Article Per Year (5 Year)
p-Index From 2021 - 2026
2.663
P-Index
This Author published in this journals
All Journal E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Jurnal Ekonomi, Manajemen, dan Akuntansi Universitas Ngudi Waluyo ProBisnis : Jurnal Manajemen Jurnal Algoritma The International Conference on Education, Social Sciences and Technology (ICESST) Indonesian Journal of Midwifery (IJM) "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika AMMA : Jurnal Pengabdian Masyarakat International Journal of Economics and Management Sciences Jurnal Informatika dan Kesehatan INOVTEK Polbeng - Seri Informatika Management Dynamics: International Journal of Management and Digital Sciences
Kustiyono
Universitas Ngudi Waluyo
Humanities Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Medicine & Pharmacology Nursing Public Health Social Sciences

Published : 17 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 17 Documents
Search

 1   2 
a Sentiment Analysis of Free Meal Plans on Social Media using Naïve Bayes Algorithms Yoga Zaen Vebrian; Kustiyono
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 1 (2025): March
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/3m2fcz69

Abstract

This study analyses public sentiment towards the "Free Meal Plan" initiative introduced by the political pair Prabowo-Gibran. This policy aims to assist underprivileged communities in Indonesia and is a significant issue in the social and political context. Data was collected from the social media platform X (formerly Twitter), gathering 501 relevant comments based on their connection to the topic and high levels of engagement (such as retweets and likes). The comments were then processed using Text Preprocessing and TF-IDF techniques and applied to a Naïve Bayes model. The model achieved an accuracy of 69.3%, a precision of 72%, a recall of 57.05%, and an F1 score of 54.5%. These results indicate that the model is capable of classifying public sentiment, though it has challenges in accurately detecting negative sentiment. These findings provide valuable insights for policymakers to design more effective communication and policy strategies, particularly in addressing criticism or public dissatisfaction. The study highlights the importance of using text processing and machine learning techniques to analyze social media data in a structured way.
Customer Data Management For Citynet Using Geolocation-Based Internet Broadband Registration Form Application Alfiano Aldo Pamungkas; Kustiyono
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 1 (2025): March
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/60hw1d67

Abstract

This study aims to address the inefficiencies in CityNet's customer data management by developing a geolocation-based registration form application. Currently, CityNet relies on Google Forms for data collection and WhatsApp for location sharing, leading to inaccuracies, inefficiencies, and delays in the installation process. The proposed system integrates geolocation to automatically capture customer locations, reducing input errors and streamlining data processing. This research follows the waterfall development model, encompassing needs analysis, system design, implementation, and usability testing involving CityNet administrators and customers. The results indicate an 80% reduction in input errors and a 30% improvement in operational efficiency. Additionally, the system seamlessly integrates with Google Spreadsheet, Telegram, and email, ensuring real-time data synchronisation and faster response times. While the application significantly enhances CityNet's operational workflow, challenges such as user adoption and dependency on internet connectivity remain. This study provides a scalable solution for broadband providers seeking efficient customer data management with location-based automation.
An Evaluation of the Accounting Information System of BUMDes Maju Rahayu Kustiyono Kustiyono
International Journal of Economics and Management Sciences Vol. 2 No. 4 (2025): November : International Journal of Economics and Management Sciences
Publisher : Asosiasi Riset Ekonomi dan Akuntansi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ijems.v2i4.1013

Abstract

Village-Owned Enterprises (BUMDes) function as important economic institutions that contribute to enhancing the welfare and independence of rural communities. BUMDes Maju Rahayu, as one of the rapidly developing BUMDes, requires a reliable and effective accounting information system to support transparent and accountable financial management. This study aims to evaluate the implementation of the accounting information system at BUMDes Maju Rahayu using a qualitative approach with a case study method. Data collection was conducted through in-depth interviews with BUMDes managers and direct observation of financial recording and reporting processes. The findings reveal that the existing accounting system still faces several challenges, including incomplete documentation, limited internal control, and dependence on manual bookkeeping. These issues hinder the accuracy and timeliness of financial information. The study recommends capacity-building for human resources, adoption of technology-based accounting systems, and strengthening of internal control procedures to improve financial management quality and organizational performance in BUMDes operations.
Pengembangan Sistem Informasi Persediaan Barang Menggunakan Model Waterfall untuk Meningkatkan Efisiensi Pengelolaan Stok Fathoni, Muhammad; kustiyono
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2533

