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All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Jurnal Mantik Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Jurnal Informatika dan Rekayasa Elektronik Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Informatika dan Sistem Informasi (JUISI) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Pendidikan dan Teknologi Indonesia Journal of Information Technology (JIfoTech) Jurnal Abdimas Bina Bangsa COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Algoritme Jurnal Mahasiswa Teknik Informatika Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science DEVOTE: Jurnal Pengabdian Masyarakat Global Jurnal INFOTEL SmartComp SAINTEK Infact: Jurnal Sains dan Komputer Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) UPGRADE: Jurnal Pendidikan Teknologi Informasi
Haeni Budiati
Universitas Kristen Immanuel
Aerospace Engineering Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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A Conversion of Signal to Image Method for Two-Dimension Convolutional Neural Networks Implementation in Power Quality Disturbances Identification Berutu, Sunneng Sandino; Chen, Yeong-Chin; Wijayanto, Heri; Budiati, Haeni
JOIV : International Journal on Informatics Visualization Vol 6, No 4 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.4.1529

Abstract

The power quality is identified and monitored to prevent the worst effects arise on the electrical devices. These effects can be device failure, performance degradation, and replacement of some device parts. The deep convolutional neural networks (DCNNs) method can extract the complexity of image features. This method is adopted for the power quality disruption identification of the model. However, the power quality signal data is a time series. Therefore, this paper proposes an approach for the conversion of a power quality disturbance signal to an image. This research is conducted in several stages for constructing the approach proposed. Firstly, the size of a matrix is determined based on the sampling frequency values and cycle number of the signal. Secondly, a zero-cross algorithm is adopted to specify the number of signal sample points inserted into rows of the matrix. The matrix is then converted into a grayscale image. Furthermore, the resulting images are fed to the two-dimension (2D) CNNs model for the PQDs feature learning process. When the classification model is fit, then the model is tested for power quality data prediction. Finally, the model performance is evaluated by employing the confusion matrix method. The model testing result exhibits that the parameter values such as accuracy, recall, precision, and f1-score achieve at 99.81%, 98.95%, 98.84, and 98.87 %, respectively. In addition, the proposed method's performance is superior to the previous methods. 
The Design and Evaluation of a Decentralized E-Voting System Using Ethereum Smart Contracts Hurit, Ludgerdus Pati; Sumihar, Yo'el Pieter; Budiati, Haeni
TIN: Terapan Informatika Nusantara Vol 6 No 8 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i8.8997

Abstract

The widespread implementation of electronic voting systems poses ongoing challenges related to data integrity, transparency, and centralized control, which can increase the risk of vote manipulation and reduce traceability. To address these issues, this study designs and evaluates a decentralized electronic voting system implemented using Ethereum smart contracts. The objective of this research is to test the ability of blockchain technology to support a secure, transparent, and tamper-resistant voting process in a decentralized environment. The research methodology includes requirements analysis, system design, system implementation, and functional testing. Black-box testing was conducted to verify the system's functionality throughout the voting process. The proposed system permanently records voting transactions on the blockchain, preventing unauthorized modifications while allowing transaction verification by network participants. Voter privacy is maintained by separating voter identity data from voting records and implementing blockchain address abstraction, ensuring that individual votes cannot be directly linked to voter identities. System evaluation focuses on transaction costs and confirmation times. Performance testing was conducted using six test transactions on the Sepolia blockchain network. The total transaction cost recorded was 0.006076 ETH, with an average cost of 0.001013 ETH per transaction. The minimum transaction cost of 0.000091 ETH occurred during voting operations, while the maximum cost of 0.005596 ETH was associated with smart contract deployment and higher network base fees. The average transaction confirmation time was approximately 12 seconds. Although the evaluation was based on a limited number of transactions, the results indicate that the proposed system demonstrates reliable transaction execution, acceptable gas usage, and high transparency. Further large-scale testing is recommended for future work.
Sistem Pengenalan Citra Dokumen Teks Terdistorsi menjadi Teks Menggunakan Metode Deep Learning Talenta Teholi Zalukhu; Agustinus Rudatyo Himamunanto; Haeni Budiati
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 10 No 1 (2026): JANUARY 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v10i1.4700

