Article Per Year (5 Year)
p-Index From 2020 - 2025
2.612
P-Index
This Author published in this journals
All Journal Jurnal Computech & Bisnis (e-Journal) International Journal of Quantitative Research and Modeling Jurnal Pengabdian Masyarakat Tapis Berseri Nuansa Informatika Jurnal Bhakti Karya dan Inovatif Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)
Akbar, Imannudin
Sistem Informasi, Fakultas Teknologi Dan Informatika, Universitas Informatika Dan Bisnis Indonesia
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Library & Information Science Physics Social Sciences Other

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search
Journal : Nuansa Informatika

 1 
ANALISIS DAN PERANCANGAN SISTEM PENJUALAN PADA TOKO XYZ BERBASIS WEB DAN MOBILE MENGGUNAKAN UML Imannudin Akbar; Budiman; Zatin Niqotaini; Ari Rizki Fauzi
NUANSA INFORMATIKA Vol. 17 No. 2 (2023): Volume 17 No 2 Tahun 2023
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v17i2.13

Abstract

Technological advancements have a significant impact on businesses, particularly in the realm of sales. XYZ store currently relies on manual business processes, leading to a non-computerized and uncoordinated sales system. Consequently, there is a need for an innovative new business model that utilizes web and mobile-based systems. In this study, Rosa A.S.'s Prototype research method is employed to design the sales system using UML notation in the form of diagrams. The designed sales system caters to three user categories: customers accessing the mobile platform, store clerks, and store owners accessing the website platform. The study's outcomes consist of an analysis report and the design of a web- and mobile-based sales information system (mock-up) for XYZ store. The aim is to create a user-friendly interface that facilitates understanding for the sellers, making sales transactions more efficient. Moreover, the system aims to enhance convenience for customers and buyers, enabling them to conduct transactions and access product information from any location
Analisis Dan Perancangan Website SMKN 13 Bandung Imannudin Akbar
NUANSA INFORMATIKA Vol. 18 No. 1 (2024): Nuansa Informatika 18.1 Januari 2024
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v18i1.68

Abstract

Information and communication technology plays an important role in supporting and increasing efficiency in managing daily activities, as well as enabling work to be done from anywhere. 13 Bandung Vocational High School is a secondary level school in the city of Bandung which has competency expertise in the fields of Chemical Analysis, Computer Network Engineering and Software Engineering. 13 Bandung Vocational High School needs a website as a school media for conveying information about school activities and as a media for promoting the school to the general public so that people know more about SMKN 13 Bandung. The system development method uses the prototype development method. Prototyping is the creation of an accurate testing system. Through a prototype, managers can get an overview and ideas regarding the application design requirements. The results of this research are to provide the results of the analysis and provide the results of designing the 13 Bandung Vocational High School website with the hope that this website design can be used for the implementation process of creating the 13 Bandung Vocational High School website
A Bidirectional GRU Approach with Hyperparameter Optimization for Sentiment Classification in Game Reviews : Pendekatan GRU Dua Arah dengan Optimasi Hiperparameter untuk Klasifikasi Sentimen dalam Ulasan Game Alamsyah, Nur; Titan Parama Yoga; Budiman; Imannudin Akbar; Hendra, Acep; Januantara Prima, Alif
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.399

Abstract

Sentiment analysis plays a vital role in understanding user perspectives, especially in domains such as game reviews where user feedback influences product perception and engagement. This study presents a comparative approach using Gated Recurrent Unit (GRU), hyperparameter-tuned GRU, and Bidirectional GRU models to classify sentiments in a dataset of game reviews. The experiment begins with standard preprocessing and tokenization steps, followed by vectorization and supervised training. Hyperparameter optimization is conducted using Keras Tuner to identify the most effective configuration of embedding dimensions, GRU units, dropout rates, and learning rates. The best model, a Bidirectional GRU with tuned parameters, achieves a validation accuracy of 85.37% and shows superior performance across key metrics such as precision, recall, and F1-score. Despite the relatively small and imbalanced dataset, the Bidirectional GRU model demonstrates robust generalization. This study also highlights future directions, including class balancing techniques and the integration of pretrained word embeddings to further improve model performance.
A Data-Driven Approach to Comparative Evaluation of Regression Models for Accurate House Price Prediction: Pendekatan Berbasis Data untuk Evaluasi Komparatif Model Regresi untuk Prediksi Harga Rumah yang Akurat Permata Hati, Tiara; Budiman, Budiman; Akbar, Imannudin; Alamsyah, Nur
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.411

Abstract

This study aims to develop and evaluate a property price prediction model in Bandung by applying machine learning (ML) algorithms. The need for more accurate property price predictions is increasing due to fluctuations in the property market. This study analyzes property characteristics, including the number of bedrooms, bathrooms, land area, building area, and location, as well as their impact on house prices. The study evaluates four regression algorithms, including linear regression, K-Nearest Neighbors (KNN), Random Forest, and XGBoost. Finally, this study proposes price_per_m2 and building_land_ratio as new features recommended for improvement in accuracy. The bottleneck method is derived from the data collection area of the Rumah123.com website, encompassing data preprocessing and data exploration. The following metrics will be used to evaluate each model: Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared (R²). Based on our study, we conclude that both Random Forest Regression and XGBoost Regression achieve the highest accuracy, with R² values of 0.9941 and 0.9955, respectively, after adjustment. Conversely, Linear Regression and KNN Regression have the lowest accuracy, with KNN Regression being the least accurate. The primary contribution of this study is the development of a more accurate house price prediction model that can be applied in cities with similar market characteristics. These findings provide practical insights for property developers and buyers when making investment decisions.
Co-Authors Acep Hendra Ari Rizki Fauzi Arnold Ropen Sinaga Berly Bagoes Daniswara Budiman Dani Setiawan Dena Susanti Fikri Muhamad Fahmi Habibi, Chairul Januantara Prima, Alif Lestari, Gita Ayu Marwondo Niqotaini, Zatin Nugraha Nugraha Nur Alamsyah Nursyanti, Reni Permata Hati, Tiara R. Yadi Rakhman Alamsyah Ramadhani, Muhammad Wahyu Reni Nursyanti Setiana, Elia Setiana, Elia Setiana Sinaga, Arnold Ropen Sinaga Syahira Putri Himmaniah Taufik Hidayah Titan Parama Yoga Venia Restreva Danestiara