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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Jurnal Buana Informatika Jurnal Inovasi Teknologi Pendidikan Jurnas Nasional Teknologi dan Sistem Informasi JAIS (Journal of Applied Intelligent System) Proceeding SENDI_U Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Sistemasi: Jurnal Sistem Informasi Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JOURNAL OF APPLIED INFORMATICS AND COMPUTING MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JISKa (Jurnal Informatika Sunan Kalijaga) Infotekmesin Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Komtekinfo Community: Jurnal Pengabdian Pada Masyarakat Jurnal Informatika: Jurnal Pengembangan IT Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) INOVTEK Polbeng - Seri Informatika
Utomo, Danang Wahyu
Universitas Dian Nuswantoro
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Social Sciences Other

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Peningkatan Kesadaran Kanker Usus pada Siswa SMP Ibu Kartini melalui Aplikasi Mobile Dewi, Ika Novita; Utomo, Danang Wahyu; Salam, Abu; Luthfiarta, Ardytha; Octaviani, Dhita Aulia; Dzaki, Azmi Abiyyu; Haresta, Alif Agsakli
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 8, No 2 (2025): MEI 2025
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v8i2.2987

Abstract

Kanker usus merupakan salah satu penyakit yang dapat dicegah melalui kesadaran kesehatan yang baik dan deteksi dini. Namun, kurangnya edukasi kesehatan di kalangan remaja menjadi tantangan dalam upaya pencegahan penyakit ini. Program kemitraan masyarakat (PKM) ini bertujuan untuk memberikan edukasi dan meningkatkan pemahaman siswa SMP Ibu Kartini Semarang tentang pola hidup bersih dan sehat (PHBS), faktor risiko, serta deteksi dini kanker usus. Selain itu, program ini juga memperkenalkan aplikasi mobile Oncodoc sebagai sarana untuk deteksi dini kanker secara mandiri. Kegiatan dalam program ini mencakup sesi edukasi kesehatan, demonstrasi penggunaan aplikasi mobile Oncodoc, serta evaluasi pemahaman peserta melalui diskusi dan tanya jawab. Hasil evaluasi menunjukkan bahwa setelah mengikuti program, pemahaman siswa mengenai faktor risiko kanker usus, pentingnya pola hidup sehat, dan manfaat deteksi dini meningkat secara signifikan. Siswa juga menunjukkan ketertarikan terhadap penggunaan teknologi sebagai alat bantu dalam menjaga kesehatan. Temuan dari program ini mengindikasikan bahwa edukasi berbasis teknologi dapat menjadi metode yang efektif dalam meningkatkan kesadaran kesehatan remaja. Oleh karena itu, program serupa direkomendasikan untuk diperluas ke sekolah lain dengan tambahan sesi tindak lanjut guna memastikan pemanfaatan aplikasi secara optimal dalam mendukung edukasi kesehatan
Diabetes Detection Using Stacking Technique: A Combination of XGBoost, Gradient Boosting, and Meta Model Aden Rahmat, Aden Rahmat; Wahyu Utomo, Danang
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/48asdy77

Abstract

Type 2 diabetes mellitus is a chronic and progressively increasing global health issue that necessitates early detection to mitigate serious complications such as kidney failure, neuropathy, and cardiovascular disorders. While numerous studies have developed predictive models using machine learning techniques, many are limited by their reliance on single algorithms and inadequate handling of class imbalance. This research introduces a novel strategy by employing an ensemble stacking method that integrates Gradient Boosting, XGBoost, and Random Forest, with Random Forest acting as the meta-learner. The dataset, comprising 100,000 patient records, underwent preprocessing and was balanced using the SMOTE-Tomek approach to correct class distribution disparities. The stacking process is implemented in two phases: base models generate preliminary predictions, which are subsequently used as input for the meta-model to refine the final outcomes. The evaluation demonstrates that the stacking model achieves superior performance, recording 98% accuracy and an F1-score of 0.98, outperforming the individual models. The key distinction of this study lies in the effective application of ensemble stacking to enhance prediction accuracy, especially in dealing with imbalanced and complex medical data. This methodology has the potential to improve clinical decision support systems, making them more accurate and responsive.  
Enhancing Liver Cirrhosis Staging Accuracy using Optuna-Optimized TabNet Arifin, Muhammad Farhan; Dewi, Ika Novita; Salam, Abu; Utomo, Danang Wahyu; Rakasiwi, Sindhu
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.11011