Abstract

A common issue in document image processing is the inability of OCR systems to accurately read text from blurred images. This study aims to develop a deep learning-based OCR pipeline capable of recognizing text in blurred document images. The process begins with image enhancement using the DnCNN model for deblurring, followed by character segmentation and classification of A–Z characters using a CNN trained on the EMNIST Letters dataset. The recognized characters are then reconstructed into complete text. Experiments were conducted on 300 blurred images with varying levels of blur (low, medium, and high). Evaluation using PSNR and SSIM metrics showed improvements in image quality, with an average PSNR of 29,56 dB and SSIM of 0.89. Furthermore, the character classification accuracy reached 95.64%. Compared to the baseline (direct Tesseract OCR without deblurring), the proposed system showed a significant improvement in text readability. These results demonstrate the effectiveness of CNN-based approaches in enhancing OCR performance on blurred document images.
Analisis Sentimen Berbasis ASOQE dan Taksonomi pada Program MBG di X mendrofa, victor crisman; Berutu, Sunneng Sandino; Budiati, Haeni
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 6 No 2 (2026): April 2026 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v6i2.15636

Abstract

The Free Nutritious Meal (MBG) program faces implementation challenges regarding distribution, menu quality, and budget sustainability, sparking diverse public discourse on social media. This study analyzes public sentiment toward the MBG program using an Aspect-Opinion-Qualifier Extraction (ASOQE) approach based on policy taxonomy. The dataset was obtained from X (formerly Twitter) via web scraping and processed through standardized text preprocessing. Automatic annotation used a lexicon-based BIO labeling approach to generate a silver-standard dataset. The classification model was trained using an IndoBERT-BiLSTM architecture to identify contextual aspects and opinions. Inference results were mapped into five sentiment classes and five policy dimensions: nutritional quality, implementation, social impact, policy, and effectiveness. Evaluation showed excellent performance, with F1-scores exceeding 0.98. Findings reveal that social impact and implementation dimensions dominate public discourse, showing significantly positive sentiment. This research demonstrates the potential of Aspect-Based Sentiment Analysis as a data-driven tool for comprehensive public policy evaluation.
PERANCANGAN APLIKASI DETEKSI CORAK KAIN TRADISIONAL BERBASIS ANDROID Gulo, Eniria; Budiati, Haeni; Sumihar, Yo’el Pieter
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 4 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i4.5566

Abstract

Perkembangan teknologi era digital telah memberikan peluang baru untuk pelestarian warisan budaya, khususnya dalam hal dokumentasi dan promosi tekstil tradisional. Salah satu tantangan utama adalah kehilangan informasi mengenai nilai dan makna di balik pola tekstil tradisional hal ini disebabkan karena kurangnya alat yang memadai untuk mengidentifikasi dan menginterprestasikan motif tersebut secara akurat. Penelitian ini bertujuan untuk mengembangkan sebuah aplikasi berbasis android yang dapat mengenali pola tekstil tradisional dengan menggunakan teknologi pemrosesan gambar dan kecerdasan buatan. Metode yang digunakan meliputi pungumpulan data gambar tekstil, pelatihan model kecerdasan buatan menggunakan Teknik deep learning, dan pengembangan antar muka pengguna. dengan metode pengolahann data Convolutional Neural Network (CNN) yang efektif dalam pengenalan pola visual, dan pengembangan antarmuka pengguna. Hasil dari penelitian ini diharapkan dapat menjawab bagaimana teknologi modern dapat dimanfaatkan untuk mendukung pelestarian, pemahaman, dan promosi warisan budaya tekstil, serta meningkatkan kesadaran masyarakat luas terhadap kekayaan budaya yang terwakili melalui motif tekstil tradisional.
Rancang Bangun Robot 4WD Kendali Jarak Jauh Berbasis Arduino Uno dan RF24L01+PA/LNA Br Pinem, Tessy Ocharina; Setyawan, Gogor Christmass; Budiati, Haeni
TIN: Terapan Informatika Nusantara Vol 6 No 11 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i11.9592

