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INDONESIA
Jurnal Infra
Published by Universitas Kristen Petra Surabaya
ISSN : -     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
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Articles 58 Documents
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Search results for , issue "Vol 8, No 1 (2020)" : 58 Documents clear
Prediksi Skor Pertandingan Sepak Bola menggunakan Neuroevolution of Augmenting Topologies dan Backpropagation Welly Winata; Lily Puspa Dewi; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Football, or soccer is the most popular sport in the world. Whatmakes football special is the uncertainty and unpredictable result.There are a lot of factors that can affect the result of a footballmatch, such as strategy, skill, or even luck. Therefore, predictingthe outcome of football match can be challenging yet interestingtask.This research started with neuroevolution of augmentingtopologies, which useful to find the structur of a neural network.Then, the network produced by NEAT is optimized usingbackpropagation. Player ratings, team ratings, and playerposition are used as features of neural network.The hightest accuracies achieved are 81.5% on the final resultpredicting, and 48% on score predicting, were obtained throughNEAT network that optimized by backpropagation, with playerratings, team ratings, and total position from each sectors areused as features.However, on real life test, the player and team ratings areunknown. To calculate the player and team ratings, averagesmethods are used. Unfortunately, the network performed poorlycausing the accuracies to dropped significantly. Lack ofconsistency from player ratings are believed to be the mainproblem on calculating the player and team ratings.
Analisis Kinerja Genetic Algorithm yang diakselerasi untuk Travelling Salesman Problem pada Platform Multicore CPU dan CUDA Alexander Thomas Kurniawan Pratomo; Henry Novianus Palit; Darian Gunamardi
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Advancement in technology brings about both new challenges and opportunities. One of which is the opportunity to accelerate an algorithm which usually took a very long time to finish. Genetic algorithm is one such algorithm that can be accelerated using these advancements. Certain ways to accelerate this algorithm is done by tuning the parameters, but these methods are usually unable to retain the quality that is obtained from previous, non-accelerated method. This research applies parallel computing using the multicore technology of CPU and GPU to accelerate genetic algorithm without any changes to the parameters. The purpose of the research is to analyze the differences in performance of the algorithm upon being accelerated with the technologies. The technologies used are CUDA platform and OpenMP API for GPU and CPU respectively. Aside from the technology itself, choosing the algorithm segments on which the implementation is done will also greatly affect the performance of the algorithm. According the testing results, Genetic Algorithm can be accelerated with parallelization using either OpenMP with CPU or CUDA with GPU.
Menggunakan SPADE Algorithm Untuk Sistem Rekomendasi Film Aldy Noah; Rolly Intan; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Nowadays, internet has become main thing in everyday life. This cause the consumption of entertainment media can be done anywhere and everywhere. One of the entertainments we enjoy is movie. With the increasing popularity of streaming media, movie fans also increase.Because of the increase of movie fans, the need of recommendation system that can recommend movie to its user also rise. System recommendation for movie is a complicated thing because of considerable amount of movie and movie fans.Sequence pattern mining is one of data mining method that can be used to gain frequent pattern from a set of data. Frequent pattern is a series of items that forms a pattern in a set of data. SPADE is one of the methods to find frequent sequence. The advantage of using SPADE is that speed in which SPADE can find frequent sequence in a data set. The benefit of using SPADE algorithm is in the speed of the algorithm to find frequent sequence. The resulting frequent sequence then can be used as a basis for recommendation to the user.
Power Meter Monitoring Dengan Mobile Apps dan Metode Direct Calculation Kevin Wibisono Lokananto; Resmana Lim; Alexander Setiawan
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Electricity is a basic need that is still not optimal in Indonesia, and  the waste of electricity in Indonesia which is quite large, therefore with this tool can help to save electrical energy, but it can also monitor the burden attached to the tool can help manage financial because this tool displays total usage and total price.The tool that I made consisted of several main components such as the Arduino microcontroller, the ZMPT101B voltage sensor module, the ACS712 30A current sensor module. From the installed load, the data in the form of voltage and current will be read by the sensor and sent to the microcontroller for calculation.The calculation results will be uploaded to Firebase, which later will be fetched and showed by the Android application, The application will also be equipped with other features such as, on-off switch, reset, history,setkwh and total cost .
Pengenalan Intent pada Natural Language Understanding Berbahasa Indonesia dengan Menggunakan Metode Convolutional Neural Network Daniel Adi; Leo Willyanto Santoso; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

