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All Journal Jurnal Buana Informatika Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science (JOINTECS) JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA INOVTEK Polbeng - Seri Informatika Indonesian Journal of Information System JTAM (Jurnal Teori dan Aplikasi Matematika) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Sebatik Indonesian Journal of Computing and Modeling Jurnal Informatika JUSIM (Jurnal Sistem Informasi Musirawas) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Journal of Information Systems and Informatics Aiti: Jurnal Teknologi Informasi Idealis : Indonesia Journal Information System Jurnal Teknik Informatika (JUTIF) Jurnal Indonesia : Manajemen Informatika dan Komunikasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Ilmiah Sains Jurnal Ilmiah Ilmu Terapan Universitas Jambi Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Midang Jurnal Pendidikan Teknologi Informasi (JUKANTI) Jurnal Indonesia : Manajemen Informatika dan Komunikasi d'Cartesian: Jurnal Matematika dan Aplikasi Indonesian Journal of Intelligence Data Science (IJIDS) International Journal of Information Technology and Business JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal DIMASTIK
Yessica Nataliani
Universitas Kristen Satya Wacana
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Social Sciences Other

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ANALISIS SENTIMEN MASYARAKAT TERHADAP PENGGUNAAN VAKSIN COVID-19 DI INDONESIA MENGGUNAKAN METODE NAÏVE BAYES Leony Martiyana Putri; Yessica Nataliani
Indonesian Journal of Intelligence Data Science Vol 2 No 1 (2023): Volume 2 No. 1 2023
Publisher : Faculty of Mathematics and Natural Sciences Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

COVID-19 was officially declared a global pandemic by WHO on March 11, 2020. In Indonesia, cases of COVID-19 were first detected on March 2, 2020 and there were more and more positive confirmations every day. The government's strategy in fighting this pandemic is by carrying out vaccinations. The use of vaccination has received various responses from the public, both those who support it and those who oppose it. This study aims to analyze public opinion on vaccination, thereby helping the public to see whether vaccines are well received or not. The data used are 600 tweets for three keywords, namely "astra", "sinopharm", and "sinovac", with 200 tweets for each keyword. Each data is divided into 70% training data and 30% testing data. Classification is done using the Naïve Bayes method. Sentiment results with the keyword "astra" show 159 tweets giving neutral sentiment, 19 tweets giving positive sentiment, and 22 tweets giving negative sentiment, with an accuracy of 68,66%. The keyword "sinovac" shows 134 tweets giving neutral sentiment, 13 tweets giving positive sentiment, and 23 tweets giving negative sentiment, with an accuracy of 82,86%. The keyword "sinopharm" shows 77 tweets giving neutral sentiment, 22 tweets giving positive sentiment, and six tweets giving negative sentiment, with an accuracy of 28,77%. It can be concluded that the results of public sentiment towards vaccination received good support from the community.
Multi-Objective k-Nearest Neighbor for Breast Cancer Detection Nataliani, Yessica; Arthur, Christian; Wellem, Theophilus; Hartomo, Kristoko Dwi; Wahab, Nur Haliza Abdul
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2669

Abstract

Early detection of cancer is crucial. This study aims to increase the efficiency of breast cancer detection using the modified k-nearest neighbor (k-NN) algorithm. Since k-NN faces challenges with sensitivity to k values and computational complexity, a modification of k-NN was proposed, namely a multi-objective k-NN model. It was developed to incorporate multi-objective optimization and local density to create a more robust and efficient classification algorithm. The model dynamically determines the k value based on the sample density, optimizing accuracy and efficiency. Breast cancer data were collected from the University of Wisconsin Hospitals, Madison. The experimental results showed that the multi-objective k-NN model outperformed traditional k-NN and k-NN with feedback support. The proposed model achieved an accuracy of 93.7%, with precision values of 93% for the negative cancer class and 94% for the positive cancer class. These results indicate that the multi-objective k-NN model provides superior accuracy and precision in breast cancer detection, demonstrating its potential for clinical applications.
Penentuan bidang unggulan akademik universitas melalui metode topik Linear Discriminant Analysis (LDA) Mramra , Welianus Yohanes Yehuda; Nataliani, Yessica
IT Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Vol 4 No 1 (2025): IT-Explore Februari 2025
Publisher : Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/itexplore.v4i1.2025.pp93-105

