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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.

Arjuna Subject : -

Articles 413 Documents

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Identifikasi Jenis Bambu Berdasarkan Tekstur Daun dengan Metode Gray Level Co-Occurrence Matrix dan Gray Level Run Length Matrix Endina Putri Purwandari; Rachmi Ulizah Hasibuan; Desi Andreswari
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 4, Year 2018 (October 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Bamboo species can be identified from the bamboo leaf images. This study conducted the identification of bamboo species based on leaf texture using Gray Level Co-occurrence Matrix (GLCM) and Gray Level Run Length Matrix (GLRLM) for texture feature extraction, and Euclidean distance for measure the image distance. This study used the images of bamboo species in Bengkulu province, that are bambusa Vulgaris Var Vulgaris, bambusa Multiplex, bambusa Vulgaris Var Striata, Gigantochloa Robusta, Gigantochloa Schortrchinii, Gigantochloa Serik, Schizostachyum Brachycladum, and Dendrocalamus Asper. The bamboo application was built using Matlab. The accuracy of the application was 100% for bamboo leaf test images captured using a smartphone camera and 81.25% for test images downloaded from the Internet.

Deteksi Tingkat Risiko Kehamilan dengan Metode Fuzzy Mamdani dan Simple Additive Weighting Tri Wulandari; Ajib Susanto
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 3, Year 2018 (July 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

The risk of pregnancy is a contributing factor in increasing mother maternal mortality (MMR). This study aimed to produce a pregnancy risk detection system based on patient examination results. This research combines fuzzy Mamdani and Simple Additive Weighting (SAW) methods using 11 criteria to determine the risk of pregnant women, that is low, high, and very high. The criteria that determine the risk of pregnancy are expressed as fuzzy statements. In system testing to 100 pregnant women patients, obtained an accuracy of 88% using recognition rate method.

Sistem Cerdas Reservasi dan Pemantauan Parkir pada Lokasi Kampus Berbasis Konsep Internet of Things Dody Ichwana Putra; Ratna Aisuwarya; Styviandra Ardopa; Indah Purnama
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 2, Year 2018 (April 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

At present time, the people who use vehicles on the campus is increasing. It makes more difficult to find an empty slot parking area on the campus. This study aims to develop a system parking reservation and monitoring on-campus area using NFC and IoT concept. NFC was used to confirm booking code that generated by the system. In the parking area, ultrasonic sensors were installed to detect parking space availability. IoT concept has been applied to build this system. Apps on users smartphone can do the reservation process to the desired parking location via internet. Black box testing was done by building a prototype using the number of data locations parking slots in the Andalas University. The test results showed that this system has been able to detect the location of vacant parking slots and do reservations with time for sending data to the server is 0.7952 sec.

Sistem Pelacakan Objek Menggunakan Kombinasi Algoritma Optical Flow dan Template Matching Ahmad Fahriannur; Ronny Mardiyanto; Meilana Siswanto
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 1, Year 2018 (January 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

This study aimed to develop a tracking system algorithm by combining optical flow and template matching algorithms to strengthen tracking and minimize the resulting errors. The system has been tested on a football video game with the ball as a tracking object. The optical flow and template matching algorithms are used interchangeably based on the coordinates of both ranges calculated using the Euclidean distance equation. The result shows that the system is able to do tracking, although it is temporarily blocked by other objects, more stable and the distance error between the coordinates of the tracking result and the actual coordinates is not more than 110 pixels compared to using only optical flow or template matching algorithm.

Back Matter - JTSiskom Volume 6 Nomor 3 Tahun 2018 JTSiskom, Editor in Chief
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 3, Year 2018 (July 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (499.563 KB)

This article contains back-matter of JTSiskom Volume 6 Issue 3 Year 2018, which includes the author's index, author guidelines, copyright notice and its transfer agreement, publication ethics statements and journal content licenses.

Layanan Infrastruktur Komputasi Multitenant dengan OpenStack di Lingkungan MaaS Joan Ricard Panggabean; Agung Budi Prasetijo; Eko Didik Widianto
Jurnal Teknologi dan Sistem Komputer Volume 5, Issue 4, Year 2017 (October 2017)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

The growth of high-quality computing needs triggers the development of infrastructure that requires huge costs and resources. This research applied OpenStack in Metal as a Service (MaaS) environment to provide multitenant infrastructure services in the form of virtual machines (IaaS). The capacity of this IaaS system can be configured based on the needs of the computing resources (CPUs, memory, storage, and network interfaces). Users within the tenant can request infrastructure services as their needs without requiring human interaction with each service provider.

Front Matter - JTSiskom Volume 6 Nomor 2 Tahun 2018 JTSiskom, Editor in Chief
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 2, Year 2018 (April 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (417.91 KB)

This article contains front-matter of JTSiskom Volume 6 Number 2 Year 2018, which includes 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.

Front Matter - JTSiskom Volume 6 Nomor 1 Tahun 2018 JTSiskom, Editor in Chief
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 1, Year 2018 (January 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (455.205 KB)

This article contains front-matter of JTSiskom Volume 6 Number 1 Year 2018, which includes 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.

Front Matter - JTSiskom Volume 5 Nomor 4 Tahun 2017 JTSiskom, Ketua Editor
Jurnal Teknologi dan Sistem Komputer Volume 5, Issue 4, Year 2017 (October 2017)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (415.063 KB)

This article contains front-matter of JTSiskom Volume 5 Number 4 Year 2017, which includes 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.

Paralel Spatial Pyramid Convolutional Neural Network untuk Verifikasi Kekerabatan berbasis Citra Wajah Reza Fuad Rachmadi; I Ketut Eddy Purnama
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 4, Year 2018 (October 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

In this paper, we proposed a parallel spatial pyramid CNN classifier for image-based kinship verification problem. Two face images that compared for kinship verification treated as input for each parallel convolutional network of our classifier. Each parallel convolutional network constructed using spatial pyramid CNN classifier. At the end of the convolutional network, we use three fully connected layers to combine each spatial pyramid CNN features and decided the final kinship prediction. We tested the proposed classifier using large-scale kinship verification dataset, called FIW dataset, consists of seven kinship problems from 1,000 families. In our approach, we treated each kinship problem as a binary classification problem with two output. We train our classifier separately for each kinship problem with same training configuration. Overall, our proposed method can achieve an average accuracy of more than 60% and outperform the baseline method.

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