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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Muhammad Aminul Akbar
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Implementasi Dynamic Difficulty Adjustment pada Racing Game Menggunakan Metode Behaviour Tree Isthofi Aslim Sofyan; Muhammad Aminul Akbar; Tri Afirianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Video games is all about entertainment and challenge. Without challenge video games will be too easy and boring. But if the challenge is too hard it can make the player frustrated and give up. This related to flow-state where the goal is to find balance between player skills and game challenge. In general, almost every game has difficulty level settings. The difficulty usually ranged from easy, medium, to hard. Unfortunately, this type of difficulty is static, giving inequalities between players and AI. To solve this problem Dynamic Difficulty Adjustment is applied in this research. By applying DDA the difficulty of the game will automatically adjusts to player's ability as the game progress. To support DDA implementation, Behavior Tree is used to help AI to adapt to player's ability. By implementing both method, the game used in this research become less boring and challenging for player.
Implementasi Dynamic Difficulty Adjustment Pada Racing Game Menggunakan Metode Fuzzy Reza Saputra; Muhammad Aminul Akbar; Tri Afirianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Some racing games have a feature to play the game competitively against other player or against Artificial Intelligence (AI) or commonly called as a bot. In its implementation, we tend to find that the ability between the player and the bot is far. This causes boredom if the player has much higher ability than the bot, and will produce anxiety if the player's ability is much lower when compared with the bot. In some racing games there is an option to choose the difficulty level before starting the game, but this feature is still considered less effective to balance the ability of player and bot, because the ability of players can increase as the time goes by, and new players tend to confused that they don't know what category of difficulty that suits their abitility. To solve the problem, the researcher will implement Dynamic Difficulty Adjustment (DDA) by using Fuzzy method that able to adjust the ability of the bot according to player's ability over time. DDA testing is done by playing and matching static bots with DDA bots. Test results show that DDA bots are able to adjust their behavior with the static bots ability, in which the output parameter value changes at 35 seconds, the output parameter values generated for caution angle, steer sensitivity, max wander distance, and wander rate are 41,83, 0.012, 3,57, and 0,03 respectively. The overall value of the parameter categorized as HARD.
Sistem Rekomendasi Pemilihan Benih Varietas Unggul Padi Menggunakan Metode Fuzzy Analitycal Hierarchy Process - Simple Additive Weighting Agung Dwi Budiarto; Edy Santoso; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The continuously increasing number of Indonesian population each year is directly proportional to the increase in national food needs. The increase in this demand is not matched by an increase in agricultural production in the country, so the government is constantly imports to meet their food needs. It takes effort to increase production, especially rice which is considered as a major food ingredient majority of the public. One of the solutions is by activating seeding rice varieties. However, the number of criteria considered making farmers had difficulty in determining their choice. Judging from the problems that arise, there are a number of methods that can be implemented to solve the problems of farmers in decision-making, namely the presence of a recommendation system that is capable of solving the problems of multiple criteria using Fuzzy Analytical Hierarchy Process (Fuzzy AHP) to calculate the weight of the criteria and Simple Additive Weighting (SAW) method to measure the alternatives rank. Functional testing system generates a value of 100%, which means that the system is functioning properly in accordance with the design requirements. While the correlation testing using Spearman method produce the rank-order correlation coeficient of each variety, which coeficient of the INPARI varieties is 0,999, INPAGO is 1,000, INPARA is 1,000, and HIPA is 0,981. So, it can be concluded that the Fuzzy AHP-SAW methods on this system can be used for recommending selection of seed varieties of rice, because it has a positive relationship that approach perfectly with the expert's rank data.
