Jurnal Teknologi dan Sistem Komputer最新文献

{"title":"Intelligent System for Determining Parking Locations in Campus Areas Using Fuzzy Logic Based on Internet of Things","authors":"Dody Ichwana, S. D. Saputra, S. Ekariani","doi":"10.14710/jtsiskom.7.2.2019.64-70","DOIUrl":"https://doi.org/10.14710/jtsiskom.7.2.2019.64-70","url":null,"abstract":"The increasing use of vehicles at campus locations makes it more difficult to find an empty parking lot. This paper develops a system for determining parking locations on campus areas using cloud-based fuzzy logic and Internet of Things (IoT). NFC is used to confirm the order code of the location that has been generated by the system. At the parking location, a sensor is installed to detect parking availability. The concept of IoT has been applied to build this system. Applications on smartphone devices are used for reservations at desired parking locations via the internet. The results show that the system has been able to detect the location of empty parking lots and make reservations in the Andalas University campus environment. The application of fuzzy logic has succeeded in obtaining parking location sequences based on distance and total capacity to find the best parking location.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67028545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Manajemen Alokasi Bandwidth Layanan Internet Menggunakan Fractional Knapsack Problem","authors":"Ahmad Rizaqu Muttaqi, Sri Wahjuni, Shelvie Nidya Neyman","doi":"10.14710/JTSISKOM.7.2.2019.71-76","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.2.2019.71-76","url":null,"abstract":"The technical problems faced in e-government implemented by the Ministry of Religion of Indonesia since 2015 are minimal bandwidth requirements to provide information services and behavior of users who access entertainment sites. When peak hours occur, the congested network often occurs which becomes a significant bottleneck. This study aims to implement bandwidth management using the fractional knapsack problem method by limiting access to entertainment services. The QoS parameters used in this management are throughput, delay, and jitter. The method was tested using a paired t-test using throughput, jitter, and delay test parameters by comparing test parameters before and after bandwidth management applied. The significance value produced is between 75-85%. The method used can control the amount of traffic for each service, but on the other, hand the delay and jitter are still high. It is necessary to add additional free space to each service that can be used when needed to reduce the delay and jitter.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49641870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Algoritma Genetika untuk Optimasi Komposisi Makanan Bagi Penderita Hipertensi","authors":"A. Purnomo, Davia Werdiastu, Talitha Raissa, R. Widodo, Vivi Nur Wijayaningrum","doi":"10.14710/JTSISKOM.7.1.2019.1-6","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.1.2019.1-6","url":null,"abstract":"Hypertension can be prevented and handled by eating nutritious foods with the right composition. The genetic algorithm can be used to optimize the food composition for people with hypertension. Data used include sex, age, weight, height, activity type, stress level, and patient hypertension level. This study uses a reproduction method that is good enough to be applied to integer chromosome representations so that the search results provided are not local optimum solutions. The testing results show that the best genetic algorithm parameters are as follows population size is 15 with average fitness 20.97, the generation number is 40 with average fitness 50.10, and combination crossover rate and mutation rate are 0.3 and 0.7 with average fitness 41.67. The solution obtained is the optimal food composition for people with hypertension.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43568848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perbandingan Kinerja Block Storage Ceph dan ZFS di Lingkungan Virtual","authors":"Faza Abdani Auni Robbi, Agung Budi Prasetijo, Eko Didik Widianto","doi":"10.14710/JTSISKOM.7.1.2019.7-11","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.1.2019.7-11","url":null,"abstract":"The growth of data requires better performance in the storage system. This study aims to analyze the comparison of block storage performance of Ceph and ZFS running in virtual environments. Tests were conducted to measure their performances, including IOPS, CPU usage, throughput, OLTP Database, replication time, and data integrity. Testing was done using 2 node servers with a standard configuration of the storage system. Server virtualization uses Proxmox on each node. ZFS has a higher performance of reading and writing operation than Ceph in IOPS, CPU usage, throughput, OLTP and data replication duration, except the CPU usage in writing operation. The test results are expected to be a reference in the selection of storage systems for data center applications.