Abstract

This study addresses stock-management challenges at Toko Sinar Mulia, where inventory processes are still performed manually and are prone to errors, by designing a web-based inventory system using the Laravel framework. Adopting the Waterfall model within the Software Development Life Cycle (SDLC), the information system aims to improve the efficiency and accuracy of stock recording and management. The main contribution of this research is providing a structured solution for digitizing inventory management, which previously lacked automation, thereby supporting more effective decision-making and store operations.
Prediksi Kepadatan Sampah Menggunakan Metode Regresi Linear Berbasis Web gulo, titusman; Kustiyono
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2550

Abstract

The issue of household waste is a crucial issue that has a direct impact on environmental cleanliness and public health. This study aims to develop a web-based household waste density prediction system using the Laravel framework, employing linear regression to model the relationship between time and waste volume. The research data was obtained through a survey of a number of families who recorded their weekly waste volume in kilograms. This system is designed to provide estimates of waste volume for the following week based on historical data patterns, thereby helping the community and environmental managers at the neighborhood association (RT/RW) level to plan waste collection and transportation more efficiently. The linear regression method was chosen because it is simple yet effective in describing trends in waste volume changes over time. The implementation results show that the system is capable of producing predictions that are close to actual conditions, equipped with informative graphics and a user-friendly interface. With this system, household waste management can be carried out in a more planned, efficient, and data-driven manner.
Sistem Prediksi Kemacetan di Jalan Desa Menggunakan Metode Rule-Based System Ghufronul A, M Mufti; Kustiyono
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2555

Abstract

Traffic congestion does not only occur in urban areas, but is also beginning to be felt in rural areas, especially on main roads connecting villages. This condition can hamper community mobility and inter-regional logistics distribution. To overcome this problem, this study specifically designed and implemented a congestion prediction system on village roads by utilizing historical traffic data, weather conditions, and community activities as the main parameters. The classification method used is the Rule-Based System algorithm. The results of this system can be used by village governments or local transportation managers to take preventive measures, such as adjusting logistics distribution schedules or deploying traffic officers. The system was tested in a village in Central Java, with a prediction accuracy of 87%. These results demonstrate the system's potential in assisting traffic management in villages.
Unlocking the Potential of Metaverse Technology: A Novel Approach to Enhancing Digital Skills and Collaboration in Virtual Workspaces Kustiyono Kustiyono; Asrini Mahdia; Dedi Muliadi; Abeda Muhammad Iqbal
Management Dynamics: International Journal of Management and Digital Sciences Vol. 1 No. 2 (2024): April: International Journal of Management and Digital Sciences
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/managementdynamics.v1i2.483

Abstract

The integration of metaverse technology in employee training has the potential to significantly enhance digital skills, collaboration, and overall learning outcomes in virtual workspaces. This study explores the effectiveness of metaverse-based training compared to traditional methods, focusing on participant engagement, learning retention, and practical application in immersive virtual environments. The results indicate that metaverse technology leads to increased participant engagement, offering real-time communication, interactive simulations, and realistic task scenarios that foster deeper involvement and better skill acquisition. Additionally, the immersive nature of metaverse platforms improves learning effectiveness, especially for high-risk tasks such as medical procedures and technical skills that benefit from hands-on experience. However, challenges such as technological barriers, infrastructure limitations, and initial resistance from employees were identified, requiring organizations to provide adequate support and training for smooth adoption. While the upfront costs of developing and maintaining metaverse training platforms are significant, the long-term benefits—such as scalability, reduced need for physical resources, and enhanced training outcomes—outweigh these initial investments. Organizations looking to implement metaverse-based training solutions should carefully consider the required technological infrastructure, support for employees, and privacy concerns. Future research should explore advancements in metaverse technology, including AI integration, and investigate the broader adoption of these technologies across various industries, focusing on overcoming adoption barriers and measuring their long-term impact on workforce development.
Co-Authors Abdul Aziz Abeda Muhammad Iqbal Ade Pratama Agung Wibowo Alfiano Aldo Pamungkas Asrini Mahdia Aulia, Izza Ghufronul A, M Mufti gulo, titusman Hendri Saputra Hendrike Priventa Hevi Alvina Muhammad Fathoni, Muhammad Muliadi, Dedi Najib Sadam Rinto Sigit Ambar Widyawati Sigit Kharisma Silvi Meilani Sofiyanti, Ida Umi Handayani Wahyu Riani , Rosalina Wira Wati , Adilla Yoga Zaen Vebrian