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Susunan Obyek Terbaik Pada Permainan Puzzle Instalasi Dimensi Dua Menggunakan Algoritma Genetika Prameswari, Citra Ratih; Yuniarno, Eko Mulyanto; Susiki Nugroho, Supeno Mardi
Journal of Animation & Games Studies Vol 1, No 2 (2015): Oktober 2015
Publisher : Institut Seni Indonesia Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24821/jags.v1i2.1300

Abstract

One of the technique to support education that grown today is the game. This research developing installation game as a form of simulation to support education. Installation game is an art to install, unify, and compile recycle objects into a new form that is more meaningful. The game was made by 2D visualization, the genre is puzzle game, and can be used as a learning tool creativity of primary school students. This research designed 2D puzzle game installation, and the way to get the optimal score. Optimal scores obtained when vast number of object that arranged by player approaching the reference template. Genetic algorithm determines the most optimal combination of objects automatically and quickly that are used as a reference in accordance with the broad template, but it can't help determine the score of each player in terms of aesthetics, because the data that is random. The test in this research conducted in two ways, they are: actual and compared it with genetics algorithm as wide as the template. The Scores obtained using genetic algorithms may be the same, better, or worse than the calculation of the actual scores obtained.Keywords: scoring, puzzle game, 2D installation, genetic algorithm. AbstrakSalah satu teknik untuk menunjang pendidikan adalah dengan permainan. Penelitian ini mengembangkan permainan instalasi sebagai suatu bentuk dari media untuk menunjang pendidikan. Permainan puzzle instalasi dimensi dua merupakan sebuah seni memasang, menyatukan, dan menyusun barang bekas yang dapat didaur ulang menjadi suatu bentuk baru yang lebih bermakna yang dibuat dengan tampilan dimensi dua, ber-genre puzzle game, dan dapat digunakan sebagai alat bantu dalam pembelajaran kreatifitas siswa sekolah dasar. Penelitian ini merancang permainan puzzle instalasi dimensi dua serta cara untuk mendapatkan skor yang optimal. Skor yang optimal merupakan skor yang terbaik mendekati luas template acuan. Algoritma genetika menentukan kombinasi obyek paling optimal yang digunakan sebagai acuan sesuai dengan luas template secara otomatis dan cepat, namun tidak dapat membantu menentukan skor setiap pemain dari segi estetika, karena data yang dimunculkan bersifat random. Pengujian pada penelitian ini dilakukan dengan dua cara, yaitu dengan cara actual dan kemudian dibandingkan dengan algoritma genetika sesuai dengan luas template yang diperoleh pemain. Skor yang diperoleh dengan menggunakan algoritma genetika dapat sama, lebih baik, maupun lebih buruk dari perhitungan skor yang didapatkan secara aktual.Kata kunci: perhitungan skor, permainan puzzle, instalasi dimensi dua, algoritma genetika.
OPTIMIZING OF BOXING AGENT BEHAVIOR USING ELITISM BASED GENETIC ALGORITHM Adisusilo, Anang Kukuh; Hariadi, Mochamad; Zaini, Ahmad; Susiki Nugroho, Supeno Mardi
Kursor Vol 7, No 2 (2013)
Publisher : University of Trunojoyo Madura

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Abstract

OPTIMIZING OF BOXING AGENT BEHAVIOR USING ELITISM BASED GENETIC ALGORITHM aAnang Kukuh Adisusilo, bMochamad Hariadi, cAhmad Zaini, d Supeno Mardi Susiki Nugroho aDepartment of Information Engineering, Faculty of Engineering, University of Wijaya Kusuma Surabaya b,c,dIntelligent Network Expertise Multimedia Department of Electrical Engineering, Faculty of Industrial Technology, Sepuluh Nopember Institute of Technology Surabaya Email: anang@anang65.web.id Abstrak Pola perilaku agen tinju pada permainan tinju dipengaruhi oleh beberapa faktor antara lain teknik gerakan bertinju, jenis pukulan tinju, stamina, dan energi pukulan. Pola perilaku agen tinju secara umum menggunakan variabel random dengan distribusi event dari setiap state secara acak. Penelitian dengan menggunakan FSM (Finite State Machine) berbasis algoritma genetika, menghasilkan nilai fitness 0.96, untuk pola perilaku agen cenderung maju kearah lawan, energi pukulan cenderung sedikit, dan menggunakan jenis pukulan dengan objektivitas tinggi. Penelitian ini menggunakan fungsi elitism pada algoritma genetika untuk dapat menghasilkan nilai fitness yang stabil dan pola perilaku agen tinju yang lebih baik dibandingkan tanpa menggunakan fungsi elitism. Nilai fitness yang dihasilkan dari penelitian ini diantara 3.101748 sampai 3.14738 dan nilai fitness optimal diantara 2.78083 sampai 3.167174, dengan siklus algoritma genetika lebih besar sama dengan generasi ke-25. Pola perilaku agen tinju yang dihasilkan berdasarkan nilai fitness adalah menyerang menggunakan satu jenis pukulan uppercut right dan tiga pukulan jab, dengan energi pukulan diantara 48 sampai 52 dan pola permaianan cenderung maju sambil melindungi wajah (covered). Pola perilaku agen tinju dari nilai fitness adalah menyerang menggunakan satu jenis pukulan uppercut right dan tiga pukulan jab dengan energi pukulan diantara 48 sampai 52 dengan pola permaianan cenderung maju dan melindungi wajah (covered). Kata kunci: Perilaku agen, Algoritma Genetika, Optimasi, Permainan Tinju, FSM. Abstract Boxing agent behavior patterns in the game of boxing is affected by several factors, i.e. the technique of boxing movements, type of punch, stamina, and energy of the punch. Boxing agent behavior patterns in general use variable random event where is state distribution randomly. A study using FSM (Finite State Machine) based on genetic algorithms, resulting fitness value 0.96 for boxing agent behavior patterns that tend to move towards the opponent , used energy to blow is likely small, and it uses the kind of blow that has high objectivity. This study will utilize elitism function in genetic algorithms to produce a stable fitness and better boxing agent behavior patterns than the one use genetic algorithms without elitism function. Fitness value result from this study between 3.14738 and 3.101748 and the optimal fitness value between 2.78083 to 3.167174, with a genetic algorithm cycle equal or more than the 25th. The boxing agen behavior patterns generated from fitness value is to attack using single type of blow, right uppercut punch and jab with a three-punch blow energy between 48 to 52 and patterns game that tend to move foward with covered the face. Key words: Agent behavior, Genetic Algorithm, Optimation, Boxing game, FSM
Opinion Detection of Public Sector Financial Statements Using K-Nearest Neighbors Arianto, Ahmad Dwi; Affandi, Achmad; Susiki Nugroho, Supeno Mardi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (248.178 KB)

