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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal Teknologi dan Sistem Komputer International Journal of Artificial Intelligence Research Communications in Science and Technology SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Elektrika Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Abdi Insani Jurnal Pengabdian kepada Masyarakat Nusantara Journal of Community Development Bookchapter Pendidikan Universitas Negeri Semarang Indonesian Journal of Mathematics and Natural Sciences
Nugroho, Anan
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Implementasi Multilayer Perceptron Artificial Neural Network untuk Prediksi Konsumsi Energi Listrik PT PLN (Persero) UP3 Salatiga Saputra, Roni; Sunardiyo, Said; Nugroho, Anan; Subiyanto, Subiyanto
Elektrika Vol. 15 No. 2 (2023): October 2023
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/elektrika.v15i2.6411

Abstract

Electricity is energy that flows through cable networks and has become an important part of the progress of human civilization in various fields. The high demand for electrical energy for consumers requires providers of electrical energy to provide a reliable but economical supply of electrical energy. Therefore, strategies and methods are needed to adjust the supply and demand of electrical energy. This can be achieved by carrying out proper and appropriate operational planning. One of the important steps in planning the operation of an electric power system is predicting the demand for electrical energy. However, in the existing research there are still deficiencies in the form of a high error rate. The purpose of this study was to determine the implementation of the multilayer perceptron artificial neural network to predict electricity in 2022-2026 at PT PLN (Persero) UP3 Salatiga. The study used time series data on electricity consumption for the previous 5 years. Based on the research that has been done, the best network variation is TRAINGDA 4 hidden layer with 20 hidden layer nodes, this network model at the training stage produces output with MAD of 2,624,072 kWh and MAPE of 2.79%, and at the stage testing produced an output with MAD of 3,728,386 kWh and MAPE of 3.24%. Keywords: Multilayer perceptron artificial neral network, Forecasting, Electricity consumption.ABSTRAK  Listrik merupakan energi yang mengalir melalui jaringan kabel serta sudah menjadi bagian yang penting dalam kemajuan peradaban manusia di berbagai bidang. Tingginya kebutuhan energi listrik pada konsumen mengharuskan penyedia energi listrik menyediakan suplai energi listrik yang handal tetapi tetap ekonomis. Oleh karena itu, diperlukan strategi dan metode untuk penyesuaian antara supplay dan demand energi listrik. Hal tersebut dapat dicapai dengan melakukan perencanaan operasi yang baik dan tepat, salah satu langkah perencanaan operasi sistem tenaga listrik yang penting yaitu prediksi kebutuhan energi listrik. Namun dalam penelitian yang ada masih terdapat kekurangan berupa tingkat kesalahan yang masih cukup tinggi. Tujuan dari penelitian ini adalah untuk mengetahui implementasi multilayer perceptron artificial neural network untuk melakukan prediksi listrik pada tahun 2022-2026 pada PT PLN (Persero) UP3 Salatiga. Penelitian menggunakan data time series konsumsi energi listrik 5 tahun sebelumnya. Berdasarkan penelitian yang telah dilakukan didapatkan variasi jaringan terbaik yaitu TRAINGDA 4 hidden layer dengan 20 node hidden layer, model jaringan ini pada tahap training menghasilkan output dengan nilai MAD sebesar 2,624,072 kWh dan MAPE sebesar 2.79%, serta pada tahap testing menghasilkan output dengan nilai MAD sebesar 3,728,386 kWh dan MAPE sebesar 3.24%.
PEMANFAATAN TEKNOLOGI COMPUTER VISION BERBASIS YOLO UNTUK MENDETEKSI KERUMUNAN DI SMKN 4 MALANG Nugroho, Anan; Indaryanto, Faizal; Suni, Alfa Faridh; Arfriandi, Arief; Wibawanto, Hari; Oktaviyanti, Dwi; Savitri, Dina Wulung
Jurnal Abdi Insani Vol 11 No 1 (2024): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v11i1.1437

