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Jurnal Teknologi dan Sistem Komputer

JTSISKOM
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Published by Universitas Diponegoro

ISSN : 26204002 EISSN : 23380403 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

Jurnal Teknologi dan Sistem Komputer (JTSiskom, e-ISSN: 2338-0403) adalah terbitan berkala online nasional yang diterbitkan oleh Departemen Teknik Sistem Komputer, Universitas Diponegoro, Indonesia. JTSiskom menyediakan media untuk mendiseminasikan hasil-hasil penelitian, pengembangan dan penerapannya di bidang teknologi dan sistem komputer, meliputi sistem embedded, robotika, rekayasa perangkat lunak dan jaringan komputer. Lihat fokus dan ruang lingkup JTSiskom. JTSiskom terbit 4 (empat) nomor dalam satu tahun, yaitu bulan Januari, April, Juli dan Oktober (lihat Tanggal Penting). Artikel yang dikirimkan ke jurnal ini akan ditelaah setidaknya oleh 2 (dua) orang reviewer. Pengecekan plagiasi artikel dilakukan dengan Google Scholar dan Turnitin. Artikel yang telah dinyatakan diterima akan diterbitkan dalam nomor In-Press sebelum nomor regular terbit. JTSiskom telah terindeks DOAJ, BASE, Google Scholar dan OneSearch.id Perpusnas. Lihat daftar pengindeks. Artikel yang dikirimkan harus sesuai dengan Petunjuk Penulisan JTSiskom. JTSiskom menganjurkan Penulis menggunakan aplikasi manajemen referensi, seperti Mendeley, Endnote atau lainnya. Penulis harus register ke jurnal atau jika telah teregister, dapat langsung log in dan melakukan lima langkah submisi artikel. Penulis harus mengupload Pernyataan Pengalihan Hak Cipta saat submisi. Artikel yang terbit di JTSiskom akan diberikan nomer identifier unik (DOI/Digital Object Identifier) dan tersedia serta bebas diunduh dari portal JTSiskom ini. Penulis tidak dipungut biaya baik untuk pengiriman artikel maupun pemrosesan artikel (lihat APC/Article Processing Charge). Jurnal ini mengimplementasikan sistem LOCKSS untuk pengarsipan secara terdistribusi di jaringan LOCKSS privat.

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Articles 9 Documents

Search results for , issue "Volume 7, Issue 1, Year 2019 (January 2019)" : 9 Documents clear

Sistem Penegakan Speed Bump Berdasarkan Kecepatan Kendaraan yang Diklasifikasikan Haar Cascade Classifier Muhammad Zulfikri; Erni Yudaningtyas; Rahmadwati Rahmadwati
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Driving at high speed is among the frequent causes of accidents. In this research, a warning system was developed to warn drivers when their speed beyond the safety limit. Haar cascade classifier was proposed for the detection system which comprises Haar features, integral image, AdaBoost learning, and cascade classifier. The system was implemented using Python OpenCV library and evaluated on road traffic video collected in one way traffic. As a result, the proposed method yields 97.92% of car detection accuracy in daylight and MSE of 2.88 in speed measurement.

Metode SURF dan FLANN untuk Identifikasi Nominal Uang Kertas Rupiah Tahun Emisi 2016 pada Variasi Rotasi Aris Wahyu Murdiyanto; Adri Priadana; Aris Wahyu Murdiyanto
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

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.

Pengaruh Masukan Kendali Terhadap Hasil Identifikasi Parameter Pesawat Udara Konfigurasi Konvensional Matra Terbang Longitudinal Eries Bagita Jayanti; Novita Atmasari; Hidayati Mardikasari; Ardian Rizaldi; Fuad Surastyo Pranoto; Singgih Satrio Wibowo
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

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.

Front Matter - JTSiskom Volume 7 Issue 1 Year 2019 JTSiskom, Editor in Chief
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (382.959 KB)

This article contains front-matter of JTSiskom Volume 7 Number 1 Year 2019, which includes a cover page, title page, editorial team, acknowledgment, editorial policy and table of contents. JTSiskom's editorial policies include focus and scope, review process statement, publication frequency, open access policy, archiving policy and statement of article processing fee.

Algoritma Genetika untuk Optimasi Komposisi Makanan Bagi Penderita Hipertensi Anggi Mahadika Purnomo; Davia Werdiastu; Talitha Raissa; Restu Widodo; Vivi Nur Wijayaningrum
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

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.

Perbandingan Metode Segmentasi K-Means Clustering dan Segmentasi Region Growing untuk Pengukuran Luas Wilayah Hutan Mangrove Tyas Panorama Nan Cerah; Oky Dwi Nurhayati; R. Rizal Isnanto
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

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.

Back Matter - JTSiskom Volume 7 Issue 1 Year 2019 JTSiskom, Editor in Chief
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (344.217 KB)

This article contains back-matter of JTSiskom Volume 7 Issue 1 Year 2019, which includes the author's index, author guidelines, copyright notice and its transfer agreement, publication ethics statements and journal content licenses.

Perbandingan Kinerja Block Storage Ceph dan ZFS di Lingkungan Virtual Faza Abdani Auni Robbi; Agung Budi Prasetijo; Eko Didik Widianto
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

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.

Prediction of Call Drops in GSM Network using Artificial Neural Network Olaonipekun Oluwafemi Erunkulu; Elizabeth Nnonye Onwuka; Okechukwu Ugweje; Lukman Adewale Ajao
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

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.

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