Abstract:In the Industry 4.0 era, achieving sustainable business success requires organizations to harness unique, rare, and inimitable resources. These resources demand a long learning curve within the organization and are critical…
cal for sustaining competitive advantage. This study explores the Era 4.0 Organizational Sustainability Model, a hybrid framework that demonstrates the interrelation of key organizational elements, including core competencies, business outcomes, and strategic objectives essential for long-term operational sustainability. In a landscape of intense competition, survival and growth are imperative goals for organizations. Central to this endeavor is the management of human resources, particularly the Millennial workforce, known for its unique challenges in turning weaknesses into opportunities for development. This research highlights the critical role of tailored talent management strategies in addressing generational characteristics, fostering employee growth, and aligning workforce capabilities with organizational needs. By employing an innovative and holistic HR strategy, organizations can enhance their ability to compete sustainably while driving long-term profitability and resilience in the face of rapid technological and market changes.
Abstract:This study examines the impact of Microfinance Institutions' (MFIs) performance on economic growth in Cambodia, using annual panel data from 62 MFIs for the period 2017–2023. Employing advanced econometric techniques, the…
the findings reveal nuanced relationships between key indicators of MFI performance and GDP growth. Notably, Non-Performing Loans (NPLs) show an unexpected positive relationship with GDP growth, highlighting the Cambodian microfinance sector's resilience in mitigating adverse effects through sustained economic activity. Inflation is also positively associated with GDP growth, suggesting that moderate inflation can drive economic expansion, though careful management is necessary to avoid destabilization. Conversely, the study finds a negative relationship between the number of MFIs and GDP growth, indicating potential inefficiencies from sector oversaturation. Lastly, a positive link between Return on Equity (ROE) and GDP growth underscores the importance of profitability in ensuring financial stability and economic development. The findings emphasize the need for policy measures to manage sector growth, maintain moderate inflation, and enhance MFI profitability for sustainable economic progress in Cambodia.
Keywords: Microfinance Institutions (MFIs); Cambodia; Economic Growth.
Abstract:This study explores the relationship between economic interests and legal formation through the lens of Max Weber's perspective. The key issue addressed is the extent to which economic factors influence legal structures…
and their reciprocal impact on economic systems. The objective is to analyze how economic rationality shapes lawmaking processes and the implications for modern transactions. The study employs a qualitative method, relying on textual analysis of Weber’s works and related legal theories. The findings reveal that economic interests are fundamental drivers of legal predictability, calculability, and stability, which are essential for fostering business growth and investment confidence. However, the tension between formal legal rationality and substantive justice poses challenges to achieving equity. These insights underscore the necessity of a structured legal framework that aligns with dynamic economic needs while ensuring fairness. The results contribute to a deeper understanding of the interplay between economics and law, offering guidance for policymakers to balance economic progress with social equity.
Abstract:This study aims to analyze the impact of Good Corporate Governance (GCG) on tax aggressiveness in mining companies listed on the Indonesia Stock Exchange (IDX). A quantitative approach was used in this research, with secondary…
ondary data obtained from financial statements and annual reports of companies over a certain period. The results show that GCG, particularly independent board commissioners and the frequency of board meetings, has a negative and significant impact on tax aggressiveness. However, the influence of the audit committee and the nomination and remuneration committee on tax aggressiveness is not significant. These findings underscore the importance of stronger GCG implementation to reduce risks associated with corporate tax policies. This study provides important implications for companies and regulators in enhancing effective corporate governance to reduce tax aggressiveness in the mining sector.
Abstract:The major of this study was to estimate the impact of Adoption of Small-Scale Irrigation in Dugda district. Data were collected from both primary and secondary data sources. Primary data was collected from 384 household…
heads in four kebeles of the district using structured questionnaire. Descriptive, logit and propensity score matching techniques were used for data analysis. The study finding from the propensity score matching technique revealed that the incomes of adopters of small scale irrigation were increased by 37,696.06ETB per annum. This calls for strengthening the available irrigation facilities and expansion of irrigation sector in the study area.
Abstract:Analysis of Company Bankruptcy Potential at PT. Gowa Makassar Tourism Development TBK. Thesis. Department of Management, Faculty of Economics and Business. Makassar public university. Supervised by Mr. Muhammad Ilham Wardhana…
dhana Haeruddin and Mr. Nurman. This study aims to determine the potential for corporate bankruptcy at PT. Gowa Makassar Tourism Development Tbk Period 2017 to 2021. The type of research used is quantitative descriptive. The population in this study is the financial statements of PT. Gowa Makassar Tourism Development Tbk. The sample of this research is the income statement and balance sheet from the financial statements of PT. Gowa Makassar Tourism Development Tbk. 2017 to 2021. The data collection technique used is Documentation. Data analysis techniques are used to assess, identify, and explain the possibility of bankruptcy. The results of this study indicate the analysis of the level of bankruptcy of the modified Altman Z-score model of PT. Gowa Makassar Tourism Development TBK. the 2017-2021 period is categorized as being in good health or not bankrupt.
