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INDONESIA
Jurnal Mahkota Bisnis (Makbis)
Published by Universitas Mahkota Tricom Unggul
ISSN : -     EISSN : 28302273     DOI : https://doi.org/10.59929
Core Subject : Economy, Science, Education,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science
Jurnal MAKBIS memiliki ISSN 2830-2273. MAKBIS menyediakan sarana publikasi nasional bagi para peneliti baik profesional maupun akademisi pada bidang penelitian yang berhubungan dengan Manajemen Sumber Daya Manusia, E-Marketing, Kewirausahaan, Manajemen Keuangan, Bisnis Syariah. Jurnal MAKBIS diterbitkan oleh Universitas Mahkota Tricom Unggul dengan metode peer-review, secara periodik (2 bulanan) pada bulan: Juni dan Desember
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 76 Documents
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THE INFLUENCE OF SELF-EFFICACY, FINANCIAL MANAGEMENT, AND INVESTMENT KNOWLEDGE ON INVESTMENT INTEREST AMONG GENERATION Z STUDENTS AT UNIVERSITAS MAHKOTA TRICOM UNGGUL Frans Gidion Sinuhaji
Jurnal Mahkota Bisnis (Makbis) Vol 4 No 2 (2025): Jurnal Mahkota Bisnis (Makbis)
Publisher : MTU PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59929/mm.v4i2.123

Abstract

This study examines the influence of self-efficacy, financial (money) management, and investment knowledge on investment interest among Generation Z students at Universitas Mahkota Tricom Unggul. The research employs a quantitative approach using multiple linear regression analysis. The results of the F-test indicate that self-efficacy, money management, and investment knowledge simultaneously have a significant effect on students’ interest in investing (F = 15.520; Sig. = 0.000), confirming that the regression model is statistically fit. The coefficient of determination (R² = 0.445) shows that 44.5% of the variation in investment interest can be explained by the independent variables, while the remaining 55.5% is influenced by other factors outside the model. The Adjusted R Square value of 0.417 suggests good explanatory power. The Durbin–Watson value of 0.720 indicates no serious autocorrelation in the residuals. Overall, the findings highlight the importance of enhancing investment knowledge, financial management skills, and self-efficacy to increase investment interest among Generation Z students. These results provide practical implications for universities and policymakers in designing financial education and investment literacy programs.
TRANSFORMASI SOCIAL CROWDFUNDING DI INDONESIA: ANALISIS REGULASI, INOVASI DIGITAL, PERILAKU DONATUR, DAN DAMPAK SOSIAL DALAM PERSPEKTIF LITERATUR Eka Martyna Theodora; Yenni Yenni; Edi Faisal Harahap
Jurnal Mahkota Bisnis (Makbis) Vol 4 No 2 (2025): Jurnal Mahkota Bisnis (Makbis)
Publisher : MTU PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59929/mm.v4i2.124

Abstract

The advancement of digital technology has transformed philanthropic practices in Indonesia through the emergence of social crowdfunding. This study aims to integrate empirical findings related to regulatory frameworks, digital innovation, donor behavior, social capital, and social impact of crowdfunding in Indonesia. A systematic literature review was conducted on 20 national scholarly articles published between 2015–2024. The analysis employed thematic classification and conceptual synthesis. The findings indicate that the success of social crowdfunding is influenced by trust, transparency, technological innovation, social capital, and digital communication strategies. Islamic crowdfunding also demonstrates significant potential in strengthening social legitimacy. Regulatory and governance issues remain major challenges. This study proposes an integrative conceptual model explaining the relationship between digital innovation, trust, regulation, donor participation, and social impact in contributing to societal welfare. The findings offer theoretical contributions to digital philanthropy literature and practical implications for regulators and platform managers.
STRATEGI AKSELERASI PEMASARAN DIGITAL PADA UMKM KACANG TOJEN DI KELURAHAN RENGAS PULAU DALAM MENGHADAPI PERSAINGAN PASAR MODERN Ali Syah Putra
Jurnal Mahkota Bisnis (Makbis) Vol 4 No 2 (2025): Jurnal Mahkota Bisnis (Makbis)
Publisher : MTU PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59929/mm.v4i2.127

Abstract

The development of digital technology has transformed marketing patterns and business competition, including within the Micro, Small, and Medium Enterprises (MSMEs) sector. The Kacang Tojen MSME located in Rengas Pulau Village faces competitive challenges from modern market products that possess more structured distribution and promotional systems. This study aims to examine digital marketing acceleration strategies that can be implemented by MSMEs to enhance their competitiveness. The method employed in this research is a literature study by analyzing various journals and scientific references related to digital marketing, MSME strategies, and digital transformation. The findings indicate that the optimization of social media, the utilization of marketplaces, strengthening branding, and improving digital literacy are the primary strategies for accelerating the sustainable growth of MSME marketing.
Dinamika Perkembangan Modal Ventura di Indonesia: Sebuah Tinjauan Literatur Arsyaf Tampubolon; Gabril Dhava Obrien Sinamo
Jurnal Mahkota Bisnis (Makbis) Vol 5 No 1 (2026): Jurnal Mahkota Bisnis (Makbis)
Publisher : MTU PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59929/mm.v5i1.138

