Abstract:This study aims to determine the effect of service quality on repurchasing and the effect of customer satisfaction on repurchasing halal fashion products at the Bone Sewing House (RJA). The variables used are Service Quality…
lity (X1), Customer Satisfaction (X2) as the independent variable and Repurchase (Y) as the dependent variable. This study uses a quantitative approach. The research was conducted using a purposive sampling technique, with a sample of 80 respondents. The data collection method was through distributing questionnaires to the customer population of the Bone Sewing House (RJA). The data analysis technique used is Partial Least Square (PLS). The results of this study indicate that service quality (X1) has a significant effect on repurchase (Y) and customer satisfaction (X2) has a significant effect on repurchase (Y) with a sig value of 0.000, which means the value is less than α 0.05 or (0.000 < 0.05).
Abstract:This study aims to find out how the effect of e-service quality on e-loyalty through e-satisfaction at Mandar Coklat Shop Macoa. The population in this study were customers at Mandar Coklat Shop Macoa the sample used was…
60 customers. Data collection was carried out using the questionnaire method which was distributed via Google from. The data analysis technique used is partial least squares (PLS) using measurement model analysis (outer model) and structural model analysis (inner model) where the research results show a direct effect of E-Service (X) on E-Loyalty (Y), where from the results of the statistical test the result is a p-value (0.011) <0.05, which means that the p-value is less than the significance level of 0.05 so that there is a direct effect of E-Service on E -Loyalty.
Abstract:This research aims to know and explain the effects of internal motivation (X1) and external motivation (X2) on teacher Performance (Y). To figure out the internal motivation influence (X1) partially towards the teacher's…
performance (Y) and external motivation influence (X2) partially towards the teacher's performance (Y). This research was conducted at SMP Negeri di Tarowang Kabuaten Jeneponto Sub-district. The population and samples in this study are all honorary teachers at SMP Negeri in Tarowang Sub-district of Jeneponto district amounting to 34 people. The data collection techniques are done by providing questionnaires and observations. The data analysis technique used is multiple linear regression through the SPSS 21 application. External motivation to the performance of the honorary teachers had a very strong relationship. The results of multiple linear regression analyses showed that the contribution given by internal motivation and external motivation to the performance of the honorary teacher of the state Junior high School in Tarowang sub-district of Jeneponto was 63%.
Abstract:This research is a qualitative research that aims to find out how the level of financial literacy affects the sustainability of SMEs in Gowa Regency. The sample in this study consisted of 8 informants from small and medium…
um enterprises. The research data analysis technique uses the help of Atlas.ti 9. The results of the analysis show thatsmall businesses are classified as sufficient literate (62.5%) and medium businesses are classified as well literate (37.5%). Based on the financial literacy of SMEs, it can be concluded that small businesses have potential and medium businesses have great potential for sustainability.
Abstract:This research aims to determine the application of value chain model in zakat management at the Makassar City National Amil Zakat Agency. Population in this research is financial statements BAZNAS Makassar City in 2016 to…
o 2018. Sample this research is data zakat conducted by BAZNAS Makassar City in 2016-2018. Data collection in research is by documentation, observation and interviews. The analysis technique used is descriptive method of value chain model analysis. The results showed that value chain model application can describe the activities carried out and increase the BAZNAS Makassar City value added. Primary activities consisting of zakat receipts, management functions application, zakat distribution, distribution and services. Furthermore secondary activities consist of administration, technology development, human resources management, and institutional facilities.
Abstract:Viral Marketing is a trend that is able to attract the attention of consumers through social media. This study aims to determine the effect of viral marketing and brand image on purchase decisions through e-trust. This research…
esearch is a quantitative study using the SPSS 22 program. The population in this study is Kahf's Instagram followers. The sample in this research is 200 respondents. In addition, to test the feasibility of the instrument used validity and reliability tests, classical assumption tests, and hypothesis testing. Path analysis analysis technique. The results of this study indicate that (1) viral marketing has a positive and significant effect on e-trust, (2) brand image has a positive and significant effect on e-trust (3) viral marketing has a positive and significant effect on purchase decisions, (4) brand image has a positive and significant effect on purchase decision, (5) e-trust has a positive and significant effect on purchase decision. Based on the research results, suggestions for business actors provide more attractive advertisements for consumers, make product designs more attractive, and set products according to needs.