Evaluasi User Experience Pada Game Augmented Reality (Sub Projection Mapping ) : Wall Climbing Menggunakan Heuristic Playbility (PLAY) (Studi Kasus : Wahana Jawa Timur Park 3) Aryo Seto Dwisaputra; Retno Indah Rokhmawati; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Climbing Wall with Augmented Reality is one of attractions in Funtech, Jawa Timur Park 3. This games combines Projection Mapping techonlogies with conventional climbing wall which has been modified so it can be played for everyone, especially for kids. A new kind of user experience that occur in augmented reality is the reason of this study. Playtesting method used with Heuristic Playbility (Play) as instrument. There are 30 visitors of Funtech who played Climbing Wall as respondent with different background. The result of this study show that there are no different between dimension insisde heuristic playbility instrument with significance rate. The conclusion from those 3 categories are Climbing Wall games has provided a unique and good experience for the player itself. Meanwhile, there are some troubles like control of the game that decrease user experience.
Pengembangan Aplikasi Pembelajaran Pengucapan Bahasa Inggris Berbasis Android Menggunakan Automatic Speech Recognizer (ASR) Mohammad Chaliffilardhy Syaifuddin; Agi Putra Kharisma; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

English is one of the most spoken languages in the world. English speakers in Indonesia are below the average in the Asian region. This is due to a lack of interest, lack of basic knowledge, a less supportive environment, often forgetting the concepts learned, and no opportunity to learn. In addition, Indonesian people in general have difficulty in speaking English words or sentences. A new learning media is needed to make it easier to learn English pronunciation. This research develops an Android application that is able to assess and learn English pronunciation. This application implements Automatic Speech Recognition (ASR) for assessment features and implements Text To Speech for learning features. The rating and learning of English pronunciation in applications are limited to 10 words, namely gigantic, architecture, enormous, notorious, tiny, fabulous, enough, voracity, prosperity, and failure. Pronouncement assessment results are shown using the terms Perfect, Good, Not Bad, Bad, and Horrible. Perfect shows the highest value and Bad shows the lowest value. Pronunciation learning is implemented by voicing examples of pronunciation for 10 words assessed on the application. Accuracy and usability testing was conducted on 21 students of class XI (eleven) majoring in language. The accuracy testing results 82.38% of the assessment in accordance with the assessment of the English teacher. Usability testing results show 89.73% of users are satisfied with the application interface and appearance.
Penerapan Algoritme Finite State Machine Berbasis Fragment Shader untuk Proses Pengambilan Keputusan pada Non Player Character (Studi Kasus Game Battle Tank) Muhtadin Ziqi Maulana; Eriq Muh. Adams Jonemaro; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Non player character (NPC) is a character in a game that is not controlled by players, but is controlled through computer programs made by humans. According to the gameAI model the NPC has the ability to make movements and decision making. The battle tank game that was developed by the author in this study also has an NPC developed. there is the game the researcher uses the finite state machine (FSM) algorithm in the decision making process of the NPC. But there is an idea about the application of the FSM algorithm that is by using a shader fragment. With the implementation of the FSM algorithm based on shader fragments, it is expected to get better performance. Because the process of the shader fragment is done in the graphics processing unit (GPU). So that the process carried out can be carried out in parallel between the decision making process and other processes. In applying FSM algorithms based on shader fragment requires three maps, namely world map, agent map and fsm map. After testing the effect of the number of NPCs using 1, 5, 10 and 15 NPCs, respectively, obtained an average yield of 147, 69, 24 and 1 FPS. Whereas for testing the effect of game map size using map sizes of 20x20, 30x30 and 40x40 in succession yielding an average value of 66, 61 and 60 FPS.
Penerapan Naive Bayes untuk NPC Braking Decision pada Racing Game Steven Willy Sanjaya; Muhammad Aminul Akbar; Tri Afirianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Racing is a video game genre that is still popular today. Its development processes cannot be separated from the need to have Non-Player Character (NPC) in them. NPCs act as the opponents for the players, and thus the developers are always challenged with the problem of how to make the NPCs smarter than them. One of the problems is related with breaking decision, specifically when the NPCs decided to slow down their speed during races by using brakes. One commonly used method for this type of experiment is the Brake Zone. Although, this method also has its own shortcomings, such as the devs have to manually place the zone themselves in the designated locations for the brake test. Other solution that can be applied is Smart AI System by Racing Game Starter Kit (RGSK), but this also has its problem in which to get the best result, a proper configuration is needed. To resolve the problem, researcher proposes the method of machine learning, Naive Bayes for the braking decision. Naive Bayes use three features for the data input, and two output class in which the data will be obtained from the player. The test result showed that the braking decision from Naive Bayes was able to prevent the vehicle from crashing with the outer wall without dropping the game's FPS (Frames per Second). Time acquisition each lap from Naive Bayes was able to keep up with the player's time at an average of 52,5 seconds during 10 laps.
