Article Per Year (5 Year)
p-Index From 2021 - 2026
3.67
P-Index
This Author published in this journals
All Journal Kompak : Jurnal Ilmiah Komputerisasi Akuntansi JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Computatio : Journal of Computer Science and Information Systems Jurnal Komunikasi Building of Informatics, Technology and Science Jurnal Teknologi Dan Sistem Informasi Bisnis Infotech: Journal of Technology Information Humantech : Jurnal Ilmiah Multidisiplin Indonesia Innovative: Journal Of Social Science Research International Journal of Application on Economics and Business
Dyah Erny Herwindiati
Faculty of Information Technolgy Tarumanagara University
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

Published : 31 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 31 Documents
Search

 1   2   3   4 
ANALISIS HUBUNGAN MATA KULIAH KOMPUTASI DASAR DENGAN IPK MAHASISWA TEKNIK INFORMATIKA MENGGUNAKAN SUPPORT VECTOR REGRESSION Perdana, Novario Jaya; Ferdinand, Kelvin; Gozali, Carisha Puspa; Herwindiati, Dyah Erny
Infotech: Journal of Technology Information Vol 11, No 1 (2025): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i1.383

Abstract

Student academic performance serves as a key indicator in higher education assessment. For students in Informatics Engineering, foundational computing skills are critical to their academic progression, and these are primarily acquired through first-semester courses. This study proposes a predictive model for Cumulative Grade Point Average (GPA) using the Support Vector Regression (SVR) method with a Radial Basis Function (RBF) kernel. The courses "Introduction to Algorithms," "Computation I," "Computation II," and "Data Structures" were selected as independent variables, as they provide essential computing foundations for subsequent coursework. The dataset comprised 270 records, each containing grades from the aforementioned courses and the corresponding GPA achieved by students in their fourth semester. To ensure data quality, outlier detection was performed using the Z-score method, resulting in a refined dataset of 200 entries. This dataset was then split into 75% for training and 25% for testing. A grid search optimization identified the best hyperparameter combination: C = 100, γ = 0.05, and ε = 0.05. Model evaluation yielded promising results, with a Mean Absolute Error (MAE) of 0.0742, a Mean Absolute Percentage Error (MAPE) of 2.19%, a Mean Squared Error (MSE) of 0.012, and an R² score of 0.8695—indicating strong predictive accuracy. Furthermore, the F-test produced a value of 74.9440, which exceeds the critical F-value of 2.5787, confirming the statistical significance of the independent variables in predicting GPA. This model has the potential to support academic monitoring and enhancement efforts by delivering actionable predictions and insights for the Informatics Engineering program.
SAVING BEHAVIOR OF THE MILLENNIAL GENERATION IN JAKARTA Pamungkas, Ary Satria; Herwindiati, Dyah Erny; Taba, Muhammad Idrus
International Journal of Application on Economics and Business Vol. 3 No. 2 (2025): May 2025
Publisher : Graduate Program of Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/ijaeb.v3i2.732-738

Abstract

Indonesian people's interest in saving has decreased to only 15.4% as of May 2024. Bank Indonesia invites the public, especially the millennial generation, to get into the habit of saving. This study aims to determine the effect of peer influence, socialization of parents and self-control on saving behavior. The number of samples in this study was 240 people from the millennial generation who already have income in Jakarta. For data analysis, this study used Structural Equation Modelling (SEM). The results of this research show that peer influence, socialization of parents and self-control have a positive effect on saving behavior.
Classification of Vegetable Types Using Singular Value Decomposition (SVD) and K-Nearest Neighbor (KNN) Algorithms Jong, Fenny; Herwindiati, Dyah Erny
Innovative: Journal Of Social Science Research Vol. 4 No. 5 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i5.14523

