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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.
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Articles 14 Documents
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Search results for , issue "Vol. 18 No. 1 (2020): July 2020" : 14 Documents clear
Pemanfaatan Teknologi Machine Learning Untuk Klasifikasi Wilayah Risiko Kekeringan di Daerah Istimewa Yogyakarta Menggunakan Citra Landsat 8 Operational Land Imager (OLI) Ayuningtyas, Fajar; Prasetyo, Sri Yulianto Joko
Jurnal Transformatika Vol. 18 No. 1 (2020): July 2020
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v18i1.2140

Abstract

Drought is a natural disaster that occurs slowly and lasts a long time. Bantul and Gunung Kidul Regencies, Special Region of Yogyakarta are also areas affected by high drought risk. This happened because the area was the result of the construction of a cement factory and limestone mining along the Sewu Mountains. Prediction and classification of areas affected by drought can be done more accurately over large areas by extracting vegetation indices through remote sensing imagery. This research was conducted to provide information about the potential risk of drought in the region using Landsat 8 OLI spectral vegetation index data. Prediction or classification of drought potential using Artificial Neural Network. Vegetation index used in this study is NDVI, TCI, VCI, and VHI. Correlation results between vegetation indices showed the highest correlation occurred between the vegetation index TCI and VHI with the potential for a medium drought of 0.501 and the potential for a high drought of 0.684. Also obtained are the results of the classification of 9 villages that fall into the category of high drought potential (High Risk). Accuracy results and Kappa values indicate that Random Forest is the best method used with a breakdown of values of 99.91% and 99.81%, respectively. Spatial prediction results are performed using Inverse Distance Weighted (IDW) on vegetation index and prediction. Testing of spatial relationships between villages that have the potential for drought is done using Moran s I. analysis.  
Pengelompokkan Data Akademik Menggunakan Algoritma K-Means Pada Data Akademik Unissula Kurniadi, Dedy; Sugiyono, Andre
Jurnal Transformatika Vol. 18 No. 1 (2020): July 2020
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v18i1.2277

Abstract

A Higher education in the digital era as it is now common to use IT technology (Information Technology) in supporting their daily activities, but the use of IT raises a problem that is serious enough if there is no support and no further management this is only produce a data noise , Sultan Agung Islamic University (Unissula) has implemented an IT-based academic information system, in use of this information systems by time this systems produce a lot of data in the unissula academic database and this data is monotonous data and not clustered or also called data noise data that overlap without any benefit and information further in it, the purpose of this study is to solve the problem of these data into student performance data based on the GPA from semester 1 to semester 4 and make it to be a best data to support an alternative decision by the leader, this study uses the method of datamining and k-means algorithms, k-means algorithm is very good to be used as a solution for problems related to clustering, k-means algorithm is an algorithm that is unsupervised and the data can be adjusted by its self according to its class, the results of this study are a decision support system for grouping academic data in the form of dashboard information systems.
Halaman Depan Vol 18, No 1 (2020) Editorial Board, Cover
Jurnal Transformatika Vol. 18 No. 1 (2020): July 2020
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v18i1.2902

Abstract

Cover & Daftar Isi
Implementation of Smart Contracts Ethereum Blockchain in Web-Based Electronic Voting (e-voting) Susanto, Ajib
Jurnal Transformatika Vol. 18 No. 1 (2020): July 2020
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v18i1.1779

Abstract

The increasing of digital technology today has helped many people to fulfill their needs. But the election system, still conventionally using paper in its implementation. Elections in general still use a centralized system, where there is an organization that manages it. Some of the problems that may occur in traditional electoral systems are that there are organizations that have full control over the database and system, so the possibility of hacking the database is quite a big opportunity.Blockchain innovation is one arrangement that can be utilized in light of the fact that it has a decentralized framework and the whole database is duplicated by all clients. Blockchain itself has been used by Bitcoin and Ethereum cryptocurrency which is known as a decentralized system. By using the blockchain in database recording on an e-voting system can reduce one source of fraud that is database manipulation. This study discusses the recording of voting data using blockchain technology. The implementation of Smart Contracts contained in the Ethereum Blockchain will be implemented to create this voting system

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