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JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Published by Universitas Kristen Maranatha
ISSN : 24432210     EISSN : 24432229     DOI : https://doi.org/10.28932/jutisi
Core Subject : Science,
Computer Science & IT
Paper topics that can be included in JuTISI are as follows, but are not limited to: • Artificial Intelligence • Business Intelligence • Cloud & Grid Computing • Computer Networking & Security • Data Analytics • Datawarehouse & Datamining • Decision Support System • E-Systems (E-Gov, E-Health, E-Commerce, etc.) • Enterprise System (SCM, ERP, CRM) • Human-Computer Interaction • Image Processing • Information Retrieval • Information System • Information System Audit • Enterprise Architecture • Knowledge Management • Machine Learning • Mobile Computing & Application • Multimedia System • Open Source System & Technology • Semantic Web & Web 2.0
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 479 Documents
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Penerapan Metode Random forest untuk Analisis Risiko pada dataset Peer to peer lending
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 Ariel Elbert Budiman; Andreas Widjaja
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 Edward Hanafi Fernando; Hapnes Toba
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 Andrew Sebastian Lehman; Joseph Sanjaya
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.
Modifikasi Skema Teknik Tanam Padi dan Bajak Sawah Berbasis Square Transposition 64-bit Nadya Glorya Najoan; Magdalena Ariance Irene Pakereng
Jurnal Teknik Informatika dan Sistem Informasi Vol 7 No 1 (2021): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v7i1.2973

Abstract

Cryptography is a study discussing mathematic technics that related to information security aspects such as secrecy, data integrity, and authenticity. Cryptography is also a method to secure data or information in the form of a password that makes it hard to understand the meaning. This research discusses how to modify a scheme while looking for random points using different pickup points and income points. While looking for the random point in the modified scheme research using the rice planting and field plow techniques, it has three testing processes which were runtest, monobit, and blockbit tests. This research used square transpositions 64-bit with the size 8x8 and it got a high result with p-value 7.32395E-10, p-value monobit 1.00000000 and p-value blockbit 1 that showed non-random result with the smallest p-value was 0.011662392 with p-value monobit 1.00000000 and the p-value blockbit 0.99990476 that made thisresearch got a random result.
Buku Penghubung Berbasis Android Menggunakan Metode Prototyping Heri Maulana; Kasmawi Kasmawi; Depandi Enda
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.
Pengelompokan Komentar Dataset Sentipol dengan Modified K-Means Clustering Ruddy Cahyanto; Antonius Rachmat Chrismanto; Danny Sebastian
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.v6i3.3006

Abstract

Clustering is a technique in data mining thatgroups data sets into similar data clusters. One of thealgorithms that is commonly used for clustering is K-Means.However, the K-Means algorithm has several weaknesses, oneof them is the random factor in initial centroid selection, sothat cluster result is inconsistent even though it is tested withthe exact same data. The Modified K-Means algorithm focuseson selecting the initial centroid to overcome inconsistencies ofcluster results in the K-Means method. The test was conductedusing sentipol dataset and only focused on comment data.Furthermore, the specified number of clusters is 3 based on thenumber of existing comment labels (positive, negative, andneutral). According to testing result proves that Modified KMeans algorithm produces better purity value than K-Meansalgorithm. Modified K-Means algorithm produces average ofpurity value 0,42, while K-Means produces average of purityvalue 0,391. Meanwhile, from testing related to random factorsconducted 5 times with the same attributes and test data, theresults of the cluster on the Modified K-Means algorithm didnot change, so automatically the resulting purity value was alsothe same. Whereas in the K-Means algorithm, the clusterresults always change in each test, so the result of purity valueis also likely to change.
Deteksi Buah Menggunakan Supervised Learning dan Ekstraksi Fitur untuk Pemeriksa Harga Kristiawan Kristiawan; Deon Diamanta Somali; Try Atmaja Linggan jaya; Andreas Widjaja
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.v6i3.3029

Abstract

The role of technology in the business world is growing over time. The development of technology, making machines step by step is able to replace the work done by humans. The industrial revolution is a clear example of such technologial development and its use in our daily life. in the fourth industrial revolution that we face today, IOT technology provides the ability of the five senses and think like humans to machines. Over time, human work will be replaced by such technology which provides efficiency like never before. One technology that can provide efficiency is computer vision. In retail context, computer vision can help humans to recognize fruits in supermarkets so that it will help customers do self-service, without having to ask the clerk in the fresh section of the supermarket so that supermarkets can be more efficient and customers can be served better and faster. Computer Vision and machine learning can help retail companies provide self service price checkers for fruit products in supermarkets.
Sistem Rekomendasi Suku Cadang Berdasarkan Item Based Filtering Christian Wibisono; Lucky Surya Haryadi; Juan Elisha Widyaya; Swat Lie Liliawati
Jurnal Teknik Informatika dan Sistem Informasi Vol 7 No 1 (2021): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v7i1.3036

Abstract

Replaceable spare part on workshop have many transaction and possibility thus recommender system is needed to simplify the selection process. We propose recommender system with item collaborative filtering, with high data sparsity. With Single Value Decomposition we reduce the matriks to improve the system and decrease “noise” value. Model will be evaluated using MAE, RMSE, and FCP metrics. The results of recommendation model are MAE = 1.2752, RMSE = 1.4882, dan FCP = 0.4947.

Page 26 of 48 | Total Record : 479

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