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Pengaruh Kualitas Pelayanan Dan Kualitas Produk Terhadap Kepuasan Pelanggan Coffee Shop PT Jagat Pramudita Aksata: The Influence of Service Quality and Product Quality on Customer Satisfaction of PT Jagat Pramudita Aksata Coffee Shop Hafiz, Abdul; Hastasari, Ratih; Saputra, Wawan
Jurnal Mnajemen | Ekonomi | Akuntansi Vol 2 No 3 (2026): Juni 2026 - Agustus 2026
Publisher : CV Warnak Johanna Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63921/jmaeka.v2i3.418

Abstract

Abstracts - The Coffeee shop industry in Indonesia has seen rapid growth in recent years, driven by changing urban lifestyles, especially among millennials and Gen Z. Coffeee shops are no longer just places to enjoy beverages but have become social and productive spaces. PT. Jagat Pramudita Aksata, originally operating in earphone distribution, has expanded into the F&B sector by launching the Coffeee shop “JOY Listening Space”. In an increasingly competitive market, the company must pay close attention to product and service quality as key drivers of customer satisfaction. This study aims to examine the effect of Service Quality and Product Quality on Customer Satisfaction. A quantitative approach was employed using a non-probability sampling technique with 100 respondents. Data were analyzed using validity and reliability tests, multiple linear regression, t-test, and F-test. The results show that Service Quality does not have a significant partial effect on Customer Satisfaction (t-value 0.754 < t-tabel 1.661), while Product Quality does (t-value 3.174 > t-tabel 1.661). Simultaneously, both variables significantly influence Customer Satisfaction (F-value 9.157 > F-tabel 2.70, sig. 0.001 < 0.005). These findings emphasize the importance of enhancing both product and service quality to retain customer loyalty.
Multivariate Exploration of Food Security in the Sulampua Region Identification of Clusters and Dominant Dimensions of Food Security Saputra, Wawan; Alfiryal, Naufalia; Prasetya, I Putu Gde Inov Bagus; Fitrianto, Anwar; Alifviansyah, Kevin
Journal of Applied Food Technology Vol 12, No 2 (2025)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17728/jaft.29754

Abstract

Food security is a strategic issue closely related to economic development, community welfare, and the achievement of sustainable development goals. The Food Security Index (FSI) is an important instrument for measuring food security conditions at the provincial and district/city levels. However, FSI performance in Indonesia still shows regional disparities, particularly in Sulawesi, Maluku, and Papua (Sulampua), which tend to have low scores. This study aims to explore patterns of food security and vulnerability in Sulampua through multivariate analysis and regional clustering using K-Means and K-Medoids (PAM) methods. The analysis begins with Principal Component Analysis (PCA) to reduce the dimensionality of FSI indicators and identify dominant factors contributing to data variation. The PCA results show that the first three components explain more than 77% of the variance, with dominant factors including poverty, food expenditure, basic infrastructure access, as well as health and nutrition indicators. The clustering analysis produces two main groups: cluster 1, which includes the majority of districts/cities in Sulawesi and Maluku with relatively better food security, and cluster 2, consisting of 16 districts/cities in Papua with significant food insecurity. Cluster validity evaluation indicates that the K-Medoids method performs better than K-Means, being more robust to outliers and producing more consistent cluster separation. This study contributes to the literature by providing multivariate visual exploration and regional classification based on FSI indicators, which can serve as a basis for formulating more targeted food security policies in the Sulampua region.
Regional Clustering of Food Insecurity to Support the Attainment of SDG 2: Zero Hunger through Machine Learning Approaches Nuradilla, Siti; Saputra, Wawan; Rizal, Muhammad
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.475

Abstract

Food security remains a persistent development challenge in Indonesia, with regional disparities posing significant barriers to achieving equitable access to nutritious and sufficient food. This study aims to classify and cluster districts and cities in Indonesia based on their food security vulnerability levels, thereby supporting the attainment of SDG 2: Zero Hunger. We employed a machine learning approach using a dataset of 514 regions and nine food security indicators sourced from national databases. The classification phase compared three algorithms, Random Forest, XGBoost, and LightGBM, under multiple data preprocessing scenarios, including outlier handling (IQR and Isolation Forest) and class balancing (SMOTE). LightGBM with IQR preprocessing delivered the best performance, achieving an accuracy and F1-score of 0.984. For clustering, DBSCAN and HDBSCAN were applied using the six most important features identified by the classifier. DBSCAN showed slightly better performance based on Silhouette Score (0.5639), resulting in three regional groupings: food-secure, highly vulnerable, and outlier regions. The analysis revealed that socio-economic factors and access to basic infrastructure remain critical determinants of food insecurity. The results underscore the importance of data-driven approaches in policy formulation and highlight the value of machine learning in producing more targeted, efficient, and adaptive food security interventions in Indonesia.
Pengaruh Motivasi Kerja Dan Disiplin Kerja Terhadap Kinerja Pegawai Kantor Kecamatan Cibodas : The Effect of Work Motivation and Work Discipline on the Performance of Employees at the Cibodas Subdistrict Office Cahyani, Indah Rahma; Hastasari, Ratih; Saputra, Wawan
Jurnal Mnajemen | Ekonomi | Akuntansi Vol 1 No 4 (2025): September 2025 - November 2025
Publisher : CV Warnak Johanna Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63921/jmaeka.v1i4.190

Abstract

This research is driven by the importance of employee performance in achieving organizational goals. Work motivation and work discipline are considered crucial factors influencing performance. The objective of this study is to analyze the simultaneous and partial effects of work motivation and work discipline on the performance of employees at the Cibodas Sub-district Office. The research method employed is quantitative, utilizing primary data obtained through questionnaires. The population of this study comprises all employees of the Cibodas Sub-district Office. Data analysis included validity tests, reliability tests, multiple linear regression analysis, t-test, F-test, and coefficient of determination. The results of the t-test indicate that work motivation (X1) partially has a significant effect on employee performance (Y) with a Sig. value of 0.000 (< 0.05), and work discipline (X2) also has a significant partial effect with a Sig. value of 0.000 (< 0.05). The F-test results show that work motivation and work discipline simultaneously have a significant effect on employee performance with a Sig. value of 0.000 (< 0.05). The partial coefficient of determination for work motivation is 36.3%, and for work discipline is 34.6%. Meanwhile, the multiple coefficient of determination is 71.2%, indicating that work motivation and work discipline explain 71.2% of the variation in employee performance.