cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Mohammad Sani Suprayogi
Contact Email
yogie@usm.ac.id
Phone
-
Journal Mail Official
santi@usm.ac.id
Editorial Address
-
Location
Kota semarang,
Jawa tengah
INDONESIA
Jurnal Transformatika
Published by Universitas Semarang
ISSN : 16933656     EISSN : 24606731     DOI : -
Core Subject : Science,
Computer Science & IT
Transformatika is a peer reviewed Journal in Indonesian and English published two issues per year (January and July). The aim of Transformatika is to publish high-quality articles of the latest developments in the field of Information Technology. We accept the article with the scope of Information Systems, Web Technology, Computer Networks, Artificial Intelligence, and Multimedia.
Arjuna Subject : -
Articles 7 Documents
 1 
Search results for , issue "Vol 14, No 2 (2017): January 2017" : 7 Documents clear
FUZZY MULTI-ATRIBUTE DECISION MAKING (FUZZY MADM) DENGAN METODE SAW UNTUK PEMILIHAN MAHASISWA BERPRESTASI Bernadus Very Christioko; Henny Indriyawati; Nurtriana Hidayati
Jurnal Transformatika Vol 14, No 2 (2017): January 2017
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v14i2.441

Abstract

Penentuan mahasiswa berprestasi (mawapres) tingkat fakultas terkadang mengalami kendala disaat penilaian kriteria tertentu pada kandidat kurang memenuhi namun di kriteria lain penilaian yang diperoleh melebihi ketentuan, juga apabila data-data atau informasi yang diberikan baik oleh juri maupun data kriteria dari kandidat tidak lengkap atau mengandung ketidakpastian yang mengakibatkan ketidakpastian nilai. Oleh karena itu tujuan dari penelitian ini adalah menerapkan metode Fuzzy untuk mengatasai ketidakpastian data atau informasi dan Multi-Attribute Decision Making (FMADM) dengan metode Simple Additive Weighting (SAW) untuk metode pengambilan keputusan dalam pemilihan mahasiswa berprestasi. Hasil dari penelitian ini adalah penerapan metode FMADM untuk mendukung pengambilan keputusan dalam pemilihan mahasiswa berprestasi tingkat fakultas dengan kandidat yang berasal dari setiap program studi.
PENERAPAN ANALYTIC NETWORK PROCESS (ANP) PADA SISTEM PENDUKUNG KEPUTUSAN Prind Triajeng Pungkasanti; Titis Handayani
Jurnal Transformatika Vol 14, No 2 (2017): January 2017
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v14i2.437

Abstract

Technology as a learning material will impact students impact in the future, in certain and details lesson material. Decission Support System teach how to solve the problems with algorythm methods application. One of them is Analytic Network Process (ANP). ANP is a complex methods with various stages in solving problems. ANP is difficult to understand in convensional way. Furthermore, this research aimed to solve the problems by create experimental tool called ANP application.
APLIKASI MOBILE AUGMENTED REALITY BERBASIS VUFORIA DAN UNITY PADA PENGENALAN OBJEK 3D DENGAN STUDI KASUS GEDUNG M UNIVERSITAS SEMARANG Atmoko Nugroho; Basworo Ardi Pramono
Jurnal Transformatika Vol 14, No 2 (2017): January 2017
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v14i2.442