Abstract

Remote-controlled robots often face challenges related to communication stability and limited signal range. This study aims to design and develop a 4WD (Four Wheel Drive) robot based on Arduino Uno using NRF24L01+PA/LNA wireless communication and to evaluate system performance in terms of control responsiveness and communication reliability. The research method includes system design, hardware and software implementation, and performance testing under various distance conditions. The evaluated parameters include response time, data transmission success rate, and maximum communication range. The results show that the system achieves a communication success rate of 100% at 1 meter, 99% at 10 meters, and 96% at 50 meters. At the maximum distance of 200 meters, the system maintains a success rate of 75%. The response time is relatively low, enabling real-time control performance. This study contributes to the evaluation of NRF24L01 wireless communication performance in a 4WD robot system for remote control applications.
Implementasi Augmented Reality dalam Pengembangan Media Pembelajaran Biologi di Tingkat Sekolah Menengah Pertama Depni Novela; Agustinus Rudatyo Himamunanto; Haeni Budiati
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 15, No 1 (2026): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v15i1.9177

Abstract

Kemajuan tekonologi digital mendorong perluasan inovasi dalam proses pembelajaran, terutama untuk konsep-konsep abstrak seperti pembelajaran fotosintesis. Siswa mengalami kesulitan dalam memahami materi ini karenamelibatkan proses kimia yang cukup rumit dan tidak dapat dilihat secara langsung. Upaya alternatif dalam menangani permasalahan tersebut adalahmelalui proses perancangan dan pengembangan media pembelajaran berbasis Augmented Reality(AR) yang memvisualisasikan proses fotosintesis dalam bentuk 3D yang interaktif dan mudah dipahami. Penelitian ini menggunakan pendekatan deskriptif dengan model pengembangan Multimedia Development Live Cycle (MDLC) yang terdiri dari lima tahapan: Consept (Pengonsepan), Design (Perancangan), Material Collecting (Pengumpulan Materi), Assembly (Pembuatan), dan Testing (Pengujian). Aplikasi AR dikembangkan menggunakan Unity dan Vuforia, kemudian diuji coba kepada murid kelas VIII di SMP Negeri 2 Ngemplak. Hasil yang diperoleh menunjukkan bahwa aplikasi AR yang dikembangkan mudah digunakan, tampilan visual menarik, dan membantu meningkatkan pemahaman siswa terhadap materi fotosintesis, khususnya reaksi terang dan reaksi gelap. Selain itu, aplikasi ini juga menerima umpan balik yang baik dari pengguna terkait fitur dan desain antarmuka. Dengan  demikian,  penelitian ini mengindikasikan bahwa AR dapat berfungsi sebagai alat edukasi biologi yang interaktif , inovatif dan menyenangkan.
Co-Authors Agustinus Rudatyo Himamunanto Antonius Bima Murti Wijaya Apriani, Apriani Barita Suci Vernando Zebua Bobby Girsang Bolo, Naomi Tena Br Pinem, Tessy Ocharina Budet, Vincensa Woytimena Chen, Yeong-Chin Delima Zai Depni Novela Emerita Setyowati Febe Maedjaja Febe Maedjaja Fornieli Gulo Gallu, Apliana Gogor Christmass Setyawan Gulo, Eniria Heri Wijayanto Hermas Rizzal Himamunanto, A. R. Himamunanto, AR Himamunanto, AR. Hurit, Ludgerdus Pati Ina, Osmanila Tamo Jatmika Jatmika Jatmika Jatmika Jatmika Jatmika Juli Supriyanto Gea Kristian Juri Damai Lase Laia, Yardiana Lase, Anan Sosmita Lase, Kristian J.D. Liefson Jacobus, Liefson Lukas Agung Heriputranto Magdalena, Mensiana Mendrofa, Milka Justine mendrofa, victor crisman Nauli, Sumitta Nehe, Pius Hermanto Niasiska, Niasiska Olam, Enos Nikodemus P.Hurit, Lud Gerdus Peter1 Putri, Farelia Devi Julia Rudatyo Himamunanto, Agustinus Setiawan Matangkin, Jimmi Setyawan, Gogor C Sumihar, Yo'el Pieter Sumihar, Yo’el Pieter Sunneng Sandino Berutu Supriadi, Joseph Surjawirawan Dwiputranto Swasono, Natan Enggal Talenta Teholi Zalukhu Tasane, Elshaddai L Timothy Ageng Pracaya Veren, Yolanda Victor Crisman Mendrofa Wanda, Melifan Yo’el Pieter Sumihar Zendrato, Agus Dirgahayu Ziliwu, Johni Revormasi