Claim Missing Document
Check
Articles

Found 33 Documents
Search

Inovasi Solar Dryer Aktif untuk Meningkatkan Kualitas dan Efisiensi Pengeringan Biji Kakao Pascapanen Mufarida, Nely Ana; Effendy , Machmud; Ariyani, Sofia
ARMATUR : Artikel Teknik Mesin & Manufaktur Vol. 7 No. 1 (2026): Jurnal Armatur (in Progress)
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/armatur.v7i1.10694

Abstract

Drying is a crucial stage in post-harvest handling of cocoa beans because it significantly determines the final quality, storage stability, and market value of the product. Traditional drying methods, still widely used by farmers, often face challenges such as weather dependence, long drying times, and the risk of contamination. This study aimed to evaluate the performance of an active solar dryer as a more efficient and hygienic alternative technology. A prototype was designed using solar collectors and a solar panel-powered ventilation system to maintain a steady flow of hot air throughout the drying process. The results showed that the active solar dryer was able to maintain a drying temperature of 45–60°C, reducing the moisture content of cocoa beans from approximately 58% to 7% in 48–72 hours. In contrast, traditional methods require 120–144 hours to achieve the same moisture content. The physical quality of cocoa beans produced by the active solar dryer was superior, with a more uniform color, an even dry texture, and no signs of case hardening. Furthermore, the fermentation aroma was stronger and the level of microbial contamination was lower than that of traditional drying. Overall, the active solar dryer technology has been shown to improve drying efficiency and cocoa bean quality, thus offering potential for widespread adoption at the farmer level.
PEMBERDAYAAN MITRA TEACHING FACTORY MELALUI INOVASI BROWNIES BATIK KHAS JEMBER BERBASIS KREATIVITAS BUDAYA LOKAL Mufarida, Nely Ana; Ariyani, Sofia; Rosyidah, Ulya Anisatur
JMM (Jurnal Masyarakat Mandiri) Vol 10, No 1 (2026): Februari
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v10i1.37251

Abstract

Abstrak: Permasalahan utama kegiatan pengabdian ini adalah minimnya variasi dan inovasi produk kuliner yang mengangkat identitas budaya lokal pada Teaching Factory Mulia Bread & Cakes di SMK Muhammadiyah 5 Kencong, Jember. Tujuan pengabdian adalah meningkatkan kreativitas, keterampilan inovasi produk, jiwa kewirausahaan, serta nilai jual produk berbasis budaya lokal. Metode pelaksanaan meliputi sosialisasi dan workshop inovasi produk, praktikum pembuatan brownies motif batik khas Jember, pelatihan standar produksi higienis, serta pelatihan digital marketing. Kegiatan melibatkan mitra Teaching Factory dan 20 siswa, dengan evaluasi melalui observasi keterampilan, kualitas produk, dan capaian penjualan. Hasil kegiatan menunjukkan peningkatan hardskill pengolahan dan desain produk sebesar ±35%, peningkatan softskill kewirausahaan dan kreativitas sebesar ±40%, serta peningkatan nilai ekonomis produk sebesar ±30% dibanding produk sebelumnya. Inovasi Brownies Motif Batik Khas Jember berhasil menjadi produk unggulan yang bernilai budaya dan berdaya saing pasar.Abstract: The main problem addressed in this community service program was the limited product variation and low innovation reflecting local cultural identity at the Mulia Bread & Cakes Teaching Factory, SMK Muhammadiyah 5 Kencong, Jember. The program aimed to enhance students’ creativity, product innovation skills, entrepreneurial mindset, and the economic value of local culture-based products. The methods included socialization and workshops on product innovation, hands-on practice in producing batik-patterned brownies inspired by Jember’s traditional motifs, training on hygienic production standards, and digital marketing training. The program involved the Teaching Factory partner and 20 students, with evaluation conducted through skill observation, product quality assessment, and sales performance analysis. The results showed an improvement in hard skills related to processing and product design by approximately 35%, soft skills such as creativity and entrepreneurship by around 40%, and an increase in product economic value by about 30% compared to previous products. The Batik Motif Brownies emerged as a competitive and culturally distinctive flagship product. 
Ultrasound Image Classification of Breast Cancer Using MobileNet Arwoko, Heru; Sofia Ariyani
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol. 11 No. 1 (2026): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v11i1.4860

Abstract

Breast cancer is one of the most prevalent diseases affecting women and has a high mortality rate if not detected at an early stage. Therefore, the development of an automated and accurate system for breast cancer diagnosis is of critical importance. One of the most commonly used methods for early breast cancer detection is medical ultrasonography (US) imaging, as it is safe and easily accessible. However, ultrasound images suffer from several limitations, including low image quality, high noise levels, and heterogeneous characteristics, which make the classification of cancer types challenging. In this study, a transfer learning approach is employed for breast ultrasound image classification by utilizing the MobileNet architecture, which is lightweight and computationally efficient, to enhance model performance. The classification task is performed on three classes: benign tumors, malignant tumors, and normal tissue. The dataset used is the BUSI (Breast Ultrasound Images) dataset obtained from Baheya Hospital, Cairo, Egypt, consisting of 780 breast ultrasound images. Experiments are conducted using several pre-trained architectures, including MobileNet, MobileNetV2, Xception, and InceptionV3. The evaluation results demonstrate that the MobileNet architecture achieves the best performance with an F1-score of 89%. These results indicate that the proposed approach is effective for classifying ultrasound images, as features are automatically and globally learned by the neural network without requiring manual geometric feature analysis.