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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Journal Information System Development Jiko (Jurnal Informatika dan komputer) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Sains Teknologi dan Sistem Informasi Brilliance: Research of Artificial Intelligence Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi
Chandra, Wenripin
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Transportation Veterinary Other

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Prediksi Klasifikasi Perawatan pada Dataset Kanker Payudara Coimbra Memakai Metode Naive Bayes Ferawaty, Ferawaty; Chandra, Wenripin; Ivanka, Kelvin
Journal Information System Development (ISD) Vol 5, No 1 (2020): Journal Information System Development (ISD)
Publisher : UNIVERSITAS PELITA HARAPAN

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

Abstract

Breast cancer is a dreaded disease and a major cause of death. In this study, the Naïve Bayes method is used to predict the category of breast cancer treatment for the Breast Cancer Coimbra Dataset. Test results involving nine variables in the dataset resulted in 44.8% of the "Healthy Controls" category and 55.2% of the "Patient" category.Keywords : Breast Cancer, Naive Bayes, Coimbra, Classification.
Human Age Estimation Through Audio Utilising MFCC and RNN Ken Ken; Quinn, Osfredo; Pardosi, Irpan Adiputra; Chandra, Wenripin
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12656

Abstract

Age is one of human main attributes. Age is important factor to improve communication experience. Age estimation has been used in several applications to improve user experience. Therefore, an approach is needed to estimate the user age, one of which is through audio. In this study, Mel Frequency Cepstrum Coefficients (MFCC) and Recurrent Neural Network (RNN) will be used to estimate age through audio. MFCC is used to get features from audio data, while RNN is used to estimate age. Dataset used here was taken from corpus of user speech data on the Common Voice website. This study shows that MFCC and RNN methods are able to estimate human age through audio with highest accuracy obtained in SimpleRNN is 0.5647, and 0.7087 in LSTM.
Rancang Bangun, Penyerahan, dan Sosialisasi Sistem Informasi Jasa Katering Berbasis Web Jefri Junifer Pangaribuan; Ilhami, Mirza; Chandra, Wenripin; Romindo, Romindo
ABDIKAN: Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Vol. 3 No. 2 (2024): Mei 2024
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdikan.v3i2.4009

Abstract

Catering services are integral to the food and beverage industry, particularly in providing meals for various events such as weddings and corporate functions. However, many catering businesses still rely on outdated, conventional systems that result in inefficiencies and difficulties in reaching potential customers. To address these challenges, this research focuses on developing a modern information system tailored to the needs of catering enterprises. The development process began with the design of a Use Case Diagram, followed by the creation of a user-friendly interface and a robust database structure. The final product is a fully functional website that streamlines the ordering process, enhances customer interaction, and provides a platform for suppliers to effectively promote their products. The system was rigorously tested, and user feedback was gathered through questionnaires. The results indicated a satisfaction rate of 80%, demonstrating that the website meets the users' needs and successfully resolves issues related to service accessibility and promotional outreach. This project highlights the importance of integrating modern technology into traditional business models to improve efficiency and customer satisfaction.
Evaluasi Keberhasilan Aplikasi CapCut dalam Pembuatan Video Promosi Produk: Pendekatan DeLone and McLean Riche, Riche; Jepronel Saragih; Chandra, Wenripin; Ariwibowo, Suminar; Napitupulu, Segar
SATESI: Jurnal Sains Teknologi dan Sistem Informasi Vol. 5 No. 1 (2025): April 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian ALGERO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/satesi.v5i1.4181

Abstract

CapCut is a popular video editing application among young people due to its diverse features and ease of use. This application is widely used for creating product promotional videos; however, several limitations affect user experience. Some common issues include video compression when uploaded from a PC, features experiencing bugs, and restrictions on using music outside the application. Therefore, this study aims to analyze the functionality of the CapCut application in supporting promotional video creation using the DeLone and McLean model.  Data collection was conducted online using the purposive sampling method, focusing on online business owners in North Sumatra. The total number of eligible respondents analyzed was 156, based on the Slovin formula. The collected data were analyzed using Structural Equation Modeling - Partial Least Squares (SEM-PLS) with the assistance of SmartPLS software.  The results indicate that system quality and the level of application usage have a positive and significant impact on user satisfaction. Furthermore, user satisfaction significantly contributes to the net benefits gained from using the application. However, the analysis also reveals that direct application usage does not significantly contribute to net benefits perceived by users.  These findings suggest that improving system quality and user experience are key factors in enhancing the benefits of CapCut for users in creating promotional videos. 
Facial Recognition on System Prototype to Verify Users using Eigenface, Viola-Jones and Haar Robin, Robin; Handinata, Aldrick; Chandra, Wenripin
Journal of Computer Networks, Architecture and High Performance Computing Vol. 3 No. 2 (2021): Journal of Computer Networks, Architecture and High Performance Computing, July
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v3i2.1058