Abstract:This study aims to determine the potential for bankruptcy experienced by industrial companies in the cigarette sub-sector in 2017-2021. This type of research uses descriptive quantitative with a population of issuers in…
the cigarette sub-sector during 2017-2021. Sampling using purposive sampling method to get 4 companies. Data collection was carried out using documentation techniques. Data analysis techniques using the First Altman Z-Score. The results showed that in the last five years the potential for bankruptcy in cigarette sub-sector companies was low because there was only one company that had the potential to go bankrupt, namely PT. Bentoel Internasional Investama Tbk. The company is in a vulnerable precautionary zone for bankruptcy during 2018-2019 and there are indications that the company is experiencing financial difficulties in 2020. The company PT. Gudang Garam Tbk, PT. Hanjaya Mandala Sampoerna, PT. Wismilak Inti Makmur Tbk, has no potential for bankruptcy.
Abstract:Perkembangan pesat teknologi Artificial Intelligence (AI) telah mengubah lanskap pendidikan tinggi secara signifikan, terutama dengan hadirnya tutor virtual berbasis AI yang mampu memberikan umpan balik cepat, tepat, dan…
personal. Analisis Real merupakan salah satu mata kuliah yang paling menantang dalam program pendidikan matematika karena sifat abstraknya sering menyebabkan rendahnya self-efficacy mahasiswa. Penelitian ini bertujuan menganalisis pengaruh pemanfaatan AI sebagai tutor virtual terhadap self-efficacy mahasiswa Pendidikan Matematika Universitas Asahan yang menempuh mata kuliah Analisis Real. Penelitian menggunakan pendekatan kuantitatif dengan desain quasi-experimental one-group pretest-posttest, melibatkan 15 mahasiswa yang dipilih melalui purposive sampling. Instrumen angket self-efficacy dikembangkan berdasarkan tiga dimensi Bandura (magnitude, strength, generality), divalidasi melalui expert judgment dengan Cronbach’s Alpha sebesar 0,84. Hasil analisis deskriptif menunjukkan peningkatan rata-rata skor self-efficacy dari 65,67 (pre-test, kategori sedang) menjadi 79,93 (post-test, kategori tinggi), dengan peningkatan sebesar 21,7%. Uji Wilcoxon Signed-Rank Test menghasilkan nilai Z = −3,408 dengan p-value = 0,001 (p < 0,05), yang mengkonfirmasi terdapat perbedaan signifikan self-efficacy mahasiswa sebelum dan sesudah intervensi enam minggu menggunakan AI tutor virtual.
The rapid development of Artificial Intelligence (AI) technology has significantly transformed higher education, particularly through AI-based virtual tutors capable of providing fast, precise, and personalized feedback. Real Analysis, one of the most challenging mathematics education courses, frequently causes low self-efficacy among students due to its abstract nature and demands for formal proof-writing. This study examines the effect of utilizing AI as a virtual tutor on self-efficacy of mathematics education students at Universitas Asahan. A quantitative quasi-experimental one-group pretest-posttest design was employed with 15 students selected via purposive sampling. The self-efficacy questionnaire was based on Bandura’s three dimensions: magnitude, strength, and generality, validated by expert judgment with Cronbach’s Alpha coefficient of 0.84. Descriptive analysis results showed an increase in mean self-efficacy scores from 65.67 (pre-test, moderate category) to 79.93 (post-test, high category), representing a 21.7% improvement. The Wilcoxon Signed-Rank Test yielded Z = −3.408 with p-value = 0.001 (p < 0.05), confirming a significant difference in student self-efficacy before and after the six-week AI virtual tutor intervention.
Abstract:Penggunaan dompet digital yang terus meningkat menghasilkan banyak ulasan pengguna yang dapat dimanfaatkan untuk mengevaluasi kualitas layanan. Penelitian ini bertujuan meningkatkan akurasi klasifikasi sentimen pengguna…
dompet digital menggunakan metode Stacking Ensemble Machine Learning yang mengombinasikan Support Vector Machine (SVM), Multinomial Naïve Bayes (MNB), dan AdaBoost dengan Logistic Regression sebagai meta-learner. Data ulasan diproses melalui tahapan text preprocessing meliputi case folding, cleaning, tokenizing, stopword removal, stemming, dan pembobotan fitur menggunakan TF-IDF. Penyeimbangan data dilakukan dengan SMOTE, sedangkan evaluasi model menggunakan 5-Fold Cross-Validation. Hasil penelitian menunjukkan bahwa model Stacking Ensemble memperoleh akurasi rata-rata 80,55%, lebih tinggi dibandingkan algoritma dasar. Evaluasi menggunakan Confusion Matrix, Classification Report, dan ROC Curve juga menunjukkan peningkatan nilai precision, recall, F1-score, dan kemampuan diskriminasi model. Hasil ini menunjukkan bahwa pendekatan Stacking Ensemble Machine Learning efektif untuk meningkatkan akurasi klasifikasi sentimen pengguna dompet digital serta mendukung evaluasi kualitas layanan berbasis opini pengguna.