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:The advancement of information technology has accelerated digital transformation in healthcare, particularly through the implementation of Electronic Medical Records (EMRs). However, many healthcare facilities still use…
hybrid systems that combine manual and digital record-keeping without proper integration, resulting in inefficient patient data management. This study aims to develop an integrated hybrid Electronic Medical Record system at Damai Clinic to improve healthcare services and patient data management. A descriptive research method with a system development approach was employed through system analysis, problem identification, and system design. The results indicate that the proposed system successfully integrates patient registration, medical examination, pharmacy services, payment, and reporting into a single system. The hybrid implementation allows paper-based records to remain as supporting archives while electronic records become the primary source of patient information. The developed system is expected to improve service efficiency, reduce documentation errors, enhance data security, and support digital transformation in healthcare facilities.
Abstract:Promosi penerimaan mahasiswa baru (PMB) merupakan salah satu faktor penting dalam meningkatkan jumlah dan kualitas calon mahasiswa. Namun, strategi promosi yang belum memanfaatkan data historis secara optimal dapat menyebabkan…
babkan kegiatan promosi kurang tepat sasaran. Penelitian ini bertujuan untuk menganalisis data historis PMB sebagai dasar dalam menyusun strategi promosi yang lebih efektif pada Jurusan Teknologi Informasi dan Komputer Politeknik Negeri Lhokseumawe. Penelitian menggunakan pendekatan kuantitatif deskriptif dengan memanfaatkan data sekunder PMB periode 2023–2025. Analisis dilakukan melalui tahapan data cleaning, transformasi data, statistik deskriptif, segmentasi calon mahasiswa, dan visualisasi data menggunakan dashboard analitik. Variabel yang dianalisis meliputi program studi, asal sekolah, jurusan asal sekolah, kecamatan, kabupaten/kota, provinsi, jalur masuk, dan sumber informasi pendaftar. Hasil penelitian menunjukkan bahwa sebagian besar pendaftar berasal dari Provinsi Aceh, khususnya Kabupaten Aceh Utara dan Kota Lhokseumawe, dengan dominasi lulusan jurusan IPA serta peminat terbesar pada Program Studi Teknik Informatika. Instagram dan website menjadi sumber informasi utama bagi calon mahasiswa. Pemanfaatan data historis melalui visualisasi data mampu memberikan informasi yang lebih komprehensif mengenai karakteristik calon mahasiswa sehingga dapat mendukung pengambilan keputusan dalam penyusunan strategi promosi PMB yang lebih terarah, efektif, dan berbasis data.
New student admissions (PMB) promotion is an important factor in increasing the number and quality of prospective students. However, promotional strategies that do not optimally utilize historical data can result in less targeted promotional activities. This study aims to analyze historical PMB data as a basis for developing a more effective promotional strategy in the Information and Computer Technology Department of the Lhokseumawe State Polytechnic. The study uses a descriptive quantitative approach utilizing secondary PMB data for the 2023–2025 period. The analysis was carried out through the stages of data cleaning, data transformation, descriptive statistics, prospective student segmentation, and data visualization using an analytical dashboard. The variables analyzed included study program, school of origin, major of origin of school, sub-district, regency/city, province, admission route, and applicant information sources. The results show that most applicants come from Aceh Province, especially North Aceh Regency and Lhokseumawe City, with a predominance of science graduates and the greatest interest in the Informatics Engineering Study Program. Instagram and websites are the main sources of information for prospective students. The use of historical data through data visualization can provide more comprehensive information regarding the characteristics of prospective students so that it can support decision-making in developing more targeted, effective, and data-based PMB promotion strategies.