Articles
Plant Growth Modeling Using L-System Approach and Its Visualization
Suyantohadi, Atris;
Alfiyan, Alfiyan;
Hariadi, Mochamad;
Purnomo, Mauridhi Hery
Makara Journal of Technology Vol. 14, No. 2
Publisher : UI Scholars Hub
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The visualization of plant growth modeling using computer simulation has rarely been conducted with Lindenmayer System (L-System) approach. L-System generally has been used as framework for improving and designing realistic modeling on plant growth. It is one kind of tools for representing plant growth based on grammar sintax and mathematic formulation. This research aimed to design modeling and visualizing plant growth structure generated using L-System. The environment on modeling design used three dimension graphic on standart OpenGL format. The visualization on system design has been developed by some of L-System grammar, and the output graphic on three dimension reflected on plant growth as a virtual plant growth system. Using some of samples on grammar L-System rules for describing of the charaterictics of plant growth, the visualization of structure on plant growth has been resulted and demonstrated.
Determining the Standard Value of the Oily Distortion of Acquisition the Fingerprint Images
Syam, Rahmat;
Hariadi, Mochamad;
Purnomo, Mauridhi Hery
Makara Journal of Technology Vol. 15, No. 1
Publisher : UI Scholars Hub
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Determining the Standard Value of the Oily Distortion of Acquisition the Fingerprint Images. This research describes a novel procedure for determining the standard value of the oily distortion of acquisition the fingerprint images based on the score of clarity and ridge-valley thickness ratio. The fingerprint image is quantized into blocks size 32 x 32 pixels. Inside each block, an orientation line, which perpendicular to the ridge direction, is computed. The center of the block along the ridge direction, a two-dimension (2-D) vector V1 (slanted square) with the pixel size 32 x 13 pixels can be extracted and transformed to a vertical 2-D vector V2. Linear regression can be applied to the onedimension (1-D) vector V3 to find the determinant threshold (DT1). The lower regions than DT1 are the ridges, otherwise are the valleys. Tests carried out by calculating the clarity of the image from the overlapping area of the gray-level distribution of ridge and valley that has been separated. Thickness ratio size of the ridge to valley, it is computation per block, the thickness of ridge and valley obtained from the gray-level values per block of image in the normal direction toward the ridge, the average values obtained from the overall image. The results shown that the standard value of the oily distortion of acquisition the fingerprint image is said to oily fingerprint when the images have local clarity scores (LCS) is between 0.01446 to 0.01550, global clarity scores (GCS) is between 0.01186 to 0.01230, and ridge-valley thickness ratio (RVTR) is between 6.98E-05 to 7.22E-05.
Are IEEE 754 32-Bit and 64-Bit Binary Floating-Point Accurate Enough?
Hutabarat, Bernaridho;
Purnama, I Ketut Eddy;
Hariadi, Mochamad;
Purnomo, Mauridhi Hery
Makara Journal of Technology Vol. 15, No. 1
Publisher : UI Scholars Hub
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This paper describes a research toward the accuracy of floating-point values, and effort to reveal the real accuracy. The methods used in this research paper are assignment of values, assignment of value of arithmetic expressions, and output the values using floating-point value format that helps reveal the accuracy. The programming-tool used are Visual C# 9, Visual C++ 9, Java 5, and Visual BASIC 9. These tools run on top of Intel 80 x 86 hardware. The results show that 1*10-x cannot be accurately represented, and the approximate accuracy ranges only from 7 to 16 decimal digits.
Serious game self-regulation using human-like agents to visualize students engagement base on crowd
Khothibul Umam;
Moch Fachri;
Fresy Nugroho;
Supeno Mardi Susiki Nugroho;
Mochamad Hariadi
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/eei.v11i5.3780
Nowadays, the emergence of artificial intelligent (AI) technology for games has been advancely developed. A serious game is a technology employing AI to create a virtual environment in a serious gamification strategy. This research describes AI based virtual classrooms to adopt proper strategies and focusing on maintaining and increasing student engagement by encouraging self-regulation behavior at the learning process. The self-regulation behavior describes student's ability to direct their own learning to achieve learning targets on a path full of obstacles. By employing a human-like agent to visualize student engagement, this visualization aims to provide human-like experiences for users to comprehend student behavior. A reciprocal velocity obstacles (RVO)-based crowd behavior is employed to visualize student engagement. RVO is an autonomous navigation approach for directing the achievement of agents target. The human-like agents behave in various ways to reach the goal points depending on the performances and the obstacles before them. We employ our method in an investigation of students' learning activities in a pedagogically-centered learning environment at Universitas Islam Negeri (UIN) Walisongo, Semarang, Indonesia. The results demonstrate the best scenario changes along with the performances and obstacles faced to reach the goal points as well as the learning target.
