IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
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Hospital Nurse Scheduling Optimization Using Simulated Annealing and Probabilistic Cooling Scheme
Get PDFNurse’s scheduling in hospitals becomes a complex problem, and it takes time in its making process. There are a lot of limitation and rules that have to be considered in the making process of nurse’s schedule making, so it can fulfill the need of nurse’s preference that can increase the quality of the service. The existence variety of different factors that are causing the nurse scheduling problem is so vast and different in every case. The study is aimed to develop a system used as an equipment to arrange nurse’s schedule. The working schedule obtained will be checked based on the constraints that have been required. Value check of the constraint falsification used Simulated Annealing (SA) combined with cooling method of Probabilistic Cooling Scheme (PCS). Transitional rules used cost matrix that is employed to produce a new and more efficient state. The obtained results showed that PCS cooling methods combined with the transition rules of the cost matrix generating objective function value of new solutions better and faster in processing time than the cooling method exponential and logarithmic. Work schedule generated by the application also has a better quality than the schedules created manually by the head of the room
Motion Detection and Face Recognition for CCTV Surveillance System
Get PDFClosed Circuit Television (CCTV) is currently used in daily life for a variety purpose. Development of the use of CCTV has transformed from a simple passive surveillance into an integrated intelligent control system. In this research, motion detection and facial recognation in CCTV video is done to be a base for decision making to produce automated, effective and efficient integrated system. This CCTV video processing provides three outputs, a motion detection information, a face detection information and a face identification information. Accumulative Differences Images (ADI) used for motion detection, and Haar Classifiers Cascade used for facial segmentation. Feature extraction is done with Speeded-Up Robust Features (SURF) and Principal Component Analysis (PCA). The features was trained by Counter-Propagation Network (CPN). Offline tests performed on 45 CCTV video. The test results obtained a motion detection success rate of 92,655%, a face detection success rate of 76%, and a face detection success rate of 60%. The results concluded that the process of faces identification through CCTV video with natural background have not been able to obtain optimal results. The motion detection process is ideal to be applied to real-time conditions. But in combination with face recognition process, there is a significant delay time
An Optimal Stock Market Portfolio Proportion Model Using Genetic Algorithm
Get PDFTo reduce the amount of loss due to investment risk, an investor or stockbroker usually forms an optimal stock portfolio. This technique is done to get the maximum return of investment on shares to be purchased. However, in forming a stock portfolio required a fairly complex calculations and certain skills. This work aims to provide an alternative solution in the problem of forming the optimal and efficient stock portfolio composition by designing a system that can help decision making of investors or stockbrokers in preparing stock portfolio in accordance with the policy and risk investment. In this work, determination of optimal stock portfolio composition is constructed by using Genetic Algorithm. The data used in this work are the 4 selected stocks listed on the LQ45 index in 2017. Meanwhile, the calculation of profit and loss rate utilizes a single index model theory. The efficiency of the algorithm has been examined against the population size and crossover and mutation probabilities. The experimental results show that the proposed algorithm can be used as one of solutions to select the optimal stock portfolio
Local Triangular Kernel-Based Clustering (LTKC) for Case Indexing on Case-Based Reasoning
Get PDFThis study aims to improve the performance of Case-Based Reasoning by utilizing cluster analysis which is used as an indexing method to speed up case retrieval in CBR. The clustering method uses Local Triangular Kernel-based Clustering (LTKC). The cosine coefficient method is used for finding the relevant cluster while similarity value is calculated using Manhattan distance, Euclidean distance, and Minkowski distance. Results of those methods will be compared to find which method gives the best result. This study uses three test data: malnutrition disease, heart disease, and thyroid disease. Test results showed that CBR with LTKC-indexing has better accuracy and processing time than CBR without indexing. The best accuracy on threshold 0.9 of malnutrition disease, obtained using the Euclidean distance which produces 100% accuracy and 0.0722 seconds average retrieval time. The best accuracy on threshold 0.9 of heart disease, obtained using the Minkowski distance which produces 95% accuracy and 0.1785 seconds average retrieval time. The best accuracy on threshold 0.9 of thyroid disease, obtained using the Minkowski distance which produces 92.52% accuracy and 0.3045 average retrieval time. The accuracy comparison of CBR with SOM-indexing, DBSCAN-indexing, and LTKC-indexing for malnutrition diseases and heart disease resulted that they have almost equal accuracy
Sentiment Analysis of Movie Opinion in Twitter Using Dynamic Convolutional Neural Network Algorithm
Get PDFMovie has unique characteristics. When someone writes an opinions about a movie, not only the story in the movie itself is written, but also the people involved in the movie are also written. Opinion ordinary movie written in social media primarily twitter.To get a tendency of opinion on the movie, whether opinion is likely positive, negative or neutral, it takes a sentiment analysis. This study aims to classify the sentiment is positive, negative and neutral from opinions Indonesian language movie and look for the accuracy, precission, recall and f-meausre of the method used is Dynamic Convolutional Neural Network. The test results on a system that is built to show that Dynamic Convolutional Neural Network algorithm provides accuracy results better than Naive Bayes method, the value of accuracy of 80,99%, the value of precission 81,00%, recall 81,00%, f-measure 79,00% while the value of the resulting accuracy Naive Bayes amounted to 76,21%, precission 78,00%, recall 76,00%, f-measure 75,00%
