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All Journal Jurnal Masyarakat Informatika Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Dinamika Rekayasa (DINAREK) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Abdimasku : Jurnal Pengabdian Masyarakat JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat Scientific Journal of Informatics Jurnal Karya untuk Masyarakat (JKuM)
Ibnu Utomo Wahyu Mulyono
Universitas Dian Nuswantoro
Humanities 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 Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences

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IT SERVICE MANAGEMENT FOR BUSINESS PROCESS OF STAFF ARCHIVE DIGITALIZATION USING ITIL 3TH VERSION FRAMEWORK (CASE STUDY: BKPP OF SEMARANG CITY) Yupie Kusumawati; Anggia Rizkika Hanin; Novita Kurnia Ningrum; Ibnu Utomo Wahyu Mulyono; Ajib Susanto; Karis Widyatmoko
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 9 No. 1 (2024)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v9i1.187

Abstract

The role of archivist in an agency is as needed as in the Badan Kepegawaian, Pendidikan dan Pelatihan Kota Semarang (BKPP of semarang).Badan Kepegawaian, Pendidikan dan Pelatihan Kota Semarang currently has digitized archive services Employment is e-file service. The problem we found today is service the e-file is only used as a data archive and has not yet supported the business process resources. Another problem found on e-file services is not yet available service contact and lack of human resources. To support the business process then this research will design the management of it services on digitalization of employment archives. On this rre-design, e-file services will be linked to other IT services such as SISDM and E-Fungsional. This research uses the framework ITIL 3th Version domain service design with the sub domain service design package and service catalogue for document creation of the entire sequence of design. On this research there are also multiple support services like a service in contact, hours level services, risk identification, enhanced resources and structures the organization proposal so that current e-file services can support business processes digitalization of employment archives on the BKPP Kota Semarang
Regionprops Segmentation in Convolutional Neural Network for Identification of Lung Cancer Disease and Position Zahra Ghina Syafira; Christy Atika Sari; Ibnu Utomo Wahyu Mulyono; Feri Agustina; Suprayogi Suprayogi; Mohamed Doheir
Jurnal Masyarakat Informatika Vol 16, No 2 (2025): November 2025
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.16.2.73967

Abstract

Lung cancer is one of the leading causes of death in the world, so early detection is very important to increase the chances of patient recovery. This study aims to develop a method for identifying lung cancer types using Convolutional Neural Network (CNN) combined with Regionprops segmentation technique to determine the position of cancer in CT scan images. The dataset used consists of 1,294 CT scan images classified into three classes, namely Benign, Malignant, and Normal, with variations in the ratio of training and testing data: 80:20, 70:30, 60:40, 50:50, and 40:60. The CNN method is used to perform classification, while the Regionprops segmentation technique is applied to determine the position of the cancer. The results showed that the model with a data ratio of 80:20 achieved the highest accuracy of 99.54%, indicating a very good generalization ability of the model. The Regionprops segmentation technique successfully separated the nodule area in the CT scan image clearly, thus providing more detailed information regarding the position of the cancer. The conclusion of this study shows that the combination of CNN and Regionprops segmentation methods is effective in detecting and analyzing lung cancer and has the potential to be used as a diagnostic tool in the medical field. This study recommends further testing with a larger dataset and optimization of model parameters to improve classification and segmentation performance.
Analisa Visual Citra Hasil Kombinasi Steganografi dan Kriptografi Berbasis Least Significant Bit Dalam Cipher Ibnu Utomo Wahyu Mulyono; Yupie Kusumawati; Novita Kurnia Ningrum
Jurnal Masyarakat Informatika Vol 14, No 1 (2023): May 2023
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.14.1.51484

