cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Hapnes Toba
Contact Email
hapnestoba@it.maranatha.edu
Phone
-
Journal Mail Official
jutisi@it.maranatha.edu
Editorial Address
Fakultas Teknologi Informasi, Universitas Kristen Maranatha Sukawarna, Sukajadi, Bandung City, West Java 40164 Telepon: (022) 2012186
Location
Kota bandung,
Jawa barat
INDONESIA
jurnal teknik informatika dan sistem informasi
Published by Universitas Kristen Maranatha
ISSN : -     EISSN : 24432229     DOI : https://journal.maranatha.edu/
Core Subject : Science,
Computer Science & IT
Jurnal Teknik Informatika dan Sistem Informasi (JuTISI) menerima topik-topik sebagai berikut, namun tidak terbatas pada : Artificial Intelligence • Business Intelligence • Cloud & Grid Computing • Computer Networking & Security • Datawarehouse & Datamining • Decision Support System • E-System • Enterprise System (SCM, ERP, CRM) • Human Computer & Interaction • Image Processing • Information Retrieval • Information System • Information System Audit • Enterprise Architecture • Knowledge Management • Mobile Computing & Application • Multimedia System • Open Source System & Technology • Semantic Web & Web 2.0 • Internet of Things
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 18 Documents
 1   2 
Search results for , issue "Vol 6 No 3 (2020): JuTISI" : 18 Documents clear
Implementasi DenseNet Untuk Mengidentifikasi Kanker Kulit Melanoma Pardede, Jasman; Putra, Dwi Adi Lenggana
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.2814

Abstract

Skin is a part of a human body that covers the entire body and protect the lower layer from direct sunlight and another microorganism. Because of that, skin cells are always changing and could be changed because of genetic mutation that causes skin cancer. In general, skin cancer is divided into three groups, namely : skin cancer Basal cell carcinoma, skin cancer Squamous cell carcinoma, and skin cancer Melanoma. Melanoma skin cancer is caused by abnormal growth in melanocyte cells. Several methods are proposed to predict Melanoma skin cancer using ResNet, LeNet, and Support Vector Machine. System performance is measured based on the value of accuracy, precision, recall, and f-measure. This experiment is conducted using a Melanoma skin cancer dataset that obtained the average value in terms of accuracy, precision, recall, and f-measure are 0.94, 0.95, 0.92, and 0.94 respectively. Based on that result, the proposed DenseNet121 performs better with 0.94 accuracy, compared with ResNet, LeNet, and Support Vector Machine method. Keywords— Convolutional Neural Network; Image Classification; Melanoma Classification; DenseNet121.
Implementasi Algoritma Caesar Cipher Dan Steganografi Least Significant Bit Untuk File Dokumen Yusup, Irvan Maulana; Carudin, Carudin; Purnamasari, Intan
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.2817

Abstract

Abstract — Security and confidentiality of a file are important aspects because the owner of the file does not want the data to be known by irresponsible parties. To keep the file secret and secure there are techniques called cryptographic algorithms and steganographic algorithms. Cryptographic algorithms are a way to change the contents of the file to be incomprehensible, while steganographic algorithms are a way of inserting files that you want to keep secret with other file types such as images, sounds, or videos. One type of cryptography is Caesar Cipher and steganography is Least Significant Bit (LSB). Caesar Cipher is a way of securing and keeping the contents of a file secret by shifting letters, while the Least Significant Bit (LSB) is a method of insertion by replacing the rightmost or backmost bits. This research uses waterfall software development with the stages consist of needs analysis, system design, implementation, and testing. The program code is written in Java language and uses the Netbeans 8.2 application. The result of the research is that with 10 research materials, 5 document files (* .doc) and 5 image files (* .png), only 2 files of each research material can be processed by this software. The tests carried out included testing the functions and steganographic criteria such as Fidelity, Recoverable, and Robustness. Keywords — Algorithm, Caesar Cipher; Least Significant Bit (LSB); Netbeans;
Klasifikasi American Sign Language Menggunakan Ekstraksi Fitur Histogram of Oriented Gradients dan Jaringan Syaraf Tiruan Al Rivan, Muhammad Ezar; Noviardy, Mochammad Trinanda
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.2844

