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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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Model CNN LeNet dalam Rekognisi Angka Tahun pada Prasasti Peninggalan Kerajaan Majapahit Tri Septianto; Endang Setyati; Joan Santoso
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 3, Year 2018 (July 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

The object of the inscription has a feature that is difficult to recognize because it is generally eroded and faded. This study analyzed the performance of CNN using LeNet model to recognize the object of year digit found on the relic inscriptions of Majapahit Kingdom. Object recognition with LeNet model had a maximum accuracy of 85.08% at 10 epoch in 6069 seconds. This LeNet's performance was better than the VGG as the comparison model with a maximum accuracy of 11.39% at 10 epoch in 40223 seconds.

Detektor Dini Kebakaran Multisensor Terintegrasi Android Menggunakan Komunikasi Bluetooth Maulana Hasan; Adnan Rafi Al Tahtawi
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 2, Year 2018 (April 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

This research aims to design fire early warning system using Arduino and Android with Bluetooth communication. The system is constructed using three sensors which are KY-026 flame detector, DS18B20 temperature sensor, and MQ-07 gas sensor. The communication used HC-05 Bluetooth module to send sensor data from Arduino to Android. Testing results show that Arduino through Bluetooth communication able to send sensor data to Android within range of 20 cm with no obstacle condition and range of 10 cm if there exists the obstacle. The system will send ‘normal’ status to Android when fulfilled this conditions: flame sensor value less than 200, temperatures less than 30°C, and gas levels less than 300 ppm. There are seven other conditions that contain ‘warning’ and ‘danger’ data if those condition above not fulfilled.

Pengenalan dan Analisis Ucapan pada Sistem Kontrol Perangkat Listrik Menggunakan Arduino Uno Dania Eridani; Ivan Sanusi; Eko Didik Widianto
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 1, Year 2018 (January 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

This study aims to develop an electrical device control system using speech recognition and perform the analysis factors that affect the accuracy of speech recognition. The system used the Arduino Uno as the main control board of the system, an Elechouse's voice recognition module as speech processing device and several output devices such as relays, LEDs and an LCD. This research resulted in 92,7% accuracy of speech recognition at the ideal condition and 66,85% at the noise condition. This study shows that the frequency, amplitude, slow tempo and timbre of command speech greatly affect the success of speech recognition.

Yoruba Handwritten Character Recognition using Freeman Chain Code and K-Nearest Neighbor Classifier Jumoke Falilat Ajao; David Olufemi Olawuyi; Odetunji Ode Odejobi
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 4, Year 2018 (October 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

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.

Peningkatan Akurasi Klasifikasi Tingkat Penguasaan Materi Bahan Ajar Menggunakan Jaringan Syaraf Tiruan Dan Algoritma Genetika Oman Somantri; Slamet Wiyono
Jurnal Teknologi dan Sistem Komputer Volume 5, Issue 4, Year 2017 (October 2017)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Decision support systems can be applied to perform a lecturer's performance assessment. This research aims to develop a hybrid model using the artificial neural network (ANN) and genetic algorithm (GA) that can be implemented and used as a model of decision support data analysis that produce better accuracy, specifically to assess the lecturer's comprehension of their teaching materials. The use of GA in determining the ANN parameter has increased the accuracy from 85.36% to 85.73%. The training cycle is also reduced to 624 from 1000. The use of this JST-GA model can be applied to provide a better lecture's performance assessment system.

Back 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 (500.59 KB)

This article contains back-matter of JTSiskom Volume 6 Issue 2 Year 2018, which includes the author's index, author guidelines, copyright notice and its transfer agreement, publication ethics statements and journal content licenses.

Back 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 (511.041 KB)

This article contains back-matter of JTSiskom Volume 6 Issue 1 Year 2018, which includes the author's index, author guidelines, copyright notice and its transfer agreement, publication ethics statements and journal content licenses.

Back 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 (508.821 KB)

This article contains back-matter of JTSiskom Volume 5 Issue 4 Year 2017, which includes the author's index, author guidelines, copyright notice and its transfer agreement, publication ethics statements and journal content licenses.

Perbandingan Unjuk Kerja Algoritme Klasifikasi Data Mining dalam Sistem Peringatan Dini Ketepatan Waktu Studi Mahasiswa Ari Fadli; Mulki Indana Zulfa; Yogi Ramadhani
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 4, Year 2018 (October 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Observation of growing academic data can be carried using data mining methods, for example, to obtain knowledge related to the determinants of timeliness of students graduation. This study conducted a performance comparison of the classification algorithms using decision tree (DT), support vector machine (SVM), and artificial neural network (ANN). This study used students academic data from Faculty of Engineering, Universitas Jenderal Soedirman in the 2014/2015 odd semester until the 2017/2018 odd semester and the attributes that conform to the academic regulations. The analytical method used is CRISP-DM. The results showed that SVM provided the best performance in an accuracy of 90.55% and AUC of 0.959, compared to other algorithms. A Model with SVM algorithm can be implemented in an early warning system for timeliness of student graduation.

Human Vital Physiological Parameters Monitoring: A Wireless Body Area Technology Based Internet of Things Aliyu Ahmed; Ajao Adewale Lukman; Agajo James; Olaniy Olayemi Mikail; Buhari Ugbede Umar; Emmanuel Samuel
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 3, Year 2018 (July 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Human vital physiological parameters (HVPP) monitoring with embedded sensors integration has improved the smart system technology in this era of a ubiquitous platform. Several IoT-based healthcare applications have been proposed for remote health monitoring. Most of the devices developed require one on one contact with doctors before any medical diagnosis is undertaken. Thereby, make it difficult for frequent visitation to the health center. In this paper, embedded heartbeat and temperature sensors for remote monitoring have been developed using Arduino lily as the system controller and processing unit. The Bluetooth low power enables with Android mobile apps is used for remote monitoring and communication of HVPP in a real time. This gives medical personnel and individual customers opportunity of monitoring their vital physiological parameters such as heartbeat rate and body temperature. However, it moderates sudden attack of chronic ailment like hypertension and reduces congestion of patient in the hospitals.

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