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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Masyarakat Informatika MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Journal of Informatics and Technology Jurnal Sains dan Teknologi Semantik TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer JOIV : International Journal on Informatics Visualization Jurnal Penelitian Pendidikan IPA (JPPIPA) ComTech: Computer, Mathematics and Engineering Applications Journal of Information Systems and Informatics Jurnal Guru Dikmen & Diksus Jurnal Teknik Informatika (JUTIF) Indian Journal of Forensic Medicine & Toxicology Journal of Social Research Engagement: Jurnal Pengabdian Kepada Masyarakat
Aris Sugiharto
Program Studi Ilmu Komputer, Universitas Diponegoro, Semarang
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Other

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DETEKSI SIDIK JARI DENGAN NEURAL NETWORK BACKPROPAGATION DAN TRANSFORMASI WAVELET DISKRIT Ragil Saputra; Aris Sugiharto
Jurnal Masyarakat Informatika Vol 1, No 2 (2010): Jurnal Masyarakat Informatika
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.1.2.2516

Abstract

Sidik jari merupakan salah satu bagian dari tubuh manusia yang bersifat unik yaitu dapat digunakan untuk membedakan antara manusia satu dengan yang lain. Cara untuk mengidentifikasi sebuah sidik jari sangatlah sulit, karena pola sidik jari antara manusia satu dengan yang lain memiliki tingkat kemiripan yang tinggi. Untuk dapat mengenali pola-pola tersebut di gunakan pendekatan dengan neural network dan tranformasi wavelet diskrit. Transformasi wavelet digunakan untuk mengelompokkan citra berdasarkan nilai frekuensinya (multiresolusi). Dan neural network dimanfaatkan untuk melakukan proses pelatihan neuron - neuron yang digunakan untuk mengenali pola sidik jari yang akan dicocokkan dengan sidik jari pada basis data. Hasil yang diperoleh adalah nilai korelasi yang menunjukkan hubungan antara kedua sidik jari.
ALGORITMA BACK PROPAGATION NEURAL NETWORK UNTUK PENGENALAN POLA KARAKTER HURUF JAWA Nazla Nurmila; Aris Sugiharto; Eko Adi Sarwoko
Jurnal Masyarakat Informatika Vol 1, No 1 (2010): Jurnal Masyarakat Informatika
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (385.588 KB) | DOI: 10.14710/jmasif.1.1.74

Abstract

Back Propagation Neural Network (BPNN) is a type of algorithm in Neural Network that can be use for Javanese alphabets character recognition. Matlab 7.1 has been used as a software to support the program. The main purpose of this research is order to find out BPNN’s training characteristic from each samples. On the other hand, this research also gives BPNN’s accurancy value in Javanese alphabets character recognition. The result of research shows that each part of the samples having different BPNN’s characteristic based on the best training.   Keywords : NN, BPNN
Bibliometrics Analysis of Bankruptcy Prediction Trends in MSMEs: Global Insights from (2020–2025) Supriyono Supriyono; Purwanto Purwanto; Aris Sugiharto
Journal of Information System and Informatics Vol 8 No 1 (2026): February
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i1.1378

Abstract

The purpose of this study is to map the development of research on bankruptcy prediction in Micro, Small, and Medium Enterprises (MSMEs) during 2020–2025 and to identify major scientific trends, influential authors, and dominant methodological approaches. Using a bibliometric method, data were collected from the Scopus database, producing 144 initial documents that were filtered into 23 final publications based on relevance and open-access availability. Performance analysis and science mapping were carried out using VOSviewer through co-authorship, co-citation, and keyword co-occurrence networks. The findings reveal four main research clusters: (1) financial-ratio-based distress models, (2) machine-learning approaches for SME risk prediction, (3) post-pandemic MSME resilience, and (4) credit scoring using non-financial indicators. Scientometrics is identified as the most influential journal, while Edward I. Altman and Alessandro Giannozzi emerge as central scholars. The United States, Italy, and the United Kingdom appear as the most collaborative and productive countries. The novelty of this research lies in its specific focus on MSME bankruptcy prediction during the post-pandemic era, the use of an open-access-filtered dataset, and the identification of emerging thematic clusters. However, this review is limited to Scopus-indexed, English-language, and open-access publications, which may exclude relevant studies from other sources.
Comparative Analysis of User Satisfaction of End User Computing Satisfaction, DeLone & McLean and Webqual 4.0 Methods Wahyu Tedi Prastio; Farikhin; Aris Sugiharto
Jurnal Penelitian Pendidikan IPA Vol 10 No 9 (2024): September
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i9.8484

Abstract

This study aims to analyze the level of user satisfaction of the SIAP Undip Mobile Application version 2.1.9 using three evaluation methods: End User Computing Satisfaction (EUCS), Delone and McLean, and Webqual 4.0. The study involved 100 Diponegoro University student respondents who used the application. Data was collected through a questionnaire distributed via Google Form and analyzed with SmartPLS 4.0 software to test validity, reliability, and research hypotheses. In this study, there were 11 hypotheses tested with three models. In the EUCS model, one hypothesis is accepted, namely Format has a significant effect on user satisfaction, while the other four hypotheses are rejected. In the Delone and McLean model, two hypotheses were accepted (Information Quality and System Quality) and one hypothesis was rejected (Service Quality). In the Webqual 4.0 model, one hypothesis is accepted (Service Interaction Quality) and two hypotheses are rejected (Information Quality and Usability Quality). The results of this study also provide suggestions for improvement for the development of the SIAP Undip version 2.1.9 application.
Image Cryptography Process Using Arnold’s Cat Map And Henon Map Algorithms Al Ghifari, Moch Azhar; Surarso, Bayu; Sugiharto, Aris
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 3 (2026): JUTIF Volume 7, Number 3, June 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.3.5354

