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INDONESIA
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Published by Universitas Brawijaya
ISSN : -     EISSN : -     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering
Jurnal Pengembangan Teknlogi Informasi dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya merupakan jurnal keilmuan dibidang komputer yang memuat tulisan ilmiah hasil dari penelitian mahasiswa-mahasiswa Fakultas Ilmu Komputer Universitas Brawijaya. Jurnal ini diharapkan dapat mengembangkan penelitian dan memberikan kontribusi yang berarti untuk meningkatkan sumber daya penelitian dalam Teknologi Informasi dan Ilmu Komputer.
Arjuna Subject : -
Articles 6,850 Documents
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Implementasi Adaptive AI Pada Game Turn-Based RPG Dengan Menggunakan Metode Hierarchial Dynamic Scripting Intishar Fadi Abdillah; Eriq Muh. Adams Jonemaro; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

There are many methods used by game developers in applying Artificial Intelligence (AI) into Non Playable Character (NPC) which aims to inhibit gamers in achieving their goals or mission. Scripting method is one of the most used method of game developers in designing AI in NPC because of its simple, flexible (easy to modify), and powerful process. Scripting method is a way to design behavior NPC through a combination of rules that are modeled with if-then sentences. The combination of these rules is explicitly written on source code or other external files (commonly referred to as hard coded) which is not possible to change the NPC behavior when the game has been released. This causes the NPC is often easily exploited by gamers who have understood the pattern of the NPC behavior. To overcome these problems, we need a method capable of producing an adaptive NPC behavior while still providing the nature of Scripting method that is simple, flexible, and powerful. Therefore, Hierarchial Dynamic Scripting method tries to answer the problem in this research. Hierarchial Dynamic Scripting method is an advanced development of the Dynamic Scripting method by adding Hierarchial Task Network architecture in it. The main principle of the Dynamic Scripting method is to assign specific weights to the set of rules and combine them into a dynamic script. Adaptive test results conducted in the game with the genre of Turn-Based Role Playing Game based on three parameters of the test of effectiveness, efficiency, and variation shows that the NPC using Hierarchial Dynamic Scripting method has a high effectiveness with the average fitness value of 0.73 and High efficiency by achieving an average turn-point value of 6 against all scenario tactics in this study. In addition, testing the value of break even point yields the best value of 0.5 to get a good level of NPC adaptability.
Analisis Sentimen Tingkat Kepuasan Pengguna Penyedia Layanan Telekomunikasi Seluler Indonesia Pada Twitter Dengan Metode Support Vector Machine dan Lexicon Based Features Umi Rofiqoh; Rizal Setya Perdana; Mochammad Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sentiment analysis is a part of research from Text Mining which is usefull to classify text documents contained opinion based on sentiment. Text document that is used in research comes from Twitter from people's opinion about cellular telecommunication service provider. The used method is Support Vector Machine with using Lexicon Based Features as its feature renewal instead of using TF-IDF features. The used data in this research is 300 data which divided into two types of data with ratio 70% for training data and 30% for testing data. The result of system accuracy that is obtained from sentiment analysis using Support Vector Machine and Lexicon Based Features method is 79% using degree value 2, constant learning rate value 0.0001, and maximum iteration is 50 times. While sentiment analysis system without using Lexicon Based Features is resulting accuracy at 84% with the same parameter values.
Prediksi Jumlah Permintaan Koran Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation Nabilla Putri Sakinah; Imam Cholissodin; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In the era of globalization, community needs for information is increasing by years. This can be seen from the behavior of the community in responding to everything, both global and national. The quantity of media provided convenience for the community to get information actually. Print media is one of media which has actuality and accuracy which can be trusted. One example of media is print media or newspaper. Newspaper is information tool and educational tool which until nowstill useful for every community. There are many forecasting methodthat have been used to predict which is proven in some forecasting and providing the good result, for example forecasting of water consumption, rainfall consumption, the exchange rate of dollar and forecasting electrical load. In accordance with the tests conducted using the data sales of Radar Madura in 2015, resulted the best iterations is 200, and the value of learning rate is 0.6, and the test of training data and test data yields the best value of training data is 100 and test data 10. With error rate 0.0162.