Penerapan Neural Network untuk NPC Braking Decision pada Racing Game Herlambang Yudha Prasetya; Muhammad Aminul Akbar; Issa Arwani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The popularity of the racing game genre is still visible today. Factors that supporting the popularity of this genre are speed driving which provides an exciting experience, interesting track variations, stunning graphics, and unique challenges presented by artificial intelligence. An important factor to be developed and in line with the core of the racing game that provides a fun challenge is artificial intelligence. Artificial intelligence behavior that is not varied and easy to guess, or even playing badly will affect the fun of the challenge of racing games. To avoid this, artificial intelligence is needed which is able to learn mindset and imitate human decisions when playing, especially braking decision or gas and brake determination. That is the basis of the Neural Network algorithm implemented for Artificial Intelligence in the Racing Game Starter Kit. The complexity of the code on the machine is simplified by changing the decision process to some intelligent neural networks that are similar to human neurons, especially how it works. Coupled with the adaptation process in a dynamic environment makes this algorithm interesting for AI researchers. By utilizing Cross-Validation, learning this algorithm with human behavior has a similarity rate of 76 percent. In a 10-round trial, the time results showed 12% or 72 seconds faster than the kit's AI, and a stable frame rate with an average of 59 frames per second.
Penerapan Flocking Behavior Untuk Pergerakan Berkelompok Non Player Character pada 2D Endless Runner Game Yosua Yosua; Eriq Muh. Adams Jonemaro; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

2D Endless Runner Game is a game where the player will keep on moving forward thus no end point and will present obstacles for the player and keep the player's adrenaline driven to keep on playing. The obstacles on some of Endless game differs, for this research, the game which will be made will have differently obstacles such as obstacle and group movement. The game will have obstacle where there will be many opponents moving as a group to fight the player's character. The group of assailants which will fight the player, will be applied on simultaneously moving NPC. Flocking is the most famous methods from artificial intelligence which moves a group.Flocking's movement sometimes has this restrained moment, therefore, applied one of the pathfinding method that is A* to make the group's movement not be restrained. Based on this problem, the researcher will develop a game which will have assailant's group have the Flocking Behavior. The results of this study indicate that flocking can be applied in group movements and the resulting FPS affects the number of NPCs in the group This result was proven by testing 3 NPCs to produce FPS ranging from 43.6 and with 8 NPCs producing FPS around 33.7. NPCs also make it to the destination without being blocked.
Penerapan Procedural Content Generation untuk Perancangan Level pada 2D Endless Runner Game menggunakan Genetic Algorithm Muadz Askarul Muslim; Eriq Muhammad Adams Jonemaro; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

With the rapid development of the gaming industry, the amount of content needed in the game continues to increase. Increasing the amount of content is needed to keep players interested, so design work is increasingly needed to meet these requirements. Procedural Content Generation is a solution to save time and money and has been successfully implemented in several Endless Runner Games. Here the author uses the Genetic Algorithm method to implement the Procedural Content Generation on 2D Endless Runner Game. The author's Geographical Algorithm chooses because the Algorithm can optimize which is suitable for many cases of an environment. In addition to optimization, the Genetic Algorithm is modular, so it is separate from the application and can be applied to other cases without significant changes in it. Making levels can be done by using a random technique. But the results of the randomly obtained level can have problems such as the inappropriate results desired because there are no criteria as a measure of appropriateness from the results that are made randomly as can be passed the level that has been made. Whereas in Genetic Algorithm there is a section that can select each individual and population to fit the specified criteria. The results of the tests show the time needed for the program to make a level very short, which is 0.02 seconds. From these results show that the algorithm can be applied and works well in the creation of levels. The resulting level can also be skipped by players based on the results of testing by a sample of players. But the difficulty of the level produced cannot be controlled using the Genetic Algorithm used.