Abstract

Sign languages have various types, one of which is American Sign Language (ASL). In this study, ASL images from the handshape alphabet were extracted using Histogram of Oriented Gradient (HOG) then these features were used for the classification of Artificial Neural Networks (ANN) with various training functions using 3 variations of multi-layer network architecture where ANN architecture consists of one hidden layer. Based on ANN training, trainbr test results have a higher success rate than other training functions. In architecture with 15 neurons in the hidden layer get an accuracy value of 99.29%, a precision of 91.84%, and a recall of 91.47%. The test results show that using the HOG feature and ANN classification method for ASL recognition gives a good level of accuracy, with an overall accuracy of 5 neurons 95.38%, 10 neurons 96.64%, and 15 neurons with 97.32%. Keywords— Artificial Neural Network; American Sign Language; Histogram of Oriented Gradient; Training Function
Pendeteksian Penyakit pada Daun Cabai dengan Menggunakan Metode Deep Learning Rosalina, Rosalina; Wijaya, Ardi
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.2857

Abstract

Chili is one of the most essential horticultural plants in Indonesia. In addition to the lack of supply of plants, the price of chili on the market has increased dramatically. The shortage is affected by unpredictable climate changes, which have to result in many chili plants suffering from crop failure. It was because the disease infects chili plants so that harvests are decreased. This work would incorporate Deep Learning for image processing in Disease Detection Systems. This disease detection method will be used to help users, in particular chili farmers, identify whether or not the leaves of their chili plants are contaminated with the disease. This system would take a picture of chili leaf using a Raspberry Pi camera and implement image processing on the chili leaf image to collect valuable information on the image to find out whether or not the chili leaf is contaminated with the disease. The purpose of this research is to make a desktop application for a disease detection system that has the ability to detect whether or not a chili leaf is infected by several diseases, display the condition of the chili leaves, display the type of disease that infects the chili leaves (if any), and provide a percentage probability of the system in detecting the image of the chili leaves correctly (whether it is healthy chili leaves or sick chili leaves). The system reaches 100 percent accuracy with good brightness and distance less than 1 meter, while the system reaches 68.8 percent accuracy with poor brightness and distance greater than or equal to 100 percent. Keywords— chili leaf; deep learning; disease detection; raspberry pi
Penerapan Metode Random forest untuk Analisis Risiko pada dataset Peer to peer lending Renata, Erick; Ayub, Mewati
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.2890

Abstract

Abstract — Peer to peer lending (P2PL) is one of financial technology (fintech) that develops very fast in society. On the other side, P2PL project has many risks. The risk of P2PL project can be analyzed using classification. There are two conditions of a loan, namely a good loan and a bad loan. This study uses two methods to analyze a P2PL dataset, that are Random Forest method and Logistic Regression method. Data is taken from P2PL loan dataset provided by Data World, which contains 887.379 entries with 74 features. The result of experiments is a model that can be used to predict and classify a P2PL loan as a good or bad one. Keywords— Fintech; Logistic Regression; Peer to peer lending; Random forest
Analisis Pengaruh Teks Preprocessing Terhadap Deteksi Plagiarisme Pada Dokumen Tugas Akhir Budiman, Ariel Elbert; Widjaja, Andreas
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.2892

Abstract

Final Project Report at a university has the potential for plagiarism. To detect possible plagiarism, String Similarity can be used. Text preprocessing is needed to process words which can make String Similarity results inaccurate. The value of the distribution of the results of the similarity that is getting higher shows the level of accuracy is also getting higher. Reports that contain many words can make it difficult to find plagiarism recommendations. In this study, we try to divide the report into each chapter to provide more detailed recommendation material. By using text preprocessing and comparison methods in the same chapter, can determine the characteristics of each chapter. The discovery of the characteristics of each chapter can be used as plagiarism recommendation material in more detail than a full text report. The experiment was a comparison of the results of cosine similarity between the same chapters and full text, then combined with preprocessing stopword removal and stemming. The experimental results show that the use of preprocessing stopword removal and stemming can produce the highest distribution value and the similarity ratio in each chapter can show its characteristics. Words that represent the characteristics of a chapter can potentially become a stopword.
Pemanfaatan Latent Semantic Indexing untuk Mengukur Potensi Kerjasama Jurnal Ilmiah Lintas Universitas Fernando, Edward Hanafi; Toba, Hapnes
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.2894

Abstract

Abstract— This paper presents a cooperation recommendation strategy between higher education institution. The recommendation is based on the contents of journals published in a university journal portal. As a case study, we concentrate our approach for the journals with information technology themes. All journals from 10 reputed universities will be compared by using keywords and the contents of the journal themselves. A partnering recommendation list is built by utilizing Latent Semantic Indexing (LSI). LSI technique is used to reduce the curse of dimensionality from the original data set and to generate topical analysis from all journals as semantic representation for each journals. Topic modeling is used to calculate the categorical similarity in the data set of each university journal and a search query. After all categorical similarities have been calculated, an average value of journal topics coherence is used to construct the final recommendation of partner candidates. This approach ensure that the final recommendation is based on the interest of each university rather than the frequencies of matched keywords in each journal.
Sistem Pengenalan Spesifikasi Mobil pada Showroom Berbasis Haar-Like Features Lehman, Andrew Sebastian; Sanjaya, Joseph
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.2903

