Article Per Year (5 Year)
p-Index From 2021 - 2026
2.687
P-Index
This Author published in this journals
All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Edukasi dan Penelitian Informatika (JEPIN) SMATIKA JOIN (Jurnal Online Informatika) Jurnal Sisfokom (Sistem Informasi dan Komputer) JISKa (Jurnal Informatika Sunan Kalijaga) Khazanah Pendidikan Islam JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Computer Science and Information Technologies Online Learning in Educational Research Jurnal Abdimas Peradaban ISTEK
Yana Aditia Gerhana, Yana Aditia
Teknik Informatika Fakultas Sains dan Teknologi UIN Sunan Gunung Djati Bandung
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Library & Information Science Mathematics Social Sciences Other

Published : 23 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 23 Documents
Search

 1   2   3 
Deteksi Generatif Teks pada Penilaian Otomatis Tes Esai Berbahasa Indonesia Menggunakan IndoBERT Pitriani, Pitriani; Maylawati, Dian Sa’adillah; Gerhana, Yana Aditia
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 11, No 2 (2025): Volume 11 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v11i2.93221

Abstract

Hadirnya model generative artificial intelligence (GenAI) membawa tantangan baru dalam dunia pendidikan, khususnya terkait integritas. Salah satu isu yang mencuat adalah potensi penggunaan teks yang dihasil GenAI dalam jawaban pada proses penilaian pembelajaran peserta didik. Oleh karena itu, penelitian ini bertujuan untuk mendeteksi generatif teks hasil perangkat AI pada penilaian otomatis evaluasi pembelajaran dalam bentuk esai dengan bahasa Indonesia. Metode penelitian yang digunakan mengadaptasi model pre-trained Indonesia Bidirectional Encoder Representations from Transformers (IndoBERT). IndoBERT digunakan untuk deteksi generatif teks dengan AI melalui fine-tuning dan penilaian esai otomatis dengan representasi embedding dan cosine similarity dengan mempertimbangkan hasil deteksi GenAI. Hasil eksperimen menunjukkan fine-tuning pada model pre-trained IndoBERT berhasil mencapai akurasi sebesar 93.91% dengan nilai validation loss sebesar sebesar 0.1895. Sementara itu, pada tahap integrasi model deteksi teks GenAI ke dalam penilaian otomatis menunjukkan bahwa deteksi teks GenAI dapat mempengaruhi nilai akhir, khususnya pada jawaban yang memiliki similaritas tinggi dengan kunci jawaban namun terindikasi AI.
Implementation of Rule-Base and Internet Methods of Things Optimizing Water Mangement For Improving Seed Quality Gerhana, Yana Aditia; Suparman, Deden
ISTEK Vol. 13 No. 1 (2024): Juni 2024
Publisher : Fakultas Sains dan Teknologi UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/istek.v13i1.930

Abstract

System hydroponics Nutrients Film Technique (NFT) is one of the increasingly popular plant cultivation techniques used because it can increase the efficiency of water and nutrient use as well as crop yields. The NFT Hydroponic System has problems that are often faced in the form of control that must be optimal for important parameters like pH, temperature water, And concentration nutrition, so that can influence plant health and growth and need a good environment controlled To avoid decline quality plant or withering plant. Study This design uses Arduino Uno as a center control system monitoring hydroponics NFTs Which in add sensors pH For read value from pH water, sensors TDS used For read density nutrition, sensors temperature DS18B20 used For read temperature water Because own waterproff and water sensor features flow to read the amount of water flow. Data is read by the sensor and Then sent to Firebase through module NodeMCU which has been connected to the Arduino Uno then from Firebase it is created output form information to the user through the application mobile. Results testing done with the use 3 media Which were different as much 60 time experienced 58 successes and 2 failures resulted in a score accuracy of 96.6% of the total testing.
Implementation of Convolutional Neural Network CNN Algorithm to Detect Coffe Fruit Maturity Gerhana, Yana Aditia; Heryanto, Rafi Rai; Syaripudin, Undang; Suparman, Deden
ISTEK Vol. 13 No. 2 (2024): Desember 2024
Publisher : Fakultas Sains dan Teknologi UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/istek.v13i2.1247

Abstract

Fruit ripeness detection is important in the agriculture and food processing industries to ensure optimal product quality. Proper fruit ripeness can affect flavour, texture and nutrition, making it a key focus in production process monitoring and control. The fruit ripeness detection process still needs to be done manually, which can be inefficient and inaccurate. This research aims to address these challenges by implementing the CNN algorithm with VGG-19 architecture to detect coffee fruit ripeness automatically. The process involves collecting datasets of fruit images with various ripeness levels, image pre-processing including cropping and resizing, training the CNN VGG-19 model with feature learning and hyperparameter optimisation and evaluating model performance using a confusion matrix. This experiment aims to evaluate the model's performance in detecting fruit ripeness and measure the speed and efficiency of the CNN-based detection system with VGG-19 architecture. The results of this research are expected to help develop a better system for identifying fruit ripeness.
Co-Authors Agra, Agra Agung Wahana ALAWIYAH, RIZKA Aldy Rialdy Atmadja Anggayana, Denta Pratama Anwar, Muhammad Afian Arief Fatchul Huda Aulia, Salman Fauzan Fahri Ayu Puji Rahayu Azis, Aaz Muhammad Hafidz Beki Subaeki, Fatkhan Gunawan, Aldy Rialdy Atmadja, Beki Cecep Nurul Alam Cepy Slamet Dahriah, Iis Deden Suparman, Deden Devi Novitasari Dewi, Citra Deliana Dhanis Al Ghifari Diena Rauda Ramdania Dikdik Firman Sidik Dzulfikar, Wildan Budiawan Erwin Setiawan, Erwin Faiz M. Kaffah Firdaus, Muhammad Deden Heryanto, Rafi Rai Ichsan Taufik, Ichsan Khaerul Manaf Khaerunnisa, Rifa Kusuma Pradana, Galih Maylawati, Dian Sa'adillah Maylawati, Dian Sa’adillah Mintarsih, Mimin Muhammad Ali Ramdhani Muharam, Aldi Fahluzi Nur Lukman Nurlatifah, Eva Padilah, Muhamad Farid Pitriani, Pitriani Qomaruddin, Nurhadi Rahman, Titik Khawa Abdul Rusyana, Meta Barokatul Karomah Solehudin, Muhammad Alwy Somantri, E. Aris Taufik, Ichsan Undang Syaripudin, Undang