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Potensi Tanaman Sirih (Betel) sebagai Bahan Baku Pemberdayaan Ekonomi Produktif Masyarakat Retnowati, Retnowati; Purwatiningtyas, Purwatiningtyas; Anwar, Sariyun Naja; Mulyani, Sri
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 6 No 4 (2022): November
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v6i4.10230

Abstract

Sirih merupakan tanaman yang digunakan sebagai tanaman obat bagi masyarakat di Indonesia. Sirih tumbuh merambat sehingga tidak selalu memerlukan lahan yang luas. Tanaman ini dapat hidup subur di daerah yang dingin. Sidorejo Lor adalah kelurahan di kota Salatiga, yang berudara sejuk, di mana tanaman sirih banyak ditanam oleh masyarakat. Selain memiliki manfaat sebagai obat, sirih juga dapat menjadi bahan dasar produk olahan makanan dan minuman, yang bernilai ekonomi produktif. Masyarakat yang ingin diberdayakan dalam pengabdian pada masyarakat ini adalah kelompok Wanita kreatif (KWK) Seroja, dengan anggota ibu rumah tangga dan memiliki usaha rumahan. Dalam situasi pandemik Covid-19, anggota KWK Seroja berharap tetap berkreasi dengan menghasilkan produk ekonomi tetapi dengan bahan dasar yang mudah dan murah. Kegiatan ini bertujuan untuk memberikan contoh aplikatif, bernilai jual, melalui bahan dasar daun sirih, yaitu makanan ringan kripik sirih dan minuman mojito sirih. Selain itu kegiatan ini juga memberikan pemahaman tentang pentingnya produk kemasan sebagai media promosi. Hasilnya menunjukkan bahwa pertama, olahan kripik sirih dan mojito sirih dapat dibuat dengan mudah dan bernilai jual, kedua anggota KWK Seroja paham pentingnya kemasan produk sebagai sasaran pemasaran yang lebih luas.
Enhancing skin cancer detection using transfer learning and AdaBoost: a deep learning approach Listiyono, Hersatoto; Retnowati, Retnowati; Purwatiningtyas, Purwatiningtyas; Nur Wahyudi, Eko; Maskur, Ali
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.10379

Abstract

Skin cancer is one of the most prevalent types of cancer worldwide, with early detection playing a critical role in improving patient outcomes. In this study, we propose a deep learning model based on LeNet-7 combined with adaptive boosting (AdaBoost) to classify skin lesions as either benign or malignant using the International Skin Imaging Collaboration (ISIC) dataset. We evaluate the proposed model alongside other well-established deep learning architectures, such as residual network (ResNet), VGGNet, and the traditional LeNet model, through various performance metrics including precision, recall, F1-score, specificity, Matthew’s correlation coefficient (MCC), area under the receiver operating characteristic curve (AUC-ROC), and testing accuracy. Our results demonstrate that the proposed model (LeNet-7+AdaBoost) significantly outperforms the other models, achieving a testing accuracy of 91.3%, precision of 0.92, recall of 0.91, and AUC-ROC of 0.93. The model successfully addresses issues of overfitting and generalization, providing a robust solution for skin cancer classification. However, some misclassifications of visually similar benign and malignant lesions highlight areas for future improvement. The proposed model shows promise in real-world medical applications and paves the way for further research into optimizing deep learning models for skin cancer detection.
Pemanfaatan Gemini AI untuk Kreasi Konten Visual Promosi UMKM Kota Semarang Rara Sriartati Redjeki; Eko Nurwahyudi; Purwatiningtyas Purwatiningtyas; Budi Hartono; Theresi Dwiati Wismarini
Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial Vol. 2 No. 4 (2025): November : Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/karya.v2i4.2240

Abstract

This community service activity stems from a core challenge faced by Micro, Small, and Medium Enterprises (MSMEs) in Semarang City: the difficulty in consistently producing high-quality promotional visual content, primarily due to budget constraints and the lack of professional design skills. This condition severely hampers their competitiveness in the digital marketplace. The main goal of this activity was to enhance the technical capability of MSME participants in using Gemini AI as a multimodal model to generate professional, ready-to-use visual assets, thereby achieving significant cost and time production efficiency. The solution offered was a hands-on training focusing on Prompt Engineering defined as the art of formulating detailed commands to control the AI's output. The activity was conducted through an intensive workshop and case study mentorship for 25 MSME actors. The evaluation results demonstrated a highly significant increase in competence. The participants' average cognitive score drastically rose from 48.5% on the pre-test to 87.9% on the post-test, proving the successful mastery of Prompt Engineering. Applied results showed that participants were able to produce product visual assets with an average quality of 87.5%. Participant satisfaction reached 95.0%, especially concerning the indicators of cost and time efficiency. This activity successfully democratized design, empowering MSMEs to be self-sufficient in content production, and tangibly strengthening their brand identity and competitiveness across digital platforms.