Jurnal Teknik Informatika dan Sistem Informasi
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Rancang Bangun Edugame "History of Shodanco Supriyadi": Sejarah Perlawanan Pasukan PETA Blitar Terhadap Jepang
Get PDFGames are not only for entertainment but games can be a means of learning. Historical subjects are often considered boring and uninteresting lessons because there are no innovations to attract students' curiosity. Therefore, a learning media was created and an introduction to the history of the resistance of the Blitar PETA forces through an adventure edugame. The methodology used is an iteration with three increments, each of which consists of the analysis, design, code, and test phases. The game design uses Unity 3D as a tool. Tests carried out include integration testing, system testing, and acceptance testing. From the results of these tests it was found that the edugame application that had been developed was able to assist students in introducing the history of the resistance figure PETA Blitar named Supriyadi
Implementasi Forward Chaining dan Metode Simpleks untuk Menentukan Ransum Unggas yang Ekonomis
Get PDFPoultry need food to maintain their lives and to produce. To meet the needs of these nutritional elements, poultry eat from various types of food. Because there is no single food ingredient that contains a complete nutritional element, so we need a variety of appropriate and balanced food ingredients to meet nutritional needs. This can be done by choosing cheap food ingredients without ignoring the quality of the nutritional content that is adjusted to the type and age of poultry. To solve the above problems, an expert system with a forward chaining method can be used to determine the nutritional needs and nutritional content of food ingredients, while linear programming with the simplex method is used to determine the combination of poultry feed-forming ingredients that meet economical poultry nutritional needs. The combination of the forward chaining method and the simplex method can accelerate the preparation of combinations of food ingredients, so that the resulting application can provide a solution in making decisions for the selection of food ingredients forming ration effectivel
Implementasi Deteksi Warna Pada Game Finding Color Menggunakan Ekstraksi Fitur Warna dan Fuzzy Decision Tree
Get PDFRecognizing color is an ability that must be trained from an early age. But the ability to recognize color in early childhood is still low. One of the most preferred media by children is games. Android mobile games have the advantage of providing interactive multimedia, challenges, and rewards. Finding Color games can be used to help children play actively in exploring and observing colors in the surrounding environment because they can detect colors using the camera. The stages in color detection in games are feature extraction and color classification. Color feature extraction will get the color value at the selected pixel coordinates on the screen. The color classification uses fuzzy decision tree ID3. The test results of the application of color feature extraction produce an accuracy value of 100%. The fuzzy decision tree classification is evaluated using a confusion matrix, resulting in an accuracy value in outdoor light conditions of 94.4%. There is an increase of 4.4% compared to indoor conditions.
Keywords— Color Detection; Color Feature Extraction; Fuzzy Decision Tree; Game; Mobile Android
 
Prediksi Pencapaian Target Kerja Menggunakan Metode Deep Learning dan Data Envelopment Analysis
Get PDFAlong with the rapid development of technology, especially in the computer field, several methods have been developed for target setting. Data Envelopment Analysis (DEA) is commonly employed to analyze efficiency levels based on historical data with static targets. Data Envelopment Analysis results in a low level of efficiency against the use of static targets. A new target setting solution is needed to handle dynamic targets. Based on the need, we propose a method to predict more realistic dynamic targets using Deep Learning Long Short Term Memory (LSTM) approach from the results of the Data Envelopment Analysis (DEA). This study leads to a prediction model with 71.2% average accuracy.
 
Pengaruh Metode Penyeimbangan Kelas Terhadap Tingkat Akurasi Analisis Sentimen pada Tweets Berbahasa Indonesia
Get PDFNowadays internet access is getting easier to get. Because of the ease of access to the internet, almost all internet users have social media. Social media is widely used by users to call out their opinions or even to make complaints about a matter and also discuss a topic with other social media users. From many existing social media, one that is popularly used for that activity is Twitter. Sentiment analysis on Twitter has become possible because of the activities of these Twitter users. In this research, the authors explore sentiment analysis with bag-of-words and Term Frequency Inverse Document Frequency (TF-IDF) features extraction based on tweets from Indonesian Twitter users. The data obtained is in imbalanced condition, so that it requires a method to overcome them. The method for overcoming imbalanced dataset uses a resampling approach which combines over and under sampling strategies. The results of sentiment analysis accuracies with Naïve Bayes and neural networks before and after input data resampling are also compared. Naïve Bayes methods that will be used are Multinomial Naïve Bayes and Complement Naïve Bayes, while the Neural Network architecture that will be used as a comparison are Recurrent Neural Networks, Long Short-Term Memory, Gated Recurrent Units, Convolutional Neural Networks, and a combination of Convolutional Neural Networks and Long Short-Term Memory. Our experiments show the following harmonic scores (F1) of the sentiment analysis models: the Multinomial Naïve Bayes F1 score is 55.48, Complement Naïve Bayes is 51.33, Recurrent Neural Network is 75.70, Long Short-Term Memory is 78.36, Gated Recurrent Unit is 77.96, Convolutional Neural Network is 76.12, and finally the combination of Convolutional Neural Networks and Long Short-Term Memory achieves 81.14
Pengembangan Sistem Informasi Pembelian, Penjualan dan Persediaan Motor Bekas menggunakan Analisis Fast-Slow-Non Moving
Get PDFAbstract — Motorcycle Company is engaged in selling used motorcycles, processing motorcycle inventory data to manage the optimal number of purchases and sales. Based on monthly sales data, it can be predicted the need to buy a used vehicle to the seller. Through FSN (Fast-moving, Slow-moving and Non-moving) analysis is to consider quantity, the rate of consumption of item and how often they are issued or used. The results of analysis can be used to guide the decision of the right amount of inventory to be placed in the warehouse, the frequency to buy or even delete certain items in stages. In order for the FSN analysis to be carried out successfully, it is necessary to analyze the items based on their respective categories, within a certain period of time. The purpose of this research is to design and build an information system for the sale of used motor vehicles, purchase of used motorcycles by considering the optimal inventory using the FSN method.
