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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika Jurnal Ilmu Komputer dan Informasi IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science Semantik MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Bulletin of Electrical Engineering and Informatics Rekam : Jurnal, Fotografi, Televisi Animasi JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmiah Kursor Journal of Urban Society´s Arts Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Mathematical and Fundamental Sciences Journal of ICT Research and Applications Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics agriTECH JFA (Jurnal Fisika dan Aplikasinya) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Register: Jurnal Ilmiah Teknologi Sistem Informasi SMATIKA EMITTER International Journal of Engineering Technology Proceeding of the Electrical Engineering Computer Science and Informatics Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Conference on Innovation and Application of Science and Technology (CIASTECH) JAVA Journal of Electrical and Electronics Engineering Jurnal Mnemonic Indonesian Journal of Electrical Engineering and Computer Science Aiti: Jurnal Teknologi Informasi Journal of Computer Networks, Architecture and High Performance Computing JAREE (Journal on Advanced Research in Electrical Engineering) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Teknologi Informasi Cyberku Makara Journal of Technology
Mochamad Hariadi
Institut Teknologi Sepuluh Nopember
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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Segmentation of Facial Bones from Skull Point Clouds Based on Smoothed Deviation Angle Ulinuha, Masy Ari; Yuniarno, Eko Mulyanto; Purnama, I Ketut Eddy; Hariadi, Mochamad
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 3, August 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i3.1464

Abstract

The human skull was the subject of study in various fields. Segmentation could be a basic tool for better understanding the skull. One of the most challenging tasks was facial bone segmentation. Our previous study had succeeded in segmenting facial bones from skull point clouds, however the quality of the results needed to be improved. In this paper, we proposed a new method to improve the results of facial bone segmentation from skull point clouds. The method consists of three stages: deviation angle extraction, smoothing, and thresholding. Each point in the point cloud was assigned a value based on the deviation angle. These values then went through a smoothing process to clarify the differences between the facial bone region and other regions. Next, thresholding was performed to divide the skull into two regions, namely facial bone and non-facial bone. The proposed method had succeeded in improving the quality of the segmentation results by achieving precision=0.931, recall=0.9854, and F=0.9573.
Enhancing image quality using super-resolution residual network for small, blurry images Hindarto, Djarot; Wahyuddin, Mohammad Iwan; Andrianingsih, Andrianingsih; Komalasari, Ratih Titi; Handayani, Endah Tri Esti; Hariadi, Mochamad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i4.pp4654-4666

Abstract

In the background, when low-resolution images are utilized, image identification tasks are frequently hampered. By employing the residual network super-resolution framework, super-resolution techniques are used to enhance image quality, specifically in the detection and identification of small and blurry objects. Improving resolution, decreasing blur, and enhancing object detail are the main goals of the suggested approach. The novelty of this research resides in its application of the activation exponential linear unit (ELU) to the super-resolution residual network (SR-ResNet) framework, which has been demonstrated to enhance image sharpness. The experimental findings demonstrate a substantial enhancement in the quality of the images, as evidenced by the training data's structural similarity index (SSIM) of 0.9989 and peak signal-to-noise ratio (PSNR) of 91.8455. Furthermore, the validation data demonstrated SSIM 0.9990 and PSNR 92.5520. The results of this study indicate that the implementation of SR-ResNet significantly enhances the capability of the detection system to detect and classify diminutive and opaque entities precisely. The expected and projected enhancement in image quality significantly influences image processing, especially in situations where accuracy and object differentiation are vital.
Penempatan Posisi Multi Kamera Berdasarkan Gaya Sutradara Berbasis Logika Fuzzy Junaedi, Hartarto; Pranata, Jaya; Hariadi, Mochamad; Purnama, I Ketut Eddy
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 5 No 6: Desember 2018
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (4185.037 KB) | DOI: 10.25126/jtiik.2018561117