Self-Training Naive Bayes Berbasis Word2Vec untuk Kategorisasi Berita Bahasa Indonesia
Joan Santoso;
Agung Dewa Bagus Soetiono;
Gunawan;
Endang Setyati;
Eko Mulyanto Yuniarno;
Mochamad Hariadi;
Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 2: Mei 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada
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News as one kind of information that is needed in daily life has been available on the internet. News website often categorizes their articles to each topic to help users access the news more easily. Document classification has widely used to do this automatically. The current availability of labeled training data is insufficient for the machine to create a good model. The problem in data annotation is that it requires a considerable cost and time to get sufficient quantity of labeled training data. A semi-supervised algorithm is proposed to solve this problem by using labeled and unlabeled data to create classification model. This paper proposes semi-supervised learning news classification system using Self-Training Naive Bayes algorithm. The feature that is used in text classification is Word2Vec Skip-Gram Model. This model is widely used in computational linguistics or text mining research as one of the methods in word representation. Word2Vec is used as a feature because it can bring the semantic meaning of the word in this classification task. The data used in this paper consists of 29,587 news documents from Indonesian online news websites. The Self-Training Naive Bayes algorithm achieved the highest F1-Score of 94.17%.
DESAIN SERIOUS GAME SOSIALISASI BENCANA BERBASIS MODEL TEORI AKTIFITAS
Nugroho, Fresy;
Mulyanto Yuniarno, Eko;
Hariadi, Mochamad
Jurnal Mnemonic Vol 2 No 1 (2019): Mnemonic Vol. 2 No. 1
Publisher : Teknik Informatika, Institut Teknologi Nasional malang
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DOI: 10.36040/mnemonic.v2i1.53
Sosialisasi bencana masih mengalami beberapa kendala antara lain kesulitan bila dilakukan secara offfline, mengingat untuk sosialisasi offline membutuhkan waktu khusus, memerlukan persiapan yang lama dan memerlukan alokasi dana khusus. Makalah ini memberikan sebuah pendekatan baru berupa sosialisasi bencana dalam bentuk serious game. Sehingga dinamakan serious game sosialisasi bencana. Dalam mendesain serious game sosialisasi bencana, menggunakan model teori aktivitas utnuk serious game dan tahapan sosialisasi bencana sebagaimana di isyaratkan dalam undang-undang tentang penanggulangan bencana dan diuraikan pusat vulkanologi dan mitigasi bencana geologi. Untuk membuat sebuah serious game dibutuhkan pula metode finite state machine untuk memudahkan mesin mengatur permainan. Visualisasi juga di rancang untuk menunjukkan capaian yang diperoleh pemain agar lebih menarik.
Crowd navigation for dynamic hazard avoidance in evacuation using emotional reciprocal velocity obstacles
Fachri, Moch;
Prasetyo, Didit;
Damastuti, Fardani Annisa;
Ramadhani, Nugrahardi;
Susiki Nugroho, Supeno Mardi;
Hariadi, Mochamad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijai.v13.i2.pp1371-1379
Crowd evacuation can be a challenging task, especially in emergency situations involving dynamically moving hazards. Effective obstacle avoidance is crucial for successful crowd evacuation, particularly in scenarios involving dynamic hazards such as natural or man-made disasters. In this paper, we propose a novel application of the emotional reciprocal velocity obstacles (ERVO) method for obstacle avoidance in dynamic hazard scenarios. ERVO is an established method that incorporates agent emotions and obstacle avoidance to produce more efficient and effective crowd navigation. Our approach improves on previous research by using ERVO to model the perceptive danger posed by dynamic hazards in real-time, which is crucial for rapid response in emergency situations. We conducted experiments to evaluate our approach and compared our results with other velocity obstacle methods. Our findings demonstrate that our approach is able to improve agent coordination, reduce congestion, and produce superior avoidance behavior. Our study shows that incorporating emotional reciprocity into obstacle avoidance can enhance crowd behavior in dynamic hazard scenarios.
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
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DOI: 10.22219/kinetik.v7i3.1464
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
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DOI: 10.11591/ijai.v13.i4.pp4654-4666
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
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DOI: 10.25126/jtiik.2018561117
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.