Keywords — Inventory Management, Selling-buying Used Motorcycle, Fast-moving, Slow-moving and Non-moving Anylysis
Analisis Arsitektur Bisnis Sistem Penerimaan Mahasiswa Baru dan Akademik
Get PDFAbstract — University in Bandung already has an IT Blueprint in 2009 and has successfully implemented several integrations in the financial system for academics. However, until 2020 there was no integration between the new student admission system and the academic system. Therefore, through this research, preparation and analysis were carried out to then proceed with the design in order to gradually document the IT Blueprint. And on this occasion discussed the preparation and analysis of the new student admission system and the academic system. The framework used is TOGAF 9.1 and TOGAF 9.2, namely in the preparation stage to phase B Architecture Vision. This research has been conducted from June 2019 to August 2020 and has produced a Value Chain Diagram, Stakeholder Map, and Solution Concept Diagram which will become the basis for phase B. The resulting Value Chain Diagram consists of the Value Chain Diagram for the admission system and the Value Chain Diagram for the academic system. In each diagram discusses the main activities and support activities of each system. The stakeholder map will explain each stakeholder involved in the admission system and the academic system and their relationship to architectural design. The Solution Concept Diagram illustrates the concept diagram as a solution architecture vision for admission and the academic system at University.
Keywords— analysis; Enterprise Architecture; preliminary, Architecture Vision, TOGA
IMPLEMENTASI BALANCE SCORECARD DALAM DASHBOARD KINERJA SUPPLIER. STUDI KASUS: ONLINE TRAVEL AGENT
No full textTujuan dari penelitian adalah mengembangkan dashboard kinerja supplier untuk kebutuhan online travel agent (OTA). Dashboard kinerja adalah aplikasi sistem informasi yang menyajikan tampilan visual dari informasi penting, yang diperlukan untuk mencapai satu atau beberapa tujuan, dengan mengkonsolidasikan dan mengatur informasi dalam satu layar (single screen), sehingga kinerja organisasi dapat dimonitor dalam sekali waktu. Klikhotel.com sebagai sebuah perusahaan online travel agent yang memiliki lebih dari 2000 supplier membutuhkan dashboard kinerja supplier berdasarkan metode balanced scorecard untuk memudahkan analisa kinerja supplier secara cepat dan akurat. Target diharapkan adalah dashboard bisa menggerakkan semua personil perusahaan untuk bekerja secara sinergis mencapai target perusahaan. Selain itu, sistem ini juga diharapkan dapat meningkatkan kepuasan supplier, sebagai partner penting dari OTA
Pengenalan Alfabet American Sign Language Menggunakan K-Nearest Neighbors Dengan Ekstraksi Fitur Histogram Of Oriented Gradients
Get PDFSign Language use to communicate to people with dissabilities. American Sign Language (ASL) one of popular sign language. Histogram of Oriented Gradient (HOG) can be use as feature extraction. Then feature stored in database. K-Nearest Neighbor use to measure distance between feature train and feature test. There are three distance use in this paper consist of Euclidean Distance, Manhattan Distance and Chebychev Distance. The best result are 0,99 when using Euclidean Distance and Manhattan Distance with k=3 dan k=
Algoritma Pemilihan Objek pada Interaksi Antarmuka Berbasis Titik Pandang Mata
Get PDFEye tracking provides an alternative input modality to control the interactive contents in computers, particularly in assistive technology and public display. Instead of fixational eye movement, smooth pursuit eye movement has been used for object selection in gaze-based interactive applications. However, some previous works did not consider various similarity measures to match trajectory of eye movement and the presented dynamic stimulus. Furthermore, there was no correction towards the drift of eye movement during object selection. Hence, gaze-based object selection based on smooth pursuit eye movement is still inaccurate and unstable. To fill the research gaps, we proposed a novel approach for accurate gaze-based object selection using linear regression for eye movement’s drifting correction. We measured accuracy, success timing, and stability of object selection to validate performance of the proposed method. From the experimental results, object selection could be performed without the usage of chinrest using Euclidean distance, moving average and linear regression in gaze-based interfaces. The usage of chinrest did not give significant effect on accuracy, success timing and stability of object selection in gaze-based interfaces. The use of linear regression for predicting gaze points and correcting drift of eye movement has improved overall performance of object selection .In future, our results maybe used as a guideline for developing more accurate and more stable interactive applications based on smooth pursuit eye movement