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Basis Data Semu Menggunakan Lembar Kerja Elektronik pada Sistem Otomatisasi Perkantoran Feri Sulianta
Jurnal Sekretaris dan Administrasi Bisnis Vol 1 No 1 (2017): Jurnal Sekretaris dan Administrasi Bisnis
Publisher : LPPM Universitas Taruna Bakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31104/jsab.v1i1.9

Abstract

The development of information technology nowadays encourages users to use the software appropriately so that commercial software can be maximally empowered that contribute to the efficiency and effectiveness of the job. To support its work, users use Microsoft's Microsof Excel Office Automation System worksheet commonly used by end users for clerical, repetitive and independent work. Microsoft Excel applications are generally used for office worker, clerical computation and users generally use only a portion of the features of some features owned by the application. In this case, the user can maximize the ability of Excel by creating an interactive pseudo database using only Microsoft Excel, so users can organize data with automated database schema. It is intended for time efficiency and also improves the data security factor of human error in handling data. Keywords: Office Automation System, Pseudo Database, Electronic Worksheet, Automatic
ATURAN ASOSIASI MENGGUNAKAN ALGORITMA APRIORI UNTUK MENCIPTAKAN STRATEGI PEMASARAN PADA APOTEK Feri Sulianta; Eriko Prayogo
E-Link: Jurnal Teknik Elektro dan Informatika Vol. 19 No. 1: Mei 2024
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/e-link.v19i1.5951

Abstract

The sales of pharmaceutical products among the public are increasing, especially with the recent pandemic that has led to an increase in drug sales. This has created significant potential for the pharmaceutical industry or drug sales businesses. However, proper marketing plans are required in the pharmaceutical industry to optimize revenue. Analyzing drug sales trends can provide valuable insights for creating excellent marketing plans. To develop a superior marketing plan, an analysis of sales transaction data is necessary with the help of data mining, which is useful for obtaining important information from the dataset being analyzed. The Apriori algorithm is used in this research to examine association rule patterns of drug sales in pharmacies The sales information used as dataset is consisting of 600,000 transactional data collected over six years (2014–2019). This dataset includes the date and time of sales, pharmaceutical drug brands, and other relevant information.
Digital Marketing Maturity Models: A Comprehensive Literature Review Endang Amalia; Feri Sulianta; Ucu Nugraha
International Journal of Multidisciplinary Approach Research and Science Том 4 № 01 (2026): International Journal of Multidisciplinary Approach Research and Science
Publisher : PT. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/ijmars.v4i01.2087

Abstract

Digital marketing has become a critical enabler of organizational transformation, requiring firms to adopt customer-centric strategies and optimize processes in increasingly complex environments. However, the conceptualization and measurement of digital marketing maturity remain inconsistent across the literature. This study addresses this gap by conducting a Systematic Literature Review (SLR) of evolutionary digital marketing maturity models published between 2020 and 2024. Following a four-stage methodological framework—comprising selection and exclusion criteria, database search, quality assessment, and data extraction and synthesis—the review identifies similarities, differences, strengths, and limitations among existing models. The findings reveal that while current models provide useful structures for guiding digital transformation, they lack a precise conceptual definition and standardized measurement framework. The study contributes theoretically by advancing the operationalization of digital maturity and practically by offering executives a framework to assess, benchmark, and monitor progress in digital transformation. Furthermore, it establishes a foundation for future research on the relationship between digital maturity and corporate performance across cultural and regional contexts.
DEVELOPING AN IT INFRASTRUCTURE MODEL FOR ENHANCING DIGITAL LITERACY THROUGH WEB-BASED LEARNING: A COMPREHENSIVE FRAMEWORK Feri Sulianta; Fitrah Rumaisa; Yan Puspitarani; Sriyani Violina; Ai Rosita
JIKO (Jurnal Informatika dan Komputer) Vol 7 No 3 (2024)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i3.8761