Penerapan Metode K-Means-ACO Untuk Pengelompokan Biji Wijen Berdasarkan Sifat Warna Cangkang Biji Pangestu Ari Wijaya; Rekyan Regasari Mardi Putri; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 4 (2018): April 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sesame is one kinds of the groceries that produce vegetable oil. Nowadays, the needs of sesame is increasing so it is necessary to pick a good quality in producing sesame. To conduct sesame plants crossing, the color of sesame seed shell is very infuential on its quality. Several previous studies used in this research has been done to cluster sesame seed with qualitative and quantitative method. The qualitative method in this research is conducted by field observation while the quantitative method is conducted by processing the sesame data from measurement result by using chromameter which resulted of an L*, a* and b* color. Several previous studies has successfully done the clustering by using qualitative method namely IWOKM, PSOKM and GAKM method. This study will categorize and compare the result of sesame data with same of data by using K-Means-ACO method with the previous method. From several journals, the method is proved that K-Means-ACO method has optimal results because in the analysis step combined the optimization and clustering algorithm method. Based on the test results of the K-Means-ACO method compared with the previous method, the good result of clustering sesame seed based on the color of the seed shell. It is proven by the grouping result is 233:58. After all, this research could be concluded that the K-Means-ACO method could be used as the alternative method to conduct the sesame seed classification based on its seed shell color.
Seleksi Fitur Dengan Particle Swarm Optimization Untuk Pengenalan Pola Wajah Menggunakan Naive Bayes (Studi Kasus Pada Mahasiswa Universitas Brawijaya Fakultas Ilmu Komputer Gedung A) Satria Habiburrahman Fathul Hakim; Imam Cholissodin; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 10 (2017): Oktober 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The Presence system of students in the Faculty of Computer Science, Brawijaya University is still using the manual system that is very prone to be misused by the students as entrusted that presence to his friend. Therefore we need a system that has been digitized and also fast in finding solution problem. Optimization method is a method of searching for faster solutions. For this time the researchers is using the Particle Swarm Optimization (PSO) method, that method was inspired by the social behavior of bird movements in their daily lives. While the method of classification is a method that is closely related to the probability hypothesis. So there are 2 methods and have different functions in facial recognition at the student presences where PSO here is as a feature selection and Naive Bayes here as a classification engine as well as a function to get fitness. In the test results obtained that iteration with the best total fitness value is on the number of particles 38 with the highest total fitness is 13,38, then on testing the effect of the number of iterations obtained the conclusion that the largest total fitness is at iteration 190 is 36,799, in other words the greater of iteration the fitness is also better and the last test is on testing for the weight of inertia is 1,2 with the highest total fitness result is 1,588.
Klasifikasi Penyakit Kulit Pada Manusia Menggunakan Metode Binary Decision Tree Support Vector Machine (BDTSVM) (Studi Kasus: Puskesmas Dinoyo Kota Malang) Dyan Dyanmita Putri; Muhammad Tanzil Furqon; Rizal Setya Perdana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The skin is an organ in the human body is very important because it lies on the outside of the body that serves to receive stimuli such as touch, pain and other influences from the outside. Skin disease is one of the most common diseases in tropical countries such as Indonesia. The lack of knowledge about the type of skin disease and do not know how to prevent it cause a person can get acute skin disease. So with the help of computer technology is expected to attack the skin of the human body can be detected early and it can minimize the occurrence of more dangerous diseases. This research aims to determine the classification of skin diseases in humans using the method of Binary Decision Tree Support Vector Machine (BDTSVM) Based on the test results obtained the best accuracy of 97.14% with SVM parameter test that is the value of λ (lambda) = 0,5, C (complexity) = 1, constant γ (gamma) = 0,01, and itermax = 10.
Penerapan Sentimen Analisis Acara Televisi Pada Twitter Menggunakan Support Vector Machine dan Algoritma Genetika sebagai Metode Seleksi Fitur I Made Budi Surya Darma; Rizal Setya Perdana; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Rating is one approach method that can be used to find out about audience satisfaction of a TV show. In Indonesia, rating was calculated by using AGB Nielsen services. However, rating that AGB Nielsen produced was based on the people watching bahavior in 10 major cities in Indonesia. Therefore, rating in Indonesia requires another method to get the watching behavior of the whole people in Indonesia. Twitter, can be used to get Indonesia people watching behavior. Through the published tweets, it can be applied the process of extracting information by using classification techniques to get the opinions. One of the classification techniques that can be applied to text categorization is the Support Vector Machine (SVM) it`s suitable for multiple dimension data. By optimizing the features that will be used, it can provide optimal results with less features used. One of the feature selection methods that can be applied to SVM is the genetic algorithm (GA). System calculates the rating, based on positive and negative sentiments about the TV show and divided by the population of the tweet used. The rating comparison test that produced by AGB Nielsen and system shows an average error value of 0.562. In testing the accuracy before and after the feature selection method is applied, showed results with average error value 0.62%.