Abstract

The identification of academic flagship areas is crucial for higher education institutions as it helps enhance academic reputation and produce graduates who are competent in the workforce. However, the determination of these flagship areas is often subjective. Therefore, this study aims to identify the academic flagship areas at XYZ University using the Topic Modeling Latent Dirichlet Allocation (LDA) method. In this study, the LDA method is specifically used in the research field to analyze research journals at XYZ University from 2017 to 2021. The research results reveal three main topics that dominate the academic publications at XYZ University: business risk analysis, application system implementation particularly related to the pandemic, and information management with a framework in information technology. Based on this analysis, the flagship areas of XYZ University can be concluded to be in the fields of Information Technology and Business. Consequently, the University can more efficiently direct research resources and academic programs, as well as strengthen collaborations and its reputation as a center of excellence in these fields.
Pemanfaatan k-Means Clustering dan Analytic Hierarchy Process terhadap Penilaian Prestasi Kerja Pegawai Advensius Natalis; Yessica Nataliani
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 1 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i1.4243

Abstract

 As a government agency related to education and culture, the Department of Education and Culture of Bengkayang Regency needs qualified employees in their performance. Clustering can be used to determine whether the employee is performing well, moderately, or poorly. The clustering method used in this study is the k-Means method. The research wasconducted by studying and understanding the k-Means method and knowing employee performance data at the Education and Culture Office of Bengkayang Regency. The results of calculations using the k-Means method and the Analytic Hierarchy Process (AHP) method are as many as six employees have good performance (where two of them got the highest score in the AHP calculation), nine employees have moderate performance, and five employees have poor performance. These results can be used as a benchmark for employees in the cluster either to be promoted or rank, while employees in the cluster less are able to begiven employee performance training, in order to be better in the future. With this, employees can become more competitive and superior in the face of increasingly rapid developments.
Perancangan sistem informasi manajemen gudang berbasis web pada Cozy Mart Prandiska, Kelvin; Nataliani, Yessica
IT Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Vol 4 No 2 (2025): IT-Explore Juni 2025
Publisher : Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/itexplore.v4i2.2025.pp186-195

Abstract

PT. Surya Cahaya Kembar or known as Cozy Mart aims to improve the delivery process and inventory management by using a web-based warehouse management information system. Companies have difficulty monitoring stock and distribution accurately as their business grows rapidly. The system analysis and software development method used in this research is Agile, which allows quick adjustments to user needs. The system is designed to include delivery tracking, stock management features and reports to assist staff in making decisions. System design uses Unified Modeling Language (UML) which describes system functionality as a whole. Test results show significant improvements in user satisfaction, as well as the speed and accuracy of warehouse management. PT. Surya Cahaya Kembar (Cozy Mart) hopes to reduce operational errors and optimize business processes by implementing this system. This helps the overall growth of the company.
Sentiment Analysis of Customer Review Using Classification Algorithms and SMOTE for Handling Imbalanced Class Sediatmoko, Nur Siradj; Nataliani, Yessica; Suryady, Irwan
Indonesian Journal of Information Systems Vol. 7 No. 1 (2024): August 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i1.8879

Abstract

Ralali.com is a B2B e-commerce platform that offers various brands across categories ranging from automotive to building materials. The Play Store is a tool for downloading applications used by many people. This research aims to compare and find the best model among Naïve Bayes (NB), Support Vector Machine (SVM), and k-Nearest Neighbor (k-NN) in classifying the sentiment reviews of Ralali.com's application on the Play Store, and analyze the negative labels to provide recommendations for Ralali.com developers. Based on the research results, the NB Algorithm stands out as the best choice compared to SVM and k-NN in addressing class imbalance. The use of SMOTE generally improves the model performance on minority classes for Precision, Recall, and F-Measure, although there are still challenges related to the lower Accuracy compared to the use of non-SMOTE.
TEXT MINING WITH LATENT DIRICHLET ALLOCATION FOR ANALYZING PUBLIC COMMENTS ON THE M-PASSPORT APPLICATION Hapsari, Theresia Shinta; Nataliani, Yessica
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.1929