Abstract

In today's rapidly evolving educational landscape, there is a growing need to develop an IT infrastructure model that can effectively support web-based learning environments to enhance digital literacy. The proposed model offers a comprehensive framework for educational institutions to integrate digital technologies into their curricula seamlessly. Key elements of the model include essential hardware, user-friendly software, and advanced security measures, each playing a vital role in creating a seamless, secure, and efficient digital learning experience. This study explores the dynamic interactions among these components and their collective influence on fostering a conducive and productive web-based learning environment. By addressing the need for reliable infrastructure, scalable solutions, and robust security protocols, the model provides a holistic approach to improving digital literacy in educational contexts. The research underscores the critical role of a well-structured IT infrastructure in supporting digital education, offering actionable insights and recommendations for implementation. Moreover, it emphasizes that a well-developed IT infrastructure is foundational for the long-term success of web-based learning programs, enabling institutions to meet diverse learner needs, adapt to technological advances, and ensure sustainability in the digital education landscape.
Rancang Bangun Website Edukatif di Sekolah SDN 162 Warung Jambu Kiaracondong berbasis Laravel Feri Sulianta; Fitrah Rumaisa; Yan Puspitarani; Sriyani Violina; Ai Rosita
Jurnal Pengabdian Masyarakat Indonesia Vol 5 No 4 (2025): JPMI - Agustus 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpmi.3623

Abstract

Dalam era digital, sistem informasi berbasis web menjadi kebutuhan mendesak bagi institusi pendidikan untuk meningkatkan pendistribusikan informasi akademik, dan keterlibatan pendidik, peserta didik serta orang tua siswa. SDN 162 Warung Jambu Kiaracondong menghadapi kendala dalam peningkatan visibilitas dan pendistribusian informasi sekolah yang masih dilakukan secara manual. Oleh karena itu, dilakukan perancang dan pengembangkan situs web sekolah berbasis Laravel menggunakan metode Waterfall sebagai aspek dari digitalisasi pendidikan. Proses pengembangan mencakup analisis kebutuhan, desain, implementasi, pengujian Black Box, serta evaluasi menggunakan alat ukur kualitatif dan deskriptif. Perancangan Antar muka menggunakan metode Design Thinking yang mengakomodasi aspek Interface dan User Experience.  Hasil menunjukkan bahwa situs web ini mampu meningkatkan efisiensi yaitu: mempercepat akses informasi sekolah, serta memperkuat interaksi antara siswa, guru, dan orang tua. Pengujian sistem membuktikan bahwa seluruh fitur berfungsi sesuai dengan spesifikasi yang ditetapkan. Implementasi situs web sekolah ini menjadi solusi yang efektif dalam mendukung digitalisasi pendidikan dan meningkatkan distribusi informasi akademik bagi seluruh pemangku kepentingan di kalangan eduskatif SDN 162 Warung Jambu Kiaracondong.
OPTIMIZING TRANSFORMER-BASED LEARNING MODEL WITH TABTRANSFORMER FOR PREDICTING ANTIBIOTIC SUSCEPTIBILITY FROM MICROBIOLOGY MEDICAL RECORDS Feri Sulianta; Endang Amalia; Rosalin Samiharjo; Noval Eka Herdinata
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.7582

Abstract

Antimicrobial Resistance (AMR) has become a growing threat due to the increase in infections that are unresponsive to conventional therapies. Therefore, the development and optimization of Transformer-based Deep Learning using TabTransformer was employed to model the complex interactions between categorical features. This model was trained to predict antibiotic susceptibility at the individual culture level using the Antibiotic Resistance Microbiology Dataset (ARMD). To address the challenge of highly imbalanced data, the methodology applied includes extensive feature engineering to create historical and clinical variables, as well as the use of Focal Loss during training. After optimization, the final model demonstrated excellent discriminatory ability, with an Area Under the ROC Curve (AUC-ROC) of 0.93 and balanced classification performance, yielding a macro average F1-score of 0.82. Interpretability analysis using SHAP confirmed that patient clinical history and prior drug exposure were the most dominant predictive factors. These findings suggest that the Transformer-based Deep Learning architecture using TabTransformer, combined with clinically relevant feature engineering, can produce a reliable and evidence-based predictive tool