Abstract

Kriptografi dan steganografi adalah teknik yang digunakan untuk mengamankan data untuk meminimalkan pencurian data dan akses oleh orang yang tidak berwenang. Kombinasi Rivest Cipher 4 - Least Significant Bit diusulkan dalam penelitian ini untuk memberikan perlindungan bagi pesan dan berbagai format file yang tertanam dalam gambar digital. Pesan rahasia dienkripsi dengan metode RC4 sebelum dimasukkan kedalam gambar menggunakan LSB. Studi ini juga menganalisis kinerja kombinasi algoritma LSB – RC4 pada berbagai file dan ukuran gambar sampul. Gambar sampul menggunakan gambar dengan saluran RGB. Untuk pengukuran kinerja imperceptibilitas digunakan Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), dan analisis histogram.Nilai rata – rata PSNR yang didapatkan pada penelitian ini lebih dari 30 dB, ini membuktikan bahwa kualitas gambar stego sangat baik dan kualitas gambar stego yang baik memiliki nilai PSNR minimal 30 dB. Nilai PSNR yang didapatkan secara keseluruhan lebih dari 30 dB dengan nilai terendahnya 45,15 dB dengan ukuran citra 128x128 pixel.
Pelatihan Chse Pengelolaan Homestay pada Desa Candirejo yang Tergabung di PT Wimbo Izza Ulumuddin Ahmad Asshofi; Emik Rahayu; Joseph Aldo Irawan; Aji Kusumah Ramdhani; Karis Widyatmoko; Ibnu Utomo Wahyu Mulyono; Imang Dapit Pamungkas; Dian Indriana Hapsari; Nurjanah
Jurnal Karya untuk Masyarakat (JKuM) Vol 4 No 1 (2023): JANUARI 2023
Publisher : Universitas Tarakanita

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36914/1b8p9y88

Abstract

Pandemi Covid-19 memberikan dampak buruk pada masyarakat salah satunya pada sektor industri pariwisata. Seluruh dunia tidak terkecuali Indonesia mengalami kondisi tersebut, seluruh elemen pada sektor pariwisata di Indonesia mengalami penurunan pendapatannya secara drastis sebab wisatawan khawatir berpergian dan terpapar Covid-19. Salah satu yang terdampak oleh Covid-19 ini ialah homestay yang dikelola masyarakat desa Candirejo. Sebuah kebijakan dikeluarkan oleh Kementerian Pariwisata dan Ekonomi Kreatif yaitu CHSE (Cleanliness, Health, Safety, & Environment Sustainability) untuk meningkatkan kembali kepercayaan para wisatawan. Masyarakat desa Candirejo sebagai pengelola homestay harus mendapatkan sertifikat CHSE sebagai bentuk pengakuan secara resmi dari negara karena telah menerapkan protokol kesehatan melalui penerapan CHSE dalam bidang pariwisata. Universitas Dian Nuswantoro bermitra dengan PT Wimbo merancang sebuah pelatihan CHSE bagi pengelola homestay untuk memberikan pengetahuan perihal penerapan CHSE. Pelaksanaan pelatihan ini dilakukan pada tanggal 26 November 2022. Kegiatan berlangsung dengan lancar dan mendapat sambutan positif dari masyarakat desa Candirejo yang tergabung dalam kegiatan pelatihan CHSE dalam pengelolaan homestay di masyarakat desa Candirejo.
Digitalisasi dan Optimasi Pelayanan Administrasi Kependudukan dalam Mendukung Go Digital dan Smart City di Kelurahan Pedurungan Karis Widyatmoko; Abdussalam Abdussalam; Lekso Budi Handoko; Ajib Susanto; Ibnu Utomo Wahyu Mulyono
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 9, No 2 (2026): MEI 2026
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v9i2.3234

Abstract

Kegiatan pengabdian masyarakat ini dilatarbelakangi oleh pesatnya perkembangan teknologi digital dan dukungan terhadap masterplan Smart City Kota Semarang 2021-2026. Masalah utama yang ditemukan di Kelurahan Pedurungan Tengah adalah proses administrasi kependudukan yang masih bersifat manual, sehingga memerlukan digitalisasi untuk meningkatkan efisiensi pelayanan publik. Metode yang digunakan dalam kegiatan ini meliputi tahap identifikasi dan observasi, perancangan serta pengembangan sistem, sosialisasi dan pelatihan kepada 50 warga, hingga tahap implementasi dan evaluasi. Hasil dari kegiatan ini adalah terwujudnya platform digital "RT/RW Online" melalui website resmi https://rt3rw16pedteng.my.id/users/home yang memungkinkan warga melakukan pengajuan surat secara mandiri. Kesimpulannya, implementasi sistem ini berhasil mengoptimalkan pelayanan publik dengan mengubah sistem manual menjadi digital yang lebih transparan dan cepat. Meskipun demikian, variasi tingkat literasi digital di antara warga tetap memerlukan pendampingan intensif sebagai langkah keberlanjutan program.Kata kunci: Administrasi Kependudukan, Digitalisasi, Pelayanan Publik, Pedurungan Tengah, Smart City.
Hiragana Character Classification Using Convolutional Neural Networks Methods based on Adam, SGD, and RMSProps Optimizer Ibnu Utomo Wahyu Mulyono; Yupie Kusumawati; Ajib Susanto; Christy Atika Sari; Hussain Md Mehedul Islam; Mohamed Doheir
Scientific Journal of Informatics Vol. 11 No. 2: Regular Issue
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i2.2313

