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All Journal Jurnal Informatika Ekonomi Bisnis Journal of Computer Networks, Architecture and High Performance Computing Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Pengabdian Pelitabangsa Jurnal Informatika Ekonomi Bisnis
Rifa'i, Anggi Muhammad
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Analisis Perubahan Perilaku Konsumen dalam Konteks Bisnis Elektronik Pasca-Pandemi COVID-19: Implikasi dan Strategi Pengembangan Bisnis Gunawan, Achmad Rezky; Amali, Amali; Kurniawan, Jidan Restu; Saepul, Muhammad; Rifa'i, Anggi Muhammad
Jurnal Pelita Teknologi Vol 19 No 1 (2024): Maret 2024
Publisher : Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/pelitatekno.v19i1.4268

Abstract

The COVID-19 pandemic has changed the global business environment significantly, especially in the electronics and e-commerce industries. In this context, consumer behavior has changed dramatically, with a significant increase in online purchases and a preference for brands that offer exceptional digital experiences. The impact of these changes is significant for e-commerce companies, which must adapt their strategies to remain relevant and competitive in an increasingly digital and online marketplace. This analysis focuses on factors that influence changes in consumer behavior, including: Changing purchasing preferences, improving online security and privacy, and seeking better digital experiences. In addition, we discuss business development strategies that can help companies face challenges, such as increasing investment in technology infrastructure, developing marketing strategies that focus on customer experience, and improving data security and privacy. By understanding the dynamics of changing consumer behavior post-pandemic, the business world can take the right steps to position themselves effectively in this growing market and strengthen their competitiveness in the digital business era.
Web-Based Attendance Information System At Diskominfosantik Bekasi District With Prototype Method Panjaitan, John David Willy; Rifa'i, Anggi Muhammad; Suprianto, Asep
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6753

Abstract

The rapid development of information technology has encouraged government agencies to utilize digital systems to improve operational efficiency and effectiveness, including in managing employee attendance data. This study aims to design and implement a Web-Based Attendance Information System at the Department of Communication, Informatics, Statistics, and Encryption (Diskominfosantik) of Bekasi Regency. The system was developed using the prototype method, allowing for a gradual design process involving users directly in evaluation and development. The main features of the system include login authentication for administrators and employees, barcode scanning for attendance validation, GPS data integration to verify attendance locations, digital leave requests, and real-time attendance data management and reporting. System testing was conducted using the black box testing method across various scenarios to ensure all functions operated as expected without errors. The system design is also supported by use case and class diagrams that illustrate the workflow and relationships between entities in the system. The results of the study indicate that the web-based attendance information system can improve recording accuracy, accelerate the attendance data recap process, and support transparency in personnel management. Thus, the system has the potential to serve as a model for other government agencies in digitizing employee attendance processes.
Analisis Sentimen Ulasan Aplikasi Jamsostek dengan SVM, Random Forest, dan Logistic Regression Butsianto, Sufajar; Rifa'i, Anggi Muhammad
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1266

Abstract

The digitalization of public services has encouraged the development of the Jamsostek Mobile (JMO) application by BPJS Ketenagakerjaan. This application is expected to provide convenience in accessing information, JHT claims, and other services. However, user reviews on the Google Play Store show diverse perceptions, ranging from satisfaction to technical complaints. This study aims to conduct sentiment analysis on user reviews of the JMO application by classifying opinions into positive, negative, and neutral sentiments. Data were collected through crawling from the Google Play Store and processed using text preprocessing stages, including data cleaning, case folding, stopword removal, tokenization, stemming, and Term Frequency–Inverse Document Frequency (TF-IDF) weighting. The classification process was then carried out using three machine learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Logistic Regression. The results indicate that negative sentiment dominates with 46%, followed by positive sentiment at 40% and neutral at 14%. Most complaints are related to login difficulties, application errors, and technical bugs in claim features. In terms of algorithm performance, SVM with a linear kernel achieved the highest accuracy of 87.5% and an F1-score of 0.87, outperforming Random Forest (85.3%) and Logistic Regression (82.7%). Academically, this study reinforces the effectiveness of SVM in sentiment analysis using TF-IDF, while practically providing recommendations for BPJS Ketenagakerjaan to improve system stability, login speed, and reduce application bugs to enhance user satisfaction.
Analisis Sentimen Ulasan Aplikasi Jamsostek dengan SVM, Random Forest, dan Logistic Regression Butsianto, Sufajar; Rifa'i, Anggi Muhammad
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1266