Co-Authors Abdurrahman Prawira Purmiaji Abi Firmandhani Adam Hendra Brata Ade Suluh Novriananda Aditasha Fadhila Ramdani Aditya Luthfi Alvari Ramadhan Aditya Rachmadi Agi Putra Kharisma Agung Dwi Budiarto Ahmad Afif Supianto Ahmad Fadli Naharu Akbar Ramadhan Aldo Rizky Saputra Allen Nazario Istalaksana Anderson Manurung Andhi Indra Lestya Wicaksono Andri Alfian Arief Alamsyah Aryo Pinandito Aryo Seto Dwisaputra Bondan Sapta Prakoso Bugi Pradana Nugroho Cahyono Hadi Kurniawan Carlista Naba Christian Doxa Hamasiah Chrysler Imanuel Chyntia Savrila Putri David Hosea Sipahutar Davin Benaya Dessy Amri Raykhamna Dheanisa Putri Rahayu Ditya Enandini Palupi Djoko Pramono Dwi Rama Malawat Edy Santoso Eriq M. Adams Jonemaro Eriq Muh. Adams Jonemaro Eriq Muhammad Adams Jonemaro Eriq Muhmmad Adams Jonemaro Fathony Teguh Irawan Fathurrahman Annafabi Fikri Ihsan Ahmad Firadi Surya Pramana Firdaus Rahmat Prasetyo Fitraldy Soefana Fitrantika Diashafira Hanifah Muslimah Az-Zahra Hariz Farisi Hendro Dwi Prasetyo Herlambang Yudha Prasetya Herman Tolle Hilmi Ilyas Rizaldi I Made Wira Satya Dharma Ian Setyo Aji Ilham Akbar Ahmadi Ilmam Achmadiarsyi Ilman Naafian Firmansyah Indi Rachmah Winona Intishar Fadi Abdillah Iqbal Firmansyah Iqbal Putra Santosa Ismiarta Aknuranda Issa Arwani Isthofi Aslim Sofyan Jermias Kristian Komang Candra Brata Lailatussaadah M Nur, Lailatussaadah Lutfi Fanani Luthfi Fawwaz Putranto Mayovio Ahmad Mahendrata Mochamad Halim Mohamad Ilham Ridho Mohammad Alauddin Mohammad Chaliffilardhy Syaifuddin Muadz Askarul Muslim Muchtar Prawira Sholikhin Muhamad Arifin Ramadhan Muhammad Arif Nabil Lesmana Muhammad Aufa Athallah Muhammad Azmi Muhammad Azzam Al-Ghifari Habiburrahman Muhammad Reza Pahlevi Muhammad Satrio Bayu Pamungkas Muhtadin Ziqi Maulana Mujahid Bariz Hilmi Musavi Ardabilly Taufik Nashrul Azhar Mas'udi Niken Hendrakusma Nur Muhammad Rashid Panji Yodantara Pramudya Vizkal Arfianto Rahadian Fernandika Ramadhan Rizki Arga Putra Ratih Kartika Dewi Retno Indah Rokhmawati Reza Saputra Richard Hans Octavian Robertus Dwi Ari Utomo Ryan Aristo Sandhi Wistara Shandya Fajar Widyono Shena Star Sarwodi Steven Willy Sanjaya Syarief Noor Permadi Togan Jagat Raya Tri Afirianto Viqi Hanada Wibisono Sukmo Wardhono Widhy Hayuhardhika Nugraha Putra Winny Ardhian Septiko Yolanda Saputri Yoshua Aditya Kurnia Yosua Yosua Yudha Hadi Pratama Yuka Bimatara Putra Yuki Pradana Yusi Tyroni Mursityo Zulfikar Fahmi Falakh