Rancang Bangun Low Power Sensor Node Menggunakan MSP430 Berbasis NRF24L01 Rizky Putra Pratama; Sabriansyah Rizqika Akbar; Adhitya Bhawiyuga
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 3 (2017): Maret 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Communication technology is now very grown even more with their wireless technology. This technology is very popular due to their ability to transmit data or information wirelessly. One of the utilization of wireless technology is the Wireless Sensor Network. In the Wireless Sensor Network, the data transmission between sensor nodes is highly dependent on the power source in the form of batteries which have a limited capacity, this can cause problems because the sensor nodes are required to be able to survive as long as possible. To overcome the problem of resource savings, research on low-power mode in Wireless Sensor Network technology that is by applying the mechanism of sleep mode at the sensor node that resources can the battery last longer. In accordance with the above problems, the author makes the design of sensor nodes using MSP430 microcontroller which will regulate all the processes on the node, including regulating the use sleep mode as a way of saving power supply. For data transmission, the system uses NRF24L01 as communication modules. The data is sent in the form of calculation of the temperature of the LM35 temperature sensor. The results of the study in terms of the use of power-saving sleep mode can be used by the nodes. This is evidenced by the saving power used by the nodes without using sleep mode with nodes that use sleep mode reaches 33.31%. The accuracy of data transmission in this study was divided into two, the data transmission without hindrance average accuracy of data transmission up to 100%. While the data transmission with the hindrance an average accuracy of the data transmission only reached 87.7%.
Pengembangan Aplikasi Pembelajaran Bahasa Isyarat Berbasis Android Tablet Maharoni Hendra Pradikja; Herman Tolle; Komang Candra Brata
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sign language is used in the daily lives of people with hearing and speech impaired. One of the difficulties is how the deaf can inform the sign language used and can be understood by people who can hear so deaf people can communicate, interact, socialize, make friends, and dialogue occurs in everyday social. Applications "PemBais" designed to help reduce the difficulties faced by the deaf and mute. Applications "PemBais" This provides a method of learning Indonesian Sign Language for the deaf and speech impaired quickly and practical for using the means of Android-based applications on smartphone devices. Applications Functional testing has been done with each of the test cases have been tested and properly, with the result declared all valid. Usability testing is obtained from a very satisfactory result for analysis of the application "PemBais" to achieve an average score of 87,18%.
Evaluasi Manajemen Risiko Teknologi Informasi Menggunakan Framework COBIT 5 (Studi Kasus : PT. Kimia Farma (Persero) Tbk - Plant Watudakon) Novia Dwi Setyaningrum; Suprapto Suprapto; Ari Kusyanti
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Information technology is almost implemented in all companies, including the PT.Kimia Farma plant Watudakon this company has implemented information systems based on Enterprise Resource Planning (ERP). Using information systems certainly has many risk opportunities. In the event of a problem will have an overall impact. As is often the case, the system issues on the part of the warehouse, then the process of receiving data information from the warehouse for finance will be disrupted, which may occur due to server down or other problems. Therefore, risk management is required to manage all possible risks. So this research was conducted to determine the value of capability level by evaluating the risk management PT.Kimia Farma using COBIT 5 framework on domain EDM03 (Ensure Risk Optimization) and APO12 (Managed Risk). The data were collected by questionnaire, observation and interview. From the data, we get the capability level for EDM03 at level 2 and APO12 at level 1. After knowing the level of risk the next step is to conduct a risk assessment to determine risks that are still within the company's risk appetitte, then to determine risk mitigation measures. From the results of the two analyzes will be a reference as the preparation of recommendations. Proposed recommendations such as the preparation of risk profile documents, establishing management to manage risk.

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