Abstract

Facial recognition is one of the most popular way to authenticate user into a system. This method is preferable considering the tendency of users for using the same password across multiple sites which made the user has already made his own account securities in vulnerable states. Using biometrics might supply solutions to solve this problem and facial recognition is one of the best biometric methods can be apply as a digital account security solution. This study to design a prototype system implementing facial recognition to verify users to measure how accurate these methods are. The method used here is Viola-Jones for face detection, Eigenface and Haar feature for face recognition from the OpenCV. The system was designed in Java. Based on the test results from the system designed, system can recognize user face with 100% accuracy if faces are shot in a well desirable condition. The system is able to recognize the user's face with various expressions including with or without glasses. However, the system has difficulty in recognizing user’s face in facing up, down, sideways position or blocked by accessories or body parts such as hands. After some experiment, it was proven that the system designed is accurate, reliable and safe enough to be implemented to digital authorization process.
COMPARISON OF NAÏVE BAYES CLASSIFIER AND K-NEAREST NEIGHBOR ALGORITHMS IN SENTIMENT ANALYSIS ON SOCIAL MEDIA X WITH VADER LEXICON Tiang, Steven; Chandra, Wenripin; Ferawaty, Ferawaty; Manulang, Mangasa A. S.
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 2 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i2.9865

Abstract

The increasing use of social media as a platform for expressing public opinion has established platform X (formerly Twitter) an important data source for sentiment analysis. However, the ever-growing volume of data and the lack of sentiment labels present significant challenges for manual analysis, which is inefficient and time-consuming. This research addresses the problem of selecting effective algorithms for accurate and efficient sentiment classification on large-scale unlabeled data. The study aims to compare the performance of the Naïve Bayes Classifier and K-Nearest Neighbor (KNN) algorithms in sentiment classification related to the Value Added Tax (VAT) increase on platform X. To support classification accuracy, sentiment labeling is performed automatically using the VADER Lexicon. The research methodology involves data scraping, automatic sentiment labeling, implementation and training of classification models, and performance evaluation using a Confusion Matrix and ROC curve. The results show that the KNN algorithm with k = 1 achieved the best performance with an accuracy of 93.19%, precision of 94.07%, recall of 92.96%, a misclassification error of 6.81%, and an AUC of 0.95. In contrast, the Naïve Bayes Classifier achieved an accuracy of 88.29%, precision of 87.43%, recall of 86.67%, misclassification error of 11.71%, and an AUC of 0.93. Therefore, KNN is proven to be superior in classifying sentiment more accurately and efficiently than the Naïve Bayes Classifier.
Face Recognition Implementation as an Attendance Feature on Web-Based Video Conference Application Robin; Hermanto, Fransiskus; Chandra, Wenripin
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3216

Abstract

Online meeting by video conference has been used extensively in business, government, education and many more. One important aspect in doing online meeting is making sure the attendees recorded. In order to make attendance record, the hosts often have to spend some time to do attendance record because most of video conference applications do not have automatic attendance feature. To ease the meeting host in creating attendance record, we utilized computer vision to do attendee face recognition and then record the identity of the face owner and implement this into a web application to facilitate the usage in real life situation
Co-Authors Ariwibowo, Suminar Ferawaty, Ferawaty Handinata, Aldrick Hermanto, Fransiskus Ilhami, Mirza Irpan Pardosi Ivanka, Kelvin Jepronel Saragih Ken Ken Manulang, Mangasa A. S. Napitupulu, Segar Pangaribuan, Jefri Junifer Quinn, Osfredo Riche Riche Robin Robin Robin, Robin Romindo Tiang, Steven