Abstract

Vegetables are widely grown in Indonesia, but sometimes they can be prepared poorly and pose risks to consumers. To solve this problem, we need a high-quality system that can identify good and safe vegetables. This study aims to create a vegetable classification system using pictures and computer algorithms. The system analyzes different types of vegetable images, including color and shape. It uses special techniques called Singular Value Decomposition (SVD) and K- Nearest Neighbor (KNN) to classify the vegetables based on their features. The researchers used a dataset of 121 vegetable images, which were divided into 73 training images and 48 test images. The results showed that the system was able to classify the vegetables with a high accuracy rate of 85.42%. This study has the potential to help improve the quality of vegetables and contribute to the development of automated systems in the agricultural industry.
FACTORS THAT INCREASE PURCHASE INTENTION OF ELECTRIC CARS IN JAKARTA Ruslim, Tommy Setiawan; Setiawan, Kevin; Hapsari, Claudia Gita; Herwindiati, Dyah Erny
International Journal of Application on Economics and Business Vol. 1 No. 3 (2023): Agustus 2023
Publisher : Graduate Program of Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/ijaeb.v1i3.968-977

Abstract

Global warming has become an issue for the whole world until now. The cause of global warming is air pollution produced by engine fuels from various automotives that can produce carbon dioxide. This encourages people to be more concerned about the environment, including the automotive industry. The rise of the movement to care for the environment encourages automotive companies to make electric car products which can be a solution to reduce pollution. In recent years, electric cars have started to enter the market in Indonesia. However, this is not well received by the Indonesian people. This is related to the low purchase intention of the electric car itself. The purpose of this study was to determine empirically the effect of attitude, subjective norm, perceived behavioral control, and price sensitivity on consumer purchased intention of electric cars in Jakarta. This study uses data collected from 153 respondents who are people who at least are undergoing undergraduate studies and have knowledge of electric cars in Jakarta. The data was obtained by distributing an online questionnaire in the form of a google form through social media. The data is then processed using SmartPLS 3.2.9 software. The results of this study are attitude, subjective norm, and price sensitivity have a positive and significant influence on the purchase intention of electric cars in Jakarta. Meanwhile, perceived behavioral control has no effect on the purchase intention of electric cars in Jakarta.
THE IDENTIFICATION OF PURCHASE INTENTION AMONG IPHONE CUSTOMERS IN DEPOK VIEWED FROM EWOM, BRAND IMAGE, BRAND TRUST, PERCEIVED VALUE, AND BRAND PREFERENCE Ruslim, Tommy Setiawan; Nova, Nova; Herwindiati, Dyah Erny; Cokki , Cokki
International Journal of Application on Economics and Business Vol. 1 No. 4 (2023): November 2023
Publisher : Graduate Program of Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/ijaeb.v1i4.2354-2367

Abstract

Communication has become a kind of activities performed by human beings everyday, either directly or indirectly. Handphone as one among the communication means, was then developed into smartphone. Due to many smartphones released every year, customers are then faced with so many choices. One among the global reputable smartphone brands is Apple. Therefore, Apple sellers must be able to attract the customers’ attention and increase their purchase intention toward iPhone products, so that these products can compete with others and survive in the market. This research aimed to test the effects of EWOM, brand image, brand trust, perceived value, and brand preference on purchase intention among iPhone customers in Depok, West Java, Indonesia. This descriptive research was conducted to depict the characteristics or functions of a population. By using questionnaire distributed online and among 355 respondents filling-out, there were only 349 respondents from which the data can be processed further by using the SmartPLS-SEM software. The result of this research supported that brand image, brand trust, perceived value, and brand preference have positive and significant effects on purchase intention among iPhone customers in Depok, while EWOM does not have significant effect on purchase intention.
FINANCIAL LITERACY, RISK PERCEPTION, MATERIALISM AND PROPENSITY TO INDEBTEDNESS Pamungkas, Ary Satria; Herwindiati, Dyah Erny; Taba, Muhammad Idrus
International Journal of Application on Economics and Business Vol. 2 No. 1 (2024): February 2024
Publisher : Graduate Program of Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/ijaeb.v2i1.3044-3050

Abstract

The purpose of this paper is to study the influence of financial literacy, risk perception and materialism on propensity to indebtedness. The number of samples in this study was 200 respondents who were credit card users who already had income in the Jakarta area. For data analysis, this study used Structural Equation Modelling (SEM). The result of this study indicated that Financial Literacy and Risk Perception has a negative effect on Propensity to Indebtedness, while Materialism has a positive effect on Propensity to Indebtedness.
Program Konversi Citra Notasi Balok Menjadi Notasi Angka Gunawan, Hendy; Hendryli, Janson; Herwindiati, Dyah Erny
Computatio : Journal of Computer Science and Information Systems Vol. 2 No. 2 (2018): COMPUTATIO : JOURNAL OF COMPUTER SCIENCE AND INFORMATION SYSTEMS
Publisher : Faculty of Information Technology, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/computatio.v2i2.2278

