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Prediction of Sleep Disorders Based on Occupation and Lifestyle: Performance Comparison of Decision Tree, Random Forest, and Naïve Bayes Classifier Lestiawan, Heru; Jatmoko, Cahaya; Agustina, Feri; Sinaga, Daurat; Erawan, Lalang
(JAIS) Journal of Applied Intelligent System Vol. 8 No. 3 (2023): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i3.8987

Abstract

Health is a very important thing in life. Therefore, to maintain health, we need adequate rest. Without adequate rest, the body will not be healthy and fit. In this study, a person's sleep disorder prediction will be made based on their lifestyle and work. The predictions made will classify sleep disorders that are absent, sleep apnea and insomnia from certain lifestyles and work. The methods used to make predictions are decision tree classifier, random forest classifier and naïve Bayes classifier. The test was carried out using a total of 375 data which was broken down into 70% training data and 30% testing data. The results obtained after testing with test data are by using the decision tree classifier algorithm to get an accuracy of 89.431%, using the random forest classifier algorithm to get an accuracy of 90.244% and by using the naïve Bayes classifier algorithm to get an accuracy of 86.992%.
Completing Sudoku Games Using the Depth First Search Algorithm Alfany, Fauzan Maulana; Sari, Christy Atika; Jatmoko, Cahaya; Laksana, Deddy Award Widya; Irawan, Candra; Huda, Solichul
(JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v9i1.10017

Abstract

Sudoku is a digital game that is included in the type of logic-based puzzle game where the goal is to fill in the puzzle with random numbers. Therefore, in this research it is proposed to use Artificial Intelligence which contains the Depth First Search Algorithm to track the number of possible solutions that lead to only one so that it becomes efficient. This game has different levels of difficulty such as easy, medium and difficult. The time and complexity of execution will vary depending on the difficulty so it is proposed to use Android Studio software. The experimental results prove that there is an increase in playing the Sudoku game quickly and accurately by applying the Depth First Search Algorithm method. This is proven by the ability to complete this game using the Depth First Search Algorithm using the Android Studio programming language. The average time at the easy level is 11:04 minutes, at the normal level is 10:52 minutes, at the hard level is 25:46 minutes, and at the extreme level is 38 minutes.
Non-Blind Watermarking Menggunakan Discrete dan Wavelet Transform Sinaga, Daurat; Jatmoko, Cahaya
Jurnal Masyarakat Informatika Vol 13, No 1 (2022): JURNAL MASYARAKAT INFORMATIKA
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.13.1.43714

Abstract

Pada zaman sekarang orang mudah untuk mengakses internet sehingga semua orang dapat memperoleh suatu karya seni digital seperti gambar dengan mudah, kemudian seseorang dapat memodifikasi dan menyebarkan kembali karya tersebut tanpa izin atau tanpa memberikan sumber originalnya. Pada masalah ini dibutuhkan upaya untuk memberikan watermark yang tidak terlihat sehingga tidak mudah untuk menghilangkan watermark gambar tersebut, menggunakan kombinasi DCT dan DWT 1 level untuk memberikan watermark secara tak terlihat pada suatu karya seni. Dari metode kombinasi DCT-DWT diperoleh dengan gambar watermark 64x64 nilai PSNR 39.1529 dB dari hasil tersebut dapat disimpulkan bahwa metode kombinasi DCT-DWT mendapatkan nilai imperceptibility yang baik. Ketahanan gambar diuji dari berbagai proses maipulasi gambar seperti noise, filter, kompresi JPG, dan lain-lain. Hasil dari manipulasi gambar mendapatkan rata-rata NCC bernilai lebih dari 0.6 sehingga dapat disimpulkan metode DCT-DWT tahan (robust) terhadap beberapa serangan citra.
Real-time detection of indonesian sign language (ISL) gestures based on long short-term memory Sari, Christy Atika; Rachmawanto, Eko Hari; Saifullah, Zidan; Jatmoko, Cahaya; Sinaga, Daurat
Journal of Soft Computing Exploration Vol. 5 No. 3 (2024): September 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i3.452