Abstract

Realitas tertambah, atau kadang dikenal dengan singkatan bahasa Inggrisnya AR (augmented reality), adalah teknologi yang menggabungkan benda maya dua dimensi dan ataupun tiga dimensi ke dalam sebuah lingkungan nyata tiga dimensi lalu memproyeksikan benda-benda maya tersebut dalam waktu nyata. Tidak seperti realitas maya yang sepenuhnya menggantikan kenyataan, realitas tertambah sekedar menambahkan atau melengkapi kenyataan.Penelitian ini menggunakan metode pengembangan sistem waterfall, dimana alur penelitian akan mengikuti fase – fase yang ada di waterfall. Aplikasi ini akan dibangun dengan menggunakan Unity3D dan Vuforia.Tujuan dari penelitian ini adalah menghasilkan suatu aplikasi bantu pembelajaran untuk memudahkan mahasiswa dalam memahami materi augmented reality melalui perangkat mobile. Sehingga mahasiswa juga dapat memahami bagaimana mobile augmented reality dapat membantu mahasiswa melihat secara nyata objek 3D secara interaktif.
Random Obstacle Advoidance oleh Non Player Character Menggunakan Algoritma A* Latius Hermawan; Maria Bellaniar Ismiati
Jurnal Transformatika Vol 14, No 2 (2017): January 2017
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v14i2.438

Abstract

Belum ditemukannya solusi yang optimal untuk menyelesaikan masalah pathfinding. Biasanya solusinya tergantung pada spesifik dari ketentuan untuk dapat menemukan jalan keluar untuk setiap permainan yang diberikan. Pathfinding yang optimal merupakan suatu hal yang sulit untuk ditemukan, dimana terdapat perbedaan antara istilah path dan shortest path. Sehingga pathfinding yang ada bertujuan untuk menemukan jalur terpendek yang optimal. Salah satu algoritma yang digunakan pada pathfinding adalah A* digunakan dalam melakukan pencarian jalur yang optimal yang menghubungkan dua titik pada peta (grafik) dari permainan yang ada. Algoritma A* dapat membantu NPC untuk menemukan rute dalam mencari keberadaan target dengan berbagai halangan yang disediakan secara acak dalam satu waktu. Sehingga algoritma ini dapat digunakan untuk mencari rute walaupun ada banyak obstacle yang bermunculan secara acak.
PENERAPAN SENTIMENT ANALYSIS PADA HASIL EVALUASI DOSEN DENGAN METODE SUPPORT VECTOR MACHINE Valonia Inge Santoso; Gloria Virginia; Yuan Lukito
Jurnal Transformatika Vol 14, No 2 (2017): January 2017
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v14i2.439

Abstract

The quality of lectures can be determined by some feedbacks from students. From the feedbacks, we can give appreciations for those lectures who get good feedback from students, and evaluations for those who get bad feedback. The problem is classifying large size of feedbacks manually isn’t effective and took a lot of time. Therefore, we need a system that can classify feedbacks automatically. These feedbacks will be classified into positive, negative, and neutral, usually called as sentiment analysis. Sentiment analysis implementation can be done by several methods, one of them that has a good accuracy is Support Vector Machine (SVM). SVM performance in this research is measured with the level of accuracy. The number of accuracy indicate the success level of system. The conclusion of this research is factors that affects the accuracy. The factors are the range of each classes and number of unique words in the training document.
ANALISA PENDETEKSIAN WORM dan TROJAN PADA JARINGAN INTERNET UNIVERSITAS SEMARANG MENGGUNAKAN METODE KALSIFIKASI PADA DATA MINING C45 dan BAYESIAN NETWORK Rastri Prathivi; Vensy Vydia
Jurnal Transformatika Vol 14, No 2 (2017): January 2017
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v14i2.440

Abstract

Worm attacks become a dangerous threat and cause damage in the Internet network. If the Internet network worms and trojan attacks the very disruption of traffic data as well as create bandwidth capacity has increased and wasted making the Internet connection is slow. Detecting worms and trojan on the Internet network, especially new variants of worms and trojans and worms and trojans hidden is still a challenging problem. Worm and trojan attacks generally occur in computer networks or the Internet which has a low level of security and vulnerable to infection. The detection and analysis of the worm and trojan attacks in the Internet network can be done by looking at the anomalies in Internet traffic and internet protocol addresses are accessed.This research used experimental research applying C4.5 and Bayesian Network methods to accurately classify anomalies in network traffic internet. Analysis of classification is applied to an internet address, internet protocol and internet bandwidth that allegedly attacked and trojan worm attacks.The results of this research is a result of analysis and classification of internet addresses, internet protocol and internet bandwidth to get the attack worms and trojans.
Pengaruh Pembelajaran Kurikulum Berbasis Kompetensi Pada Mata Kuliah Jaringan Komputer (Studi Kasus : Program Studi Teknik Informatika-Universitas Semarang) Sri Handayani
Jurnal Transformatika Vol 14, No 2 (2017): January 2017
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v14i2.436

