A significant challenge in contemporary education is the limited understanding of technical subjects by students, such as the starter system within the Automotive Engineering program. The use of less engaging learning media leads to a decrease in student motivation, which ultimately affects academic performance. This study investigates the impact of an e-module, designed with Flipbook Maker, on student comprehension of the starter system. A quantitative approach was employed, utilizing pretests and posttests, along with surveys distributed to measure changes in understanding and student responses to digital learning media. The collected data was analyzed using simple linear regression through the SPSS software. The study involved a sample of 70 students from the XI grade of the Automotive Engineering program at SMK Negeri 1 Kandeman. The results revealed that the use of the e-module significantly improved student understanding, with a correlation coefficient (R) of 0.469 and an effect size (R Square) of 0.673, indicating that 67.3% of the variance in understanding was explained by the e-module. In conclusion, the e-module effectively enhanced student comprehension of the starter system. Students expressed a preference for digital learning media due to its flexibility in being accessed anytime and anywhere, both online and offline.

Early Childhood Education shapes children's intellectual development, character, and Islamic values. Lihai Islamic Preschool in Bandung became a community service partner to design a visual information design solution with an Islamic approach. This program aims to utilize empty school areas as interesting and educational visual information media, including depictions of animal characters from the Koran in children's daily activities. The design process involves needs analysis, concept discussion with the school, and design implementation. This visual information is expected to not only beautify the school environment but also support learning through creative visual media. This program demonstrates that successful graphic design is not only aesthetically pleasing, but also has a positive social and educational impact. The implementation results provide a more attractive environment for children as well as an effective learning medium. In the future, this solution can be developed into other forms of information media that are more flexible and dynamic as needed.

Purpose: The purpose of this study is to enhance the classification of batik motifs through the implementation of a novel approach utilizing Multi-Layer Convolutional Neural Networks (CNN). Batik, a traditional Indonesian textile art form, boasts intricate motifs reflecting rich cultural heritage. However, the diverse designs often pose challenges in accurate classification. Leveraging advancements in deep learning, this research proposes a methodological framework employing Multi-Layer CNN to improve classification accuracy.
Methods: The methodology integrates Multi-Layer CNN architecture with an image dataset comprising various batik motifs, meticulously collected and preprocessed for uniformity. The CNN architecture incorporates convolutional layers of different sizes (3x3, 5x5, and 7x7) to extract unique features from batik images. Training options, including the Adam optimizer and validation frequency, are optimized based on parameters to enhance model efficiency and effectiveness.
Result: Results from the experimentation demonstrate significant improvements in classification accuracy, with an overall accuracy rate of 90.88%. Notably, precision and recall scores for individual batik motifs, such as Motif Cual Bangka and Motif Rumah Adat Belitung, reached remarkable levels, showcasing the efficacy of the proposed approach.
Novelty: This study contributes novelty through the integration of Multi-Layer CNN in batik classification, offering a robust and efficient method for identifying intricate batik motifs. Additionally, the research presents a pioneering application of deep learning techniques in preserving and promoting traditional cultural heritage, thereby bridging the gap between tradition and modern technology.

Dalam era digital saat ini, guru dan dosen diharapkan mampu mengintegrasikan teknologi dalam proses pembelajaran. Pelatihan pengembangan media pembelajaran menggunakan Animaker diadakan untuk membantu mereka dalam menciptakan konten pembelajaran yang menarik dan interaktif. Pelatihan ini dilaksanakan tim dosen UDINUS Semarang yang melibatkan 125 peserta yang terdiri dari guru dan dosen dari PPMULTINDO. Tujuan pelatihan ini agar bisa meningkatkan literasi digital dan keterampilan teknis peserta dalam membuat bahan ajar yang interaktif. Hasil dari kegiatan ini, para guru dan dosen mampu menghasilkan bahan ajar yang lebih inovatif, sehingga dapat meningkatkan motivasi belajar siswa. Dengan demikian, pelatihan ini menjadi langkah penting dalam mendukung transformasi pendidikan di era digital.

Dalam pengelolaan lahan petanian kacang hijau di Desa Kedungwinagun, Kecamatan Klirong, Kabupaten Kebumen belum memiliki kemampuan guna menganalisis kondisi kelembapan tanah. Hal tersebut dapat berpengaruh pada proses pertumbuhan tanaman. Maka dari itu diperlukannya alat serta sistem yang dapat membantu petani untuk menganalisis nilai kelembapan tanah, dengan menerapkan internet of things. Dalam pengembangannya, sistem ini menerapkan metode prototype. Data yang diperoleh merupakan data hasil dari pembacaan sensor kelembapan tanah yang terhubung dengan mikrokontroler dan terkoneksi dengan jaringan internet. Hasil akhir dari sistem ini yaitu saat kondisi kelembapan tanah < 40% maka pompa air akan mati, hal ini dikarenakan kondisi tanah terdeteksi basah. Nilai kelempan tanah 40 – 60% pompa air akan mati karena nilai kelembapan tanah dalam rentang normal, sedangkan nilai kelembapan tanah > 60% pompa air akan hidup, karena kondisi tanah terdeteksi kering. Nilai sensor kelembapan tanah akan ditampilkan pada website dalam bentuk grafik secara real-time.