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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Ganendra: Majalah IPTEK Nuklir Jurnal Teknik Elektro Khizanah al-Hikmah : Jurnal Ilmu Perpustakaan, Informasi, dan Kearsipan Jurnal EECCIS Teknofisika Seminar Nasional Informatika (SEMNASIF) Jurnal Kajian Informasi & Perpustakaan JURNAL NASIONAL TEKNIK ELEKTRO Wikrama Parahita : Jurnal Pengabdian Masyarakat Jurnal Otomasi Kontrol dan Instrumentasi Jurnal Teknik Informatika (JUTIF) Warta LPM
Nazrul Effendy
Departemen Teknik Nuklir Dan Teknik Fisika Fakultas Teknik, Universitas Gadjah Mada
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Physics Social Sciences Other

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Evaluasi Status Gizi Siswa SDN 1 Sikunang, Wonosobo, melalui pengukuran Antropometri dengan WHO AnthroPlus Dewi, Wulan May Kusuma; Effendy, Nazrul; Birru, Muhammad Ismail Al
Warta LPM WARTA LPM, Vol. 27, No. 3, November 2024
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/warta.v27i3.4803

Abstract

Students of SDN 1 Sikunang, Wonosobo habitually consume unhealthy foods that affect their nutritional status, which is intervened by their lifestyle, parenting, and the unhealthy food condition of the school canteen. It is proven by 30.3% of students in grades 4-6 have abnormal nutritional status. Therefore, it requires an assessment of nutritional status by anthropometric measurement of body mass index based on age to all students. This community service aims to measure the level of nutritional status of students at SDN 1 Sikunang and can be implemented by the school in the long term. A total of 114 students were measured anthropometrically using analog weight scales and microtoise to determine body mass index. The data was analyzed together with the age data of each student utilizing WHO AnthroPlus to determine the level of IMT/U nutritional status. From this activity, 3.5% of students were found to have severely thinness, 9.7% of students with thinness, 73.7% with normal nutrition, 4.4% with overweight, and 3.5% as obese. These results indicate that 26.3% of students at SDN 1 Sikunang are still classified as having abnormal nutritional status. It is recommended that the nutritional status of these students be routinely monitored by the health unit of SDN 1 Sikunang and informed to parents. In addition, it is recommended that the school commits to implementing a healthy canteen and educating students and parents about balanced nutrition and healthy foods.
Machine learning application for particle accelerator optimization-a review Rachmawati, Isti Dian; Effendy, Nazrul; Taufik, Taufik
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i4.pp3014-3021

Abstract

Particle accelerators receive significant attention from researchers. This machine consists of various interdependent elements, so it is complex. Efficient system tuning and diagnostics are essential for utilizing accelerator technology. In addition, machine learning (ML) has been applied in several applications. ML methods such as artificial neural networks, random forest, reinforcement learning, genetic algorithm, and Bayesian optimization have been used for accelerator optimization. The optimization of particle accelerators covers their performance and efficiency. This paper reviews the application of ML techniques in optimizing particle accelerators, highlighting their importance in addressing the complexity inherent in accelerator systems and advancing accelerator science and technology.
Deteksi Osilasi Kontrol Proses Industri dengan Menggunakan Jaringan Saraf Tiruan - Review Tsanya, Nukman Tsaqib; Wardana, A.N.I.; Effendy, Nazrul
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 16 No. 3 (2022)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v16i3.1468

Abstract

Osilasi kontrol loop adalah salah satu masalah yang sering terjadi di proses industri. Osilasi menyebabkan variabel proses tidak dapat dipertahankan pada kondisi yang diinginkan yang akan menyebabkan kerugian finansial pada industri. Selama beberapa tahun terakhir sudah banyak penelitian yang dilakukan, dan salah satu pendekatan yang semakin banyak digunakan adalah menggunakan jaringan saraf tiruan (JST). Tulisan ini memberikan gambaran tentang karakterisktik JST dan penerapannya untuk deteksi dan diagnosis osilasi kontrol pada proses industri. Dari beberapa studi yang dipelajari, arsitektur JST yang paling umum dipilih untuk proses deteksi osilasi adalah multilayer perceptron (MLP), convulational neural network (CNN) dan recurrent neural network (RNN). Tiap arsitektur tersebut memiliki karakteristik dan fungsi yang berbeda. MLP memiliki karakteristik yang sederhana, dan fleksibel dibandingkan jaringan lainnya. CNN bekerja sangat baik untuk melakukan teknik deteksi dengan menggunakan pengenalan pola. Sementara RNN sangat baik digunakan untuk mendeteksi sistem dinamis pada proses industri.
HARDWARE DESIGN OF THE TOUCHLESS HAND CODE AND CONVOLUTIONAL NEURAL NETWORKS - BASED AUTOMATIC DOOR SECURITY SYSTEM Prihanto, Surya; Effendy, Nazrul; Nopriadi, Nopriadi
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 6 (2023): JUTIF Volume 4, Number 6, Desember 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.6.1117