Abstract

Teknologi komputer saat ini telah banyak digunakan dalam pengembangan animasi atau permainan komputer. Salah satu teknologi itu adalah machinima yaitu suatu sistem yang menggunakan teknologi mesin grafik 3D untuk menghasilkan produk sinematik secara real time. Dalam proses pembuatan produk sinematik itu penempatan posisi kamera sangat memegang peranan penting. Penempatan posisi kamera ini tentu harus sesuai dengan kaidah-kaidah sinematografi. Penelitian ini akan mengusulkan sebuah pendekatan agen cerdas dengan multi perilaku untuk menempatkan kamera virtual dalam lingkungan virtual secara otomatis sesuai dengan gaya seorang sutradara. Setiap kamera virtual itu akan memiliki perilaku yang berbeda berdasarkan kaidah sinematografi sehingga memiliki Point of View (POV) yang berbeda. Untuk memberikan perilaku pada kamera virtual akan digunakan pendekatan berbasis logika fuzzy dengan menggunakan metode mamdani. Jumlah variabel masukan yang digunakan sejumlah tiga dan variabel keluaran sejumlah tiga dengan membership function antara tiga sampai lima. Penelitian ini akan menggunakan simulasi permainan komputer dengan tiga kamera virtual dengan perilaku yang berbeda untuk merekam adegan yang sama dan hasilnya akan divalidasi berdasarkan hasil pengamatan dengan komunitas juru foto.  Pada akhirnya dapat diambil kesimpulan bahwa pendekatan logika fuzzy dapat digunakan untuk memberikan sebuah perilaku atau gaya sutradara pada kamera virtual.AbstractComputer technology is has been used widely in the development of animation or computer games. One of the technologies is machinima, a system that uses reak time 3D graphics engine technology to produce cinematic products. In the process of develop a cinematic product, camera positioning is a very important component. The camera positioning must be comply with cinematography’s rule. This research will propose an intelligent multi agent behavior to positining a virtual camera in a virtual environment automatically according to the director’s style. Each virtual camera will have a different behavior based on cinematographic rules so that it has a different Point of View (POV). To assign a behavior on the virtual camera will be based on  fuzzy logic using the mamdani method. The number of input variables are three and the output variables are three with the number membership functions between three to five. This research will program  a computer game simulation with three multi behavior virtual cameras to capture some scene and the results will be validated based on observations with the photographer community. Finally it can be concluded that the fuzzy logic approach can be used to assign some behavior to a virtual camera.
Akuisisi Foreground dan Background Berbasis Fitur DTC pada Matting Citra secara Otomatis Koeshardianto, Meidya; Yuniarno, Eko Mulyanto; Hariadi, Mochamad
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 3: Juni 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020732195

Abstract

Teknik pemisahan foreground dari background pada citra statis merupakan penelitian yang sangat diperlukan dalam computer vision. Teknik yang sering digunakan adalah image segmentation, namun hasil ekstraksinya masih kurang akurat. Image matting menjadi salah satu solusi untuk memperbaiki hasil dari image segmentation. Pada metode supervised, image matting membutuhkan scribbles atau trimap sebagai constraint yang berfungsi untuk melabeli daerah tersebut adalah foreground atau background. Pada makalah ini dibangun metode unsupervised dengan mengakuisisi foreground dan background sebagai constraint secara otomatis. Akuisisi background ditentukan dari varian nilai fitur DCT (Discrete Cosinus Transform) yang dikelompokkan menggunakan algoritme k-means. Untuk mengakuisisi foreground ditentukan dari subset hasil klaster fitur DCT dengan fitur edge detection. Hasil dari proses akuisisi foreground dan background tersebut dijadikan sebagai constraint. Perbedaan hasil dari penelitian diukur menggunakan MAE (Mean Absolute Error) dibandingkan dengan metode supervised matting maupun dengan metode unsupervised matting lainnya. Skor MAE dari hasil eksperimen menunjukkan bahwa nilai alpha matte yang dihasilkan mempunyai perbedaan 0,0336 serta selisih waktu proses 0,4 detik dibandingkan metode supervised matting. Seluruh data citra berasal dari citra yang telah digunakan para peneliti sebelumnyaAbstractThe technique of separating the foreground and the background from a still image is widely used in computer vision. Current research in this technique is image segmentation. However, the result of its extraction is considered inaccurate. Furthermore, image matting is one solution to improve the effect of image segmentation. Mostly, the matting process used scribbles or trimap as a constraint, which is done manually as called a supervised method. The contribution offered in this paper lies in the acquisition of foreground and background that will be used to build constraints automatically. Background acquisition is determined from the variant value of the DCT feature that is clustered using the k-means algorithm. Foreground acquisition is determined by a subset resulting from clustering DCT values with edge detection features. The results of the two stages will be used as an automatic constraint method. The success of the proposed method, the constraint will be used in the supervised matting method. The difference in results from In the research experiment was measured using MAE (Mean Absolute Error) compared with the supervised matting method and with other unsupervised matting methods. The MAE score from the experimental results shows that the alpha matte value produced has a difference of 0.336, and the difference in processing time is 0.4 seconds compared to the supervised matting method. All image data comes from images that have been used by previous researchers.
Enhanced PBFT Blockchain based on a Combination of Ripple and PBFT (R-PBFT) to Cryptospatial Coordinate wibowo, Achmad Teguh; Hariadi, Mochamad; Suhartono, Suhartono; Shodiq, Muhammad
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 8 No 2 (2022): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i2.3041

