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All Journal Jurnal Simetris Edukasi Indonesian Journal of Electrical Engineering and Computer Science Abdimasku : Jurnal Pengabdian Masyarakat Journal of Soft Computing Exploration
Novi Hendriyanto, Novi
Teknik Informatika, Fakultas Ilmu Komputer, Universitas Dian Nuswantoro Semarang
Computer Science & IT Economics, Econometrics & Finance Education Health Professions Industrial & Manufacturing Engineering Social Sciences

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IMPLEMENTASI 7 KEBIASAAN DALAM MENGHADAPI GLOBALISASI FAKULTAS ILMU KOMPUTER UNIVERSITAS DIAN NUSWANTORO SEMARANG Hendriyanto, Novi
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 9, No 1 (2018): JURNAL SIMETRIS VOLUME 9 NO 1 TAHUN 2018
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (568.388 KB) | DOI: 10.24176/simet.v9i1.1798

Abstract

Dalam perkembangan teknologi, ada pertumbuhan yang tidak kalah penting, yaitu karakter dan kebiasaan. Kebiasaan merupakan hal yang dapat membentuk karakter di masa depan dan hal ini akan sangat berpengaruh pada dihasilkannya sumber daya manusia yang handal. Pada riset ini akan diperlihatkan bahwa dengan melatih 7 kebiasaan yang sangat efektif dari Stephen R.Covey, maka akan dihasilkan sebuah bentuk manusia baru yang sangat berkualitas tinggi, dimana manusia yang dihasilkan adalah  manusia  yang  mempunyai  inovasi,  kreatifitas  dan  dapat  menghasilkan produk-produk  yang berguna buat komunitasnya dan memiliki kebiasaan, karakter, dan sikap yang dapat diandalkan sebagai seorang innovator, pemimpin dan staff. Inilah yang dinamakan dengan pertumbuhan secara aksi dan bukan pertumbuhan scientific. Memang perlu diakui konsep daripada suatu pengetahuan memang penting karena merupakan dasar dari kemampuan yang harus dikuasai, tetapi perlu sejalan dengan pertumbuhan kebiasaan. Lebih jauh lagi,  riset ini  akan  menjelaskan hubungannya dengan universitas, dosen dan mahasiswa lebih mendalam.
Development of Android-Based Digital Drawing Learning Media Using Online Applications Hendriyanto, Novi; Rokhman, Nur
Edukasi Vol 15, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukasi.v15i2.31077

Abstract

The existence of COVID-19 has caused many problems in various fields, one of which is the world of education. Students are required to study remotely so that there is a need for innovation in learning media so that learning materials can still be accepted by students. The purpose of this research is to create digital image learning media as a support for illustration courses in animation study programs where digital drawing skills are needed. The learning media is packaged in an Android-based application to make it easier for students to access because Android is currently often used by students. The method used in building this application is the waterfall method. As for the software needed to build this application, it uses Google sites technology, appsgeyser for navigation and content and Adobe Photopea for design. The result of this research is the creation of digital image learning media applications as a support for illustration courses that can be accessed easily by students. At this stage of testing this application using the black box method to test the program's functionality and also conduct a feasibility test. For the test results, all features can function properly and for the feasibility value, it gets a score of 87% or falls into the very feasible category.
Adaptive deep learning based on FaceNet convolutional neural network for facial expression recognition Al-Ghiffary, Maulana Malik Ibrahim; Cahyo, Nur Ryan Dwi; Rachmawanto, Eko Hari; Irawan, Candra; Hendriyanto, Novi
Journal of Soft Computing Exploration Vol. 5 No. 3 (2024): September 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i3.450

Abstract

Facial recognition technology has become increasingly crucial in various applications, from personal identification, security, and human-care. Facial recognition has numerous practical applications, ranging from assessing mental health and well-being through facial expressions to evaluating customer satisfaction in service quality ratings. This study aims to develop a facial recognition model using a Convolutional Neural Network (CNN) with FaceNet architecture. The proposed method utilizes an advanced deep learning approach to generate high-quality facial embeddings, enhancing the model's ability to accurately identify and verify individuals. Our methodology includes training the CNN with FaceNet architecture, achieving an impressive average accuracy of 99.93%, with precision, recall, and F1-score all reaching 100%. The model demonstrated both high accuracy and efficiency, with an average training time of 13 minutes and 51 seconds. Future research should explore incorporating data augmentation, K-fold cross-validation, and additional transfer learning techniques to further enhance model performance and generalization. These advancements could lead to more resilient and flexible facial recognition systems capable of functioning effectively in diverse and challenging real-world conditions.
Review on integration of ontology and deep learning in cultural heritage image retrieval Budiman, Fikri; Sugiarto, Edi; Hendriyanto, Novi
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 1: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i1.pp583-592

Abstract

Image retrieval methods are currently developing towards big data processing. The literature review is focused on image big data extraction with cultural heritage domain as training and testing datasets. The development of image retrieval process starts from content-based using machine algorithms, deep learning to ontology-based. Image recognition research with cultural heritage domain is conducted because of the importance of preserving and appreciating cultural heritage, in this case, cultural heritage images such as Indonesian Batik are discussed. Batik motif images are Indonesian cultural heritage that has thousands of motifs that are grouped into many classes with a non-linear hyperplane. The problem is focused on processing big data that has many classes. Currently research is evolving into knowledge-based image retrieval using ontologies due to semantic gap constraints. The results of this literature study can be the basis for developing research on the application of appropriate deep learning algorithms so as to utilize the hierarchy of classes and subclasses of image ontologies with cultural heritage domains.
Pelatihan Desainer Grafis Junior Pada Siswa Sekolah Menengah Kejuruan Negeri 1 Kendal Hendriyanto, Novi; Winarno, Agus; Irawan, Candra; Budiman, Fikri; Sugiarto, Edi
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 8, No 3 (2025): SEPTEMBER 2025
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v8i3.3009

Abstract

Program pengabdian kepada masyarakat ini dilaksanakan di SMK Negeri 1 Kendal dengan fokus pada peningkatan kompetensi siswa jurusan Desain Komunikasi Visual melalui pelatihan Desainer Grafis Junior. Kegiatan dirancang untuk mengembangkan keterampilan teknis dalam pengoperasian perangkat lunak desain profesional (CorelDraw dan Adobe Photoshop) serta memperdalam pemahaman prinsip desain visual. Pelaksanaan meliputi analisis kebutuhan, pemberian pelatihan secara bertahap, dan evaluasi capaian melalui pre-test dan post-test. Hasil pelaksanaan menunjukkan peningkatan signifikan pada aspek pengetahuan dan keterampilan peserta, dengan luaran berupa karya desain grafis, video pembelajaran, serta pendaftaran hak kekayaan intelektual.  
Co-Authors Agus Winarno, Agus Al-Ghiffary, Maulana Malik Ibrahim Cahyo, Nur Ryan Dwi Candra Irawan Edi Sugiarto Eko Hari Rachmawanto Fikri Budiman Yundari, Yundari