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KAJIAN KEBERHASILAN PENGGUNAAN SISTEM INFORMASI ACCURATE DENGAN MENGGUNAKAN MODEL KESUKSESAN SISTEM INFORMASI DELON DAN MCLEAN Jamal Maulana Hudin; Dwiza Riana
Jurnal Sistem Informasi Vol. 12 No. 1 (2016): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jsi.v12i1.444

Accurate accounting information system is one of accounting information systems used in the sixcompanies in the city of Sukabumi. DeLone and McLean information system success model is asuitable model to measure the success of the application of information systems in an organizationor company. This study will analyze factors that measure the success of DeLone & McLeaninformation systems model to the users of the Accurate accounting information systems in sixcompanies in the city of Sukabumi. The data collected from 37 respondents through surveys, is thenanalyzed using Partial Least Squares (PLS) available in SmartPLS 2.0 M3 software application.Results demonstrates that the quality of information and service quality does not have a significanteffect on the usage variable, while other variables have significant in measuring the success of theuse of Accurate accounting information systems to the value of R-squares for use 0.57, 0.94 for usersatisfaction and 0.94 for net benefit. And the value of goodness of fit (GoF) of 0.72 or 72%, so themodels are substantially enough to represent the research result.

Anteseden Kepuasan Pembeli Melakukan Transaksi M-Commerce: Eksplorasi Efek Moderasi dari Kustomisasi Tampilan M-Commerce Cahyo, Karno Nur; Achmad Fatkharrofiqi; Haris Dermawan; Dwiza Riana
E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Vol 14 No 2 (2021): Jurnal Ilmiah Ekonomi dan Bisnis
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/e-bisnis.v14i2.582

This study aims to determine the most significant factor statistically influencing customer satisfaction in the purchase transaction process using mobile commerce to test the moderating effect of customization or efforts to adapt m-commerce to consumer desires. Respondents who filled out the survey consisted of 125 respondents, spread over a span of 1 month, for customers who in the last 12 months have used m-commerce for buying and selling transactions. The results of this study are the customer trust factor, the perceived enjoyment factor when using m-commerce, the moderating effect of customization on usage benefits factor, and the customization factor are the 4 factors that most influence customer satisfaction. These findings are useful for M-commerce providers to focus their development on aspects of customer trust, customer enjoyment, and customization.

Anteseden Kepuasan Pembeli Melakukan Transaksi M-Commerce: Eksplorasi Efek Moderasi dari Kustomisasi Tampilan M-Commerce Cahyo, Karno Nur; Achmad Fatkharrofiqi; Haris Dermawan; Dwiza Riana
E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Vol 14 No 2 (2021): Jurnal Ilmiah Ekonomi dan Bisnis
Publisher : LPPM Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/e-bisnis.v14i2.582

This study aims to determine the most significant factor statistically influencing customer satisfaction in the purchase transaction process using mobile commerce to test the moderating effect of customization or efforts to adapt m-commerce to consumer desires. Respondents who filled out the survey consisted of 125 respondents, spread over a span of 1 month, for customers who in the last 12 months have used m-commerce for buying and selling transactions. The results of this study are the customer trust factor, the perceived enjoyment factor when using m-commerce, the moderating effect of customization on usage benefits factor, and the customization factor are the 4 factors that most influence customer satisfaction. These findings are useful for M-commerce providers to focus their development on aspects of customer trust, customer enjoyment, and customization.

Comparison of Segmentation Analysis in Nucleus Detection with GLCM Features using Otsu and Polynomial Methods Dwiza Riana; Jufriadif Na'am; Saputri, Daniati Uki Eka Saputri; Sri Hadianti; Faruq Aziz; Suryadi Putra Liawatimena; Alya Shafra Hewiz; Dika Putri Metalica; Teguh Herwanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 6 (2023): December 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i6.5420

Pap smear is a digital image generated from the recording of cervical cancer cell preparation. Images generated are susceptible to errors due to the relatively small cell sizes and overlapping cell nuclei. Therefore, accurate Pap smear image analysis is essential to obtain the right information. This research compares nucleus segmentation and detection using Grey Level Co-occurrence Matrix (GLCM) features in two methods: Otsu and Polynomial. The tested data consisted of 400 images sourced from RepoMedUNM, a publicly accessible repository containing 2,346 images. Both methods were compared and evaluated to obtain the most accurate features. The research results showed that the average distance of the Otsu method was 6.6457, which was superior to the Polynomial method with a value of 6.6215. Distance refers to the distance between the nucleus detected by the Otsu and the Polynomial method. Distance is an important measure to assess how closely the detection results align with the actual nucleus positions. It indicates that the Polynomial method produces nucleus detections that are on average closer to the actual nucleus positions compared to the Otsu method. Consequently, this research can serve as a reference for further studies in developing new methods to enhance the accuracy of identification.

Automated Indonesian Plate Recognition: YOLOv8 Detection and TensorFlow-CNN Character Classification Windu Gata; Dwiza Riana; Muhammad Haris; Maria Irmina Prasetiyowati; Dika Putri Metalica
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6310

The precise identification and reading of Indonesian vehicle number plates are important in many areas, including the enforcement of law, collection of charges, management of parking areas, and safety measures. This study integrates the implementation of the YOLOv8 object detection algorithm with three OCR methods: EasyOCR, TesseractOCR, and TensorFlow. YOLOv8 is capable of identifying license plates from images and videos at a high speed and reliability under different conditions and therefore is used in this study to perform plate detection in images and videos. After licenses are detected, OCR techniques are performed to segment and read the letters. Both EasyOCR and TesseractOCR performed moderately well on static images achieving accuracy rates of 70% and 68% respectively, but both suffered significantly lower performance in video scenarios. Of the 100 video frames, EasyOCR was able to correctly identify characters in 61 frames and TesseractOCR in 58 frames, while the TensorFlow-based model outperformed the other two with 75 correct recognitions. Furthermore, easy OCR and static images as input while the TensorFlow-based models completed them with 100% accuracy. This observation can be explained by its design, which utilizes a CNN with ReLU activation and Softmax outputs, trained on 10,261 annotated characters and was enhanced with five different data augmentation techniques. The model shows strong performance in its ability to handle dynamic conditions such as motion blur, changing light conditions, and rotation of the plate angle. The results underscore the drawbacks of one-size-fits-all OCR applications in real-world use cases and stress the need for bespoke model training, as well as hierarchical contouring, in the context of automatic license plate recognition (ALPR). This study provides additional insights into ALPR systems by delivering a robust, scalable, and real-time tool for plate and character recognition, which is essential for intelligent transportation systems.

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