Abstract

Venture capital has become a strategic financing instrument for the growth of startups and MSMEs in Indonesia, particularly in driving the digital economic transformation. However, its development faces various complex challenges, including the gap between regulation and practice as well as the phenomenon of philosophical shifts that threaten its fundamental characteristics. This research aims to systematically analyze the dynamics of venture capital development in Indonesia through a comprehensive literature review approach. The method used is descriptive qualitative with library research, analyzing selected scholarly articles that discuss regulations, investment practices, comparison of conventional and sharia models, as well as industrial development challenges. The findings reveal three main results. First, there is a paradoxical development pattern where the number of Venture Capital Companies tends to decrease while total assets increase significantly, indicating industrial consolidation. Second, a significant gap exists between regulatory ideals and practices, reflected by the dominance of debt financing compared to equity participation, as well as the "loss of soul" phenomenon marked by the imposition of collateral requirements that shift from risk-sharing to risk-shifting mechanisms. Third, sharia venture capital still lags behind conventional in terms of asset scale due to low literacy rates and limited human resources. This study concludes that policy reformulation is needed to simplify administrative regulations, provide fiscal incentives, and establish a risk guarantee institution to restore the philosophy of venture capital as an inclusive risk-sharing instrument. The research implications provide strategic recommendations for regulators, investors, and business actors in strengthening the role of venture capital as an engine of innovation in Indonesia's digital economy.
Klasifikasi Data Penjualan Handphone Menggunakan Algoritma C4.5 Chris Ignatius Yoni; linca Darni Zai
Jurnal Mahkota Bisnis (Makbis) Vol 5 No 1 (2026): Jurnal Mahkota Bisnis (Makbis)
Publisher : MTU PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59929/mm.v5i1.148

Abstract

The rapid growth of the mobile device industry has intensified competition among smartphone brands in the retail market, making ineffective inventory management and inappropriate sales strategies potential sources of financial loss. This study aims to classify the sales performance of smartphone models based on brand attributes using the C4.5 decision tree algorithm. The training dataset consists of 41 smartphone models from five major brands (Infinix, Oppo, POCO, Vivo, and Xiaomi), with sales performance categorized into three classes: Low-selling, Moderately Selling, and Best-selling. Mathematical calculations indicate that the system's total entropy is 1.504, while the evaluation of the brand attribute produces an Information Gain value of 0.111. The resulting decision tree reveals that the Infinix, POCO, and Xiaomi brands exhibit complete class purity (Entropy = 0.000), consistently corresponding to the Best-selling category. The implementation of this decision tree enables retail management to predict product sales performance at an early stage, thereby optimizing inventory allocation and improving procurement efficiency.
KLASIFIKASI HARGA MOTOR BEKAS MENGGUNAKAN ALGORITMA C4.5 UNTUK MENDUKUNG PENGAMBILAN KEPUTUSAN Senhora Simanjuntak; Nia Agustina
Jurnal Mahkota Bisnis (Makbis) Vol 5 No 1 (2026): Jurnal Mahkota Bisnis (Makbis)
Publisher : MTU PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59929/mm.v5i1.150

Abstract

The increasing volume of used motorcycle transactions has led to the rapid growth of vehicle-related data, providing valuable opportunities to support more objective vehicle price classification. However, in practice, the pricing of used motorcycles is often influenced by subjective assessments, resulting in prices that may not accurately reflect the actual condition of the vehicles. This study aims to apply the C4.5 algorithm to classify used motorcycle prices based on vehicle characteristics contained in the motor_second.csv dataset. The research methodology consists of data collection, data cleaning, data transformation, dataset partitioning into training and testing sets, Decision Tree model construction, and model evaluation using a confusion matrix, classification accuracy, and feature importance analysis. The results demonstrate that the C4.5 algorithm successfully generates an interpretable decision tree capable of explaining the relationship between vehicle attributes and price categories. In addition to producing a classification model, the proposed approach also generates decision rules that can serve as practical guidelines for estimating used motorcycle price categories. Therefore, the C4.5 algorithm can be effectively utilized as a decision support method for the classification of used vehicle prices.
ANALISIS KLASIFIKASI HARGA PENJUALAN MOTOR MENGGUNAKAN METODE DECISION TREE BERBASIS ENTROPY DENGAN PENDEKATAN C4.5 DAN GAIN RATIO Neza Namira; Nidya Banuari
Jurnal Mahkota Bisnis (Makbis) Vol 5 No 1 (2026): Jurnal Mahkota Bisnis (Makbis)
Publisher : MTU PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59929/mm.v5i1.151

