Article Per Year (5 Year)
p-Index From 2021 - 2026
1.665
P-Index
This Author published in this journals
All Journal INFORMATIKA Jurnal Inotera Jurnal Informatika Universitas Pamulang JSiI (Jurnal Sistem Informasi) JAMAIKA: Jurnal Abdi Masyarakat KOMMAS: Jurnal Pengabdian Kepada Masyarakat Journal of Research and Publication Innovation Indonesian Journal of Multidisciplinary on Social and Technology OKTAL : Jurnal Ilmu Komputer dan Sains
Fajar Agung Nugroho
Universitas Pamulang
Astronomy Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search

 1   2 
Pengembangan Website Profil dan Layanan Percetakan dengan Model Prototyping untuk Meningkatkan Pemasaran pada CV. Percetakan Sapitri Dandi Saputra; Ferza Ramadhon; Welman Saputra; Maulana Ardhiansyah; Fajar Agung Nugroho
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 01 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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

Abstract

The development of information technology plays an important role in supporting marketing strategies and improving services in the printing service industry. CV. Percetakan Sapitri still relies on conventional marketing and ordering methods, which limits market reach and service efficiency. This study aims to develop a company profile and printing service website using the prototyping model as a digital solution to enhance marketing effectiveness. The prototyping model was chosen because it allows direct user involvement throughout the system development process through iterative evaluation and refinement. The developed website provides features such as company profile, list of services and prices, printing gallery, and an online ordering form. System testing was conducted using the Black Box Testing method to ensure that all functions operate as expected. The results indicate that the website facilitates easier access to service information, accelerates the ordering process, and supports the expansion of marketing reach. Therefore, the prototyping-based website development contributes positively to digital transformation and competitiveness improvement at CV. Percetakan Sapitri.
Implementasi Design Thinking dalam Pengembangan Sistem Informasi Manajemen Persediaan Ban Studi Kasus Toko Tire Zone Anugerah Ban BSD Lusius Dian Margareta; Fajar Agung Nugroho
Indonesian Journal of Multidisciplinary on Social and Technology Vol. 4 No. 3 (2026): Juli - Oktober
Publisher : PT Ilmu Data Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/ijmst.v4i3.12777

Abstract

Pengelolaan persediaan merupakan salah satu aspek penting dalam mendukung kelancaran operasional perusahaan, khususnya pada usaha yang bergerak di bidang perdagangan. Toko Tire Zone Anugerah Ban BSD masih menerapkan pengelolaan persediaan secara semi-manual melalui pencatatan transaksi barang masuk dan barang keluar sebelum diinput ke Microsoft Excel, sehingga menimbulkan permasalahan seperti ketidaksesuaian data stok, double input, keterlambatan penyusunan laporan, dan kesulitan dalam memantau stok minimum. Penelitian ini bertujuan untuk menganalisis kebutuhan pengguna, mengembangkan Sistem Informasi Manajemen Persediaan Ban menggunakan metode Design Thinking, serta mengevaluasi sistem yang dihasilkan. Metode Design Thinking diterapkan melalui lima tahapan, yaitu Empathize, Define, Ideate, Prototype, dan Test. Sistem dikembangkan sebagai aplikasi berbasis web menggunakan Next.js, Supabase dengan basis data PostgreSQL dan autentikasi pengguna, serta Netlify sebagai media deployment. Pengujian sistem dilakukan menggunakan Black Box Testing dan User Acceptance Test (UAT). Hasil penelitian menunjukkan bahwa sistem mampu mengotomatisasi pengelolaan data produk, transaksi barang masuk dan barang keluar, pemantauan stok minimum, serta penyusunan laporan persediaan secara lebih efektif dan efisien. Hasil UAT menunjukkan bahwa seluruh aspek pengujian memperoleh kategori diterima sehingga sistem dinilai mampu memenuhi kebutuhan operasional Toko Tire Zone Anugerah Ban BSD. Sistem yang dikembangkan diharapkan dapat meningkatkan akurasi data persediaan, mempercepat proses administrasi, serta mendukung pengambilan keputusan melalui penyediaan informasi yang terintegrasi dan real-time.
IMPLEMENTATION OF XGBOOST AND SUPPORT VECTOR MACHINE FOR BREAST CANCER PREDICTION USING BAYESIAN OPTIMIZATION Jupron; Fajar Agung Nugroho
Jurnal Sistem Informasi Vol. 13 No. 1 (2026)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/rnfpgf88

