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Jurnal Teknologi dan Sistem Komputer
Published by Universitas Diponegoro
ISSN : 26204002     EISSN : 23380403     DOI : -
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 6 Documents
Search results for , issue "Volume 7, Issue 3, Year 2019 (July 2019)" : 6 Documents clear
Data Mining Menggunakan Algoritma Apriori untuk Rekomendasi Produk bagi Pelanggan Ariefana Ria Riszky; Mujiono Sadikin
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 3, Year 2019 (July 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (205.359 KB) | DOI: 10.14710/jtsiskom.7.3.2019.103-108

Abstract

The implementation of a marketing strategy requires a reference so that promotion can be on target, such as by looking for similarities between product items. This study examines the application of the association rule method and apriori algorithm to the purchase transaction dataset to assist in forming candidate combinations among product items for customer recommended product promotion. The purchase transaction dataset was collected in October and November 2018 with a total data of 1027. In the experiment, the minimum value of support is 85%, and the minimum confidence value is 90% by processing data using the Weka software 3.9 version. Apriori algorithm can form association rules as a reference in the promotion of company products and decision support in providing product recommendations to customers based on defined minimum support and confidence values.
Perbandingan Kinerja Perangkat Lunak Forensik untuk File Carving dengan Metode NIST Doddy Teguh Yuwono; Abdul Fadlil; Sunardi Sunardi
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 3, Year 2019 (July 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (274.209 KB) | DOI: 10.14710/jtsiskom.7.3.2019.89-92

Abstract

Data lost due to the fast format or system crash will remain in the media sector of storage. Digital forensics needs proof and techniques for retrieving data lost in storage. This research studied the performance comparison of open-source forensic software for data retrieval, namely Scalpel, Foremost, and Autopsy, using the National Institute of Standards Technology (NIST) forensic method. The testing process was carried out using the file carving technique. The carving file results are analyzed based on the success rate (accuracy) of the forensic tools used in returning the data. Scalpel performed the highest accuracy for file carving of 100% success rate for 20 document files in pdf and Docx format, and 90% for 10 image files in png and jpeg format.
Modifikasi Algoritme Bellman-Ford Untuk Pencarian Rute Terpendek Berdasarkan Kondisi Jalan Yaddarabullah Yaddarabullah
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 3, Year 2019 (July 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (301.168 KB) | DOI: 10.14710/jtsiskom.7.3.2019.109-115

Abstract

The application of the Bellman-ford algorithm for finding the shortest path both weighted and unweighted graph has a weakness in determining the shortest path based on road conditions. This study modified the Bellman-Ford algorithm by adding the Technique for Order of Preference by Similarity to the Ideal Solution method to provide alternative road assessments based on its condition criteria including road density, road width, travel time, and distance. This modified Bellman-Ford has better performance in finding the alternative shortest path by choosing a road with smoother conditions, even though distance and travel time increase.
Prediksi Kejadian Banjir dengan Ensemble Machine Learning Menggunakan BP-NN dan SVM Ike Fitriyaningsih; Yuniarta Basani
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 3, Year 2019 (July 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (211.983 KB) | DOI: 10.14710/jtsiskom.7.3.2019.93-97

Abstract

This study aims to examine the prediction of rainfall and river water debit using the Back Propagation Neural Network (BP-NN) method. Prediction results are classified using the Support Vector Machine (SVM) method to predict flooding. The parameters used to predict rainfall with BP-NN are minimum, maximum and average temperature, average relative humidity, sunshine duration, and average wind speed. The debit of Ular Pulau Tagor river is predicted by BP-NN. BPNN and SVM modeling using software R. Daily climate data from 2015-2017 were taken from three stations, namely Sampali climatology station, Kualanamu meteorological station, and Tuntung geophysics station. Prediction of river water debit is for 6 days and 30 days in the future. The best dataset is a 6 day prediction with a combination of 60% training and 40% testing. Flood prediction accuracy with SVM was 100% in predicting flood events for the next 6 days.
SMS Security Improvement using RSA in Complaints Application on Regional Head Election’s Fraud Dwi Yuny Sylfania; Fransiskus Panca Juniawan; Laurentinus Laurentinus; Harrizki Arie Pradana
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 3, Year 2019 (July 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (306.924 KB) | DOI: 10.14710/jtsiskom.7.3.2019.116-120

Abstract

In the campaign period of regional heads election, fraud can occur, such as money politics, blaming campaign facilities, campaign time violations, and black campaign. This study implemented a secure SMS application for election fraud complaints as a tool for the society to report all forms of election fraud that have occurred to the election supervisory department safely. The RSA algorithm was applied to encrypt the messages for sender privacy protection. The application was able to perform the message randomization function properly with a 10.44% avalanche effect. Brute force attack using a 16-bit key length needs 3.7 milliseconds for each try to find 32.768 possible private keys.
Sistem Pendukung Keputusan untuk Subsidi Biaya Perbaikan Kerusakan Kontainer Menggunakan Naive Bayes Agung Prakesakwa; Adhe Suryani; Rendra Gustriansyah
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 3, Year 2019 (July 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (132.898 KB) | DOI: 10.14710/jtsiskom.7.3.2019.98-102

Abstract

During the process of using containers by the importer, the shipping company as the owner of the container is often faced with the problem of those who must be responsible for handling containers that are damaged when shipping goods. This study examines the application of the Naïve Bayes method to help the container owner to make a decision in analyzing each case of objection from the importer. The analysis was carried out for each objection case submitted by the importer regarding subsidizing the cost of repairs to be given a FREE or PAID decision by considering 4 factors, which are the damaging side, the damage, the type of damage, and the cost of repairs. From 48 datasets collected and analyzed, the decision has an accuracy rate of 63.3% in subsidizing of container repair costs.

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