Abstract

The Image Conversion Program of Music Notation being Numeric Notation is a character recognition system that accepts input in form of music notation image that produces an output of a DOCX file containing the numeric notation from the input image. Music notation has notation value, ritmic value and written with a music stave. The system consists of four main processes: preprocessing (grayscale and thresholding), notation line segmentation, notation character segmentation, and template matching. Template matching is used to recognize the music notation that obtained after segmentation. The recognition process obtained by comparing the image with the template image that has been inputted before to the database. This system has 100% success rate on segmentation of the character and success rate 38,4843% on the character recognition with template matching.
KLASIFIKASI CITRA BATIK INDONESIA DAN MALAYSIA DENGAN METODE MODIFIED DISCRIMINANT ANALYSIS Cynthia, Cynthia; Hendryli, Janson; Herwindiati, Dyah Erny
Computatio : Journal of Computer Science and Information Systems Vol. 3 No. 1 (2019): COMPUTATIO : JOURNAL OF COMPUTER SCIENCE AND INFORMATION SYSTEMS
Publisher : Faculty of Information Technology, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/computatio.v3i1.2973

Abstract

The application of Indonesian and Malaysian batik image classification using the Linear Discriminant Analysis (LDA) and Modified Discriminant Analysis (MDA) method is an introduction application that is used to classify images in the form of batik. Making this application uses the Java programming language to run feature retrieval methods, namely Color Histogram and Daubechies Wavelet and classification methods, namely LDA and MDA. Testing is done by blackbox testing method and confusion matrix. Tests are performed using color features, texture features, and a combination of training images and new test images. The best percentage test results are testing using color features, whereas with texture and the combination of both features get a slightly lower test percentage result.Aplikasi klasifikasi citra batik Indonesia dan Malaysia dengan metode Linear Discriminant Analysis (LDA) dan Modified Discriminant Analysis (MDA) merupakan aplikasi pengenalan yang digunakan untuk mengklasifikasi citra berupa batik. Pembuatan aplikasi ini menggunakan bahasa pemrograman Java untuk menjalankan metode pengambilan fitur yaitu Color Histogram dan Daubechies Wavelet dan metode pengklasifikasian yaitu LDA dan MDA. Pengujian dilakukan dengan metode blackbox testing dan matriks konfusi. Pengujian dilakukan dengan menggunakan fitur ciri warna, ciri tekstur, dan gabungan dari citra latih dan citra uji baru. Hasil persentase pengujian terbaik adalah pengujian dengan menggunakan ciri warna, sedangkan dengan ciri tekstur dan gabungan mendapatkan hasil persentase pengujian sedikit rendah.
CONTENT-BASED IMAGE RETRIEVAL UNTUK PENCARIAN PRODUK PONSEL Siantar, Nickolas Cornelius; Hendryli, Jaqnson; Herwindiati, Dyah Erny
Computatio : Journal of Computer Science and Information Systems Vol. 3 No. 1 (2019): COMPUTATIO : JOURNAL OF COMPUTER SCIENCE AND INFORMATION SYSTEMS
Publisher : Faculty of Information Technology, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/computatio.v3i1.4271