Abstract

Breast cancer remains one of the most prevalent causes of cancer-related mortality among women worldwide, making early and accurate detection critically important. Machine learning techniques have been widely applied for this purpose; however, many existing studies primarily focus on predictive accuracy without providing comprehensive analysis of model optimization and interpretability. This study proposes a comparative framework integrating Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) with Bayesian Optimization to enhance hyperparameter tuning and model performance. The Breast Cancer Wisconsin Dataset, consisting of 569 samples with 30 numerical features, is used for evaluation. The proposed approach includes data preprocessing, dataset splitting, systematic hyperparameter optimization, model training, and performance evaluation. Experimental results show that the XGBoost model achieves superior performance compared to SVM, with an accuracy of 98.24% and an Area Under the Curve (AUC) of 0.994. Further analysis indicates that the model maintains a strong balance between precision and recall, with minimal misclassification. In addition, feature importance analysis reveals that attributes related to tumor size and structural irregularities contribute significantly to the prediction results, supporting the interpretability of the model in a medical context. The main contribution of this study lies in providing a more comprehensive evaluation that combines performance comparison, optimization effectiveness, and feature-level interpretation within a unified framework. The findings demonstrate that the integration of XGBoost and Bayesian Optimization offers a reliable and interpretable approach for breast cancer classification, with strong potential for implementation in machine learning–based clinical decision support systems. Keywords: breast cancer, machine learning, XGBoost, Support Vector Machine, Bayesian Optimization.
Implementation of a Web Based influencer Recommendation System Using Content Filtering and Agile Development : A Case study at Ralya Management Rahadiani Atika Putri Nurjanah; Fajar Agung Nugroho
Jurnal Inotera Vol. 11 No. 1 (2026): January-June 2026
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol11.Iss1.2026.ID591

Abstract

The development of digital marketing has led companies to increasingly rely on influencers as an effective promotional medium. However, selecting the right influencer remains a challenge because the process is often conducted manually and only considers basic attributes such as the number of followers and popularity level, this study focuses on developing a web-based influencer recommendation system that can provide more relevant and faster recommendations. The research was conducted on Ralya Management, an agency managing influencers in Indonesia that requires a system capable of improving the efficiency of influencer selection for various marketing campaigns. To achieve its objectives, this study adopts two main approaches. First, the Content-Based Filtering method is applied to match influencer content characteristics including category, keywords, engagement rate, and domicile with user preferences, resulting in more targeted recommendations. Second, the system development process utilizes the Agile Development method with the Scrum framework, enabling iterative, flexible, and adaptive development in response to influencer data updates.. The results show that the system is capable of producing more accurate influencer recommendations compared to the previous manual method. Additionally,. Overall, this system contributes significantly to enhancing the effectiveness of influencer marketing strategies, particularly for Ralya Management as the research subject.
Co-Authors Angga Esa Maulana Ari Syaripudin Aziz Wirangga Bobi Agustian Dandi Saputra Dimas Abisono Pungkastyo Dimas Abisono Punkastyo Dwi Purnama Sari Fajar Septian Farida Nurlaila Ferza Ramadhon Irawan Joko Riyanto Junianto, Mochamad Bagoes Satria Jupron Jupron Lusius Dian Margareta Maulana Ardhiansyah Muhamad Meky Frindo Muhamad Supriyanto Muhamad Yasser Arafat Muhammad Yasser Arafat Nardiono Nardiono Petricia Oktavia Petricia Oktavia Rahadiani Atika Putri Nurjanah Sartika Lina Mulani Sitio Teti Desyani Tia Febriani Welman Saputra