Abstract

The M-Passport application is a service application developed by the Directorate General of Immigration of Indonesia to assist the public in applying for new passports and replacing passports online. However, in its implementation, this application has not been able to give satisfaction to its users. It is proven by the low rating of the application and the numerous negative comments on the Google Play Store. One way to identify the application's shortcomings is by analyzing user comments. In analyzing the abundance of comment data, this study utilizes the text mining method with Latent Dirichlet Allocation (LDA) topic modeling. The analysis with this method aims to find topics frequently discussed in comments so that the government can identify the shortcomings of the M-Passport application. The results of comment analysis with LDA topic modeling produced seven topics, from which three topics with the highest coherence values were selected. These three topics are then interpreted to obtain information about the public's concerns regarding the M-Passport application. The results of this interpretation include users frequently failing to log in or register to the M-Passport application, users feeling that the M-Passport application does not assist them in passport management due to constraints in the online queue feature, and some users still finding it difficult to use the M-Passport application.
Academic Document Authentication using Elliptic Curve Digital Signature Algorithm and QR Code Wellem, Theophilus; Nataliani, Yessica; Iriani, Ade
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.6.3.872

Abstract

Paper-based documents or printed documents such as recommendation letters, academic transcripts, and diplomas are prone to forgery. Several methods have been used to protect them, such as watermarking, security holograms, or using paper with specific security features. This paper presents a document authentication system that utilizes QR code and ECDSA as the digital signature algorithm to protect this kind of document from counterfeiting. A digital signature is a well-known technique in modern cryptography used for providing data integrity and authentication. The idea proposed herein is to put a QR code in the printed documents where the QR code includes a digital signature. The signature can later be authenticated using the proposed system by uploading the document for authentication or scanning the document's QR code. The proposed system is particularly developed for digital signature generation and verification of students' final project approval documents as the case study. In traditional settings, the approval form is typically signed directly by the student's advisor dan co-advisor using handwritten signatures. However, using the conventional handwritten signature, the signature on the approval form can be falsified. Therefore, a digital signature generation and verification system is implemented herein to avoid handwritten signature falsification. The advisors can use this system to sign the approval form using a digital signature instead of a handwritten one. The signature is stored in a QR code and is generated using ECDSA with SHA-256 as the hash function. The proposed system is evaluated using documents (i.e., approval forms) with genuine and forged QR codes.  The evaluation results showed that the system could verify the authenticity of the approval forms, which contain genuine QR codes. The approval forms that contained forged QR codes were correctly identified.
Frieze Group in Generating Traditional Cloth Motifs of the East Nusa Tenggara Province Nataliani, Yessica
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 3 (2022): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i3.8568

Abstract

Ethnomathematics studies the relationship between mathematics and culture. Indonesia has many traditional cultures. One of them is traditional cloth. The traditional cloth from East Nusa Tenggara (NTT) province is called tenun ikat. Since the motif of tenun ikat consists of symmetrical and repeated patterns, it can be generated using Frieze groups. The Frieze groups are the plane symmetry groups of patterns whose subgroups of translations are isomorphic to Z. There are seven groups in the Frieze groups, i.e., F_1, F_2, F_3, F_4, F_5, F_6, and F_7. Translation, reflection, rotation, and glide reflection are the transformation used in the Frieze groups. In this paper, Frieze groups are used to generate digital tenun ikat motifs from the basic pattern. Since one piece of original tenun ikat may consist of some basic patterns, the basic patterns are identified first, and then each of them is generated into the desired pattern, according to the suitable Frieze groups. Furthermore, a GUI Matlab program is developed to generate the Frieze groups. Three motifs of tenun ikat are presented to demonstrate the implementation of Frieze groups. With the Frieze group, users can generate other patterns from a basic pattern, so users can generate new motifs of tenun ikat without leaving the cultural characteristics of NTT province. 
Feature-reduction Fuzzy c-means Clustering for Basketball Players Positioning Nataliani, Yessica
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.651

