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All Journal Syntax Literate: Jurnal Ilmiah Indonesia JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science Jurnal Indonesia Sosial Teknologi Journal Research of Social Science, Economics, and Management Journal of Business, Social and Technology Jitu: Jurnal Informatika Utama Journal of Innovation and Operational System
Riyan, Ade Bani
Politeknik Siber Cerdika Internasional
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences Transportation Other

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Smart School Sebagai Sarana Informasi Sekolah di SDIT Ibnu Khaldun Cirebon Ade Bani Riyan; Dwi Teguh Afandi; Tuti Hartati; Dita Rizki Amalia; Odi Nurdiawan
JURIKOM (Jurnal Riset Komputer) Vol 8, No 6 (2021): Desember 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v8i6.3681

Abstract

The need for information in the world of education in this modern era is very important in determining the progress of an institution. By implementing and utilizing information technology can facilitate school institutions in organizing data and will produce a database file that will make it easier for users to access data. However, the use of information technology at SDIT Ibnu Khaldun Cirebon has not been used optimally. This is where the author's desire to create a Smart School application emerged, which is an application that functions as an academic information application to support daily activities at the school.This study aims to improve the quality of schools and meet the needs of schools and parents in disseminating general school information, and student academic information at SDIT Ibnu Khaldun Cirebon.The method used in this research is the research and development method. Data collection techniques in this study using interviews. This research was conducted at SDIT Ibnu Khaldun by involving teachers, principals, students, and parents of students as research subjects.Based on the results of testing with the black box method on the Smart School application, it can be concluded that functionally it produces results that are in line with expectations
Sales Application on Distro Souplay Ade Bani Riyan
Journal of Business Social and Technology Vol. 1 No. 1 (2020): Journal of Business, Social and Technology
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (376.35 KB) | DOI: 10.59261/jbt.v1i1.27

Abstract

The development of the business world is now inseparable from the support of technology, especially computer technology and information because in increasingly modern economic activities are needed the existence of computer technology to support and facilitate all economic activities in order to achieve these goals. With the use of computers as a tool in Distro Souplay does not mean without problems, there are still troublesome things and obstacles to create a comfortable and efficient atmosphere while in Distro suoplay. The accumulation of irregular goods data. The slow search for data needed when ordering an item of goods Adds knowledge and insights, especially about the sale of goods and implements the science obtained in lectures into the business world.
Pengembangan Model Sistem Informasi Geografis Angkot Online Berbasis SCRUM: Ujicoba Kelayakan Rifa’i, Mochamad Fikri; Ghazali, Dexsa Muliana; Riyan, Ade Bani
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2581

Abstract

Angkot drivers can compete with online transportation in getting passengers via smartphones. This application is based on a geographic information system, which is a system that can show the location of a person or place online, using this system to be integrated with public transportation makes it possible to add or pick up passengers more efficiently not only by waiting in one place but can pick up passengers according to the location of the passenger and the transportation route. To overcome the above problems, making applications with a technology theme is one of the right solutions for innovative methods that will be applied to public transportation drivers so they can get passengers efficiently. The purpose of this study is to determine the user's response to the application that has been developed. The research method used is research and development with a 4D development model with “define, design, development, and dissemination stages”. Data collection was carried out by distributing questionnaires to several respondents, while the trial stages carried out included alpha version trials, beta versions trials, Version Release, and Implementation. The results of the study show that the indicators of language, appearance, and accessibility of applications that have been developed are classified as "very feasible". The developed online angkot application is expected to be a solution in dealing with technological developments that can be applied to public transportation
Perkembangan Kecerdasan Buatan (AI) Dan Dampaknya Pada Dunia Teknologi Zaenudin, Imam; Riyan, Ade Bani
Jurnal Pendidikan Umum Vol 2 No 2 (2024): Jitu: Jurnal Informatika Utama
Publisher : CV. Astina Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55903/jitu.v2i2.240