Abstract

The even semester 2014/2015 Technical Information Engineering University of Semarang (USM) has been running the Competency Based Curriculum (CBC) in the management of learning. Conversions that occur in some subjects at an increase in scheduled meetings in the classroom or in the laboratory. Computer Networks is one of the subjects who experienced a conversion. In the curriculum in 2008, Computer Networking has a number of credits 3. From the 2 credits 3 credits are for credits 1 credits for theory and practical credits. While at the CBC in 2013, Computer Networking has 4 credits, with details of 2 credits 2 credits theory and practicum. As lecture and instructor Computer Network, researchers interested in studying the effect of applying the CBC in 2013 in the subje ct of Computer Network. Does the addition of meeting practical and theoretical material renewal in accordance with the expected competencies?. Researchers tried applying the CBC in 2013 by conducting action research. Implementation of the research was conducted during an ongoing lecture that even semester 2015/2016. The results of the study during the first half of researchers will compare with the achievements that never existed when the old curriculum still in use. The goals of this research is, subjects in the Computer Network has always been one of the subjects that the content of the material and its application in the lab was able to follow the needs of the workforce

Page 1 of 1 | Total Record : 7

 1 

Filter by Year

2017 2017


Reset
Filter By Issues
All Issue Vol. 23 No. 2 (2026): January 2026 Vol. 23 No. 1 (2025): July 2025 Vol. 22 No. 2 (2025): January 2025 Vol. 22 No. 1 (2024): July 2024 Vol. 21 No. 2 (2024): Januari 2024 Vol 21, No 1 (2023): July 2023 Vol. 20 No. 2 (2023): January 2023 Vol. 20 No. 1 (2022): July 2022 Vol. 19 No. 2 (2022): January 2022 Vol. 19 No. 1 (2021): July 2021 Vol. 18 No. 2 (2021): January, 2021 Vol. 18 No. 1 (2020): July 2020 Vol. 17 No. 2 (2020): January 2020 Vol. 17 No. 1 (2019): July 2019 Vol 17, No 1 (2019): July 2019 Vol 16, No 2 (2019): January 2019 Vol 16, No 1 (2018): July 2018 Vol 15, No 2 (2018): January 2018 Vol 15, No 1 (2017): July 2017 Vol 14, No 2 (2017): January 2017 Vol 14, No 1 (2016): July 2016 Vol 13, No 2 (2016): January 2016 Vol 13, No 2 (2016) Vol 13, No 1 (2015): July 2015 Vol 12, No 2 (2015): January 2015 Vol 12, No 1 (2014): July 2014 Vol 11, No 2 (2014): January 2014 Vol 11, No 1 (2013): July 2013 Vol 10, No 2 (2013): January 2013 Vol 10, No 1 (2012): July 2012 Vol 9, No 2 (2012): January 2012 Vol 9, No 1 (2011): July 2011 Vol 8, No 2 (2011): January 2011 Vol 8, No 2 (2011) Vol 8, No 1 (2010): July 2010 Vol 7, No 2 (2010): January 2010 Vol 7, No 1 (2009): July 2009 Vol 6, No 2 (2009): January 2009 Vol 6, No 2 (2009) Vol 6, No 1 (2008): July 2008 Vol 5, No 2 (2008): January 2008 Vol 5, No 1 (2007): July 2007 Vol 4, No 2 (2007): January 2007 Vol 4, No 1 (2006): July 2006 Vol 2, No 2 (2005): January 2005 Vol 2, No 1 (2004): July 2004 Vol 1, No 2 (2004): January 2004 Vol 2, No 1 (2004) More Issue