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Pemanfaatan E-Commerce dan Kesiapan Modal dalam Peningkatan Daya Saing Usaha Mikro, Kecil dan Menengah (UMKM) di Kecamatan Sunggal, Deli Serdang Anton Sihombing; Novena Putri Antonia Sihombing
Jurnal Ilmu Manajemen METHONOMIX Vol 8 No 2 (2025): Jurnal Ilmu Manajemen METHONOMIX
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtx.Vol8No2.pp72-80

Abstract

This study aims to analyze the influence of e-commerce utilization and capital readiness on enhancing the competitiveness of Micro, Small, and Medium Enterprises (MSMEs) in Sunggal District, Deli Serdang Regency. The research is motivated by the low competitiveness of MSMEs, which is primarily due to limited adoption of digital technology and weak capital structures. The study adopts a quantitative approach with an associative research design. A total of 70 MSME actors were selected through a census using purposive sampling techniques. Data collection was carried out through questionnaires, and the data were analyzed using multiple linear regression. The results indicate that e-commerce utilization has a positive and significant effect on MSME competitiveness, with a regression coefficient of 0.592 and a significance level of < 0.05. Likewise, capital readiness also shows a positive and significant effect, with a regression coefficient of 0.272. Simultaneously, both variables exert a strong influence, with an F-statistic of 228.065 and a significance value of 0.000. The coefficient of determination (Adjusted R Square) is 0.868, indicating that 86.8% of the variance in competitiveness can be explained by e-commerce utilization and capital readiness. These findings underscore that digital transformation through e-commerce and capital strengthening are key strategies in improving MSME competitiveness. The study recommends digital training, enhanced financial literacy, facilitation of access to financing from financial institutions, and supportive government policies.
Application of Decision Tree Algorithm Method to Analyze Traffic Accident Patterns Rusmin Saragih; Marto Sihombing; Anton Sihombing; Rivalri Kristianto Hondro
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp200-202

Abstract

Traffic accidents are complex problems that involve many variables such as weather conditions, vehicle type, location, and driver behavior. With the development of data processing technology, it is possible to analyze accident data in more depth to find significant hidden patterns. The Decision Tree algorithm is applied to predict the likelihood of an accident occurring and identify the factors that contribute most to the accident. The data used consists of accident records collected from various sources, including official reports and traffic statistics. The Decision Tree algorithm was chosen due to its ability to handle both categorical and numerical data, as well as the ease of interpretation of the analysis results. The results of this study show that factors such as vehicle speed, time of occurrence, and road conditions have a significant influence on the probability of an accident occurring. The results of news extraction are analyzed by creating decision rules to determine the pattern of accidents that occur. This decision rule is in the form of a decision tree with a dataset that uses data with the highest fatalities with the imputation feature mode by concept as a method of handling missing values and toll roads as attributes, resulting in an f1-score value of 60.00% and an accuracy value of 70.40%.
Implementation of Random Forest Algorithm for Classifying Land and Building Tax Arrears and Risk Factor Analysis Dashboard Risky Firmansyah Manik; A M H Pardede; Anton Sihombing
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2326

Abstract

This study aims to develop a predictive model to identify the potential for land and building tax arrears and analyze the dominant risk factors contributing to non-compliance. The research utilizes the Random Forest classification algorithm applied to historical tax data from the Regional Financial and Revenue Management Agency of Binjai City. The approach involves data preprocessing, feature engineering including target encoding for geographical areas, and model training with hyperparameter tuning to optimize classification performance. Furthermore, a web-based interactive dashboard is developed using the Flask framework to visualize the predictions and risk factors. The results demonstrate that the Random Forest model achieves a robust and consistent accuracy of approximately 85% in classifying compliant and non-compliant taxpayers. Feature importance analysis reveals that land area is the most dominant risk factor influencing tax arrears, significantly outweighing other variables. In conclusion, the integration of the Random Forest algorithm with an interactive dashboard provides a highly accurate, efficient, and scalable solution for local governments to transition from reactive tax collection to proactive, data-driven risk management.
Co-Authors ., Novriyenni Achmad Fauzi ACHMAD FAUZI Adelia Ramadani Agung Aulia Tama Ahmad Fauzi Ahmad Nawawi Ambarita, Indah Andriansyah, M Juli Angel, Kiki Annatasia, Kristina Arliana, Lina Astari, Rizki Yulidha Astrika, Rahayu Buaton, Relita Budi Serasi Ginting Budi Serasi Ginting Clara Rosa Wijaya Desty Dwi Putri Dewi, Sintia Dhea Agustina Akmal Dhea Alfiya Ningsih Dini Syahfitri Fauzi Ahmad Muda Fauzi, Achmad Fitri Handayani Fuji Dodo Aritonang Ginting, Budi Serasi Hana Niska Tafonao Hermansyah Sembiring Hotler Manurung husnul khair husnul khair husnul khair Ihsan Wibowo Zakti Indah Malasari Julia Br Sembiring Kadim, Lina Arliana Nur Khair, Husnul Kiki Angel Kiki Angel Lailatul Magfiroh M Agung Hidayat Marto Sihombing Marto Sihombing Melda Pita Uli Sitompul Mhd Ferdiansyah Putra Muammar Khadafi Natalia Sianturi, Ruth Naufal Falaah Nduru Novena Putri Antonia Sihombing Novriyenni Novriyenni Novriyenni, Novriyenni Novriyenni, Novriyenni Pardede, Akim Manaor Hara Pramana, I Gusti Rahmat Ramadhan Ramadani, Suci Ratih Puspadini Ratna Cantika Riski Ramadhansyah Risky Firmansyah Manik Risna Serviya risna serviya risna serviya risna serviya Rivalri Kristianto Hondro Rizki Yulidha Astari Rusmin Saragih, Rusmin Selfira, Selfira Serasi Ginting, Budi Serviya, Risna Shelly Maulia Sihombing, Marto Simanjuntak, Magdalena Simanjuntak, Magdalena Sirait, Suprianto Sri Defriani Br Sembiring Suci Rahmadani Suci Ramadhani, Suci Supri Anto Sirait Suprianto Sirait Syahputra, Siswan Syahputri, Heni Tasya Maysarah Br. Sembiring Tasya Maysarah Sembiring Triono, Arif Yani Maulita