Abstract

Kecerdasan buatan (Artificial Intelligence – AI) telah berkembang pesat dalam beberapa dekade terakhir dan menjadi pendorong utama transformasi digital di berbagai sektor. AI telah diterapkan dalam industri, kesehatan, keuangan, transportasi, dan pendidikan, memungkinkan peningkatan efisiensi, otomatisasi, serta pengambilan keputusan berbasis data. Namun, perkembangan AI juga menghadirkan tantangan besar, seperti kesenjangan regulasi, bias algoritma, ancaman terhadap privasi data, serta dampaknya terhadap pasar tenaga kerja. Oleh karena itu, penelitian ini bertujuan untuk mengkaji evolusi AI, implikasinya dalam dunia teknologi, serta tantangan dan prospek pengembangannya di masa depan. Penelitian ini menggunakan kajian literatur dan analisis data sekunder dari jurnal ilmiah, buku akademik, serta laporan industri dari lembaga seperti McKinsey, World Economic Forum, Gartner, dan Stanford AI Index Report. Hasil penelitian menunjukkan bahwa AI telah meningkatkan produktivitas hingga 40% di berbagai sektor industri, dengan dampak ekonomi yang diproyeksikan mencapai $15,7 triliun pada tahun 2030. Di sektor kesehatan, AI mampu meningkatkan akurasi diagnosis hingga 96%, sementara dalam industri manufaktur, teknologi berbasis AI telah mengurangi downtime produksi sebesar 30%. Namun, tantangan utama yang dihadapi mencakup kesenjangan regulasi AI di berbagai negara, isu bias algoritma dalam pengambilan keputusan, serta risiko penggantian tenaga kerja akibat otomatisasi. Kesimpulan dari penelitian ini menegaskan bahwa AI memiliki potensi besar untuk terus berkembang dan memberikan manfaat luas, tetapi pengelolaannya harus dilakukan secara bertanggung jawab. Regulasi yang lebih komprehensif, adopsi Explainable AI (XAI), serta strategi upskilling tenaga kerja menjadi faktor kunci dalam memastikan bahwa AI berkembang secara berkelanjutan dan memberikan dampak positif bagi masyarakat global.
Digital Transformation Strategies for Operational Resilience in Manufacturing: A Case Study Approach Ade Bani Riyan
Journal of Innovation and Operational System Vol. 1 No. 1 (2024): Journal of Innovation and Operational System
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jiosjournal.v1i1.4

Abstract

This study examines the impact of digital transformation strategies on operational resilience within the manufacturing sector through a qualitative case study approach. Data were collected from five manufacturing firms across the automotive, electronics, and consumer goods sectors, focusing on the role of technologies such as IoT, data analytics, and automation in enhancing agility and responsiveness. Findings indicate that digital transformation initiatives, particularly IoT and predictive analytics, significantly improve operational resilience by enabling real-time data collection, proactive risk management, and enhanced decision-making. However, challenges such as employee resistance and integration with legacy systems highlight the need for tailored implementation strategies, including phased technology adoption and comprehensive training programs. This study supports theories of dynamic capabilities and resilience, suggesting that a strategic alignment of digital transformation efforts can foster long-term operational adaptability. Practical implications emphasize the importance of embedding digital initiatives within overall organizational strategy to ensure resilience in dynamic market conditions. Future research could explore the long-term impacts of digital transformation on resilience across various sectors.
Pendekatan Kecerdasan Buatan Hibrida dalam Meningkatkan Akurasi Prediksi Churn pada Big Data Ade Bani Riyan; Syahrul Anwar; Eko Siswo Adi Sahputra
Jurnal Indonesia Sosial Teknologi Vol. 6 No. 8 (2025): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v6i8.9094

