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All Journal Jurnal Buana Informatika JURNAL NASIONAL TEKNIK ELEKTRO Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Faktor Exacta Elektrika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer MIND (Multimedia Artificial Intelligent Networking Database) Journal Applied Technology and Computing Science Journal Jurnal Teknologi Informasi dan Terapan (J-TIT) JISA (Jurnal Informatika dan Sains) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Jurnal SASAK : Desain Visual dan Komunikasi Djtechno: Jurnal Teknologi Informasi Journal of Community Development Jurnal Ilmu Komputer dan Informatika Jurnal Akuntansi AKUNESA Jurnal Rekayasa elektrika International Journal of Healthcare and Information Technology Jurnal ilmiah teknologi informasi Asia
Zilvanhisna Emka Fitri
Politeknik Negeri Jember
Arts Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Nursing Public Health Social Sciences

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Implementasi Fuzzy Inference System untuk Pengstabilan Arus pada Baterai Lithium di Electric Vehicle Arizal Mujibtamala Nanda Imron; Satryo Budi Utomo; Dimas Aldy Darmawan; Bambang Sri Kaloko; Zilvanhisna Emka Fitri
Faktor Exacta Vol 18, No 3 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i3.26372

Abstract

The application of renewable energy in electric vehicles (EVs) is a crucial aspect that requires careful consideration. It is essential to understand the capacity characteristics of lithium polymer batteries to develop effective testing procedures. These procedures should involve monitoring the battery's voltage, current, and temperature during the discharge process with a lamp loading of 5 watts. The results of research prove that fuzzy control is an effective method for minimising the increase in battery temperature by stabilising the current used by the battery. The fuzzy control system effectively regulated a battery with a capacity of 3300 mAh and a voltage of 11.1 Volts, maintaining a stable current of 0.3 A from the 3rd minute until the battery reached its maximum capacity at the 63rd minute. Furthermore, the implementation of fuzzy control has been observed to delay the temperature rise in the battery. Specifically, the use of fuzzy control enables a delay in the temperature rise time by approximately 14 minutes when compared to the system without control. The temperature rise has a significant impact on the discharge speed of lithium polymer batteries.
PENGENALAN HURUF LATIN PADA ANAK USIA DINI DENGAN PENERAPAN METODE BACKPROPAGATION Slamet Riyadi; Zilvanhisna Emka Fitri; Arizal Mujibtamala Nanda Imron
Djtechno: Jurnal Teknologi Informasi Vol 2, No 2 (2021): Desember
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v2i2.1480

Abstract

Early childhood has difficulty remembering Latin letters or Roman characters than adults. Some of the factors that cause it are cognitive development, motivation, interest in learning, emotions and environmental factors. To overcome this, an innovative media is needed so that children can easily remember Latin letters. One of the innovative media applies digital image processing techniques and artificial intelligence. The fonts used are 10 types of letter models with image processing techniques such as preprocessing, binaryization, pixel mapping and creating vector as feature extraction.  While the artificial intelligence used is the backpropagation method. The total data is 208 letter images with 625 input features with 500 epochs, the best learning rate used by the system is 0.025 so that the best training accuracy is 93.96% and testing accuracy is 92.31%.
Ensiklopedia Digital Varietas Ubi Jalar Berdasarkan Klasifikasi Citra Daun Menggunakan KNearest Neighbor Bahtiar Adi Prasetya; Zilvanhisna Emka Fitri; Abdul Madjid; Arizal Mujibtamala Nanda Imron
Elektrika Vol. 14 No. 1 (2022): April 2022
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/elektrika.v14i1.4329

Abstract

Sweet potato is a source of carbohydrates which is an alternative food in order to accelerate food diversification. This is due to the high productivity of sweet potato so it is very profitable to cultivate. Sweet potato has many varieties, one of the differences is observed based on leaf shape which has four kinds of leaf shape, namely cordate, lobed, triangular and almost divided. The problem that often occurs is that many varieties have similarities, causing difficulties in distinguishing sweet potato varieties, especially for novice farmers. To overcome this problem, the researchers created a digital encyclopedia of sweet potato varieties based on leaf shape using computer vision. The parameters used are area, perimeter, metric, length, diameter, ASM, IDM, entropy, contrast and correlation at angles of 0 °, 45 °, 90 ° and 135 °. The amount of data used is 256 training data and 40 testing data. The K-Nearest Neighbor method is able to classify sweet potato leaf images for digital encyclopedias with an accuracy of 95% with variations in the values of K = 23 and K = 25.
Application of Feature Selection for Identification of Cucumber Leaf Diseases (Cucumis sativa L.) Lalitya Nindita Sahenda; Ahmad Aris Ubaidillah; Zilvanhisna Emka Fitri; Abdul Madjid; Arizal Mujibtamala Nanda Imron
JISA(Jurnal Informatika dan Sains) Vol 4, No 2 (2021): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v4i2.1046

Abstract

According to data from BPS Kabupaten Jember, the amount of cucumber production fluctuated from 2013 to 2017. Some literature also mentions that one of the causes of the amount of cucumber production is disease attacks on these plants. Most of the cucumber plant diseases found in the leaf area such as downy mildew and powdery mildew which are both caused by fungi (fungal diseases). So far, farmers check cucumber plant diseases manually, so there is a lack of accuracy in determining cucumber plant diseases. To help farmers, a computer vision system that is able to identify cucumber diseases automatically will have an impact on the speed and accuracy of handling cucumber plant diseases. This research used 90 training data consisting of 30 healthy leaf data, 30 powdery mildew leaf data and 30 downy mildew leaf data. while for the test data as many as 30 data consisting of 10 data in each class. To get suitable parameters, a feature selection process is carried out on color features and texture features so that suitable parameters are obtained, namely: red color features, texture features consisting of contrast, Inverse Different Moment (IDM) and correlation. The K-Nearest Neighbor classification method is able to classify diseases on cucumber leaves (Cucumis sativa L.) with a training accuracy of 90% and a test accuracy of 76.67% using a variation of the value of K = 7. 
Co-Authors Abdul Madjid Abdul Madjid Abdul Madjid ABDUL MADJID Abdul Madjid Abdurrahman Salim Achmad Amreza Alfarit Ahmad Aris Ubaidillah Ainun Nurkharima Noviana Aji Seto Arifianto Anni Nur Aisyah Ardan Venora Falahudin Ari Baskara Arizal Mujibtamala Nanda Imron Avisenna Harkat Bahtiar Adi Prasetya Bambang Sri Kaloko Brilyan Andi Syahbana Cherry Triwidiarto Datik Lestari Defi Tamara Dian Kartika Sari Dimas Aldy Darmawan Dyah Laksito Rukmi Ery Setiyawan Jullev Atmadji Fatimatuzzahra Fatimatuzzahra Lalitya Nindita Sahenda M. Haerul Anam Mega Silvia Muhammad Avan Dwi Adi Nur Kholiq Muhammad Hanip NISKE ELMY PAULINA Oryza Ardhiarisca Pramuditha Shinta Dewi Puspitasari Prawidya Destarianto Qonitatul Hasanah Rahma Rina Wijayanti Reski Yulina Widiastuti Rifqi Hakim Ariesdianto Rizkiyah Rizkiyah Satryo Budi Utomo Slamet Riyadi Sulton Mubarok Supriyadi Supriyadi Ulandari Susika Ully Nuhanatika Victor Phoa Wahyu Kurnia Dewanto Widya Yuristika Oktavia Wike Sri Widari Wildan Bakti Nugroho Yanuar Ardhika Rahmadhani Ubaidillah Yanuar Ridwan Hisyam