Abstract

In limited face-to-face learning, teachers and students must implement health protocols to prevent the spread of the Covid-19 virus. However, implementing health protocols in schools as a new habit in the midst of a pandemic is certainly not easy. There are many reports related to the number of violations of health protocols in schools during face-to-face learning. Therefore, by innovating and utilizing existing technology in the 4.0 era can help us to detect social boundaries. The purpose of this service activity is so that teachers and students can learn YOLO-based computer vision technology at SMKN 4 Malang as a means of preventing the spread of Covid-19. In addition, teachers and students can also learn to make simple applications based on YOLO. This activity begins with the socialization of YOLO-based computer vision technology as a crowd detection tool to the school. Then the design and manufacture of crowd detection tools by the service team, training in making crowd detection applications, and ending with a discussion between the trainees and the service team. The results of the service show that this activity has succeeded in developing a crowd detection tool that can help calculate the number and distance of people who do not apply health protocols at SMKN 4 Malang. This tool makes it easier for schools to monitor the activities of school residents in implementing health protocols. This service activity is very useful and in demand by teachers and students. This is evidenced by the enthusiasm of the participants in participating in the training of YOLO-based crowd detection tools.
Peningkatan kompetensi elektronika siswa SMKN 4 Semarang melalui pelatihan rakit drone quadcopter Nugroho, Anan; Wahyudi, Wahyudi; Rusiyanto, Rusiyanto; Naryanto, Rizqi Fitri; Ghulamzaki, Muhammad; Mubarak, Raihan Fa'iq; Hidayatulloh, Dimas Restu
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 8, No 3 (2024): September
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v8i3.25385

Abstract

AbstrakPentingnya penguasaan teknologi bagi siswa Teknik Elektronika Industri di SMKN 4 Semarang dapat diwujudkan melalui pelatihan perakitan quadcopter yang mendukung pemahaman dan praktik langsung dalam menghadapi perkembangan teknologi. Tujuan dari kegiatan pengabdian ini adalah agar siswa dapat belajar dan memiliki pengetahuan dalam bidang elektronika, khususnya pemahaman terkait quadcopter. Metode pelaksanaan meliputi merumuskan masalah, menentukan komponen, penyampaian materi, praktik merakit, dan praktik menerbangkan quadcopter. Pelatihan perakitan quadcopter diadakan pada hari kamis, 25 April 2024, di SMKN 4 Semarang, dengan jumlah peserta sebanyak empat puluh siswa. Pelatihan berhasil membuka wawasan bagi siswa SMKN 4 Semarang untuk mengembangkan kompetensi elektronika dengan mengetahui komponen, cara merakit, dan cara menerbangkan quadcopter.  Kata kunci: elektronika; kompetensi; quadcopter; pelatihan; perakitan AbstractThe importance of mastering technology for Industrial Electronics Engineering students at SMKN 4 Semarang can be realized through quadcopter assembly training that supports understanding and direct practice in dealing with technological developments. The purpose of this service activity is for students to learn and have knowledge in the field of electronics, especially understanding related to quadcopters. The implementation method includes observation, formulating problems, delivering material, practicing assembling, and practicing flying the quadcopter. The quadcopter assembly training was held on Thursday, April 25, 2024, at SMKN 4 Semarang, with forty students participating. The training succeeded in opening insights for SMKN 4 Semarang students to develop electronic competencies by knowing the components, how to assemble, and how to fly the quadcopter.  Keywords: electronics; competency; quadcopter; service; assembly
Optimalisasi Elementor Pro untuk Landing Page Sekolah Interaktif dengan Formulir Otomatis Berbasis WordPress Richardo, Hizkia Natanael; Astagina, Paramesti; Ariolin, Anantha Revoislami; Budiman, Kholiq; Nugroho, Anan; Alamsyah, Alamsyah
Indonesian Journal of Mathematics and Natural Sciences Vol. 48 No. 2 (2025): Vol. 48 No. 2 (2025): Volume 48 Nomor 2 October 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jm.v48i2.29374

