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Decision Support System for Major Selection in Higher Education for Multimedia Graduate Students using Fuzzy Mamdani Logic Fauziah, Khasna Nur; Arifin, Fatchul
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 8 No. 2 (2023): November 2023
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v8i2.57643

Abstract

Students at the vocational high school level are indeed prepared to be able to work directly, but it does not rule out the possibility that vocational high school students can continue higher education such as universities. But the problem that will be faced again if students who graduate from vocational high schools choose to continue their education in college is what major they will take. One of the vocational high school majors, namely Multimedia, has a wide scope, so grade 3 vocational high school students who want to go to college have a dilemma in deciding on a major. This research applies the fuzzy logic mamdani to help make decisions for majors in higher education. This study is based on 5 input parameters, namely Komputer dan Jaringan Dasar, Desain Grafis Percetakan, Dasar Desain Grafis, Teknik Audio Visual, and Animasi. There are outputs of 5 majors in Teknik Komputer, Desain Komunikasi Visual, Animasi, TV dan Film, and Fotografi. The results of this research can make it easier and can provide support for grade 3 vocational high school students, especially the Multimedia department in choosing a major in higher education. The results of the decision support system with the highest student score data in Animasi will appear a recommendation score of 79.8 in the Animasi department, and on the highest student score data on the Komputer dan Jaringan Dasar, a recommendation score of 79.8 will appear in the Teknik Komputer major in accordance with the major taken and lived by the current student.
Advanced Multimodal Emotion Recognition for Javanese Language Using Deep Learning Arifin, Fatchul; Nasuha, Aris; Priambodo, Ardy Seto; Winursito, Anggun; Gunawan, Teddy Surya
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i3.5662

Abstract

This research develops a robust emotion recognition system for the Javanese language using multimodal audio and video datasets, addressing the limited advancements in emotion recognition specific to this language. Three models were explored to enhance emotional feature extraction: the SpectrogramImage Model (Model 1), which converts audio inputs into spectrogram images and integrates them with facial images for emotion labeling; the Convolutional-MFCC Model (Model 2), which leverages convolutional techniques for image processing and Mel-frequency cepstral coefficients for audio; and the Multimodal Feature-Extraction Model (Model 3), which independently processes video and audio features before integrating them for emotion recognition. Comparative analysis shows that the Multimodal Feature-Extraction Model achieves the highest accuracy of 93%, surpassing the Convolutional-MFCC Model at 85% and the Spectrogram-Image Model at 71%. These findings demonstrate that effective multimodal integration, mainly through separate feature extraction, significantly enhances emotion recognition accuracy. This research improves communication systems and offers deeper insights into Javanese emotional expressions, with potential applications in human-computer interaction, healthcare, and cultural studies. Additionally, it contributes to the advancement of sophisticated emotion recognition technologies.
Utilizing virtual reality for real-time emotion recognition with artificial intelligence: a systematic literature review Aji Purnomo, Fendi; Arifin, Fatchul; Dwi Surjono, Herman
Bulletin of Electrical Engineering and Informatics Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i1.8847

Abstract

Efficiency and optimization in virtual reality (VR) technology is an urgent need, especially in the context of optimizing algorithms to recognize user emotions while using VR. Efficient VR technology can improve user experience and enable more immersive and responsive interactions. This study adopts the preferred reporting items for systematic reviews and meta-analyses (PRISMA) (2020) method to identify and analyze gaps in the existing literature, focusing on the optimization of electroencephalogram (EEG) signal classification algorithms to recognize VR users' emotions. The literature search was conducted through the Scopus database, with article selection based on the type of emotion classified, the classification method used, the limitations of the research, and the results obtained. Of the 1478 articles found, 74 articles passed the initial selection stage, and the final stage 13 articles were selected for further analysis. The selected articles provide important insights into the development of EEG classification algorithms for VR users, especially in multi-user settings. The findings identify potential and opportunities in the development of more efficient and accurate EEG signal classification algorithms for VR users. By focusing on emotion classification in a multi-user VR environment, this research contributes to improving the efficiency of VR technology and supporting a better and more responsive user experience.
Evaluation of YOLOv8 Algorithm for Vehicle License Plate Detection System in UNY Integrated Parking Lot Al Matiin, Muhammad Azril Haidar; Arifin, Fatchul
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 9 No. 2 (2024): November 2024
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v9i2.70032

Abstract

The YOLOv8 algorithm for the license plate detection system of vehicles entering the integrated parking lot of Universitas Negeri Yogyakarta (UNY) needs to be evaluated because license plate detection is crucial in integrated parking management to improve the security and efficiency of parking lot usage. YOLOv8, as a deep learning-based object detection algorithm, was chosen to improve the accuracy and speed of detection. This research combines the YOLOv8 approach with a dataset specifically designed for the context of UNY parking lots. The testing process was conducted using the required hardware and software to ensure the algorithm's ability to adapt to the real environment. In addition, the performance of YOLOv8 in detecting vehicle license plates under different vehicle license plate conditions, such as black plates or white plates, was also evaluated. The results show that YOLOv8 is able to provide adequate vehicle license plate detection results. This research contributes to give development result of a vehicle license plate detection system for parking management by utilizing the latest object detection technology, as well as providing an overview of the challenges and solutions for implementation of this algorithm in the specific context of UNY parking lots.
Centralized Website Optimization at Modern Islamic Boarding School Baitussalam Erman Agusta, Gino; Fatchul Arifin; Astriawati, Ningrum
International Journal of Community Service (IJCS) Vol. 4 No. 1 (2025): January-June
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/ijcs.v4i1.1233