Abstract

Liver cirrhosis is a progressive chronic disease whose early detection poses a clinical challenge, making accurate severity staging crucial for patient management. This research proposes and evaluates a TabNet deep learning model, specifically designed for tabular data, to address this challenge. In the initial evaluation, a baseline TabNet model with its default configuration achieved a baseline accuracy of 65.11% on a public clinical dataset. To enhance performance, hyperparameter optimization using Optuna was implemented, which successfully increased the accuracy significantly to 70.37%, with precision, recall, and F1-score metrics each reaching 70%. The model's discriminative ability was also validated as reliable in multiclass classification through AUC metric evaluation. In addition to accuracy improvements, the model's interpretability was validated through the identification of key predictive features such as Prothrombin and Hepatomegaly, which align with clinical indicators. This study demonstrates that Optuna-optimized TabNet is an effective and interpretable approach, possessing significant potential for integration into clinical decision support systems to support a more precise diagnosis of liver cirrhosis.
Quality Improvement for Invisible Watermarking using Singular Value Decomposition and Discrete Cosine Transform Utomo, Danang Wahyu; Sari, Christy Atika; Isinkaye, Folasade Olubusola
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 3 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3744

Abstract

Image watermarking is a sophisticated method often used to assert ownership and ensure the integrity of digital images. This research aimed to propose and evaluate an advanced watermarking technique that utilizes a combination of singular value decomposition methodology and discrete cosine transformation to embed the Dian Nuswantoro University symbol as proof of ownership into digital images. Specific goals included optimizing the embedding process to ensure high fidelity of the embedded watermark and evaluating the fuzziness of the watermark to maintain the visual quality of the watermarked image. The methods used in this research were singular value decomposition and discrete cosine transformation, which are implemented because of their complementary strengths. Singular value decomposition offers robustness and stability, while discrete cosine transformation provides efficient frequency domain transformation, thereby increasing the overall effectiveness of the watermarking process. The results of this study showed the efficacy of the Lena image technique in gray scale having a mean square error of 0.0001, a high peak signal-to-noise ratio of 89.13 decibels (dB), a universal quality index of 0.9945, and a similarity index structural of 0.999. These findings confirmed that the proposed approach maintains image quality while providing watermarking resistance. In conclusion, this research contributed a new watermarking technique designed to verify institutional ownership in digital images, specifically benefiting Dian Nuswantoro University. It showed significant potential for wider application in digital rights management.
Teknik Bagging pada Ensemble Learning untuk Kategorisasi Produk E-Commerce Churniansyah, Faskal; Utomo, Danang Wahyu
Jurnal Nasional Teknologi dan Sistem Informasi Vol 10 No 1 (2024): April 2024
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v10i1.2024.92-99

Abstract

E-commerce merupakan layanan dalam jual beli yang dijalankan secara online melalui media elektronik seperti komputer dan handphone. Adanya perkembangan teknologi informasi yang lebih canggih menjadi pendorong utama dalam meningkatkan kerja e-commerce. Peningkatan yang sering dilakukan adalah menyediakan layanan sebaik – baiknya dan semudah mungkin untuk pelanggan. Banyaknya produk e-commerce yang ditawarkan ke pelanggan menjadi isu utama dalam layanan e-commerce. Tidak sedikit pelanggan yang bingung dalam menentukan pilihan produk. Bahkan beberapa penelitian menyatakan pelanggan yang awam tentang penggunaan e-commerce bingung dalam pemilihan produk. Ada deskripsi atau ulasan produk yang berbeda terhadap produk yang sama. Penelitian ini mengusulkan kategorisasi produk pada layanan e-commerce dengan tujuan menempatkan deskripsi produk sesuai dengan kategori yang telah ditentukan. Teknik bagging adalah Teknik ensemble learning yang mampu membuat beberapa sub pohon keputusan yang nantinya dapat dicari nilai akurasi yang terbaik. Pada hasil pengujian diperoleh bahwa pada pengaturan hyperparameter n_estimators 200 menghasilkan nilai akurasi terbaik dengan nilai 93,25%., precision 93%, recall 93% dan f1-score 93%.
Penerapan Deep Learning dengan Mekanisme Attention untuk Meningkatkan Performa Segmentasi Liver dan Tumor pada Citra CT Menggunakan ResUnet Eka Putra, Zaky Dafalas; Utomo, Danang Wahyu
Jurnal Nasional Teknologi dan Sistem Informasi Vol 10 No 3 (2024): Desember 2024
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v10i3.2024.231-239