Abstract

The explosion of digital data has given birth to the era of big data, which presents great opportunities as well as significant challenges in knowledge extraction. Traditional data mining processes often face obstacles in terms of accuracy and efficiency when faced with massive data volume, variety, and speed. This study aims to propose and evaluate a hybrid model based on Artificial Intelligence (AI) to improve the performance of the data mining process on large-scale data sets. The proposed model integrates the power of Random Forest's algorithm in handling structured data and resistance to overfitting, with the ability of Neural Networks to model complex non-linear relationships. The research uses a case study on customer churn data from the e-commerce industry which contains 1.5 million records, with comprehensive data mining process stages, ranging from data preprocessing, feature engineering, to model implementation. The results of the evaluation showed that the hybrid model achieved an accuracy of 94.7% and an AUC (Area Under the Curve) value of 0.97, significantly outperforming the Random Forest (91.2% accuracy, 0.93 AUC) and Artificial Neural Network (92.5% accuracy, 0.95 AUC) models. Although hybrid models require slightly higher computational times, the substantial increase in accuracy provides a strong justification for their use in critical business scenarios. This study provides empirical evidence that the hybrid AI approach is an effective and promising strategy to address the challenges of big data analysis, particularly in critical business scenarios where predictive accuracy is a top priority.
The Influence of Business Model Canvas and Value Proposition Canvas on MSME Productivity: Structural Analysis Approach Muhammad Khoirul Umam; Puteri Kamilla; W.Sigit Rahardjo; Ade Bani Riyan
Journal Research of Social Science, Economics, and Management Vol. 5 No. 9 (2026): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jrssem.v5i9.1439

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a strategic role in economic growth and employment in Indonesia; however, their productivity remains suboptimal due to limitations in business model design and the alignment of value propositions with market needs. This research aims to analyze the effect of the Business Model Canvas (BMC) and Value Proposition Canvas (VPC) on MSME productivity using a structural analysis approach. The research employs a quantitative explanatory method, using primary data collected from 161 MSME respondents via a Likert-scale questionnaire and analyzed with Structural Equation Modeling based on Partial Least Squares (SEM-PLS). The results indicate that both the Business Model Canvas and the Value Proposition Canvas have a positive and significant effect on MSME productivity, with effects partially and simultaneously. Business Model Canvas shows the most dominant influence, while Value Proposition Canvas enhances alignment between value offerings and customer needs. The model explains 78.8% of the variance in MSME productivity. These findings highlight that the integration of business models and value propositions is a key factor in improving productivity and competitiveness of MSMEs.
Digital Transformation of Student Assignment Management through a Mobile-Friendly E-Learning System Integrated with WhatsApp Gateway and Google Drive Syahrul Anwar; Abdul Robi Padri; Ade Bani Riyan; Eko Siswo Adi Sahputra
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v11i6.64930

Abstract

Objective: To develop a mobile-friendly e-learning system for managing student assignments that integrates with a WhatsApp Gateway and Google Drive, aiming to translate digital transformation in higher education into simple, rapid, and integrated assignment management processes. Methods: This study employs a Research and Development (R&D) approach using the ADDIE model, which includes needs analysis, architectural design, prototype development, limited implementation, and evaluation of usability and functionality. The proposed system features assignment creation, automatic WhatsApp reminders, Google Drive file integration, submission status tracking, and mobile-first dashboards. The evaluation is conducted through expert validation, black-box testing, System Usability Scale (SUS) measurement, and Likert-based user perception questionnaires. Results: The implementation of the system is expected to yield improved on-time assignment submissions, a reduction in late submissions, a more efficient workflow for lecturers, and the establishment of an economical yet reliable small-scale personal Learning Management System (LMS) model. Conclusion: This research provides significant practical contributions for educational institutions seeking a lightweight, compliant, and readily adoptable digital assignment management system that enhances learning flexibility and academic engagement.
Co-Authors Abdul Robi Padri Dita Rizki Amalia Dwi Teguh Afandi Eko Siswo Adi Sahputra Ghazali, Dexsa Muliana Muhammad Khoirul Umam Odi Nurdiawan Puteri Kamilla Rifa’i, Mochamad Fikri Syahrul Anwar Tuti Hartati W.Sigit Rahardjo Zaenudin, Imam