengabdian Masyarakat Idealis : Indonesia Journal Information System Mosharafa: Jurnal Pendidikan Matematika Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Society: Jurnal Pengabdian Masyarakat Golden Ratio of Auditing Research Gemakes: Jurnal Pengabdian Kepada Masyarakat Jurnal Online Baradha International Journal of Health and Information System (IJHIS) International Journal of Healthcare and Information Technology Jurnal Archipelago SEJAGAT : Jurnal Pengabdian Masyarakat
Dian Kartika Sari, Dian Kartika
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Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Web Platform for Automated Detection of Abnormal Red Blood Cells Using Computer Vision Hasanah, Qonitatul; Fitri, Zilvanhisna Emka; Phoa, Victor; Sari, Dian Kartika
International Journal of Healthcare and Information Technology Vol. 3 No. 2 (2026): January
Publisher : P3M Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/ijhitech.v3i2.6718

Abstract

Accurate identification of red blood cell (RBC) morphological abnormalities is essential for anemia screening and hematological assessment; however, manual microscopic examination remains time-consuming, subjective, and highly dependent on expert availability. While recent deep learning studies have demonstrated promising accuracy in RBC classification, many focus primarily on model performance without addressing practical deployment constraints or system-level integration for routine laboratory use. In this study, a web-based prototype system for automated RBC abnormality classification is proposed using a lightweight MobileNetV2 architecture. The dataset consisted of 1,320 microscopic blood smear images collected from Klinik & Laboratorium Parahita in Jember and Surabaya, covering six RBC categories with balanced class distribution. All images were anonymized and verified by a certified clinical pathologist prior to use. The model was trained using transfer learning and evaluated on a held-out test set to assess generalization performance. The proposed model achieved a test accuracy of 89.77%, with consistent precision, recall, and F1-score across classes, indicating reliable multi-class classification performance. Analysis of misclassified samples revealed uncertainty primarily between morphologically similar RBC types, reflected by lower confidence scores. These results demonstrate that lightweight deep learning models can provide effective and efficient support for RBC morphology analysis when integrated into an accessible web-based system. The proposed approach contributes a deployment-oriented diagnostic support tool that has the potential to assist laboratory professionals by improving screening efficiency and consistency while preserving clinical oversight.
Lip balm Ekstrak Kulit Buah Tampoi: Formulasi, SPF dan Uji Iritasi Rahman, Ika Ristia; Kurnianto, Erwan; Sari, Dian Kartika; Hairunnisa, Hairunnisa; Puspita, Weni
Jurnal Ilmiah Farmako Bahari Vol 17 No 1 (2026): Jurnal Ilmiah Farmako Bahari
Publisher : Faculty of Mathematic and Natural Science, Garut University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52434/jifb.v17i1.43301

Abstract

Kulit buah tampoi (Baccaurea macrocarpa) diketahui mengandung senyawa flavonoid dan polifenol yang berpotensi sebagai tabir surya alami. Penelitian ini bertujuan untuk memformulasikan ekstrak etanol kulit buah tampoi dalam sediaan Lip balm serta mengevaluasi stabilitas fisik, nilai Sun Protection Factor (SPF), persentase transmisi eritema dan pigmentasi, serta uji iritasi. Lip balm diformulasikan 0,1% ekstrak kulit buah tampoi dalam tiga formula dengan variasi konsentrasi Tween 80 (2%, 3%, dan 4%). Evaluasi fisik meliputi uji organoleptis, homogenitas, pH, daya sebar, daya oles, dan titik leleh, serta uji stabilitas menggunakan metode cycling test selama enam siklus. Formula terbaik selanjutnya diuji nilai SPF menggunakan metode Mansur dan A.J. Petro, uji transmisi eritema dan pigmentasi, serta uji iritasi kulit. Hasil penelitian menunjukkan seluruh formula memiliki karakteristik fisik yang baik, homogen, pH 5, dan titik leleh 52°C. Formula dengan Tween 80 3% menunjukkan stabilitas fisik terbaik setelah uji cycling test. Formula ini memiliki nilai SPF sebesar 10,906 (metode Mansur) dan 2,094 (metode A.J. Petro), serta nilai transmisi eritema 9,12% dan transmisi pigmentasi 71,95% yang tergolong kategori regular suntan. Uji iritasi menunjukkan tidak adanya reaksi iritasi pada seluruh panelis. Dapat disimpulkan bahwa Lip balm ekstrak etanol kulit buah tampoi (Baccaurea macrocarpa) berpotensi sebagai sediaan tabir surya alami yang stabil, aman, dan efektif untuk perlindungan bibir.
Bridging the Digital Divide: Enhancing Teacher Competencies for Student-Centered Learning Through Microsite Development Dewi, Atika Ratna; Yuniati, Trihastuti; Arifa, Amalia Beladinna; Sari, Dian Kartika; Alika, Shintia Dwi
Society : Jurnal Pengabdian Masyarakat Vol. 5 No. 1 (2026): Januari
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/bn5jwa48

Abstract

Elementary school teachers at Tumiyang 1 Public Elementary School face significant challenges in adopting digital technology effectively with 73% having no prior knowledge of microsites and limited skills in creating interactive digital learning media. This digital literacy gap, common in rural educational contexts, results in conventional teaching methods that fail to engage today’s digital generation effectively. To address these challenges, a two-day intensive microsite creation training program was implemented using a participatory approach through hands-on training, mentoring, and product-based evaluation. The program consisted of three main stages, preparation, implementation, and evaluation and monitoring. Teachers learned to create web-based learning media using Google Sites and S.Id, integrating various digital resources, including Google Drive, Google Forms, YouTube, and Canva. Post-training evaluation revealed universally positive outcomes that most of the participants gained understanding of microsites, with all teachers successfully creating functional, content-rich microsites tailored to their subject areas. All participants expressed interest in further learning and rated the training as effective with clear and accessible materials. This program successfully bridged the digital competence divide, empowering rural teachers as agents of change capable of creating adaptive, interactive learning environments and contributing to educational equity between urban and rural areas.    
Co-Authors Alika, Shintia Dwi Amalia Beladinna Arifa Amaliah, Nuuraan Rizqy Andi Prademon Yunus Andreas Rony Wijaya Andriyani, Fitriya Asih, Tri Sri Noor Atika Ratna Dewi Dangin, Dangin Dewi, Riskha Dora Candra Erwin Tanur Fitri, Zilvanhisna Emka Hairunnisa Hairunnisa Kinanti, Lintang Anis Bena Kurnianto, Erwan Lintang Anis Bena Kinanti Maemunah Maemunah Mulyono Mulyono Mutaqin Akbar Nafida Hetty Marhaeni Nanang Khuzaini, Nanang NIKEN SULISTYANINGSIH Phoa, Victor Puspita, Weni Qonitatul Hasanah Rahman, Ika Ristia Reny Yuniasanti Rizky, Muhammad Rafi Fajar Sa'adah, Aminatus Satya, Malinda Capri Nurul Setyowati, Lisus Stephani Nesya Renamastika Suandana, Iwan Abdi Suciati, Amalia Susindra, Yoswenita Tantyoko, Henri Trihastuti Yuniati Wiyono, Luluk Cahyo