Abstract

In this research, we introduce the combination of two Blockchain methods. Ripple Protocol Consensus Algorithm (RPCA) and Practical Byzantine Fault Tolerance (PBFT) are applied to cryptospatial coordinates to support cultural heritage tourism. The PBFT process is still used until the preparation process to ensure a maximum error of 33%, and every node would add a new chain in all nodes, so PBFT has a slower processing speed than other methods. This research cuts the PBFT process. After the preparation process in PBFT, the data was entered into the RPCA node and was calculated using an equation to minimize errors with a maximum limit of 20%. After this process, the was were sent to the commit process to store the data in all connected nodes in the Blockchain network; we call this combination of two methods R-PBFT. Combining the two methods can enhance data processing security and speed because it still uses the PBFT work combined with the speed of RPCA. Furthermore, this method uses a fault tolerance value from the RPCA of 20% to enhance data processing security and speed.
Information System Design at FGH Stores with Unified Modelling Language Hindarto, Djarot; Hariadi, Mochamad
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2702

Abstract

This project aims to develop and execute a proficient information system at FGH Stores, to enhance sales performance and improve customer satisfaction. This study centers on incorporating information technology into routine business activities, intending to devise strategies that facilitate seamless consumer interactions and aid store management in effectively handling inventory and customer data. The research process includes the examination of business needs, the formulation of system architecture, the creation of user interfaces that prioritize ease of use, and the integration of databases. The resultant information system facilitates consumer registration as members, reduces browsing of product catalogs, and enables efficient execution of purchases. Furthermore, implementing shop management systems enables enhanced inventory monitoring, efficient customer data management, and improved responsiveness to consumer requests. This study assesses the effects of information systems on enhancing sales and operational efficiency by conducting data collection and analysis before and after deployment. The findings indicated that implementing information systems effectively enhanced the efficiency of the sales process and improved the customer experience, yielding substantial advantages for the growth of retail establishments. This study offers valuable insights into the possible utilization of information technology within the retail industry while also contributing to the comprehension of the favorable effects that information systems integration may have on corporate expansion and customer satisfaction.
The application of Neural Prophet Time Series in predicting rice stock at Rice Stores Hindarto, Djarot; Hendrata, Ferial; Hariadi, Mochamad
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2725

