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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Edutech: Jurnal Teknologi Pendidikan Semantik Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Ilmiah Kursor Indonesian Green Technology Journal Jurnal Transformatika International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics JAIS (Journal of Applied Intelligent System) JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Tech-E Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING International Journal of New Media Technology MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Data Science: Journal of Computing and Applied Informatics JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Indonesian Journal of Electrical Engineering and Computer Science International Journal of Advances in Data and Information Systems Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences JOURNAL SCIENTIFIC OF MANDALIKA (JSM) Jurnal Pendidikan dan Teknologi Indonesia Jurnal Teknologi Informasi Cyberku Studies in English Language and Education Moneter : Jurnal Keuangan dan Perbankan Scientific Journal of Informatics Journal on Pustaka Cendekia Informatika
Pulung Nurtantio Andono
Universitas Dian Nuswantoro
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Perspektif Baru Enterprise Architecture Pemerintahan Kota Mataram Berbasis TOGAF ADM Husain Husain; Pulung Nurtantio Andono; M. Arif Soeleman
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 16 No. 2 (2017)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v16i2.6

Abstract

TIK salah satu penentu keberhasilan sebuah organisasi dalam mencapai visi dan misinya. Terpilihnya pemimpin yang baru, terbentuknya SKPD baru dengan visi misi baru sehingga master plan yang lama di anggap sudah tidak relevan lagi, sehingga persoalan yang muncul diselesaikan dengan cara reaktif dan memungkinkan persoalan yang sama akan muncul kembali pada masa yang akan datang. Arsitektur enterprise adalah cara untuk membangun arsitektur TIK dari sebuah organisasi yang berfokus pada arsitektur bisnis, arsitektur data, arsitektur aplikasi dan arsitektur teknologi. Penelitian ini merupakan penelitian deskriptif kualitatif dengan pendekatan studi kasus. Metodologi yang digunakan adalah Enterprise Architecture TOGAF ADM sebagai kerangka acuan untuk perencanaan strategis TIK Pemerintahan Kota Mataram. Subyek pada penelitian ini adalah responden yang memiliki kewenangan dalam pengambilan keputusan terkait TIK dan pengguna TIK di Dinas Komunikasi dan Informatika (DISKOMINFO). Kebutuhan bisnis yang terdiri dari Arsitektur Data, Aplikasi dan Teknologi diidentifikasi dan diusulkan untuk mendukung aktivitas bisnis demi pencapaian tujuan organisasi. Hasil dari penelitian ini dengan menganalisa penggunaan penerapan teknologi informasi dan komunikasi(TIK) Seperti Sumber daya Manusia yang terlibat, kebutuhan aplikasi dan infrastruktur jaringan komputer dalam untuk mendukung proses bisnis dalam pelaksanaan roda pemerintahan Kota Mataram, dengan menggunakan metode scorecard uji kelayakan dengan rata-rata perolehan 76%.
PENDETEKSI VISUAL MAKANAN DAN JUMLAH KALORINYA MENGGUNAKAN ALGORITMA MASK R-CNN BERBASIS BOT TELEGRAM Shafa, Raihanaldy Ash; Andono, Pulung Nurtantio
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.6972

Abstract

Algoritma deteksi visual MASK R-CNN merupakan teknologi yang dapat membantu pengguna menjaga pola makan sehat dengan secara otomatis mendeteksi jenis makanan yang dikonsumsi. Sistem ini melibatkan pembuatan model berdasarkan kumpulan data, mengeksplorasi data, melatih model menggunakan algoritma Mask R-CNN, menguji model menggunakan gambar, dan menghubungkan model ke bot telegram menggunakan API. Kumpulan data dikumpulkan, dilatih, dan divalidasi, serta dikelompokkan ke dalam 40 kelas dengan berbagai jenis makanan dan minuman. Model ini memiliki tingkat akurasi total 78% dari 13 jenis gambar makanan yang diuji. Metode Mask Region Convolutional Neural Network (Mask R-CNN) dirancang untuk menyediakan akses cepat dan mudah ke informasi tentang jumlah kalori. Model ini dilatih menggunakan set data dari AIcrowd Food Recognition Challenge, dan mencapai tingkat akurasi 78%. Akurasi sistem dapat ditingkatkan dengan menggunakan set data yang lebih bervariasi dan mengoptimalkan pencahayaan pada gambar.
Underwater image enhancement with fuzzy histogram equalization and adaptive color correction Suharyanto Suharyanto; Pulung Nurtantio Andono; Ahmad Zainul Fanani; Pujiono Pujiono
International Journal of Advances in Intelligent Informatics Vol 12, No 1 (2026): February 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v12i1.2174

