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Menampilkan 1–10 dari 13 artikel
Konsumsi Fast Food Mahasiswa dalam Perspektif Masyarakat Risiko: antara Kesadaran dan Praktik: Studi pada Mahasiswa Universitas Sriwijaya
Angga Aji Saputra
; Napinurul Azizah
; Reza Anada Putri
; Vieronica Varbi Sununianti
; Istiqomah Istiqomah
; Deni Aries Kurniawan
RISOMA : Jurnal Riset Sosial Humaniora dan Pendidikan
Vol 4
, No 3
(2026)
This study aims to analyze public concerns regarding fast food consumption from the perspective of risk society, particularly among university students. The increasing consumption of fast food reflects shifts in consumption patterns influenced by globalization, practicality, and time efficiency. This research employs a qualitative approach through a literature review supported by interview data to strengthen the analysis. The findings reveal that fast food consumption is not solely driven by bio...
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Rancang Bangun Sistem Informasi Penyedia Jasa Instalasi Listrik Berbasis Web dengan Metode OOAD : Studi Kasus pada CV Givas Jaya Sentosa
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Vol 4
, No 1
(2026)
The development of information technology requires service companies to improve the effectiveness and quality of their services, including in the field of electrical installation services. CV Givas Jaya Sentosa still faces problems in managing orders, customer data, and technician scheduling, which are done manually, resulting in inefficiency. This study aims to design and build a web-based electrical installation service provider information system using the Object Oriented Analysis and Design...
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Implementing XGBoost Model for Predicting Customer Churn in E-Commerce Platforms
Andy Hermawan
; Aji Saputra
; Muhammad Dhika Rafi
; Syafiq Basmallah
; Yilmaz Trigumari Syah Putra
; Wafa Nabila
Repeater : Publikasi Teknik Informatika dan Jaringan
Vol 3
, No 2
(2025)
Customer churn is a major challenge in e-commerce, directly affecting revenue and profit. This study aims to develop a machine learning model using XGBoost to predict churn probability. To handle class imbalance, SMOTE was applied as a resampling method, and hyperparameter tuning was performed to enhance performance. The model was evaluated using the F2-score, prioritizing recall while maintaining precision. The results show that the XGBoost model with SMOTE achieves strong performance, with an...
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Predicting Hotel Booking Cancellations Using Machine Learning for Revenue Optimization
Andy Hermawan
; Aji Saputra
; Nabila Lailinajma
; Reska Julianti
; Timothy Hartanto
; Troy Kornelius Daniel
Router : Jurnal Teknik Informatika dan Terapan
Vol 3
, No 1
(2025)
Hotel booking cancellations pose significant challenges to the hospitality industry, affecting revenue management, demand forecasting, and operational efficiency. This study explores the application of machine learning techniques to predict hotel booking cancellations, leveraging structured data derived from hotel management systems. Various classification algorithms, including Random Forest, XGBoost, and LightGBM were evaluated to identify the most effective predictive model. The findings revea...
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Leveraging the RFM Model for Customer Segmentation in a Software-as-a-Service (SaaS) Business Using Python
Andy Hermawan
; Nila Rusiardi Jayanti
; Aji Saputra
; Army Putera Parta
; Muhammad Abizar Algiffary Thahir
; Taufiqurrahman Taufiqurrahman
Maeswara : Jurnal Riset Ilmu Manajemen dan Kewirausahaan
Vol 2
, No 5
(2024)
Customer segmentation plays a pivotal role in driving marketing strategies and improving customer retention across various industries. This study explores the application of the RFM (Recency, Frequency, Monetary) model for customer segmentation in a Software-as-a-Service (SaaS) business, using Python for efficient data processing and analysis. By analyzing one year of customer purchase data, we segmented customers into key groups such as "Champions," "Loyal Customers," and "At Risk." The results...
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Analisis Segmentasi Pelanggan Berbasis RFM dan Evaluasi Efektivitas Kampanye Pemasaran untuk Meningkatkan Retensi
Andy Hermawan
; Fachmi Aditama
; Lintang Rizki Ramadhani
; Nuur Muhammad Ilham
; Aji Saputra
; Nila Rusiardi Jayanti
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Vol 2
, No 4
(2024)
This research implements RFM (Recency, Frequency, Monetary) analysis to perform customer segmentation and evaluate the effectiveness of marketing campaigns in a retail company. Using a Kaggle dataset, this study identifies customers based on purchasing behaviour and assesses marketing campaign responses for each segment. The analysis reveals that Loyal, VIP, and New Customer segments showed the highest responses, especially in Campaign 6. The findings emphasize the importance of targeting resour...
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Membangun Model Prediksi Churn Pelanggan yang Akurat: Studi Kasus tentang TELCO Company
Andy Hermawan
; Nila Rusiardi Jayanti
; Zia Tabaruk
; Faizal Lutfi Yoga Triadi
; Aji Saputra
; M.Rahmat Hidayat Syachrudin
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Vol 2
, No 6
(2024)
Customer churn prediction models have become an important tool in the telecommunications industry to reduce churn rates and improve customer retention. This research focuses on building an accurate customer churn prediction model using machine learning algorithms for TELCO Company. By applying diverse feature engineering techniques and prediction models such as RandomForestClassifier, DecisionTreeClassifier, and XGBoost, this study showcases a significant improvement in prediction accuracy compa...
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Optimalisasi Strategi Pemasaran Melalui Analisis RFM pada Dataset Transaksi Ritel Menggunakan Python
Andy Hermawan
; Nila Rusiardi Jayanti
; Aji Saputra
; Cahaya Tambunan
; Dzaky Muhammad Baihaqi
; Muhammad Alif Syahreza
; Zacharia Bachtiar
Jurnal Manajemen Riset Inovasi
Vol 2
, No 4
(2024)
This study aims to optimize marketing strategies through RFM (Recency, Frequency, Monetary) analysis on a retail transaction dataset obtained from Kaggle. The dataset contains 64,682 transactions from 5,242 SKUs involving 22,625 customers over one year. Data cleaning and RFM analysis were conducted to segment customers based on recency, frequency, and monetary values. The findings reveal that customers were segmented into groups such as Champions, Loyal Customers, and At Risk. These segments pro...
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Analisis Dampak Kesalahan Pemilihan Jurusan terhadap Prestasi Akademik dan Kesejahteraan Psikologis Mahasiswa
Jurnal Ilmu Kesehatan Umum, Psikolog, Keperawatan dan Kebidanan
Vol 2
, No 2
(2024)
In education, choosing the right college major is crucial for students to achieve their academic and career potential. However, many students in Indonesia still choose majors that do not suit their interests and talents, which hurts their academic achievement and psychological well-being. This research aims to identify the impact of errors in choosing a major on students' academic achievement and psychological well-being. This research used quantitative methods with a cross-sectional design to c...
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Analisis Pengaruh Variabel Nilai TIU, TWK, Dan TKP Terhadap Kelulusan SKD Pada Tes CPNS Menggunakan Analisa Bivariat Sederhana
Andy Hermawan
; Aji Saputra
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Vol 2
, No 1
(2024)
This study aims to assess the impact of the General Intelligence Test (TIU), National Insight Test (TWK), and Personal Characteristics Test (TKP) on the success of the Basic Competency Selection (SKD) for Civil Servant Candidate (CPNS). Using data from participants in the Ministry of Law and Human Rights' SKD selection in 2023, we employed univariate analysis, simple bivariate analysis, and binning methods to comprehend variable relationships. Results reveal non-normal distributions for TIU, TWK...
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