Abstract

Efficient inventory management and consistent rice supply are pivotal for the sustainability of small-scale food stalls. This research introduces an innovative approach to address this challenge through the Neural Prophet algorithm. By synergizing neural networks with additive regression models, the Neural Prophet captures intricate temporal patterns and trends within rice sales data. Our study evaluates the Neural Prophet's effectiveness in predicting rice sales, specifically for essential food vendors. Leveraging historical sales data from June 2022 to April 2023, the algorithm incorporates seasonality and trends and integrates external events, such as holidays, to heighten prediction precision. Our findings underscore the Neural Prophet's remarkable prowess in forecasting rice sales at primary food kiosks, adeptly discerning data trends and fluctuations, culminating in reliable future sales projections. The model boasts compelling performance metrics: MAE = 12.90, RMSE = 15.80, and Loss = 0.0313. Beyond its technical merits, this research carries significant practical implications, empowering proprietors and suppliers of basic food stalls to streamline inventory management, avert stockouts, and curtail overstocking by harnessing the precision of rice demand forecasting facilitated by the Neural Prophet algorithm.
Co-Authors Abd Kadir Mahamad Achmad Teguh Wibowo Aditiya, Fajar Adlan Hakim Ahmad Agung Dewa Bagus Soetiono Ahmad Fathur Muhtadin Ahmad Zaini Ahmad Zainul Fanani Aji Prasetya Wibawa Alfiyan Alfiyan, Alfiyan Anang Kukuh Adisusilo Andreas Andrianingsih Arifin Arifin Arry Maulana Syarif Astrid Novita Putri, Astrid Atris Suyantohadi Atris Suyantohadi Atris Suyantohadi Bambang Purwantana Bandung Arry Sanjoyo Beny Yulkurniawan Victorio Nasution Beny Yulkurniawan Victorio Nasution Bernaridho Hutabarat, Bernaridho Budi Setiyono Cahyo Darujati Cahyo Darujati Catur Supriyanto Catur Supriyanto Chandra Eko Wahyudi Utomo Christyowidiasmoro Christyowidiasmoro Damastuti, Fardani Annisa Deny Kurniawan Djunaidi, Fariz DWI CAHYONO Dwi Ratna Sulistyaningrum Eko Mulyanto Yuniarno Eko Mulyanto Yuniarno Endah Tri Esti Handayani Endang Setyati Evi Rokhayati Fachri, Moch Fachrul Kurniawan Fresy Nugroho Fresy Nugroho Fresy Nugroho Gunawan Gunawan Gunawan Guruh Fajar Shidik H. Hammad, Jehad A. Harfianti, Nadya Putri Hartarto Junaedi Hendrata, Ferial Hindarto, Djarot I Ketut Eddy Purnama I Ketut Purnama, I Ketut I.G.P. Asto Buditjahjanto Ingrid Nurtanio Jarot Dwiprasetyo Jaya Pranata, Jaya Jehad A. H. Hammad Joan Santoso Johannes Gerdes Kasman Kasman Ketut Tirtayasa Khothibul Umam Koeshardianto, Meidya Kurniawan, Fachrul Latius Hermawan Lukman Zaman mardi, Supeno Masy Ari Ulinuha Matahari Bhakti Nendya, Matahari Bhakti Mauridhi H Purnomo Mauridhi H. Purnomo Mauridhi H. Purnomo Mauridhi Heri Purnomo Mauridhi Heri Purnomo Mauridhi Heri Purnomo Mauridhi Herry Purnomo Mauridhi Hery Mauridhi Hery Purnomo Mauridhi Hery Purnomo Mauridhi Hery Purnomo Mauridhi Hery Purnomo Mauridhi Purnomo, Mauridhi Mauridhy Hery Purnomo Moch Fachri Moh. Aries Syufagi Moh. Aries Syufagi Moh. Zikky Moh. Zikky, Moh. Muhammad Rivai Muhammad Shodiq, Muhammad Muharman Lubis Muhtadin ., Muhtadin Muhtadin Muhtadin Munir Munir Nugrahardi Ramadhani Padmasari, Ayung Candra Prasetyo, Didit Pulung Nurtantio Andono Radi Radi Rahmat Fauzi Rahmat Syam Ratih Titi Komalasari Restuadi Studiawan Ricardus Anggi Pramunendar Ruri Suko Basuki Saiful Bukhori Saiful Bukhori Saiful Yahya Samuel Gandang Gunanto Sharifah Saon Shung Ping Chen Soetiono, Agung Dewa Bagus Sri Wiwoho Mudjanarko, Sri Wiwoho Suhartono Sukirman Sukirman Supeno Mardi S. N, Supeno Mardi Supeno Mardi Susiki Nugroho, Supeno Mardi Surya Sumpeno Susi Juniastuti Tri Arief Sardjono Tri Daryatni Wahyuddin, Mohammad Iwan Wisnu Widiarto Yoyon K Suprapto Yoze Rizki Yuhefizar Yuhefizar Yulianto Tejo Putranto Yunifa Miftachul Arif Zaini, Ahmad Zaman, Lukman