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Pengaruh Pelatihan Dan Pengembangan SDM Terhadap Kinerja Pegawai Dinas Pemadam Kebakaran Dan Penyelamatan Kota Cilegon Fauziah, Popon; 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.v2i3.392

Abstract

The purpose of this study is to determine the influence of training and human resource development on the performance of employees at the Cilegon City Fire and Rescue Service The sample in this study uses taking objects from samples called sampling. So for sampling, the formula used is the slovin formula. distributed questionnaires to employees as many as 92 respondents. The researcher uses statistical quantitative research methods and applications that will be used to process data in this study using the IBM SPSS statistical application version 21. The results of this study show that training has a positive and significant effect on employee performance by 0.16 and human resource development has a positive and significant effect on employee performance by 0.000. Therefore, training and human resource development together affect employee performance with a value of 0.000 and the value of the simultaneous determination coefficient in this study, which is R square of 0.463 or 46.3%. This means that employee performance is influenced by 46.3% by HR training and development while the rest is influenced by other variables that are not studied in this study. It is recommended for subsequent researchers to expand the scope of variables and samples so that the results can be more general and can be applied widely in other organizational contexts
Pengaruh Kualitas Pelayanan Dan Kualitas Produk Terhadap Kepuasan Pelanggan Coffee Shop PT Jagat Pramudita Aksata 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.