Abstract

The rapid growth of the automotive industry has intensified competition in motorcycle sales. Determining the appropriate selling price is one of the key factors in improving a company's competitiveness and profitability. Various factors influence motorcycle selling prices, including brand, model, year of manufacture, engine capacity, vehicle condition, and mileage, resulting in complex data that are difficult to analyze manually. Therefore, a data mining method is needed to process historical motorcycle sales data into valuable information that supports decision-making. This study aims to analyze and classify motorcycle selling prices using the Decision Tree C4.5 algorithm based on entropy and gain ratio. The C4.5 algorithm was selected because it can generate decision rules that are easy to interpret while providing high classification accuracy for both categorical and numerical data. The research process includes data collection, data preprocessing, entropy, gain, and gain ratio calculations, decision tree construction, and classification model evaluation. The results indicate that the C4.5 algorithm is capable of identifying the most influential attributes affecting motorcycle price classification. The resulting decision tree can be used as a basis for effectively predicting motorcycle price categories. Therefore, the Decision Tree C4.5 method can assist motorcycle dealers and automotive businesses in determining appropriate sales strategies based on the characteristics of the vehicles they offer.
KLASIFIKASI REVIEW RATING PRODUK MENGGUNAKAN ALGORITMA DECISION TREE BERDASARKAN DATA TRANSAKSI PENJUALAN Naufal Nur Hidayah; Friska Intan Pasaribu; M Mansyur Lubis
Jurnal Mahkota Bisnis (Makbis) Vol 5 No 1 (2026): Jurnal Mahkota Bisnis (Makbis)
Publisher : MTU PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59929/mm.v5i1.152

Abstract

Increasing business competition requires companies to understand their product sales patterns in order to make appropriate decisions regarding inventory management and marketing strategies. One approach is to classify products based on their sales performance into best-selling and non-best-selling categories. This study aims to apply the C4.5 algorithm to classify products based on sales transaction data. The dataset consists of sales transaction records with attributes such as product category, price, quantity sold, stock, discount, and total sales. The research stages include data collection, data preprocessing, decision tree construction using the C4.5 algorithm, and model evaluation using a confusion matrix. The results indicate that the C4.5 algorithm is capable of generating easy-to-understand classification rules and achieving a good level of accuracy in determining whether products are best-selling or non-best-selling. The resulting model is expected to assist companies in making better decisions regarding inventory procurement, stock management, and the development of more effective promotional strategies.
KLASIFIKASI PERFORMA PENJUALAN AKSESORIS MOTOR MENGGUNAKAN ALGORITMA C4.5 DENGAN PENDEKATAN DATA MINING Difi Basyasyah Chan; Serius Gea
Jurnal Mahkota Bisnis (Makbis) Vol 5 No 1 (2026): Jurnal Mahkota Bisnis (Makbis)
Publisher : MTU PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59929/mm.v5i1.153

Abstract

This study aims to develop and evaluate a sales performance classification model for motorcycle accessories using the entropy-based Decision Tree (C4.5) algorithm, with Random Forest employed as a comparative model. The main objective is to identify the transaction-related factors that most significantly influence sales performance (High or Low) in an accurate and interpretable manner, thereby supporting inventory management decisions in motorcycle accessory businesses. The dataset consists of 832 motorcycle accessory sales transactions recorded throughout 2021, including attributes such as unit price, quantity sold, product category, and transaction month. The research methodology comprises data collection, preprocessing using one-hot encoding, stratified training and testing data partitioning (80:20), model development using the C4.5 and Random Forest algorithms, and performance evaluation based on accuracy, confusion matrix, classification report, ROC-AUC, and 5-fold cross-validation. The experimental results show that the C4.5 model achieved a test accuracy of 79.04% with an average cross-validation accuracy of 81.25%, while the Random Forest model achieved an accuracy of 76.05%. Feature importance analysis indicates that Quantity Tier and Unit Price Tier are the two most influential factors in determining sales performance. In conclusion, the C4.5 algorithm is effective for classifying motorcycle accessory sales performance, as it provides competitive predictive accuracy while maintaining high model interpretability, making it suitable for supporting inventory planning and marketing strategy development.
TEKNOLOGI BLOCKCHAIN PADA PEMASARAN DIGITAL Ali Syah Putra; Errie Margery; Lusiah Lusiah
Jurnal Mahkota Bisnis (Makbis) Vol 5 No 1 (2026): Jurnal Mahkota Bisnis (Makbis)
Publisher : MTU PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59929/mm.v5i1.155

Abstract

The modern era is characterized by the rapid advancement of innovative technologies and their widespread implementation across various economic activities. Digitalization involves the utilization of numerous specialized devices connected to the Internet that perform specific functions. Within an integrated system, server technologies play a crucial role by enabling the storage and processing of large volumes of information, including structured, semi-structured, and unstructured data, through high computational capabilities. The availability of powerful equipment capable of executing complex mathematical models using extensive datasets has accelerated the development and application of various machine learning algorithms. By employing different machine learning approaches, hidden patterns and relationships can be identified from the available information, allowing the creation of effective management solutions to optimize processes at the micro, macro, and meso levels. The growing volume of information has also increased the need to ensure security for both individual users and large confidential databases. At the current stage of technological development, blockchain technology is widely utilized to maintain information security and prevent data falsification within databases.

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