Abstract

The spread of viruses and bacteria through touching door surfaces is essential in maintaining public hygiene and health. In this context, a hand-coded touchless automatic door hardware design has been developed to reduce the spread of diseases through touch. This research aims to create a plan that includes interface development and hardware design to open and close doors automatically without contact. In this research, the automatic door hardware response is tested based on the numeric input from the hand code represented by the numeric database. The input and output control is connected to Python's graphical user interface (GUI). The GUI system design involves tools to connect the Python programming language and the Arduino microcontroller. Based on the experimental results, the hardware design of the automatic door security system based on hand code and Convolutional Neural Networks functions appropriately.
Implementasi Metode Deteksi Friksi Statik pada Katup Kontrol menggunakan Pencocokan Elips pada Standar IEC 61499 Wardaya, Tiar Candra; Wardana, Awang Noor Indra; Effendy, Nazrul
Jurnal Otomasi Kontrol dan Instrumentasi Vol 13 No 1 (2021): Jurnal Otomasi Kontrol dan Instrumentasi
Publisher : Pusat Teknologi Instrumentasi dan Otomasi (PTIO) - Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/joki.2021.13.1.2

Abstract

Sistem otomasi di industri menuntut untuk dilakukan proses perbaikan, pemantauan, dan pembaharuan yang dilakukan secara rutin.  Hal tersebut dilakukan  untuk menjaga agar operasi di pabrik dapat dengan baik yang salah satunya ditentukan dengan performansi dari performa dari kalang kendali. Baik buruknya performa kalang kendali proses dapat mempengaruhi kualitas, kuantitas produk maupun operasional yang sangat berimplikasi kuat pada aspek ekonomi produksi pabrik. Permasalahan yang sering terjadi pada kalang kendali proses adalah osilasi tidak linier akibat katup kontrol yang mengalami friksi statik. Dampak kerusakan alat dan variabilitas proses akibat katup kontrol yang mengalami friksi statik membuat deteksi dini secara aktif dibutuhkan. Pengembangan deteksi friksi statik secara online dan cepat membutuhkan teknologi yang memadai. Standar IEC 61499 merupakan salah satu teknologi yang memungkinkan untuk digunakan dalam sistem otomasi di industri agar menjadi lebih fleksibel dan terdistribusi. Makalah ini menjelaskan implementasi metode deteksi friksi statik pencocokan elips secara online menggunakan jendela digital yang bergerak yang diimplementasikan dengan menggunakan blok fungsi berbasis standar IEC 61499. Adanya friksi statik ditandai dengan hasil kuantifikasi nilai indeks friksi statik yang membentuk grafik kontinu (konvergen) positif. Hasil validasi menunjukkan bahwa blok fungsi yang dikembangkan menghasilkan dengan akurasi minimum sebesar 68,37% untuk deteksi variabel proses yang tidak mengalami friksi statik dan akurasi minimum sebesar 98,86% untuk deteksi variabel proses yang mengalami friksi statis.
Co-Authors Abiyu Fadhilah, Muhammad Zhafran Abrar, Haidar Alghazian Adnan Syarafi Ashfahani Agus Arif Al Birru, Muhammad Ismail Alfa Antariksa Ananda Dwi Mahendra Ananda Fathunnisa Aulia Anugrah Yuwan Atmadja Arditya Yulinggar Awang Noor Indra Wardana Beta M.G.S Birru, Muhammad Ismail Al Dana Fatadilla Rabba Dewi, Wulan May Kusuma Didi Ruhyadi Eko David Kurniawan Endro Basuki Faisal Budiman Faisal, Amir Fajar Sidik Permana Faridah Faridah Faridah Faridah Febry Wikatmono Febry Wikatmono Fikri Nur Muhammad I Nym Kusuma Wardana I Nyoman K.Wardana Intan Putri K Jihan Dhiya Faridah Kenny Dwiantoro Khoerul Anwar Kraton, Danang Wahyu Lebukan, Dirga Eka Putra M. Haekal Hasan M. Heikal Hasan Masrul Solichin Maulana Zein, Rhendiya Muhammad Agha Nandan Suteresna Nidlom Muddin Nopriadi Nopriadi Nor Agny Susetyo Utami Prihanto, Surya R Mochammad Affan Bagus Satria Rachmawati, Isti Dian Ridwan Herdiawan Rizky Pratama Rohaya, Siti Satria, R Mochammad Affan Bagus Shafanda Nabil Sembodo Sihana Sihana Sihana Sihana Singgih I Kurniawan Solekhah, Tiara Yosianti Sri Sadono Subagja Subagja Syifaun Nafisah Taufik Taufik Teuku Lukman Nur Hakim Tsanya, Nukman Tsaqib Vandy Achmad Yulianto Wardana, A.N.I. Wardaya, Tiar Candra