Abstract

Changes in science and technology have affected the structure of societies and have led to rapid change in human profile. In order to adapt to the changing human profile, reforms in advertising as well as scientific and technological enrichment in advertisement environments have become necessary. This study aims to investigate the impact of advertisement materials developed with augmented reality (AR) technology on car specification presentation and attitudes towards the advertisement, and to determine their attitudes towards AR applications. In this study, AR application was developed using haar-like features method for marker detector. A quasi-experimental design was used in which intact showroom at two different location, consisting of a total of one hundred customers, were randomly assigned to either the experimental or control group. The experimental group researched their selected car using AR technology, while the control group researched their selected car using traditional methods and the help of salesman. Customers in the experimental group were found to have higher understanding and slightly faster to learn about the car than those in the control group. In addition, the results revealed that the customers were pleased and wanted to continue using AR applications in the future. They also showed no signs of anxiety when using AR applications. In addition, it was found that advertisement achievements and attitudes of the customers in the experimental group showed a positive, significant and intermediate correlation.
Analisis Promethee II Sebagai Pendukung Keputusan Pemilihan Media Sosial Saifulloh, Saifulloh
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.2956

Abstract

Nowadays, people cannot get away from social media. Social media is a part of the life of the wider community today, from teenagers to the elderly, many of which use social media to fill their spare time. Trends in the use of social media from various circles of society have many functions, such as news updates, online communication tools, sharing (data, images, and voice) without having to meet face to face. The impact of all social media use, this study aims to select the most popular social media used based on function, interest, or interface. This study uses the Promethee II method as an analysis of social media selection decisions with the results of calculations using Excel 2019. The alternative criteria objects in this study use popular social media such as Instagram, Whatsapp, Facebook, Line, and Telegram. The research method uses the stages of data collection, namely the survey method, distributing questionnaires to respondents to provide responses to the most popular social media assessors.
Buku Penghubung Berbasis Android Menggunakan Metode Prototyping Maulana, Heri; Kasmawi, Kasmawi; Enda, Depandi
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.2993

Abstract

Abstract — The role of parents is very important in the education of their children, even though parents have entrusted their children to school. Parents also have responsibility for continuing children's learning at home. Parents of course need information about their child's learning at school, so that they guide learning at home in accordance with the lessons learned at school. In order for the information to be conveyed properly, SDN 04 Bengkalis uses a Buku Penghubung. Buku penghubung is used as a medium for communication between teachers and parents. However, the problem that arises from using it is the lack of interest of parents in using buku penghubung. Buku penghubung, also often left behind, easy to lose, and prone to damage because made of paper. This research aims to build an android-based buku penghubung application. The application features announcements, daily grades, list of lessons, and attendance. The method in this research is the prototyping. The result of this research is an android-based buku penghubung application that can be used by teachers and parents. Application testing uses the black box testing and compatibility testing. Keywords— Buku Penghubung, Android, Black Box, Compatibility.

Page 1 of 2 | Total Record : 18

 1   2 

Filter by Year

2020 2020


Reset
Filter By Issues
All Issue Vol 10 No 1 (2024): JuTISI Vol 9 No 3 (2023): JuTISI Vol 9 No 2 (2023): JuTISI Vol 9 No 1 (2023): JuTISI (in progress) Vol 8 No 3 (2022): JuTISI Vol 8 No 2 (2022): JuTISI Vol 8 No 1 (2022): JuTISI Vol 7 No 3 (2021): JuTISI Vol 7 No 2 (2021): JuTISI Vol 7 No 1 (2021): JuTISI Vol. 6 No. 3 (2020): JuTISI Vol 6 No 3 (2020): JuTISI Vol 6 No 2 (2020): JuTISI Vol 6 No 1 (2020): JuTISI Vol 5 No 3 (2019): JuTISI Vol 5 No 2 (2019): JuTISI Vol 5 No 1 (2019): JuTISI Vol 4 No 3 (2018): JuTISI Vol 4 No 2 (2018): JuTISI Vol 4 No 1 (2018): JuTISI Vol 3 No 3 (2017): JuTISI Vol 3 No 2 (2017): JuTISI Vol 3 No 1 (2017): JuTISI Vol 2 No 3 (2016): JuTISI Vol 2 No 2 (2016): JuTISI Vol 2 No 1 (2016): JuTISI Vol 1 No 3 (2015): JuTISI Vol 1 No 2 (2015): JuTISI Vol 1 No 1 (2015): JuTISI More Issue