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All Journal Applied Information System and Management Indonesian Journal of Cultural and Community Development JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Jurnal Pengabdian Masyarakat IPTEKS
Heru Arwoko
Universitas Surabaya
Humanities Computer Science & IT Control & Systems Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Implementation of Multimedia Learning Applications to Increase Understanding of Kirana Hati Bunda Tamiajeng Special School Students Endah Asmawati; Heru Arwoko; Aniva Kartika
Indonesian Journal of Cultural and Community Development Vol 14 No 3 (2023): September
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijccd.v14i3.983

Abstract

Kirana Hati Bunda Special School (SLB) is the only special school in Trawas District. This school has 19 students with special needs who come from several villages in Trawas District. The village fully bears operational costs, so the development of SLB has been quite slow. Due to limited funds, teachers are often unable to attend training to add skills and knowledge to the teaching and learning process. Teachers still have difficulties in compiling learning programs according to the different needs of students, innovating, and being creative in developing new learning media. Therefore, this program will provide training and assistance in planning, implementing, and evaluating learning for SLB Kirana Hati Bunda students. In addition, to meet the needs of teaching aids, learning applications will be made, training on application use and assistance in using multimedia learning applications with hand gesture recognition. Based on student learning results, it was found that the multimedia hand gesture recognition learning application made students more enthusiastic in learning, did not get bored of repeating exercises and the results were better when learning was done repeatedly. From two practice sessions on the same material there was a significant increase in scores
Inovasi Pembelajaran melalui Game Edukasi berbasis Visi Komputer di TK Puri Cendekia Surabaya Heru Arwoko; Sofia Ariyani
Jurnal Pengabdian Masyarakat IPTEKS Vol. 10 No. 1 (2024): JURNAL PENGABDIAN MASYARAKAT IPTEKS
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/jpmi.v10i1.2147

Abstract

Tujuan dari pengabdian masyarakat ini adalah untuk mempromosikan model inovasi pembelajaran melalui game edukasi berbasis visi komputer di TK Puri Cendekia Surabaya daerah perbatasan Gersik Inovasi pembelajaran yang dimaksudkan untuk meningkatkan interaksi dan keterlibatan anak-anak selama proses pembelajaran dan untuk meningkatkan perkembangan kognitif dan motorik mereka melalui permainan yang mendidik dan bisa menciptakan suasana yang sangat menyenangkan. Sosialisasi ini membuat dan menerapkan game edukasi yang menggunakan teknologi visi komputer untuk mengidentifikasi gerakan tangan dan tubuh anak-anak. Hal ini memungkinkan mereka untuk berinteraksi langsung dengan konten pembelajaran yang ditampilkan di layar. Hasil sosialisasi model ini menunjukkan bahwa game edukasi berbasis visi komputer dapat meningkatkan keinginan anak-anak untuk belajar, kemampuan menyelesaikan masalah, dan keterampilan motorik halus. Selain itu, komentar positif dari orang tua dan guru menunjukkan bahwa model ini dapat diadopsi secara lebih luas di berbagai institusi.
Ultrasound Image Classification of Breast Cancer Using MobileNet Heru Arwoko; 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.
Food Recommendations to Support Unsold Food Marketplace Using Content-Based Filtering Susana Limanto; Liliana; Fenny Cahyawati; Daniel Soesanto; Maya Hilda Lestari Louk; Heru Arwoko
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v9i1.47114

Abstract

Unsold food is food that has a short shelf life, is intended to be sold, and is still edible. Based on survey results, business owners usually resell unsold food at a discounted price via WhatsApp or posters placed in front of the shop or distribute it to the surrounding community. Meanwhile, consumers buy unsold food by visiting the shop directly. Unsold food promotions via WhatsApp or posters do not reach the wider community. Meanwhile, direct purchases limit the opportunity to buy unsold food from several sellers simultaneously and increase the risk of stockouts, which can lead to wasted food and missed savings for consumers. This study aims to develop an unsold food marketplace integrated with two key features: bargaining and recommendations. Recommendations are generated using content-based filtering with cosine similarity to measure the similarity between the user's purchase history and each unsold food item. The recommendation feature's findings reveal that content-based filtering generates recommendations more in line with user preferences than popularity-based ones. Validation results confirm this finding, demonstrating 100% accuracy in matching the recommended food categories with the ones users have purchased. Meanwhile, during the marketplace validation stage, 15 respondents reported strong acceptance, with average scores of 4.67 out of 5 for usefulness and 4.71 out of 5 for usability. This study highlights how an unsold food marketplace supports consumers with limited budgets, reduces food waste, and increases seller revenue, while its bargaining and recommendation features enhance user satisfaction and engagement, thereby achieving mutual benefits.
Co-Authors Aniva Kartika Endah Asmawati Fenny Cahyawati Liliana Maya Hilda Lestari Louk Soesanto, Daniel Sofia Ariyani Susana Limanto