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All Journal JUSTIFY : Jurnal Sistem Informasi Ibrahimy
Rizqiyah, Shofiatur
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Computer Science & IT

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Pengembangan Aplikasi Pendatan Aset BUMDes untuk meningkatkan Pelayanan Masyarakat Desa Binor Berbasis Framework Django Ja'far Shudiq, Wali; Rizqiyah, Shofiatur; Saskiya Iskandar, Nur Aida; Sari, Intan Purnama
JUSTIFY : Jurnal Sistem Informasi Ibrahimy Vol. 2 No. 2 (2024): JUSTIFY : Jurnal Sistem Informasi Ibrahimy
Publisher : Fakultas Sains dan Teknologi, Universitas Ibrahimy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/justify.v2i2.3953

Abstract

Leasing is an important component in starting a business. Each village has a business entity called Village-Owned Enterprises (BUMDes). This business entity has one work program, namely renting BUMDes assets consisting of market stalls, tractors and weighing scales. Like the current rental process, you need to contact the BUMDes officer or go to the village office to find out the stock of goods and register. With limited access to tenant information, it is difficult to find out stock of goods, and for officers recording tenant data manually is also inefficient. Currently, almost all activities can be done online just by using internet facilities, which can make work easier, whether using websites or cellphone applications. To achieve the expected goals, researchers used a system development model, namely using a waterfall. This model is used for conceptualization at each stage so that the system development procedures that will be created later become clearer. For system design using Flowcharts, DFD, and ERD. By using the Django Web Framework which contains registration and rental of BUMDes assets carried out by tenants online so it is faster and more efficient. Therefore, the results of the creation system will make it easier to register and rent BUMDes assets and also make it easier for BUMDes officers to record tenant data.
PREDIKSI CHURN PELANGGAN INDUSTRI TELEKOMUNIKASI MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK BERBASIS STREAMLIT Ningsih, Nilawati; Iskandar, Nur Aida Saskiya; Rizqiyah, Shofiatur; Sudriyanto, Sudriyanto
JUSTIFY : Jurnal Sistem Informasi Ibrahimy Vol. 3 No. 2 (2025): JUSTIFY : Jurnal Sistem Informasi Ibrahimy
Publisher : Fakultas Sains dan Teknologi, Universitas Ibrahimy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/justify.v3i2.5544

Abstract

Telecommunications companies face a major challenge in retaining customers as the cost of acquiring new customers is much higher than retaining existing customers. Customer churn, or the tendency of customers to stop using a service, can cause significant losses to the company. Customer churn prediction using Machine Learning techniques is crucial to address this issue. This research uses a Streamlit-based Artificial Neural Network (ANN) algorithm to predict customer churn in the telecommunications industry. Inspired by how the human nervous system works, ANN can learn complex customer data patterns, such as tenure, contract type, and monthly fee, resulting in more accurate predictions. Based on the research results, the Streamlit-based ANN method achieved 98% accuracy, higher than the previous method. However, the high accuracy indicates the potential for overfitting, so further testing with larger and more diverse datasets is needed to ensure better generalization. This model is expected to help telecommunication companies identify potentially churning customers and improve customer retention strategies effectively.
Co-Authors Intan Purnama Sari Iskandar, Nur Aida Saskiya Ja'far Shudiq, Wali Ningsih, Nilawati Saskiya Iskandar, Nur Aida