Abstract

eaf people often encounter communication challenges, and sign language serves as a crucial tool for those who cannot speak. In Indonesia, Indonesian Sign Language (ISL) or Sistem Isyarat Bahasa Indonesia (SIBI) is officially recognized by the government and is taught in Special Schools (Sekolah Luar Biasa - SLB). The sign language dictionary comprises 3483 words, facilitating communication and participation in daily life for the deaf community. This research aims to convert ISL gestures within SIBI into understandable text, employing the Long-Short-Term Memory (LSTM) method as the primary approach. The study conducted experiments with two models: Model 1, using a smaller dataset, and Model 2, employing a larger dataset and implementing the k-fold method. The results indicate that Model 2 with k-fold accuracy achieved an accuracy of 98%, while Model 1 reached an accuracy of 85%. Nevertheless, challenges persist in these models, particularly in detecting words with similar gestures, such as’maaf’ (sorry) and 'cinta' (love), which may still be misidentified. Despite these challenges, this research contributes positively to the development of assistive technology for the deaf community, enabling more effective communication through sign language.
Comparative Study of Classification of Eye Disease Types Using DenseNet and EfficientNetB3 Jatmoko, Cahaya; Lestiawan, Heru; Agustina, Feri; Erawan, Lalang
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 9, No. 3, August 2024
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v9i3.1931

Abstract

The purpose of this research is to build a classification model that can perform the eye disease identification process so that the diagnosis of eye disease can be known and medical action can be taken as early as possible. This research used a dataset which has a total of 4217 eye image data and had 4 main classes namely cataract, diabetic retinopathy, glaucoma, and normal. With the data distribution of 1038 cataract images, 1098 diabetic retinopathy images, 1007 glaucoma images, and 1074 normal images, which of this data will be divided with a data percentage scheme of 50:10:40, 60:10:30, and 70:10:20, to see the results of which dataset division can produce optimal accuracy. In this study, the classification process will use 2 CNN transfer learning architectures, namely DenseNet, and efficientnetb3, which are both trained using the ImagiNet dataset. The results obtained after completing the testing process on the model built using the DenseNet architecture get optimal accuracy when using data division as much as 60:10:30, which is 78.59% while using the efficientnetb3 architecture optimal accuracy results when using the data division of 70:10:20, which is 95.66%. In research on the classification that had previously been done, it is very rare to find a classification process for eye disease types, therefore, in this study, the classification process will be carried out and provide an overview of the eye disease classification process with the CNN transfer learning method with more optimal accuracy results.
A Hybrid Encryption using Advanced Encryption Standard and Arnold Scrambling for 3D Color Images Sari, Wellia Shinta; Astuti, Erna Zuni; Jatmoko, Cahaya
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 1, February 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i1.2058

Abstract

Digital security ensuring the confidentiality and integrity of visual data remains a paramount challenge. The escalating sophistication of cyber threats necessitates robust encryption methods to safeguard sensitive information from unauthorized access and manipulation. Despite the development of various encryption techniques, inherent vulnerabilities exist within conventional methods that can be exploited by attackers. Therefore, this research aims to investigate the effectiveness of the combined approach of Arnold Scrambling and Advanced Encryption Standard (AES) in mitigating these vulnerabilities and providing a more secure solution. The primary goal of this research is to enhance the security of digital images by mitigating vulnerabilities associated with conventional encryption methods. Arnold Scrambling introduces chaotic mapping to disperse pixel values, while Advanced Encryption Standard (AES) provides robust cryptographic strength through its substitution-permutation network. By combining these methods in an ensemble fashion, the encryption process achieves heightened resilience against various cryptographic attacks. The proposed methodology was evaluated by using standard metrics including Unified Average Changing Intensity (UACI), Number of Pixels Change Rate (NPCR), and entropy analysis. Results indicate consistent performance across multiple test images, namely: Lena, Mandrill, Cameraman, and Plane with Unified Average Changing Intensity (UACI) averaging 33.6% and Number of Pixels Change Rate (NPCR) nearing 99.8%. Entropy values approached maximum, affirming the efficacy of the encryption in generating highly randomized outputs.
Pelatihan Pembuatan dan Pengelolaan Website Madrasah bagi Guru MA Miftahul Ulum Demak Rokhman, Nur; Setiawan, Agus; Laksana, Deddy Award Widya; Jatmoko, Cahaya; Akrom, Ahmad
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.v8i2.2936