Abstract

Website today arises because of the increasingly high needs of the market and society in the field of technology. Pondok Pesantren Modern (PPM) Baitussalam has several education level units from kindergarten to high school level, including Integrated Islamic Kindergarten Baitussalam 1 Prambanan, Integrated Islamic Kindergarten Baitussalam 2 Cangkringan, Integrated Islamic Elementary School Baitussalam 1 Prambanan, Integrated Islamic Elementary School Baitussalam 2 Cangkringan, Integrated Islamic Junior High School Baitussalam Boarding School Prambanan, Integrated Islamic Junior High School Baitussalam Fullday School Cangkringan and Integrated Islamic Senior High School Baitussalam Boarding School Prambanan. Where the unit's website has not been fully centralized and several websites are not optimal. This training activity aims to integrate and optimize the website into a unified information. The method used is through training activities. Training activities use the method of lectures, questions and answers and mentoring. The result of this community service activity is that the centralized school website can integrate all education level units in PPM Baitusalam in disseminating information for teachers, female students and the general public; A centralized school website can optimize and make it easier for teachers, students and the general public to access information about the school or information about the world of education in general in one piece of information, besides that this centralized school website makes it easier for prospective students to register for all units in Pondok Pesantren Modern Baitussalam without the need to do it at school.
Perancangan Prototipe Pendiagnosa Penyakit Jantung Koroner Dengan Metode Backpropagation: DESIGNING A PROTOTYPE FOR DIAGNOSING CORONARY HEART DISEASE USING THE BACKPROPAGATION METHOD Iskandar, Ranu; Prasetyo, Prasetyo; Alfath, Muhammad Rofiq Banu; Arifin, Fatchul
Lontara Journal of Health Science and Technology Vol. 2 No. 1 (2021): Ilmu dan Teknologi Kesehatan
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Politeknik Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53861/lontarariset.v2i1.81

Abstract

Penyakit jantung koroner adalah suatu kelainan yang disebabkan oleh penghambatan pembuluh arteri yang mengalirkan darah ke otot jantung. Penyakit ini merupakan salah satu penyakit tidak menular yang kerap mengakibatkan kematian secara langsung pada para korbannya. Tujuan penulisan artikel ini adalah merancang sebuah arsitektur jaringan syaraf tiruan menggunakan metode backpropagation yang dapat memprediksi seseorang terkena penyakit jantung koroner dengan input kadar kolesterol, tekanan darah, dan kadar gula darah, dan indeks masa tubuh. Penelitian ini merupakan penelitian dan pengembangan. Metode penelitian yang digunakan pada pembuatan prototipe ini, yaitu: (1) analisa masalah, (2) analisa kebutuhan, (3) studi pustaka, (4) perancangan prototipe, dan (5) pengujian prototipe. Data pasien yang digunakan untuk menguji prototipe sejumlah 20. Hasil menunjukkan model jaringan syaraf tiruan yang digunakan memiliki nilai rata-rata kesalahan sebesar 0,792% dengan 5000 kali training. Prototipe diagnosa penyakit jantung koroner menggunakan backpropagation berjalan berhasil dibangun dengan hasil baik.
Optimization of 3D rendering algorithms for carbon reduction in virtual reality technology Purnomo, Fendi Aji; Arifin, Fatchul; Surjono, Herman Dwi
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp399-409

Abstract

Virtual reality (VR) systems are widely used across various domains, yet their high computational demands significantly contribute to energy consumption and carbon emissions. Optimizing rendering algorithms is essential to address these environmental challenges, particularly in multiuser VR environments where efficiency is critical. This study aims to evaluate the effectiveness of various rendering techniques in reducing energy consumption and carbon emissions as optimal solutions for multiuser VR applications. The research methodology followed the PRISMA framework, with a literature search conducted using the Scopus database and keywords such as “virtual reality” and “energy efficiency.” The search yielded 1,374 articles published after 2019, which were screened and narrowed down to 24 critical articles. Results demonstrate that Occlusion Culling achieves up to 85% energy savings per frame, translating to a carbon emission reduction of 76.5 g CO₂/hour, while LOD provides a 50% energy efficiency improvement, reducing carbon emissions by 45 g CO₂/hour. These findings highlight the critical role of these techniques in enhancing the sustainability of VR systems, particularly in multi-user environments, and underscore their potential as key strategies in reducing the environmental footprint of VR technology.
Determining Students' Nutritional Status Using Mamdani Fuzzy Logic Method Dyah Muslihah; Fatchul Arifin
International Journal of Scientific Multidisciplinary Research Vol. 1 No. 11 (2023): December 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijsmr.v1i11.7104

