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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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Enhancing the feature-based 3D deformable face recognition using hybrid PCA-NN Cahyo Darujati; Supeno Mardi Susiki Nugroho; Deny Kurniawan; Mochamad Hariadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp215-221

Abstract

Facial recognition is one of the most important advancements in image processing. An important job is to build an automated framework with the same human capacity’s for recognizing face. The face is a complex 3D graphical model, and constructing a computational model is a challenging task. This paper aims at a facial detection technique focused on the coding and decoding of the facial feature object theory approach to data. One of the most natural and common principal component analysis (PCA) method. This approach transforms the face features into a minimal set of basic attributes, peculiarities, which are the critical components of the original learning image collection (or the training package). The proposed technique is a combination of the PCA system and the identification of components using the neural network (NN) feed-forward propagation method. This experiment proves that recognition of deformed 3D face is doable. By taking into account almost all forms of feature extraction and engineering, the NN yields a recognition score of 95%.
Defense behavior of real time strategy games: comparison between HFSM and FSM Rahmat Fauzi; Mochamad Hariadi; Muharman Lubis; Supeno Mardi Susiki Nugroho
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp634-642

Abstract

RTS Game is one of the popular genre in PC gaming, which has been played by various type of players frequently. In RTS game, NPC Defense Building (Tower) has attacking behavior to the closest enemy without considering certain enemy parameters. This causes the NPC Tower to be more predictable by the opponent and easily defeated if NPC attacked by enemies in the group. Thus, this research simulates NPC Tower using Hierarchical Finite State Machine (HFSM) method compared with Finite State Machine (FSM). In this study, NPC Tower detects enemies by seeing at four parameters namely NPC Tower Health, Enemy's Health, Enemy Type, and Tower Distance to enemies. NPC Tower will attack the most dangerous enemy according to the ‘Degree of Danger’ parameter. Then use the decision-making logic of the rule-based system. The output of NPC Tower are three type of behaviors namely Aggressive Attacking, Regular Attacking, and Attack with Special Skill. From the test results of 3 NPC Tower, Kamandaka NPC Tower with HFSM method is winning 8.92% compare to Kamandaka Tower with FSM method. For Gayatri Tower NPC obtained equal results using both HFSM and FSM. Meanwhile, Adikara NPC with HFSM method is 4.62% superior to Adikara Tower with FSM method.
Real time face recognition of video surveillance system using haar cascade classifier Adlan Hakim Ahmad; Sharifah Saon; Abd Kadir Mahamad; Cahyo Darujati; Sri Wiwoho Mudjanarko; Supeno Mardi Susiki Nugroho; Mochamad Hariadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i3.pp1389-1399

Abstract

This project investigates the use of face recognition for a surveillance system. The normal video surveillance system uses in closed-circuit television (CCTV) to record video for security purpose. It is used to identify the identity of a person through their appearances on the recorded video, manually. Today’s video surveillance camera system usually not occupied with a face recognition system. With some modification, a surveillance camera system can be used as face detection and recognition that can be done in real-time. The proposed system makes use of surveillance camera system that can identify the identity of a person automatically by using face recognition of Haar cascade classifier. The hardware used for this project were Raspberry Pi as a processor and Pi Camera as a camera module. The development of this project consist of three main phases which were data gathering, training recognizer, and face recognition process. All three phases have been executed using Python programming and OpenCV library, which have been performed in a Raspbian operation system. From the result, the proposed system successfully displays the output result of human face recognition, with facial angle within ±40°, in medium and normal light condition, and within a distance of 0.4 to 1.2 meter. Targeted image are allowed to wear face accessory as long as not covering the face structure. In conclusion, this system considered, can reduce the cost of manpower in order to identify the identity of a person in real time situation.
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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Abstract

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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Abstract

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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Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3780

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1455.318 KB)

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (724.109 KB) | DOI: 10.36040/mnemonic.v2i1.53

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1371-1379

Abstract

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.
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