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All Journal Jurnal Teknik ITS Jurnal Sains Materi Indonesia IPTEK The Journal of Engineering IPTEK Journal of Proceedings Series JURNAL FISIKA JFA (Jurnal Fisika dan Aplikasinya) Sewagati
Dyah Sawitri
Institut Teknologi Sepuluh Nopember
Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Physics Public Health Social Sciences Other

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Energy Experiment Teaching Kit sebagai Alat Bantu Materi Pembelajaran Energi Terbarukan yang Interaktif dalam Meningkatkan Keterampilan Sains Siswa SDN Ajung 01 Kalisat Nur Fadhilah; Doty Dewi Risanti; Ruri Agung Wahyuono; Dyah Sawitri; Lizda Johar Mawarani; Zulkifli; Maktum Muharja; I Made Arimbawa; Brian Raafi’u
Sewagati Vol 7 No 4 (2023)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v7i4.591

Abstract

Kurikulum Merdeka yang saat ini diterapkan berfokus pada pendekatan proyek yang interaktif. Berdasarkan Kurikulum Merdeka pembelajaran energi terbarukan idealnya berbasis praktikum dengan disertai media pembelajaran yang mengilustrasikan implementasi energi terbarukan dalam kehidupan sehari-hari. Namun menurut observasi awal, SDN Ajung 01 Kalisat masih memiliki fasilitas yang minim dalam melakukan proses pembelajaran sehingga siswa menjadi kurang berantusias. Oleh karena itu, pengabdian ini mencoba mengatasi masalah tersebut dengan Energy Experiment Teaching Kit. Dari hasil kuisioner sebagian besar (95%) guru menyatakan bahwa dengan kit energi sangat membantu dalam menjelaskan konsep dan pengetahuan energi terbarukan kepada siswa. Sedangkan dari hasil laporan eksperimen kerja siswa mengindikasikan bahwa siswa mampu memahami secara konseptual, meningkatkan kemampuan berfikir kritis dan bekerja sama secara tim.
Rice Identification Using Convolutional Neural Network with YOLOv7 algorithm and VGG16 Assad Resi Alfurqan; Detak Yan Pratama; Andi Rahmadiansah; Dyah Sawitri; Lizda Johar Mawarani
IPTEK The Journal of Engineering Vol. 10 No. 3 (2024)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23378557.v10i3.a20143

Abstract

Rice is the most widely consumed food worldwide. The many types of rice cause various difficulties in the process of classifying rice varieties. The process of manually classifying rice varieties that rely on human power has drawbacks including the subjectivity of assessment between observers, limited physical capabilities, and longer observation times. In this research a rice variety classification system has been developed using the Convolutional Neural Network with the YOLOv7 and VGG16 algorithms. The rice varieties classified are basmati, IR64, and rojolele varieties. The model with the YOLOv7 algorithm is trained for object segmentation of rice grains and is used to create rice grain image datasets. The model with the VGG16 algorithm was trained by transfer learning and used for classifying rice grain varieties. The model with a learning rate hyperparameter of 0,000061, the ReLU activation function, the number of neurons 256 in the second classification layer, with the fine-tuning training method, has the best performance with an accuracy value of 100%. The best VGG16 model weight is used in application implementation. Identification of the type of rice with the application can be done on the image of a batch of homogeneous and heterogeneous rice grains with various arrangements.
Co-Authors - Nurfadilah Agung Budiono Ahmad Syukron Andi Rahmadiansah Assad Resi Alfurqan Bagus Novan I. Brian Raafi’u Cindy Claudia Febiola Detak Yan Pratama Doty Dewi Risanti Doty Dewi Risanti Doty Risanti ERNAWITA ERNAWITA Frieska Ariesta Syafnijal Hery Widijanto I Irwansyah I Made Arimbawa Ibnu Taufan Lizda Johar Mawarani Lizda Johar Mawarani Lizda Mawarani Maktum Muharja Maktum Muharja Muhammad Zaim Alhusna Muhammad Zaim Alhusna Muharja, Maktum Niki Etruly Nur Fadhilah Nur Fadhilah Nur Fadhilah Purwadi Agus Darwito Rima Fitria Adiati Ruri Agung Wahyono Ruri Agung Wahyuono Suko Bagus Trisnanto Varisa Rahmawati Varisa Rahmawati Yerry Susatio Yurham afif Yurham Afif Zulkifli Zulkifli Abdullah Zulkifli Zulkifli