Abstract

Perkembangan teknologi informasi mendorong institusi pendidikan untuk mengadopsi platform digital guna meningkatkan komunikasi dengan pemangku kepentingan. Penelitian ini bertujuan untuk mengkaji optimalisasi Elementor Pro dalam merancang landing page sekolah yang interaktif dengan integrasi formulir otomatis menggunakan pendekatan Agile. Metode Agile diterapkan melalui tahapan perencanaan, perancangan, pengembangan, pengujian, penerapan, dan tinjauan, dengan fokus pada efisiensi pengembangan dan pengalaman pengguna. Hasil penelitian menunjukkan bahwa Elementor Pro memungkinkan pembuatan landing page yang responsif dan menarik secara visual dengan waktu pengembangan yang lebih singkat dibandingkan metode konvensional, berkat fitur drag-and-drop dan integrasi plugin seperti Fluent Form dan FluentSMTP. Landing page yang dihasilkan mencapai waktu pemuatan rata-rata 2,8 detik dan skor Lighthouse yang optimal (Best Practices 100, SEO 85), mendukung aksesibilitas dan visibilitas daring. Integrasi formulir otomatis meningkatkan efisiensi pengelolaan data komunikasi, seperti pendaftaran siswa baru. Penelitian ini memberikan kontribusi praktis berupa solusi digital untuk sekolah dan kontribusi akademik dalam pengembangan web berbasis no-code/low-code.
Performance of Deep Face Recognition Models under Adaptive Margin Loss: A Real-Time Evaluation Aditama, Kevin Muhammad Tegar; Nugroho, Anan; Subiyanto, Subiyanto; Pongoh, Arthur Gregorius
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1.1641

Abstract

Real-time face recognition systems encounter a critical trade-off between high-security demands and computational efficiency, particularly when deployed in unconstrained open-set environments. This study presents a comprehensive benchmarking of four distinct deep learning backbones ResNet100, GhostFaceNet, LAFS, and TransFace specifically trained using the Adaptive Margin Loss (AdaFace) function to handle image quality variations. The primary objective is to identify the optimal architecture for secure attendance systems operating on standard hardware with limited training data. The evaluation protocol employs a rigorous real-world open-set test to quantify performance using False Acceptance Rate (FAR) and False Rejection Rate (FRR). The experimental results demonstrate that ResNet100 establishes the highest security standard, achieving a 0.00% FAR at strict thresholds. Meanwhile, GhostFaceNet emerges as the most balanced solution for resource-constrained deployments, delivering competitive accuracy above 93% with significantly lower computational complexity. Conversely, the Vision Transformer (TransFace) fails to generalize in this low-data regime, resulting in unacceptable false acceptance rates. These findings definitively recommend GhostFaceNet for efficient edge-based implementations, while ResNet100 remains the superior choice for mission-critical security applications.
Co-Authors Abiaska, Arya Kresna Aditama, Kevin Muhammad Tegar Afifi, Sesaria Nisa Agung Budiwirawan Agus Ardiyanto Al Wafi, Ahmad Zein Alamsyah - Alfa Faridh Suni Anggraini Mulwinda Arfriandi, Arief Ariolin, Anantha Revoislami Astagina, Paramesti Baehaqi Bambang Priyono Budi Sunarko Budiman, Kholiq Diyanasari, Ledi Dwi Oktaviyanti, Dwi Fikri, Akmal Firdaus, Agung Adi Ghulamzaki, Muhammad Hanung Adi Nugroho Hari Wibawanto Heny Setyawati Hidayatulloh, Dimas Restu Indaryanto, Faizal Lina Choridah Mahalul Azam Mubarak, Raihan Fa'iq Mukti, Gandhi Satria Noor Akhmad Setiawan Nurharsono, Tri Pongoh, Arthur Gregorius Pradana, Irzhafran Ridho Rezianto, Rizal Richardo, Hizkia Natanael Ricko Irawan Rismawan, Yudha Andriano Rizqi Fitri Naryanto Roni Saputra, Roni Rusiyanto Rusiyanto, Rusiyanto Said Sunardiyo Salsabila, Alif Mazida Savitri, Dina Wulung Septiani, Amalia Setiyawan, Farhan Taufikurrahman Setya Rahayu Simanjuntak, Jhonatur Stheven Soambaton, Muhamad Febrian Soambaton, Muhammad Febrian Soedjatmiko Soedjatmiko Sri Lestari Sri Sukamta Subagja, Mona Syahroni Hidayat Tatyantoro Andrasto Ulfah Mediaty Arief Wafi, Ahmad Zein Al Wahyudi Wahyudi Wahyudi, Tri Agus