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47101278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perbandingan Metode Segmentasi K-Means Clustering dan Segmentasi Region Growing untuk Pengukuran Luas Wilayah Hutan Mangrove","authors":"Tyas Panorama Nan Cerah, Oky Dwi Nurhayati, R. Isnanto","doi":"10.14710/JTSISKOM.7.1.2019.31-37","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.1.2019.31-37","url":null,"abstract":"This study aims to examine the k-means clustering and region growing segmentation methods to identify and measure the area of mangrove forests in the Southeast Sulawesi province. The image of the area of this study used Landsat 8 satellite imagery. The area of mangrove forest was carried out by calculating the number of pixels identified as mangrove forests with an area density of 900 m2/pixel. The accuracy of the two segmentation methods in calculating the area was compared based on the same area calculated by LAPAN. The overall accuracy of k-means clustering segmentation method has better accuracy, which is 59.26%, than region growing with 33.33% of accuracy. Both image segmentation methods, k-means clustering and region growing, can be used to calculate the area of mangrove forests in the Southeast Sulawesi region using Landsat 8 satellite imagery.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45532919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pengaruh Masukan Kendali Terhadap Hasil Identifikasi Parameter Pesawat Udara Konfigurasi Konvensional Matra Terbang Longitudinal","authors":"Eries Bagita Jayanti, Novita Atmasari, H. Mardikasari, Ardian Rizaldi, Fuad Surastyo Pranoto, S. Wibowo","doi":"10.14710/JTSISKOM.7.1.2019.25-30","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.1.2019.25-30","url":null,"abstract":"Parameter identification is a process to get real characteristics of the motion dynamics of an object which can then be used to build the dynamics model of the object, which has a very high level of validity and accuracy. The modeling process is usually carried out using aircraft input data and the results of existing navigation data recording. From the data, the model parameters are estimated using the simple least square method. In this study, the simulation was carried out by varying the deflection input in the control field and simulation time. The input given to the longitudinal dimension is the deflection of the elevator control field. The results of parameter identification in the Corsair A-7A plane in the longitudinal dimension indicate that the input form 3-2-1 has a smaller error value than using doublet and pulse inputs. This shows that the input form 3-2-1 is most suitable for the longitudinal dimension among the given inputs.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42388526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metode SURF dan FLANN untuk Identifikasi Nominal Uang Kertas Rupiah Tahun Emisi 2016 pada Variasi Rotasi","authors":"Adri Priadana, Ari Murdiyanto","doi":"10.14710/jtsiskom.7.1.2019.19-24","DOIUrl":"https://doi.org/10.14710/jtsiskom.7.1.2019.19-24","url":null,"abstract":"In December 2016, Bank Indonesia (BI) officially launched the 2016 Year Emission Rupiah. With the development of technology, the process of buying and selling are not only possible between humans and humans, but humans with a machine. In addition, the machine must also be able to read and recognize the nominal banknotes in various variations of face and rotation. This is because humans can put money in machines with various variations of face and rotation. This study aims to apply and analyze the level of accuracy of nominal rupiah banknotes identification with the SURF and FLANN methods for rotation variation. Testing for identification of nominal rupiah banknotes is carried out with different rotation variations, namely 0o, 90o, 180o, and 270o. The proposed identification method provides 100% of accuracy.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42568348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of Call Drops in GSM Network using Artificial Neural Network","authors":"Olaonipekun Oluwafemi Erunkulu, E. N. Onwuka, O. Ugweje, Lukman Adewale Ajao","doi":"10.14710/JTSISKOM.7.1.2019.38-46","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.1.2019.38-46","url":null,"abstract":"Global System for Mobile communication is a digital mobile system that is widely used in the world. Over the years, the number of subscribers has tremendously increased, the quality of service (Call Drop Rate) became an issue to consider as many subscribers were not satisfied with the services rendered. In this paper, we present the Artificial Neural Network approach to predict call drop during an initiated call. GSM parameters data for the prediction were acquired using TEMS Investigations software. The measurements were carried out over a period of three months. Post analysis and training of the parameters was done using the Artificial Neural Network to have an output of “0” for no-drop calls and “1” for drop calls. The developed model has an accuracy of 87.5% prediction of drop call. The developed model is both useful to operators and end users for optimizing the network.