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All Journal Indonesian Journal of Data and Science ARZUSIN: Jurnal Manajemen dan Pendidikan Dasar
Aulia Putri Utami
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Religion Computer Science & IT Decision Sciences, Operations Research & Management Education Mathematics Social Sciences

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Improving Multi-Class Classification on 5-Celebrity-Faces Dataset using Ensemble Classification Methods Nurul Rismayanti; Aulia Putri Utami
Indonesian Journal of Data and Science Vol. 4 No. 2 (2023): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v4i2.78

Abstract

This study aims to compare the performance between Random Forest Classifier and Gaussian Naïve Bayes Classifier in classification. Several evaluation metrics such as accuracy, precision, recall, and F1-score were used to analyze the performance of both models. The dataset used has specific characteristics that influence the evaluation results. The research findings indicate that Random Forest Classifier outperforms Gaussian Naïve Bayes Classifier in most of the evaluation metrics. Random Forest Classifier achieves higher accuracy and better precision, recall, and weighted F1-score. However, it should be noted that Random Forest Classifier also has more outliers compared to Gaussian Naïve Bayes Classifier when visualized using boxplots. Therefore, in selecting a classification model, a trade-off between higher performance and sensitivity to outliers needs to be considered. Further statistical testing and advanced evaluation are required to gain a deeper understanding of the impact and interpretation of the obtained results. This study provides valuable insights into understanding the comparison between these two classification models and their implications in different contexts.
Pengembangan Pemasaran Makanan Khas Kipang untuk Meningkatkan Pendapatan (Studi Kasus Kipang Pulut Bonjol Ita) Aulia Putri Utami; Ali Rahman
ARZUSIN Vol 6 No 4 (2026): AGUSTUS
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/arzusin.v6i4.9988

Abstract

MSME marketing strategies have received attention in various previous studies, but studies that specifically discuss the integration of conventional and digital marketing in increasing the income of traditional culinary businesses remain limited. This study aimed to analyze the marketing strategies implemented and their contribution to increasing income in the Kipang Pulut Bonjol Ita business. This study used a qualitative approach with a case study design, involving main and supporting informants selected using purposive sampling. Data were collected through in-depth interviews, observation, and documentation, and were then analyzed using interactive analysis techniques through the stages of data reduction, data display, and conclusion drawing. The results showed that the marketing strategies implemented were still dominated by conventional approaches, particularly in the aspects of distribution and promotion. Distribution expansion was proven to contribute to increasing sales volume and business income, while the use of social media in promotion was able to increase product exposure, although it had not been optimally utilized. This finding contributes to the development of marketing mix studies, particularly in the aspects of distribution and promotion in the context of traditional culinary MSMEs, and expands understanding of the importance of integrating conventional and digital marketing strategies. Thus, distribution strategy is an important factor in expanding market reach and increasing business income, while digital marketing optimization is needed to strengthen the competitiveness of traditional culinary MSMEs.
Co-Authors Ali Rahman Nurul Rismayanti