Article Per Year (5 Year)
p-Index From 2021 - 2026
2.125
P-Index
This Author published in this journals
All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Systems Engineering and Business Intelligence Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Tech-E Abdimas Dewantara JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Jurnal Tekno Kompak Abdi-Dharma JSITIK: Jurnal Sistem Informasi dan Teknologi Informasi Komputer Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Daniawan, Benny
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Social Sciences Other

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
Implementing QR Codes on Student ID for Transactions: TAM Testing Approach Noviany, Caroline; Daniawan, Benny; Suwitno, Suwitno
Sistemasi: Jurnal Sistem Informasi Vol 13, No 3 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i3.3922

Abstract

The rapid advancement of technology has had a significant impact on contemporary life. One of the technologies commonly encountered is the Quick Response Code (QR-Code) and Barcode, both of which serve a similar function, that is, to store information represented in the form of squares and lines. Three squares at the corners of the QR-Code are key to ensuring accurate scanning. Universities are educational institutions that provide Student ID Cards as a means of student identification. This research aims to design a transaction system by utilizing QR-Code technology on Student ID Cards for parking and library transactions, as well as creating a transaction system using digitized Student ID Cards. This study employs the Technology Acceptance Model (TAM) testing method to measure the factors influencing users in utilizing the application. The system design successfully incorporates QR-Codes and can be used as a transaction tool. The TAM testing results from 75 respondents regarding system acceptance conclude that the Perceived Ease of Use (PEOU) variable will influence the Perceived Usefulness (PU) variable by 67.4% and affect the Behavioral Toward Using (BITU) variable by 55.1%.
Deep Learning Based LSTM Model Hyperparameter Testing to Predict the Number of Road Accidents Siswanto, Joko; Daniawan, Benny; Haryani, Haryani; Rusmandani, Pipit
Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi Vol. 3 No. 3 (2024)
Publisher : Department of Informatics Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/snati.v3.i3.37

Abstract

Many have used the prediction of the number of road accidents, but it is still rare to find those who use and test prediction models that are not suitable. Predictive models that have been used to predict road accidents have proven successful, but have not provided model testing with data that is different from the deep learning approach. The LSTM model test is proposed to be tested with 5 different datasets from Kaggle and 3 hidden layer variations. The test results of the LSTM model are that with variations of 4 hidden layers it can achieve higher accuracy results than those without hidden layers and 2 hidden layers. The results are obtained from stability with the lowest average MSLE value and relatively balanced average time. Deep learning-based LSTM model testing was carried out to ensure and prove the stability of the model for predicting the number of road accidents in the future. Stakeholders can predict the number of road accidents using the resulting prediction model.
Optimizing Artificial Neural Network for Customer Churn: Advanced Data Balancing and Feature Selection Hermawan, Aditiya; Wijaya, Willy; Daniawan, Benny
JOIV : International Journal on Informatics Visualization Vol 9, No 3 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.3.3064

Abstract

Customers are valuable assets in the dynamic business world. However, service dissatisfaction often leads them to switch to competitors, a phenomenon known as customer churn. In the telecommunications industry, churn poses a significant challenge as it directly impacts revenue and influences other customers within their social networks to do the same. Consequently, predicting churn has become essential, with numerous researchers employing various methods to classify potential churners. This study builds upon prior research that utilized Artificial Neural Networks (ANN) or Deep Learning to predict churn, achieving an accuracy of 88.12%. To improve model performance, this research implements an Artificial Neural Network (ANN) as the primary algorithm, along with Random Over-Sampling (ROS) and Synthetic Minority Oversampling Technique (SMOTE) for data balancing, and three feature selection methods: Minimum Redundancy Maximum Relevance (mRMR), Lasso Regression, and XGBoost. The results demonstrate a 0.38% increase in accuracy compared to previous studies. The finding suggests opportunities for further exploration. Future studies can consider alternative feature selection techniques, such as Wrapper Methods or Heuristic/Metaheuristic approaches, which may produce more optimal feature combinations. Other data balancing methods, such as Undersampling techniques (e.g., Random Undersampling, Tomek Links) or Hybrid Methods (e.g., SMOTE combined with Tomek Links), could be explored to address imbalanced datasets effectively. These approaches are expected to provide better combinations and to improve overall prediction performance, enabling researchers to develop more robust and accurate models for customer churn prediction in subsequent studies.
Optimasi Sistem Informasi Pembelian, Persediaan, dan Penjualan Barang dengan Penerapan Metode Algoritma Apriori Juniar, Diana; Daniawan, Benny
Jurnal Teknik Informatika dan Sistem Informasi Vol 10 No 1 (2024): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v10i1.7647