Abstract

The identification of ethical violations committedby the auditor is very difficult to do. Artificial intelligence offersanomaly detection as an alternative method for detecting theopinion anomaly which can be an early indicator of the opiniontrading occurrence. This paper proposes the use of originalfeatures from public sector rather than the use of modifiedfeatures from the private sector to be applied in opinion detectionin public sector. By using 60% Holdout validation, 1-NNclassification showed that original featured from the public sectoroutperformed the modified featured from the private sector by5.82% through 13.10% under F-Measure Criterion and by4.22% through 9.56% under AUC criterion.
Opinion Detection of Public Sector Financial Statements Using K-Nearest Neighbors Arianto, Ahmad Dwi; Affandi, Achmad; Susiki Nugroho, Supeno Mardi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (248.178 KB)

Abstract

The identification of ethical violations committedby the auditor is very difficult to do. Artificial intelligence offersanomaly detection as an alternative method for detecting theopinion anomaly which can be an early indicator of the opiniontrading occurrence. This paper proposes the use of originalfeatures from public sector rather than the use of modifiedfeatures from the private sector to be applied in opinion detectionin public sector. By using 60% Holdout validation, 1-NNclassification showed that original featured from the public sectoroutperformed the modified featured from the private sector by5.82% through 13.10% under F-Measure Criterion and by4.22% through 9.56% under AUC criterion.
Pergerakan Otonom Pasukan Berbasis Algoritma Boid Menggunakan Metode Particle Swarm Optimization Mu'min, Syahri; Hariadi, Mochammad; Susiki Nugroho, Supeno Mardi
Journal of Animation & Games Studies Vol 1, No 1 (2015): April 2015
Publisher : Institut Seni Indonesia Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24821/jags.v1i1.895

Abstract

Real-Time Strategy game (RTS) is an interesting game, the screen is divided into the area map, units, and buildings. Play RTS games are generally made up of players who are positioned in a place on the map with multiple units or buildings, the player moves from one place to another. Group of characters or troops engaged in RTS games have broad approach, for this problem boids model. Ability Particle Swarm Optimization (PSO) to achieve optimum position creates the possibility to automatically generate non deterministic way a crowd of troops from certain positions. In this case, we focus on making the pattern moves are smooth and flexible realistic for virtual troops to take advantage of the computing facilities offered by PSO. That function is used to describe all types of objects in the system simulation, including static targets, static obstacles, and the troops which are considered as particles in finding ways to achieve the best solution. Keywords: autonomous agents, boid, particle swarm optimization, real-time strategy game.AbstrakPermainan real-time strategy (RTS) merupakan sebuah game yang menarik, layar dipisahkan menjadi peta area, unit, dan bangunan. Bermain game RTS umumnya terdiri dari pemain yang diposisikan di suatu tempat di peta dengan beberapa unit atau bangunan, pemain bergerak dari satu tempat ke tempat yang lain. Kelompok karakter atau pasukan yang bergerak dalam permainan RTS memiliki pendekatan luas, untuk masalah ini menggunakan model boids. Kemampuan Particle Swarm Optimization (PSO) untuk mencapai posisi optimum menciptakan kemungkinan untuk secara otomatis menghasilkan jalan non deterministic kerumunan pasukan dari satu posisi tertentu. Dalam kasus ini, kami fokus pada pembuatan pola bergerak yang halus dan fleksibel realistis bagi pasukan virtual dengan memanfaatkan fasilitas komputasi yang ditawarkan oleh PSO. Fungsi tersebut digunakan untuk menggambarkan semua jenis objek dalam sistem simulasi , termasuk target statis , hambatan statis , serta pasukan yang dianggap sebagai partikel dalam mencari cara untuk mencapai solusi terbaik.Kata Kunci : agen otonom, boid, particle swarm optimization, real-time game strategy