Abstract

Kanker hati merupakan salah satu penyebab kematian paling tinggi di dunia. Dalam mendeteksi kelainan pada hati perlu dilakukan segmentasi untuk mengambil bagian dari hati yang mengalami gangguan. Namun, metode segmentasi manual memakan waktu dan rawan kesalahan. Selain itu, metode tradisional juga sering kali kesulitan menangani variasi bentuk, ukuran, dan tekstur tumor, serta kualitas citra yang heterogen, sehingga mengurangi akurasi segmentasi. Oleh karena itu, penelitian ini mengusulkan penerapan model segmentasi menggunakan mekanisme Attention ResUnet, yang menggabungkan arsitektur residual dan konvolusi berbasis skip connection, ditingkatkan dengan attention untuk meningkatkan akurasi deteksi tumor. ResUnet dirancang untuk meningkatkan akurasi dan stabilitas segmentasi tumor dengan mengatasi masalah vanishing gradient dan meningkatkan kemampuan deteksi fitur kompleks. Dataset citra CT yang digunakan dalam penelitian ini dipra-pemroses melalui windowing untuk fokus pada rentang intensitas organ hati dan menghilangkan organ yang tidak penting. Hasil penelitian menunjukkan bahwa model Residual Unet dengan mekanisme Attention mampu meningkatkan performa segmentasi gambar CT hati dan tumor secara signifikan, mencapai akurasi 99.54% dan nilai Dice sebesar 95% pada segmentasi liver, serta akurasi 99.5% dan nilai Dice sebesar 90% pada segmentasi tumor. Penambahan modul Residual dan Attention secara efektif membantu model menangkap fitur yang relevan, khususnya dalam menangani lesi kompleks dan batas kabur, yang sering menjadi tantangan dalam segmentasi citra medis.
OPTIMASI INVISIBLE WATERMARKING METODE DCT BERBASIS SVD PADA CITRA BERWARNA Utomo, Danang Wahyu; Sari, Christy Atika; Rachmawanto, Eko Hari
Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) Vol 8, No 01 (2024): SEMNAS RISTEK 2024
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/semnasristek.v8i01.7140

Abstract

Studi ini mengevaluasi efektivitas metode watermarking dalam menyembunyikan informasi rahasia pada citra digital menggunakan Discrete Cosine Transform (DCT) dan Singular Value Decomposition (SVD). Pendekatan ini penting untuk menjaga keamanan dan hak cipta dalam era digital. Penggunaan DCT memungkinkan penyematan watermark tanpa mengorbankan kualitas visual citra. Hasil evaluasi menggunakan Mean Squared Error (MSE) menunjukkan bahwa citra Lena.bmp mencapai nilai MSE terendah pada Level 1 dengan 0.075, sementara Peppers.png memiliki nilai MSE terendah pada Level 1 dengan 0.0083, dan Baboon.jpg pada Level 1 dengan 0.0097. Pada sisi lain, hasil evaluasi menggunakan Peak Signal-to-Noise Ratio (PSNR) menunjukkan bahwa nilai PSNR tertinggi tercatat pada Level 1 untuk ketiga citra dengan nilai 48.17 dB. Temuan ini menunjukkan bahwa metode watermarking yang diterapkan menggunakan DCT dan SVD berhasil dalam menyematkan informasi rahasia pada citra digital dengan tingkat preservasi kualitas yang tinggi.
Pengembangan Sistem Modul Komisi Dinamis pada Modul Penjualan ERP - Odoo12 Wahyu Utomo, Danang; Kurniawan, Defri; Rosi Subhiyakto, Egia
Infotekmesin Vol 12 No 2 (2021): Infotekmesin: Juli 2021
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v12i2.729

Abstract

The improvement of the sales system not only focuses on the advantage result of the sales transaction but also can use another parameter to improve it. One of a parameter used is commission. Giving commissions to the salesperson can improve their work performance and have an impact on increasing sales targets. Based on the study literature, the problem faced by the company is the discrepancy of commission. It canbe affected by several factors such as the commission system are not integrated with the main system, improper formula, or there are many systems used in the company so it the staff are difficult to integrate the system. For example, the company using Odoo ERP to support sales transaction and use commission information system separately. The salesperson must integrate sales data into both of the systems. It can affect the time delay of decision commission. Based on the problem above, we propose a prototype commission system that integrates with Odoo12. The salesperson does not need to integrate data manually into the system because it automatically integrates into the system. This study uses a prototyping model as a software development method. The results show that the commission system can implement on the Odoo12 ERP to decide commission to the salesperson. 70% of respondent agree that system has able to use in order to setting up commission module on Odoo
Rekayasa Aplikasi Pengarsipan Surat Permohonan Hak Milik Tanah Dengan menggunakan Metode Prototyping Rosi Subhiyakto, Egia; Parti Astuti, Yani; Wahyu Utomo, Danang
Infotekmesin Vol 13 No 1 (2022): Infotekmesin: Januari, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i1.891