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49516208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sistem Kendali Agitator Dryer Biji Kakao Berbasis Android","authors":"Widya Cahyadi, Devri Agus Hidayat, Bambang Sujanarko","doi":"10.14710/jtsiskom.0.0.0.%p","DOIUrl":"https://doi.org/10.14710/jtsiskom.0.0.0.%p","url":null,"abstract":"Abstract -  This paper proposes a new novelty on telemetry-based cocoa bean circular dryer control system using android applications. There are four new additions compares to the previous one. Its communication is duplex communication which is better than the simplex communication in the previous research, and it also decreases delay due to pushing push button on 2x16LCD. It also lengthens the coverage by adding internet connection via access point. It is easier to use for operator in controlling machine continuously because the number of machine available and no more record for agitator activation and turning-off. There are several tests, namely the telemetry test which checks on the distance covered using bluetooth, wifi esp8266, and accuracy test which checks the accuracy of agitator control of cocoa bean dryers using application in android. The testing process is carried out under N-LOS conditions and LOS conditions. From the test with these two conditions result in range coverage and the accuracy of Agitator Dryer control of cocoa beans using an android based telemetry system, and apply the concept of Internet of Things. Abstrak - Penelitian ini memutakhirkan sistem kendali agitator circular dryer biji kakao berbasis telemetri dengan aplikasi android, penyempurnaan dari penelitian sebelumnya yang hanya menggunakan komunikasi telemetri satu arah, perbaikan pada LCD 2x16 yang menimbulkan delay pada saat menekan push button, menambahkan koneksi internet melalui wifi Access point untuk memperjauh jarak jangkauan. Memudahkan pengoperasian agitator bagi operator dalam mengontrol mesin secara kontinyu sebab mesin lebih dari satu serta tidak adanya catatan agitator saat diaktifkan dan harus dimatikan. Pengujian yang dilakukan, menguji kinerja sistem telemetri yang digunakan yaitu jarak maksimal yang dapat di jangkau oleh piranti nirkabel bluetooth, serta wifi esp8266, dan untuk mengetahui keakurasian pengendalian agitator Dryer biji kakao menggunakan aplikasi di android. Proses pengujian ini dilakukan pada kondisi N-LOS dan kondisi LOS. Dari pengujian dengan dua kondisi tersebut menghasilkan jarak jangkauan dan juga keakurasian pengendalian Agitator Dryer biji kakao menggunakan sistem telemetri berbasis android, serta menerapkan konsep Internet of Things.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48803890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Yoruba Handwritten Character Recognition using Freeman Chain Code and K-Nearest Neighbor Classifier","authors":"J. Ajao, David Olufemi Olawuyi, Odetunji Ode Odejobi","doi":"10.14710/JTSISKOM.6.4.2018.129-134","DOIUrl":"https://doi.org/10.14710/JTSISKOM.6.4.2018.129-134","url":null,"abstract":"This work presents a recognition system for Offline Yoruba characters recognition using Freeman chain code and K-Nearest Neighbor (KNN). Most of the Latin word recognition and character recognition have used k-nearest neighbor classifier and other classification algorithms. Research tends to explore the same recognition capability on Yoruba characters recognition. Data were collected from adult indigenous writers and the scanned images were subjected to some level of preprocessing to enhance the quality of the digitized images. Freeman chain code was used to extract the features of THE digitized images and KNN was used to classify the characters based on feature space. The performance of the KNN was compared with other classification algorithms that used Support Vector Machine (SVM) and Bayes classifier for recognition of Yoruba characters. It was observed that the recognition accuracy of the KNN classification algorithm and the Freeman chain code is 87.7%, which outperformed other classifiers used on Yoruba characters.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48353966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}