Abstract

One of the best-known clustering methods is the fuzzy c-means clustering algorithm, besides k-means and hierarchical clustering. Since FCM treats all data features as equally important, it may obtain a poor clustering result. To solve the problem, feature selection with feature weighting is needed. Besides feature selection by assigning feature weights, there is also feature selection by assigning feature weights and eliminating the unrelated feature(s). THE Feature-reduction FCM (FRFCM) clustering algorithm can improve the FCM clustering result by weighting the features and discarding the unrelated feature(s) during the clustering process. Basketball is one of the famous sports, both international and national. There are five players in basketball, each with a different position. A player can generally be in guard, forward, or center position. Those three general positions need different characteristics of players’ physical conditions. In this paper, FRFCM is used to select the related physical feature(s) for basketball players, consisting of height, weight, age, and body mass index. to determine the basketball players’ position. The result shows that FRFCM can be applied to determine the basketball players’ position, where the most related physical feature is the player’s height. FRFCM gets one incorrect player’s position, so the error rate is 0.0435. As a comparison, FCM gets five incorrect player’s positions, with an error rate of 0.2174. This method can help the coach decide the basketball new player’s position.
Co-Authors Ade Iriani Adriyanto Juliastomo Gundo Advensius Natalis Agatha Marilin Saekoko Agustinus Fritz Wijaya Alberaldo Difra Gunawan Aldi Herindra Lasso Alexander Franklyn Alwin Adi Putra Andree Eka Putra Angela Atik Setiyanti Angela Atik Setyanti Anissa Enggar Pramitasari Anton Hermawan Anton Hermawan Antoni Erga Arthur, Christian Axsana, Samuel Richard Bryan Adha Elang Praditya Cahyaningtyas, Christian Chandra, Dian W. Charitas Fibriani Chrisanty Mariana Rorimpandey Daniel D. Kameo Danny Manongga Darmawan Utomo Deinard Yordan Sihombing Dian Widiyanto Chandra Diwa Oktario Dacwanda Edi Suharyadi Eko Sediyono Elizabeth Sri Lestari Erdi Amos Saputra Ering, Anatasya Lingkanwene Erwien Christianto Ester Gea Evi Maria Febrianus Gregorry Francesco Totti Samuelly Gigih Prima Subakti Gilang Jonathan Phita Hanita Yulia Hapsari, Theresia Shinta Hendry Hindriyanto Dwi Purnomo Hindriyanto Dwi Purnomo Hui-Ming Wee Imanuel Susanto Indrastanti Ratna Widiasari Irwan Sembiring Ivanna K. Timotius Jessica Nathania Kho Jessica Widyadhana Iskandar Kirono, Aryo Sasi Krismiyati Kristoko Dwi Hartomo Leony Martiyana Putri Lorna Yertas Baisa Marchelino Nathanael Maria Feby Tri Martin Martin Mas Kahono Alif Bintang Firmansyah Matthew Gerian Merryana Lestari Michael Jonathan Mramra , Welianus Yohanes Yehuda Mulyono, Andronikus Natalis, Advensius Penidas Fodinggo Tanaem Prandiska, Kelvin Putra, Andree Eka Rama Tri Budi Ardianto Revalina Saputera Rissal Efendi Samuel Wijayadi Sugiharto Sanjaya, Rian Sediatmoko, Nur Siradj Setyanti, Angela Atik Sugiarto, Adrian Herma Suharyadi Suryady, Irwan Tambunan, Shanto Moyrano Theophilus Wellem Tigar Cahyo Wiguno Tintien Koerniawati Vigo Yano Sahertian Wahab, Nur Haliza Abdul Whigi Tantriya Putri Willson Mangoki Willy Thomas Winsy C.D Weku Yuda Novianto Yuliana Tien Bayangkhariwati Tacoh