Abstract

Marine exploration continues to increase as new technologies, such as computer vision implemented in underwater vehicles and robots, develop. Identifying underwater objects is challenging due to environmental conditions, including poor lighting and color absorption in the viewed image. Underwater image enhancement has been widely applied to overcome these obstacles. Therefore, this study presents a new workflow for improving the quality of underwater images. A combination of the fuzzy histogram equalization (FHE) and adaptive color correction (ACC) methods is used to increase contrast and restore absorbed colors. This study proposes combining FHE and ACC to improve underwater image quality, using the FHE method with the FHEACC method. The results of the UIQM and ENTROPY metrics obtained the highest values, while UCIQE ranked third. This shows that the image quality improved using the FHEACC combination method is objectively better than that achieved with the HE, AHE, CLAHE, FHE, IBLA, RCP, and UDCP methods, especially in maintaining color balance. This research can introduce a new workflow to improve the quality of underwater images by combining Fuzzy Histogram Equalization and Adaptive Color Correction methods, thereby supporting the optimization of underwater image identification systems in wild environments using computer vision technology.
IMRAD, synthesis, and hedging within expert academic writing to encourage a world discussion platform Jumanto Jumanto; Dwi Eko Waluyo; Aris Puji Purwatiningsih; Pulung Nurtantio Andono; Raden Arief Nugroho; Ismarita Ramayanti; Asnul Dahar Bin Minghat
Studies in English Language and Education Vol 11, No 3 (2024)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/siele.v11i3.34776

Abstract

This paper examines IMRAD, synthesis, and hedging within expert academic writing to encourage a world discussion platform and to enhance manuscript writing for internationally reputable journals. The research utilized 25 Quartile-1 Scopus-indexed articles from 25 scholarly journals from 2022 and 2023 publications across different subject areas. Through online searching, observation, and interpretive techniques, the patterns of IMRAD, its synthesis, and the use of hedging within the synthesis were analyzed and identified as crucial elements for creating a manuscript that serves as a world discussion platform. Based on the systematic observation and interpretation of the 25 data sources, the research findings were discussed across three aspects: the IMRAD pattern, synthesis, and hedging. The findings revealed that symmetrical IMRAD patterns were rarely employed by authors of Quartile-1 Scopus-indexed journals, with various patterns being applied and the largest proportion focusing on different aspects. Synthesis was utilized by all authors of the 25 journal articles, and hedging or cautious language was used by most authors. Authors worldwide may benefit from the results of this research when writing manuscripts to be submitted to internationally reputable journals. Additionally, academic writing teachers can use the proposed interpretive model and research results to teach expert academic writing to their students, thus enhancing the quality of student academic writing and enabling the publication of their papers in internationally reputable journals.
An image encryption based on Fibonacci sequence and fusion of advanced encryption standard-least significant bit method Purwanto Purwanto; Aris Marjuni; Erna Zuni Astuti; Christy Atika Sari; Nova Rijati; Pulung Nurtantio Andono; Md Kamruzzaman Sarker
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 6: December 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i6.26078

Abstract

Image encryption is a vital field ensuring the secure transmission of digital images. In this study, encryption is the core process, employing complex mathematical algorithms and cryptographic keys to transform the original image into a secure format, shielding visual data from unauthorized access during transmission. To enhance security, the research integrates Fibonacci and advanced encryption standard (AES)–least significant bit (LSB) methodologies for a complex key generation system. This mechanism introduces intricate transformations within the image data, creating patterns challenging for potential attackers to decipher. Evaluation of the algorithm’s performance reveals efficiency in terms of mean squared error (MSE) and peak signal-to-noise ratio (PSNR). The RGB cover image achieves the lowest MSE of 0.0001 and the highest PSNR values ranging from 44.31 to 49.27. Integration of the Fibonacci sequence notably improves visual quality, enhancing both MSE and PSNR metrics. Unified average changing intensity (UACI) and normalized pixel change rate (NPCR) assessments consistently show the effectiveness of the algorithm, with the RGB cover image presenting the highest UACI and NPCR values. Future research directions involve exploring advanced encryption algorithms, optimizing techniques for high-dimensional datasets, and addressing ethical implications in image encryption, contributing to the development of adaptable and secure solutions.
Optimation of image encryption using fractal Tromino and polynomial Chebyshev based on chaotic matrix Elkaf Rahmawan Pramudya; Moch. Arief Soeleman; Cahaya Jatmoko; Eko Hari Rachmawanto; Aris Marjuni; Pulung Nurtantio Andono; Folasade Olubusola Isinkaye
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 6: December 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i6.26080