To keep up with technological developments and people behavior, intelligent bot has become part of the business world which help them maintain good relation with their customer. Unfortunately, resource for intelligent bot in Indonesian language is very scarce compared to High Resource Language like English. Therefore further research about Natural Language Understanding in Indonesian language is needed. We use Convolutional Neural Network method to train our model. Model consist of embedding layer, convolutional layer, max pooling, flatten, dropout, and softmax layer. In the process of making model, there are many variable that can be tested such as dropout, number of filter, size of filter, etc. This research show that the amount and quality of data for each category can affect how a model understand the feature of each category which affect the overall precision. The quality of word2vec, one of the most important resource in the model can give significant impact on precision. The size of dropout can affect how the model understand the important feature of data. From various tests, we found that the best precision is 93 %. 
Aplikasi Pemetaan Penyakit Demam Berdarah di Surabaya dengan Metode Neural Network Multilayer Perceptron Ivan Enrico Widodo; Andreas Handojo; Siana Halim
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Dengue fever is a disease that caused by dengue virus. This virus is transmitted into human body through mosquito bites, aedes aegypti and aedes albopictus. This kind of mosquito are mostly found in subtropical and tropical regions, including in Indonesia. Almost every year, cases of dengue fever occur in Indonesia. Government’s effort to prevent dengue fever have been carried out. Following the development of technology, the government began to save patient data through their own health institution, the community health centers.However, the stored data cannot produce useful information instantly. The data must go through series of processes first before it can become informastion. Data processing methods that can be used are neural network. Because neural network have one function that is prediction. Then, the prediction data can be entered into a digital map for the mapping process. Mapping with digital map that have colors and display the level of sufferers can be said to produce useful information. The result of this program is a website that can display maps in the form of digital map, with data obtained based on prediction results using neural network method. So that later this website can help the government to take preventive measures againts dengue fever.
Pengenalan Alfabet Bahasa Isyarat Tangan Secara Real-Time dengan Menggunakan Metode Convolutional Neural Network dan Recurrent Neural Network Devina Yolanda; Kartika Gunadi; Endang Setyati
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Sign language is one of the communication tools commonly used by people with disabilities. The alphabet sign language is a basic tool used by teachers to teach people with hearing impairment and speech impairment to recognize basic alphabet letters. However, many people find it difficult to communicate with these groups because of a lack of community insight into hand sign language. Research on sign language has experienced much progress in processing static images but is still experiencing problems due to difficulties in processing dynamic images / video given that most of the sign language is represented by body, hand, and face movements.This study uses Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) methods with video input. The CNN method will be used as a feature extraction in the spatial feature while the RNN is tasked to tolerate between frames extracted by CNN on the temporal feature.The final result to be displayed is in the form of text alphabet which is the result of the recognition of the sign language alphabet. Based on the test carried out, obtained an average accuracy value of  60.58% for all letters while real-time testing has failed because the technology used cannot sustain the architecture created.
Sistem Rekomendasi Film Menggunakan Integrated Kohonen K-Means clustering Joshua Maximillian; Henry Novianus Palit; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

With the development of the film industry, more and more films can be watched. But because there are too many films that can be watched that cause users to be confused in finding films that match what they like. So there is a movie recommendation system to help user. The movie recommendation system itself has various ways to produce movie recommendations that users might like.The movie recommendation system using Integrated Kohonen K-Means Clustering is one of the Data Mining methods that can be used in recommending films. Intergrated Kohonen K-Means Clustering compared to Kohonen Self Organizing Maps, and also K-Means Clustering in recommending films.According to the result of Integrated Kohonen K-Means Clustering to know how many K cluster that is optimal for K-Means Clustering use the Elbow Method. To know how good the cluster you produce use Silhouette Coefficient and the score -0.389 for the Integrated Kohonen K-Means Clustering. The Mean Reciprocal Rank produced by Integrated Kohonen K-Means Clustering which score is 0.362 is better than K-Means Clustering which score is 0.003 and Kohonen Self Organizing Maps which score is 0.002.

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