Abstract

Purpose: Hiragana image classification poses a significant challenge within the realms of image processing and machine learning. Despite advances, achieving high accuracy in Hiragana character recognition remains elusive. In response, this research attempts to enhance recognition precision through the utilization of a Convolutional Neural Network (CNN). Specifically, the study explores the efficacy of three distinct optimizers like Adam, Stochastic Gradient Descent with Momentum (SGDM), and RMSProp in improving Hiragana character recognition accuracy. Methods: This research adopts a systematic approach to evaluate the performance of a Convolutional Neural Network (CNN) in the context of Hiragana character recognition. A meticulously prepared dataset is utilized for in-depth testing, ensuring robustness and reliability in the analysis. The study focuses on assessing the effectiveness of three prominent optimization methods: Stochastic Gradient Descent (SGD), RMSProp, and Adam. Result: The results of the model performance evaluation show that the highest accuracy was obtained from the RMSP optimizer with an F1-Score reaching 99.70%, while the highest overall accuracy was 99.87% with the Adam optimizer. The analysis is carried out by considering important metrics such as precision, recall, and F1-Score for each optimizer. Novelty: The performance results of the developed model are compared with previous studies, confirming the effectiveness of the proposed approach. Overall, this research makes an important contribution to Hiragana character recognition, by emphasizing the importance of choosing the right optimizer in improving the performance of image classification models.
PSNR and SSIM Performance Analysis of Schur Decomposition for Imperceptible Steganography Ajib Susanto; Daurat Sinaga; Ibnu Utomo Wahyu Mulyono
Scientific Journal of Informatics Vol. 11 No. 3: Special Issue
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i3.9561

Abstract

Purpose: This research examines how well Schur decomposition-based steganography can hide data in digital images without being noticed, while also keeping the image quality high and keeping the hidden information safe. Methods: The study starts by choosing regular test images (Lena, Plane, Peppers, Cameraman, Baboon) to use for hiding messages in. The Schur decomposition is used to hide information within images in a subtle way. To test how well the new method works, we added Gaussian noise and Salt & Pepper noise after embedding. The quality of the image is determined by looking at the Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) metrics. Result: The research shows that Schur decomposition results in very good SSIM values (greater than 0.92) and high PSNR scores (as high as 90.27 dB) for various image sizes (64x64, 128x128, 256x256). This means that the quality of the images is not greatly reduced even after steganography is applied. Novelty: This research introduces a unique use of Schur decomposition for hiding data in images without affecting their quality. The study highlights how this method can securely hide information in digital media, which could be really useful for improving steganography techniques in the future. Future studies should concentrate on making improvements to Schur decomposition-based steganography, especially for bigger images. One possibility is to create adaptive methods that can change how images are hidden based on their content. This could make it harder for others to detect and analyze hidden information in the images.
Co-Authors Abdussalam Abdussalam Aji Kusumah Ramdhani Ajib Susanto Anggia Rizkika Hanin Christy Atika Sari De Rosal Ignatius Moses Setiadi Dian Indriana Hapsari Dimas Irawan Ihya’ Ulumuddin Dwi Puji Prabowo Dwi Puji Prabowo, Dwi Puji Eko Hari Rachmawanto Feri Agustina Hussain Md Mehedul Islam Ihya Ulumuddin, Dimas Irawan Imang Dapit Pamungkas Izza Ulumuddin Ahmad Asshofi Joseph Aldo Irawan L. Budi Handoko Mohamed Doheir Novita Kurnia Ningrum Nurjanah Nurjanah Nurjanah Rahayu, Emik Sinaga, Daurat Sudaryanto Sudaryanto Suprayogi Suprayogi Tiara Anggraeny Tiara Widya Kusuma Widyatmoko Karis Yupie Kusumawati Yupie Kusumawati Zahra Ghina Syafira Zahrotul Umami