Abstract

Nutritional status is a body condition as a result of food consumption or a measure of the success of nutritional fulfillment; there is a balance between the amount of nutrient intake and the amount required by the body for a variety of biological functions such as physical growth, development, activity or productivity, health maintenance, and others. Children’s nutritional status is indicated by weight and height [6]. Theoretically, nutritional status can be determined based on Anthropometric standards. Fuzzy logic is a method to show problems from input to expected output [4]. The Mamdani fuzzy method is one of the methods of the fuzzy inference system. This research uses Matlab R2021b software to apply the fuzzy method
Peningkatan Kemampuan Kerjasama dalam Tim Melalui Pembelajaran Berbasis Lesson Study Wulandari, Bekti; Arifin, Fatchul; Irmawati, Dessy
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 1 No. 1 (2015): November 2015 (Consist of 9 Articles)
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (197.317 KB) | DOI: 10.21831/elinvo.v1i1.12816

Abstract

Penelitian ini bertujuan untuk meningkatkan kualitas pembelajaran pada mata kuliah Praktik Pengolahan Sinyal Digital dan menumbuhkan aspek kerjasama yang baik dalam satu tim pada mata kuliah Praktik Pengolahan Sinyal Digital. Peningkatan kualitas pembelajaran ini menerapkan metode pembelajaran problem based learning. Dalam penelitian ini menerapkan metod lesson study model Lewis (2002) dan pelaksanaanya dilakukan dalam 3 kegiatan, yaitu: 1) Perencanaan (plan); 2) Pelaksanaan dan  Observasi (do); 3) Refleksi (see). Subjek penelitian adalah mahasiswa S1 Prodi Pendidikan Teknik Elektronika dan data diperoleh dengan cara observasi dan perekaman. Hasil penelitian menunjukkan bahwa terjadi peningkatan kualitas proses pembelajaran. Dilihat dari jumlah mahasiswa  yang  aktif  semakin  banyak, perkuliahan  tidak  membosankan karena sebagian besar mahasiswa kelihatan antusias dalam belajar. Bagi dosen juga ada keuntungannya yaitu dapat melakukan kolaborasi dengan teman sejawat dalam upaya untuk memperbaiki pembelajaran. Melalui pembelajaran lesson study ini selain dapat meningkatkan kualitas pembelajaran  sekaligus  juga  dapat  menumbuhkan aspek kerjasama yang baik dalam satu tim pada mata kuliah Praktik Pengolahan Sinyal Digital. Hal ini terlihat dari tanggung jawab dalam pengambilan keputusan, tidak memisahkan diri dari orang lain, interaksi terhadap sumber belajar, interaksi antar mahasiswa, aktifitas menyelesaikan masalah dan mahasiswa tidak pasif.
Pengembangan Media Pembelajaran Kendali Fuzzy Logic Berbasis Arduino Nano Pada Mata Kuliah Praktik Sistem Kendali Cerdas Prabowo, Hernawan; Arifin, Fatchul
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 3 No. 1 (2018): May 2018
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (277.929 KB) | DOI: 10.21831/elinvo.v3i1.19739

Abstract

Dewasa ini berbagai aplikasi dalam bidang industri yang canggih banyak menggunakan kecerdasan buatan. Mata kuliah praktik Sistem Kendali Cerdas di Jurusan Pendidikan Teknik Elektronika & Informatika FT UNY memerlukan sebuah media pembelajaran yang terintegrasi antara hardware dan software agar kualitas pembelajaran sesuai dengan tuntutan dunia Industri. Hasil penelitian ini untuk menghasilkan media pembelajaran kendali fuzzy logic yang teruji kinerja dan kelayakannya pada mata kuliah praktik Sistem Kendali Cerdas. Pendekatan penelitian menggunakan Research and Development dengan 9 tahapan prosedur pengembangan meliputi: (1) potensi dan masalah, (2) pengumpulan data, (3) desain produk, (4) validasi desain, (5) revisi desain, (6) ujicoba produk, (7) revisi produk, (8) ujicoba pemakaian, dan (9) revisi produk. Hasil penelitian diketahui bahwa: (1) media pembelajaran kendali fuzzy logic yang dirancang terdiri dari hardware berbasis Arduino Nano dilengkapi jobsheet dengan pemrograman menggunakan Arduino IDE dan library yang mudah untuk dipelajari, (2) Unjuk kerja media pembelajaran sudah berfungsi dengan stabil baik pada setiap bagian maupun secara keseluruhan, (3) Tingkat kelayakan media dan materi memperoleh nilai 86% dan 96%. Tingkat kelayakan pemakaian berdasarkan uji pemakaian kepada 15 mahasiswa diperoleh nilai 85% termasuk dalam kategori sangat layak. Hal ini berarti media pembelajaran ini sangat layak digunakan pada mata kuliah praktik Sistem Kendali Cerdas.