Abstract

Image encryption is a critical process aimed at securing digital images, safeguarding them from unauthorized access, tampering, or viewing to ensure the confidentiality and integrity of sensitive visual information. In this research, we integrate polynomial Chebyshev, fractal Tromino, and substitution S-box methods into a comprehensive image encryption approach. Our evaluation focuses on standardized 256×256-pixel images of Lena, Peppers, and Baboon, assessing key performance metrics like mean squared error (MSE), peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), number of pixel changes rate (NPCR), and entropy. The results reveal varying encryption quality across images, with Lena exhibiting the highest MSE (4702) and the lowest PSNR (12.89 dB). However, UACI, NPCR, and entropy values remain consistent across all images, indicating the proposed method’s stability concerning changing intensity, pixel alterations, and entropy levels. These findings contribute valuable insights into the effectiveness of the proposed encryption method, providing a foundation for further exploration and optimization in the field of cryptographic research. For future research direction, it is recommended to explore the impact of varying image sizes and types on the proposed method’s performance. Additionally, by focusing on the area of cryptographic threats, further analysis of the algorithm’s resistance against advanced attacks and its computational efficiency would be beneficial.
Enhancing Support Vector Machine Classification of Nutrient Deficiency in Rice Plants Through Particle Swarm Optimization-Based Feature Selection James Hartojo; Jessica Carmelita Bastiaans; Ricardus Anggi Pramunendar; Pulung Nurtantio Andono
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3762

Abstract

The research focuses on the classification of nutrient deficiencies in rice plant leaves using a combination of Support Vector Machine (SVM) and Particle Swarm Optimization (PSO) methods for feature selection. Image features are extracted using Histogram of Oriented Gradients (HOG), which is then optimized with PSO to select the most relevant features in the classification process. Indonesia is one of the largest rice producers in the world, with food security as a major issue that requires sustainable solutions, especially in the agricultural sector. The growth and yield of rice plants are highly dependent on the availability of nutrients such as Nitrogen (N), Phosphorus (P), and Potassium (K). However, traditional observation methods to detect nutrient deficiencies in plants become inefficient as the scale of production increases. The dataset used includes images of rice leaves showing nitrogen (N), phosphorus (P), and potassium (K) deficiencies. Experiments show that the SVM model optimized with PSO provides a classification accuracy of 83.19% and a runtime of 129.63 seconds with 1150 best feature combinations out of 2303 extracted features, which is higher accuracy and faster runtime than the model that does not use PSO. These results show that the integration of PSO in the feature selection process not only improves the accuracy of the model, but also reduces the required computation time. This research makes an important contribution to the development of an automated system for the classification of nutrient deficiencies in crops, which can be implemented in large farms or other agricultural fields.
Comparative Analysis of ResNet-Based Wagner-Scale Classification for Imbalanced DFU Data Aditya Wahyu Ramadhan; Pulung Nurtantio Andono; M. Arief Soeleman
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 6 (2025): December 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i6.7016