Abstract

Phone or smartphone and online shop, there is something that cannot be separated with human. There are so many type of smartphones show up in the market that people are confused on which one to get on the online stores. Smartphones recognition is done by using the Histogram of Oriented Gradient to recognize shapes of phones, Color Quantization to recognize the color, and Local Binary Pattern to recognize texture of the phones. The output of the Feature Extractor is a feature vector which is used on the LVQ to process recognize through finding the smallest Euclidean Distance between the trained vectors. The result of this paper is an application that can recognize 16 phone types using the image with the accuracy of 9.6%. Pada saat ini, ponsel dan toko online merupakan sesuatu yang tidak dapat dipisahkan dari manusia. Begitu banyak jenis ponsel bermunculan setiap tahunnya sehingga menyebabkan manusia bingung dalam mengenali ponsel tersebut. Pada program pengenalan ponsel ini digunakan Histogram of Oriented Gradient untuk mengambil fitur berupa bentuk ponsel, Color Quantization untuk mengambil fitur warna, dan Local Binary Pattern untuk mengambil fitur tekstur ponsel. Hasil dari pengambilan fitur berupa fitur vektor yang digunakan pada Learning Vector Quantization untuk proses pengenalan dengan mencari nilai terkecil Euclidean Distance antara vektor fitur dengan vektor bobot terlatih. Hasil dari program pengenalan ini yaitu program dapat melakukan pengenalan terhadap 16 jenis ponsel dengan akurasi sebesar 9.6%.
KLASIFIKASI KAIN TENUN BERDASARKAN TEKSTUR & WARNA DENGAN METODE K-NN Kevin, Kevin; Hendryli, Janson; Herwindiati, Dyah Erny
Computatio : Journal of Computer Science and Information Systems Vol. 3 No. 2 (2019): COMPUTATIO : JOURNAL OF COMPUTER SCIENCE AND INFORMATION SYSTEMS
Publisher : Faculty of Information Technology, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/computatio.v3i2.6028

Abstract

Image classification of woven cloth based on texture and color using Gray Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP), Color Moments and classification method KNearest Neighbour (KNN) is an application for classifying motive on woven cloth. The development of this application is using Python language programming for classification system and Android studio which using Java language programming as Front-end. Classification system consist of two main process namely feature extraction process and classification process. Feature extraction process is using GLCM, LBP and Color Moments which produce feature vector for every method and classification process is using KNN method. Feature used for classification process is feature vector which has best result. Based on experiment result, the best method that produce best feature vector is LBP method with accuracy percentage higher than other method.  Klasifikasi citra kain tenun berdasarkan tekstur dan warna dengan metode Gray Level Cooccurrence Matrix (GLCM), Local Binary Pattern (LBP), Color Moments dan metode klasifikasi K-Nearest Neighbour (KNN) merupakan aplikasi yang digunakan untuk mengklasifikasi motif yang ada pada kain tenun. Pembuatan aplikasi ini menggunakan bahasa pemrograman Python sebagai sistem klasifikasi dan Android studio yang menggunakan bahasa pemrograman Java sebagai Front-end. Sistem klasifikasi dibagi menjadi dua proses utama yaitu proses ekstraksi fitur dan proses klasifikasi. Proses ekstraksi fitur dilakukan dengan metode GLCM, LBP dan Color Moments yang menghasilkan fitur vektor untuk setiap metode dan proses klasifikasi dilakukan dengan metode K-NN. Fitur yang digunakan dalam proses klasifikasi adalah fiturvektor yang memiliki hasil terbaik. Berdasarkan hasil pengujian yang telah dilakukan, metode yang dapat menghasilkan fitur terbaik adalah metode LBP dengan persentase akurasi lebih tinggi dibandingkan dengan dua metode lainnya.
Co-Authors Albert, Bryan Andri Muliawan Angel Angel Ariesta, Cindy Maharani Arifin Arifin Budianto, Willson Carlos, Daniel Chairisni Lubis Chandriyani, Ika christian christian Cokki , Cokki Cynthia Cynthia David David Denny, Mandy Sandra Dohim, Mas’ud Ferdinand, Kelvin Gozali, Carisha Puspa gunawan, Hendy halim, philip bryan Handoyo, Rico Hapsari, Claudia Gita Hendryli, Janson Hendryli, Jaqnson Hendyli, Janson Jong, Fenny Karendef Karendef Kevin kevin Kevin Setiawan Lely Hiryanto Manatap Dolok Lauro, Manatap Dolok Martha, Regina Milson, Audie Muhammad Idrus Taba Nova Nova Novario Jaya Perdana Onggo, Gilbert Alexandro Otto Randa Payangan Pamungkas, Ary Satria Sani M. Isa Sari, Endah Murtiana Siantar, Nickolas Cornelius Sitorus, Manatap Dolok Lauro Soelaiman, Lydiawati Sopany, Mitchell Ryu Stephen Christian, Stephen Sukamdani, Ryan Rici Suluh, David Tommy Setiawan Ruslim, Tommy Setiawan Tony Tony TRI SUTRISNO Wenda Kartika, Wenda