An Expert System Using Certainty Factor for Determining Insomnia Acupoint
Get PDFIn treating insomnia patients, acupuncturists who are not always in their clinics trust their patients to their assistants but because of their assistants limited knowledge, their assistants can not determine the right acupoints. Therefore, an application that able to store their knowledge about insomnia disease treatment is needed so that their assistants can handle the patients like they do.In this research, an expert system application using certainty factor method to determine the acupoint in dealing with insomnia disease was built. This research used certainty factor to accommodate uncertainty about symptoms and rules. The mechanism of certainty factor on symptoms used a measure of increased belief (MB) and a measure of increased disbelief (MD).The built expert system resulted acupoints based on symptoms experienced by insomnia patients. Accuracy value produced by the system that used certainty factor for determining acupoint dealing with insomnia is 0.933. It showed that the acupoint produced by the system is 93.3% relevant according acupuncturist expertise in treating insomnia patients
Prioritization of Natural Dye Selection In Batik Tulis Using AHP and TOPSIS Approach
Get PDFBatik is the most popular tradisional cloth made using the wax-resist dyeing technique. The fabric is found in various city in Indonesia, one of them is Lasem which popular with hand-drawn batik is called Batik Tulis Lasem. Natural dye selection is one of the most important priority for the batik tulis craftsmen. Natural dyes made from leaves and flowers. Proper selection of natural dye will impact on color, motif, and brightness on batik tulis fabric. AHP and TOPSIS methods can be used together to selecting natural dye especially the batik tulis lasem. AHP method is used in determining the weights of the criteria, and then TOPSIS method is needed for determining the best alternative on natural dye of batik tulis. According to the result of research, TOPSIS method is used to determine the priority of alternative on natural dye. Based on calculation with TOPSIS method , the fourth alternative (A4 is kayu secang) get priority value is 0.8478, so kayu secang is recommended to the craftsmen that will used this material as the natural dye
Klasifikasi Nilai Kelayakan Calon Debitur Baru Menggunakan Decision Tree C4.5
Get PDFIn an effort to improve the quality of customer service, especially in terms of feasibility assessment of borrowers due to the increasing number of new prospective borrowers loans financing the purchase of a motor vehicle, then the company needs a decision making tool allowing you to easily and quickly estimate Where the debtor is able to pay off the loans.This study discusses the process generates C4.5 decision tree algorithm and utilizing the learning group of debtor financing dataset motorcycle. The decision tree is then interpreted into the form of decision rules that can be understood and used as a reference in processing the data of borrowers in determining the feasibility of prospective new borrowers. Feasibility value refers to the value of the destination parameter credit status. If the value of the credit is paid off status mean estimated prospective borrower is able to repay the loan in question, but if the credit status parameters estimated worth pull means candidates concerned debtor is unable to pay loans..System testing is done by comparing the results of the testing data by learning data in three scenarios with the decision that the data is valid at over 70% for all case scenarios. Moreover, in generated tree and generate rules takes fairly quickly, which is no more than 15 minutes for each test scenari
Analisis Perbandingan Algoritma Perencanaan Jalur Robot Bergerak Pada Lingkungan Dinamis
Get PDFDevelopment of technology and complexity of an environment (dynamic environtment), the use of algorithms in path planning becomes an important thing to do, problem to be solved by the path planning is safe patch (collision-free), second is the distance traveled, ie, the path length is generated from the robot start position to the current target position and the thirdtravel time, ie, the timerequired by the robot to reached its destination.this research uses ACO algorithm and A-star Algorithm to determine the influence of obstacles (simple environment) and also differences in the pattern of the target motion (linier and sinusoidal)on the ability of the algorithm in pathplanning for finding the shortest path. The test results show that for a simple environtment where the state of target and obstacles still static,the resukt that A-star algorithm is betterthan ACO algorithm both in terms of travel time and travel distance. Testing with no obstacles, seen from the distance travelled differences obtained of 0,57%, whereas for testing with obstacles difference of 9%. Testing in a complex environtment where the targets and obstacles which movesdinamically with a certain pattern, from the three environmental conditions that has been tested, ACO algorithm is better than A-star algorithm where the ACO algorithm can find a path with optimal distance or the sortest distance
Platform Gamifikasi untuk Perkuliahan
Get PDFGamification in lecturing has a lot of variety designs. A flexible platform is needed for that matter. This research aims to develop a gamification platform for lecturing that flexible, has a good performance and acceptable by users.Generic Gamification Platform (GGP) concept is used to develop platform. GGP is a kind of gamification solution that applies service oriented architecture Architecture (SOA) principles and puts gamification components (data, logic and rewards) and Information System (IS) separately. The platform has some capabilities such as able to manage game mechanics, actions, tasks and rules. The other platform capabilities are able to auto generate rules and to be integrated to IS.The results of tests show that a gamification platform for lecturing can be developed. The platform has a good level of flexibility, has a good performance, and acceptable by users (5 lecturers and 2 non-lecturers but well knowing on lecturing activities). Its flexibility level is 85%. Its average of response time on event execution is lower than 336ms. Its System Usability Scale (SUS) average score is 60 and its acceptability range in low marginal