Abstract

Diabetic Foot Ulcers (DFU) are a serious complication of diabetes mellitus and carry a high risk of lower extremity amputation if not treated in a timely manner. The conventional classification process, which relies on visual inspection by clinicians, tends to be subjective and inconsistent. Therefore, this study proposes a multiclass classification model for DFU based on the Wagner Scale (Grades 0–5) using the ResNet-50 architecture with a transfer learning approach as the core machine learning method. The dataset used in this study consists of 1,415 clinical wound images that were annotated and verified by medical professionals. The dataset is highly imbalanced, with 543 images in Grade 0, 110 in Grade 1, 252 in Grade 2, 145 in Grade 3, 293 in Grade 4, and only 72 images in Grade 5. To address this imbalance, random oversampling (ROS) was applied, in addition to standard preprocessing techniques such as normalization and data augmentation to increase training data diversity.Experimental results demonstrate that the proposed model achieves high classification performance based on accuracy, precision, recall, and F1-score. Specifically, the model obtained a precision of 0.96, recall of 0.95, and F1-score of 0.95, indicating consistent and robust classification performance across all Wagner grades. The best configuration (ResNet-50 + ROS) successfully improved the classification performance across minority grades (e.g., Grade 1 and Grade 5). Moreover, the model consistently identifies minority classes and does not exhibit signs of overfitting. Model optimization using the Adam optimizer and data balancing strategies significantly improves the generalization capability of the classifier. These findings indicate that the proposed model is not only effective for automatic DFU classification, but also has great potential to support objective clinical decision making and accelerate diagnosis, particularly in healthcare facilities with limited resources.
Co-Authors Abdussalam Abdussalam, Abdussalam Achmad Ridwan Aditya Wahyu Ramadhan Affandy Agus Winarno, Agus Ahmad Zainul Fanani Al zami, Farrikh Al-Fatih, Gilang Fajar Alzami, Farrikh Anshori, Muhammad Izzul Aria Hendrawan, Aria Aris Marjuni Aris Puji Purwatiningsih Arry Maulana Syarif, Arry Maulana Asih Rohmani Asih Rohmani, Asih Asnul Dahar Bin Minghat Bastiaans, Jessica Carmelita Budi Harjo Cahaya Jatmoko Candhy Fadhila Arsyad Catur Supriyanto Catur Supriyanto Catur Supriyanto Catur Supriyanto Catur Supriyanto Catur Supriyanto Chaerul Umam Christy Atika Sari D, Ishak Bintang Danang Bagus Chandra Prasetiyo Darmawan, Aditya Aqil Denny Senata Dito, Aliffia Putri Doheir, Mohamed Dwi Eko Waluyo Dwi Puji Prabowo, Dwi Puji Dwiza Riana Edi Noersasongko Egia Rosi Subhiyakto, Egia Rosi Ekaprana Wijaya Eko Hari Rachmawanto Elkaf Rahmawan Pramudya Erna Zuni Astuti Erna Zuni Astuti Fahmy Ferdian Dalimarta Fajrian Nur Adnan Fauzi Adi Rafrastara Firman Wahyudi, Firman Fitri Yakub Folasade Olubusola Isinkaye Guruh Fajar Shidik Hamir, Mun Hanny Haryanto Hartojo, James Harun Al Azies Heru Lestiawan Hidayat, Sholeh Hisyam Syarif Husain Husain I Ketut Eddy Purnama Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Irwan, Rhedy Islam, Hussain Md Mehedul Ismarita Ramayanti Ivan Maulana James Hartojo Jessica Carmelita Bastiaans Jumanto Jumanto Junta Zeniarja Karis Widyatmoko Khafiizh Hastuti Kiat, Ng Poh Kunio Kondo L. Budi Handoko M Arief Soeleman M. Arief Soeleman M. Arif Soeleman Maria Goretti Catur Yuantari Md Kamruzzaman Sarker Megantara, Rama Aria Mila Sartika, Mila Moch Arief Soeleman Moch Arief Soeleman Moch Arief Soeleman, Moch Arief Moch. Arief Soeleman Mochamad Hariadi Mochammad Arief Soeleman Muhammad Munsarif Muhammad Naufal, Muhammad Muljono Muljono Nanna Suryana Herman Ningrum, Novita Kurnia Nita Merlina Noor Ageng Setiyanto, Noor Ageng Nova Rijati Nur Azise Ocky Saputra, Filmada Panca Hutama Caniago Paramita, Cinantya Pergiwati, Dewi Pramitasari, Ratih Prasetyoningrum, Devi Pujiono Pujiono Pujiono Pujiono Purwanto Purwanto Purwanto Purwanto Putra, Angga Permana Raden Arief Nugroho Rafsanjani, Muhammad Ivan Rahmatullah, Muhammad Rifqi Fadhlan Ramadhan Rakhmat Sani Ricardus Anggi P Ricardus Anggi Pramunendar Rohman, Muhammad Syaifur Ruri Suko Basuki Saputra, Filmada Ocky Saputri, Pungky Nabella Saputro, Wicaksono Agung Saraswati, Galuh Wilujeng Sari Ayu Wulandari Sarker, Md. Kamruzzaman Satriyawibawa, Muhammad Yiko Savicevic, Anamarija Jurcev Senata, Denny Sendi Novianto Shafa, Raihanaldy Ash Shier Nee Saw Sinaga, Daurat Sindhu Rakasiwi Siti Hadiati Nugraini Soeleman, Arief Soeleman, M Arief Soeleman, M. Arief Soeleman, Moch. Arief Soong, Lim Way Sri Winarno Sri Winarno Steven, Alvin Sudibyo, Usman Suharyanto Suharyanto Sukmawati Anggraeni Putri, Sukmawati Anggraeni Sukmono, Indriyo K. Supriyono Asfawi Suryawijaya, Tito Wira Eka Susanto, Susanto Tendi Tri Wiyanto, Tendi Tri Tengku Riza Zarzani N Thifaal, Nisrina Salwa Torhino, Rizal Wellia Shinta Sari Yaacob, Noorayisahbe Mohd Yusianto Rindra Zahrotul Umami, Zahrotul Zainal Arifin Hasibuan