Abstract

Saat ini di era digitalisasi serba online sangat urgent sekali untuk mendapatkan pelatihan dan pendampingan dalam pemanfataan teknologi dalam menciptakan website madrasah yang dapat dimanfaatkan untuk berbagi informasi seperti profil madrasah, kegiatan madrasah serta kegiatan belajar mengajar.  Dengan adanya website madrasah ini setidaknya menjadi kontribusi Universitas Dian Nuswantoro kepada madrasah ini yang sudah berjalan hampir 16 tahun lamanya namun belum mempunyai website madrasah yang dikelola dengan baik. Tujuan dari kegiatan pengabdian ini guru dapat terciptanya website madrasah yang sudah siap online, yang dapat dimanfaatkan untuk berbagi informasi kepada masyarakat, baik informasi profil madrasah maupun sebagai media pembelajaran kepada siswa dan masyarakat.  Kegiatan pelatihan dan pendampingan ini diharapkan dapat menjadi sumbangsih perguruan tinggi Universitas Dian Nuswantoro kepada generasi muda terutama melalui MA Miftahul Ulum Demak, sehingga kepercayaan masyarakat semakin meningkat.
Pelatihan Produksi Foto Panorama untuk Mendukung Pembelajaran Berbasis VR Tour untuk Guru dan Dosen pada Perkumpulan Profesi Multimedia dan Teknologi Informasi (PPMULTINDO) Sindhu Rakasiwi; Candra Irawan; Cahaya Jatmoko; Lalang Erawan; Suprayogi Suprayogi
Transformasi Masyarakat : Jurnal Inovasi Sosial dan Pengabdian Vol. 2 No. 3 (2025): Juli: Transformasi Masyarakat : Jurnal Inovasi Sosial dan Pengabdian
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/transformasi.v2i3.1728

Abstract

The COVID-19 pandemic has triggered a transformation in online learning, requiring teachers and lecturers to adapt to educational technology, including Virtual Reality (VR) Tour. However, limited understanding and motivation are the main challenges in implementing this technology. This community service aims to provide practical training in developing VR Tour as an interactive learning media for teachers and lecturers at Rumah Diklat Indonesia. The implementation method involves an online workshop using the Zoom application, which includes a tutorial on creating 360° panoramic photos via Google Street View and processing VR Tour via the Theasys.io platform. Participants also receive technical guidance and hands-on practice sessions. The results show that participants are able to produce VR Tour content for learning, as well as improve their understanding of technology integration in education. This training equips participants with basic skills to develop virtual learning media, expand students' learning access creatively and innovatively. In conclusion, the use of VR Tour has the potential to improve the quality of distance learning, while encouraging educators to continue to adapt to technological developments in the digital era.
Pemanfaatan Artificial Intelegence untuk Membangun Website Pembelajaran bagi Guru dan Dosen pada Perkumpulan Profesi Multimedia dan Teknologi Informasi (PPMULTINDO) Cahaya Jatmoko; Sindhu Rakasiwi; Feri Agustina; Daurat Sinaga; Heru Lestiawan
Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat Vol. 2 No. 3 (2025): Juli : Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bersama.v2i3.1725

Abstract

The utilization of Artificial Intelligence (AI) technology in education has become increasingly important with the development of information technology. This research aims to provide training for teachers and lecturers in using AI to build interactive and effective learning websites. The method used is online training via Zoom Meeting, which includes an introduction to basic AI concepts, practice creating learning websites, and evaluating training outcomes. The training was conducted over three days from October 26 to 28, 2024, with participants from various regions across Indonesia. The results showed that participants were able to understand AI concepts and apply them effectively in building learning websites more efficiently and creatively. Additionally, the use of AI helped improve the quality of learning content to be more personalized and adaptive to students' needs. Thus, the application of AI in education can serve as an innovative solution to enhance the quality of learning in the digital era.
Improved Chaotic Image Encryption on Grayscale Colorspace Using Elliptic Curves and 3D Lorenz System Sinaga, Daurat; Jatmoko, Cahaya; Astuti, Erna Zuni; Rachmawanto, Eko Hari; Abdussalam, Abdussalam; Pramudya, Elkaf Rahmawan; Shidik, Guruh Fajar; Andono, Pulung Nurtantio; Doheir, Mohamed
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 3, August 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i3.2251

Abstract

Digital data, especially visual content, faces significant security challenges due to its susceptibility to eavesdropping, manipulation, and theft in the modern digital landscape. One effective solution to address these issues is the use of encryption techniques, such as image encryption algorithms, that ensure the confidentiality, integrity, and authenticity of digital visual content. This study addresses these concerns by introducing an advanced image encryption method that combines Elliptic Curve Cryptography (ECC) with the 3D Lorenz chaotic system to enhance both security and efficiency. The method employs pixel permutation, ECC-based encryption, and diffusion using pseudo-random numbers generated by the Lorenz 3D system. The results show superior performance, with an MSE of 3032 and a PSNR of 8.87 dB, as well as UACI and NPCR values of 33.34% and 99.64%, respectively, indicating strong resilience to pixel intensity changes. During testing, the approach demonstrated robustness, allowing only the correct key to decrypt images accurately, while incorrect or modified keys led to distorted outputs, ensuring encryption reliability. Future work could explore extending the method to color images, optimizing processing for larger datasets, and incorporating additional chaotic systems to further fortify encryption strength.