Abstract

National Land Agency received requests for land rights every day. The letters can be submitted through two stages of acceptance and archiving. Still using conventional systems makes data retrieval requires relatively more time. This research aims to design and build an information system data archiving for incoming request at the National Land Agency. The software has been designed with login feature, data management land owners and land owner data search and print feature data. Analysis of system requirements using object-oriented method which uses the use-case diagram in order to illustrate the functionality of the system and some of the criteria of non-functional requirements are also outlined. The next step was the coding implementation and evaluation of the system built. The system development method used was the prototyping method. The selection of this method was intended, therefore the client can get a clear picture of the system being built. Evaluation was conducted in the developer and the user environment. The evaluation in the user environment was done by distributing questionnaires covering three parameters namely the usefulness of the application, ease of use and user satisfaction. The results showed that the information systems built have a useful value (85.7%) and are easy to use (100%), therefore it satisfied the users.
Implementasi Principal Component Analysis (PCA) pada Pengenalan Wajah Resolusi Rendah Tanjung, Reza Phina; Wahyu Utomo, Danang
Infotekmesin Vol 15 No 1 (2024): Infotekmesin: Januari, 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i1.2148

Abstract

Face recognition involves matching facial features by restricting the facial area. The problem found in the experiment was that the program recognized images outside the face area, especially for low-resolution images. The PCA algorithm and the proposed bounding box approach can identify the facial area and match it with training data. The experiment uses the Yaleface and Face94 datasets in various scenarios, including normal resolution and resolution reduction (75%, 50%, and 25% of the original size). On gif images, the proposed algorithm can produce similarities between the detected image and the input image in a resolution reduction of up to 50%. On jpg images, reducing resolution to 75% does not affect the performance of PCA. The proposed method can recognize faces with similarities in variations of pose and facial expression. The Euclidean value of the jpg image produces a better similarity value than the gif image.
Co-Authors Abu Salam Abu Salam Aden Rahmat, Aden Rahmat Agustina, Feri Aldhi Ari Kurniawan Ardytha Luthfiarta Arifin, Muhammad Farhan Astuti, Yani Parti Astuti, Yani Parti Catur Supriyanto Christy Atika Sari Churniansyah, Faskal Defri Kurniawan Defri Kurniawan Defri Kurniawan Defri Kurniawan Dhita Aulia Octaviani Doheir, Mohamed A S Donny Saputro Donny Saputro Dzaki, Azmi Abiyyu Egia Rosi Subhiyakto Egia Rosi Subhiyakto Egia Rosi Subhiyakto Egia Rosi Subhiyakto Egia Rosi Subhiyakto Egia Rosi Subhiyakto, Egia Rosi Eka Putra, Zaky Dafalas Eko Hari Rachmawanto Erlin Dolphina Etika Kartikadarma Fahmi Amiq Faskal Churniansyah Finda, Selma Marsya Gusnita Darmawati Haresta, Alif Agsakli Hilmi Hanif Husin Sufi Ika Novita Dewi Isinkaye, Folasade Olubusola Junta Zeniarja Kurniawan, Defri Kurniawan, Defri Liya Umaroh Maldini, Naufal Matius Rama Hadi Suryanto Muljono Muljono Ningrum, Novita Kurnia Norman, Maria Bernadette Chayeenee Novita Kurnia Ningrum Octaviani, Dhita Aulia parti astuti, yani Prajanto Wahyu Adi Prajanto Wahyu Adi, Prajanto Wahyu Pratama, Naufal Adhi Purwanto Purwanto Rahmadika Putri Tresyani Rama Hadi Suryanto, Matius Ramadhan Rakhmat Sani Riski, Habibu Rosi Subhiyakto, Egia Salsabilla, Cinta Selma Marsya Finda Sepbriant, Genta Dwigi Sindhu Rakasiwi Subhiyakto, Egia Rosi Sudibyo, Usman Tanjung, Reza Phina Tresyani, Rahmadika Putri Yani Parti Astuti Yani Parti Astuti