Abstract

The fashion retail business is a business sector that is continually growing and has many enthusiasts. Apart from companies with well-known fashion brands, this business is also often found in small and medium-scale enterprises, where business processes are implemented manually, starting from purchasing, inventory management, and selling goods. These three processes are essential in business because they are related. The recording is done manually, often allowing inaccurate data to occur. Problems that are often found are in calculating inventory, which can cause stock-outs or stock build-up. Apart from that, checking and updating data, as well as making reports, takes quite a long time and is less practical. Using a purchasing, inventory, and sales information system can help business owners in running their business because the system designed is integrated, and applies an a priori algorithm method that can help recommend which products are trending based on customer transactions, therefore business owners can optimize inventory management effectively by knowing the patterns of products frequently purchased by customers. The results of system testing using the Technology Acceptance Model (TAM), which was processed with the SmartPLS application on data from 37 respondents, gave results that the second hypothesis, namely Behavioral Intention to Use (BITU), has an effect on Actual System Use (ASU), the fourth hypothesis, namely Perceived Ease of Use (PEOU) has an impact on Perceived Usefulness (PU), and the fifth hypothesis, namely Perceived Usefulness (PU) has an effect on Attitude Towards Using (ATU), and other variables have no effect.
Pelatihan Desain Slide dengan Canva Junaedi; Wydiastuty Kusuma, Lianny; Ceng Giap, Yo; Suwitno; Hermawan, Aditiya; Rino; Daniawan, Benny; Riki
Abdi Dharma Vol. 2 No. 2 (2022): Jurnal Abdi Dharma (Jurnal Pengabdian Masyarakat)
Publisher : LP3kM Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/ad.v2i2.1737

Abstract

Perkembangan di era sekarang banyak sekali perubahan dari segi teknologi. Perkembangan teknologi ini meliputi desain grafis, pemrograman, aplikasi dan sebagainya. Hal inilah yang membuat penulis sebagai pendidik untuk melakukan pengabdian kepada masyarakat dengan cara melakukan sebuah workshop dengan tema “Pelatihan Desain Slide dengan Canva” yang bertujuan untuk memperkenalkan membuat sebuah desain pada slide presentasi dengan baik, rapih dan interaktif sebagai media penyampaian pembelajarannya. Pelatihan Desain Slide dengan Canva ini juga didukung oleh Universitas Buddhi Dharma sebagai tempat dilaksanakannya pelatihan ini. Para peserta dari Pelatihan Desain Slide dengan Canva ini diikuti oleh para romo dan rahmani dari Magabudhi Kota Tangerang. Hasil dari pelatihan ini akan di implementasikan dalam pembuatan presentasi sebagai media pembelajaran.
Co-Authors Aditiya Hermawan Akbar, Junaidi Andri Wijaya Arijanto, Rudy Ceng Giap, Yo Damayanti, Lily Danny Manongga Darmawan, Ivander Dethan, Jacob Febryadi Nithanel Edy Edy Fennita, Fennita Fenriana, Indah Hariyanto, Susanto Haryani Haryani Irwan Sembiring Joko Siswanto JUNAEDI Juniar, Diana Krismiyati Kusnadi, Michael Putra Lasut, Desiyanna Lunardi, Lidya Miechael, Miechael Nathaniel, Joese Noviany, Caroline Pipit Rusmandani, Pipit Ramona Safitri, Ramona Riki Rino Rino Rino Sutarto Wijono Sutyawati, Yuke Subaikah Suwitno Suwitno Suwitno, Suwitno Theopillus J. H. Wellem Wijaya, Ardie Willy Wijaya, Willy Wydiastuty Kusuma, Lianny Yakub, Handoyo Yusuf Kurnia, Yusuf