Abstract

The digitalization of public services has encouraged the development of the Jamsostek Mobile (JMO) application by BPJS Ketenagakerjaan. This application is expected to provide convenience in accessing information, JHT claims, and other services. However, user reviews on the Google Play Store show diverse perceptions, ranging from satisfaction to technical complaints. This study aims to conduct sentiment analysis on user reviews of the JMO application by classifying opinions into positive, negative, and neutral sentiments. Data were collected through crawling from the Google Play Store and processed using text preprocessing stages, including data cleaning, case folding, stopword removal, tokenization, stemming, and Term Frequency–Inverse Document Frequency (TF-IDF) weighting. The classification process was then carried out using three machine learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Logistic Regression. The results indicate that negative sentiment dominates with 46%, followed by positive sentiment at 40% and neutral at 14%. Most complaints are related to login difficulties, application errors, and technical bugs in claim features. In terms of algorithm performance, SVM with a linear kernel achieved the highest accuracy of 87.5% and an F1-score of 0.87, outperforming Random Forest (85.3%) and Logistic Regression (82.7%). Academically, this study reinforces the effectiveness of SVM in sentiment analysis using TF-IDF, while practically providing recommendations for BPJS Ketenagakerjaan to improve system stability, login speed, and reduce application bugs to enhance user satisfaction.
Pendampingan Promosi Digital UMKM Ayam Monster Rifa'i, Anggi Muhammad; Irfan, Yusuf; Suratman, Suratman
Jurnal Pengabdian Pelitabangsa Vol. 6 No. 01 (2025): Jurnal Pengabdian Pelitabangsa April 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jabmas.v6i01.6064

Abstract

UMKM Ayam Monster adalah usaha mikro di bidang kuliner yang mengandalkan olahan daging ayam sebagai produk utama. Usaha ini berlokasi di area strategis, namun masih menghadapi tantangan besar dalam memperluas jangkauan pasarnya. Meski memiliki potensi untuk menghasilkan produk berkualitas dengan cita rasa khas yang digemari konsumen lokal, pemanfaatan teknologi digital dalam promosi masih menjadi kendala utama. Hingga kini, UMKM Ayam Monster lebih banyak mengandalkan strategi pemasaran tradisional, seperti penyebaran selebaran, promosi dari mulut ke mulut, serta keterlibatan dalam berbagai kegiatan pasar lokal. Sayangnya, pendekatan tersebut dinilai kurang efektif untuk menghadapi persaingan di era digital yang semakin ketat. Program pendampingan ini bertujuan untuk meningkatkan kemampuan UMKM Ayam Monster dalam memanfaatkan teknologi digital sebagai sarana promosi yang lebih efektif. Fokus utamanya mencakup pelatihan digital marketing melalui pemanfaatan media sosial, peningkatan kapasitas penggunaan platform e-commerce seperti Shopee, Tokopedia, dan GrabFood, pendampingan dalam pembuatan materi promosi digital berupa foto produk, poster, hingga video pendek, serta melakukan monitoring dan evaluasi berkala guna memastikan efektivitas serta keberlanjutan strategi promosi yang dijalankan.
Co-Authors Amali, Amali Butsianto, Sufajar Gunawan, Achmad Rezky Irfan, Yusuf Kurniawan, Jidan Restu Panjaitan, John David Willy Saepul, Muhammad Suprianto Suprianto Suratman Suratman