The rapid growth of digital wallet usage has generated a large volume of user reviews that can be utilized to evaluate service quality. This study aims to improve the accuracy of digital wallet user sentiment classification using a Stacking Ensemble Machine Learning approach that combines Support Vector Machine (SVM), Multinomial Naïve Bayes (MNB), and AdaBoost with Logistic Regression as the meta-learner. User reviews were processed through text preprocessing stages, including case folding, text cleaning, tokenization, stopword removal, stemming, and TF-IDF feature weighting. Synthetic Minority Over-sampling Technique (SMOTE) was employed to address class imbalance, while model performance was evaluated using 5-Fold Cross-Validation. The experimental results show that the proposed Stacking Ensemble model achieved an average accuracy of 80.55%, outperforming the individual base learners. Furthermore, evaluations based on the Confusion Matrix, Classification Report, and Receiver Operating Characteristic (ROC) Curve demonstrated improvements in precision, recall, F1-score, and the model's discriminative capability. These findings indicate that the proposed Stacking Ensemble Machine Learning approach is effective in improving the accuracy of digital wallet user sentiment classification and can serve as a reliable tool for supporting service quality evaluation based on user opinions.
Abstract:This study aims to determine the effect of using Google Earth media through the Contextual Teaching and Learning (CTL) model on the learning outcomes of social studies on natural phenomena material for fifth-grade students…
ts of SDN Telang 2 in the 2026/2027 academic year. The study used a quantitative approach with the Pre-Experimental Design method and One Group Pretest-Posttest Design. The research subjects were 17 students. Data collection techniques were carried out through tests, observations, and documentation. The research instrument was a multiple-choice test given before and after treatment. Data were analyzed using descriptive statistics and paired sample t-test. The results showed that the average pretest score of 68.82 increased to 79.41 in the posttest, with an increase of 10.59 points. The results of the paired sample t-test showed a significance value (2-tailed) of 0.000 <0.05, so H₀ was rejected and H₁ was accepted. These findings indicate that the use of Google Earth media through the CTL model has a significant effect on the learning outcomes of social studies on natural phenomena material. The integration of Google Earth and CTL provides a more contextual, interactive, and meaningful learning experience, helping students understand the concept of natural features more concretely. Therefore, Google Earth, through the CTL model, can be used as an alternative media and effective learning model to improve social studies learning outcomes in elementary schools.
Penelitian ini bertujuan untuk mengetahui pengaruh penggunaan media Google Earth melalui model Contextual Teaching and Learning (CTL) terhadap hasil belajar IPS materi kenampakan alam pada siswa kelas V SDN Telang 2 Tahun Pelajaran 2026/2027. Penelitian menggunakan pendekatan kuantitatif dengan metode Pre-Experimental Design dan desain One Group Pretest-Posttest Design. Subjek penelitian berjumlah 17 siswa. Teknik pengumpulan data dilakukan melalui tes, observasi, dan dokumentasi. Instrumen penelitian berupa tes pilihan ganda yang diberikan sebelum dan sesudah perlakuan. Data dianalisis menggunakan statistik deskriptif dan uji paired sample t-test. Hasil penelitian menunjukkan bahwa nilai rata-rata pretest sebesar 68,82 meningkat menjadi 79,41 pada posttest, dengan peningkatan sebesar 10,59 poin. Hasil uji paired sample t-test menunjukkan nilai signifikansi (2-tailed) sebesar 0,000 < 0,05, sehingga H₀ ditolak dan H₁ diterima. Temuan ini menunjukkan bahwa penggunaan media Google Earth melalui model CTL berpengaruh signifikan terhadap hasil belajar IPS materi kenampakan alam. Integrasi Google Earth dan CTL mampu memberikan pengalaman belajar yang lebih kontekstual, interaktif, dan bermakna sehingga membantu siswa memahami konsep kenampakan alam secara lebih konkret. Oleh karena itu, Google Earth melalui model CTL dapat dijadikan alternatif media dan model pembelajaran yang efektif untuk meningkatkan hasil belajar IPS di sekolah dasar.