Abstract

The security of digital image data is a crucial aspect in various fields, such as communications, medicine, and the military. The inherent characteristics of digital images—namely high pixel correlation and large data size—render conventional encryption methods less optimal. This study aims to evaluate the encryption quality of images using the Arnold’s Cat Map (ACM) and Henon Map algorithms, both individually and in combination (ACM-Henon and Henon-ACM). ACM is utilized to rearrange pixel positions to create a confusion effect, while the Henon Map is employed to randomly alter pixel values (diffusion). The implementation is carried out using the Python programming language within the Visual Studio Code development environment. Encryption quality is assessed using parameters such as Avalanche Effect (AE), Unified Average Changing Intensity (UACI), Number of Pixels Change Rate (NPCR), and correlation coefficient. Experimental results show that the combined chaos-based methods significantly enhance security compared to the individual algorithms, particularly by analyzing the impact of algorithm order on encryption quality. The best performance was achieved by the Henon→ACM combination, producing NPCR ≈ 99.44%, UACI ≈ 19.93%, entropy ≈ 7.9874, and AE ≈ 50.12%, indicating strong randomness and resistance to differential attacks. This research demonstrates that combining confusion and diffusion mechanisms yields more secure cipher images than using either method alone. The main contribution of this study lies in providing a systematic comparative evaluation of single and combined chaos-based encryption schemes, including order-sensitive analysis across different image characteristics, rather than proposing a new encryption algorithm. However, the encryption performance is influenced by image size, parameter selection, and iteration count, which may limit consistency across different image characteristics. Future work may explore adaptive parameter optimization and improved diffusion mechanisms for higher UACI values.
An Explainable PCA-XGBoost Model for Predicting Bloodstream Infection in Hemodialysis Patients Rani Zulaikha; Budi Warsito; Aris Sugiharto
Journal of Information System and Informatics Vol 8 No 4 (2026): August
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i4.1694

Abstract

Bloodstream infection (BSI) is a life-threatening complication in hemodialysis (HD) patients with catheter-based vascular access, carrying mortality rates of 15–50%, yet early detection remains challenging due to high-dimensional clinical data with significant multicollinearity. This study develops a BSI prediction model integrating Principal Component Analysis (PCA), XGBoost, Synthetic Minority Oversampling Technique (SMOTE), and dual Explainable AI (XAI) methods to improve predictive performance and clinical transparency. A dataset of 391 HD patients (18.9% BSI-positive) was preprocessed with encoding, standardization, and median imputation. PCA reduced 37 features to 29 components retaining 95.0% variance; SMOTE was applied inside each cross-validation fold to prevent leakage; and hyperparameters were optimized via RandomizedSearchCV. The proposed model achieved 83.5% accuracy, 33.3% recall, 43.5% F1-score, 85.5% AUC-ROC, and 0.643 PR-AUC, outperforming the baseline (81.0% accuracy, 0.0% recall, 0.190 PR-AUC). Bootstrap 95% confidence intervals and Brier score calibration are reported; results require cautious interpretation given the small positive test set (n=15). SHAP and LIME identified PC1 (hematological parameters) and PC2 (inflammatory markers) as dominant predictors. This study explores PCA, XGBoost, and dual XAI integration for BSI prediction in HD patients, an approach not extensively examined in this context. External multicenter prospective validation is required before clinical deployment.
Co-Authors Abd. Rasyid Syamsuri Adi Wibowo Afry Rachmat Agus Suwandono Al Ghifari, Moch Azhar Andi Gunawan Ari Wibawa Budi Santosa Arief Hidayat Arif Wibawa, Helmie Ary Setyadi Bagoes Widjanarko Bayu Surarso Bayu Surarso Budi Warsito Budi Warsito Dedy Kurniawan Hadi Putra Didit Suprihanto, Didit Eko Adi Sarwoko eko adi sarwoko Eko Didik Widianto Eko Didik Widianto Eko Nur Hidayat Eko Prasetiawan Fajar Hari Prasetyo Fajar Nugraha Ganis Khufad Arridho Hanif Setiawan, Syariful Helmi Arif Wibawa Helmie Arif Wibawa Helmie Arif Wibawa Henny Indriyawati Hidayat, Agung Rahmad Ikhthison Mekongga Indriyati Indriyati Irfan Pradipta Juwanda, Farikhin Kamal Maulana Kushartantya Kushartantya Kusworo Adi Lusiana Kristiyanti Lutfi Rinanto Mochammad Hosam Muhammad Malik Hakim, Muhammad Malik Mustafid Mustafid Nazla Nurmila Nikmah Rahmawati Pradhitya Nur Diyah S Pramudita Eka Hananto Priyo Sidik Sasongko Purwanto Purwanto R Rizal Isnanto Ragil Saputra Rahmat Gernowo Rambing, Danni Rani Zulaikha Riyana Putri, Fayza Nayla Rizki Saputra, Naufal Roby Hanintyo Nursio Sakti Rukun Santoso Sembiring, Rinawati Septya Maharani, Septya Sinta Tridian Galih Sugiyamto Sugiyamto suhartono, Suahrtono Sukmawati Nur Endah Supriyono Supriyono Supriyono Supriyono Suryo Hartanto Sutikno Sutikno Sutopo Patria Jati Tarno Tarno Toni Prahasto Victor Gayuh Utomo Wahyu Adi, Prajanto Wahyu Krisna Hidayat Wahyu Krisna Hidayat Wahyu Tedi Prastio Wahyudi Setiawan widowati widowati Yudie Irawan Yulianto Prabowo Yusuf Fahmi Adiputera