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All Journal Jurnal Manajemen Dan Bisnis Ekonomi Jurnal Strategi Bisnis Teknologi
Galuh Aditya
Universitas Sains dan Teknologi Komputer
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Peran Strategi Pemasaran, Pelayanan dan Kualitas Produk Minyak Kayu Putih Cap Dragon terhadap Minat Beli Masyarakat di Kota Semarang Yeremia Fransica Wisesa; Bambang Widjanarko Susilo; Aftuqa Sholikatur Rohmania; Wesly Tumbur ML Tobing; Galuh Aditya
Jurnal Strategi Bisnis Teknologi Vol. 1 No. 2 (2024): Mei : Jurnal Strategi Bisnis Teknologi (JUSBIT)
Publisher : Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jusbit.v1i2.68

Abstract

This study aims to analyze the influence of the role of promotional strategies, services, and quality of cap eucalyptus oil products on people's buying interest in the city of Semarang. The sample in this study was 100 respondents using Purposive Sampling samples and the data analysis used in this study was a multiple linear regression technique. Empirical results show that Promotion Strategy has a positive effect on product buying interest, Service has a positive effect on product buying interest, Product Quality has a positive effect on product buying interest Together Promotion Strategies, Service, and Product Quality have a positive effect on Buying Interest.
Faktor-Faktor Penentu Keberhasilan UMKM di Era Digital: Pendekatan Pemodelan Prediktif Menggunakan Gradient Boosting Galuh Aditya; Siska Narulita; Agus Fitri Yanto; Andreas Tigor Oktaga
JURNAL MANAJEMEN DAN BISNIS EKONOMI Vol. 4 No. 3 (2026): Juli: JURNAL MANAJEMEN DAN BISNIS EKONOMI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jmbe-itb.v4i3.4180

Abstract

This study aims to compare the performance of three boosting algorithms, namely XGBoost, LightGBM, and CatBoost, to predict the success of MSMEs. The data used consists of 250 entries with 13 attributes that include business actor characteristics, initial capital, industry experience, financial record-keeping, internet utilization, business planning, partnerships, and the target variable success. The pre-processing stage includes checking for missing values, standardizing numerical attributes, and splitting the data into 80% training data and 20% test data. The evaluation results show that XGBoost provides the best performance with an accuracy of 0.92, precision of 0.8333, recall of 0.8333, F1-score of 0.8333, and ROC-AUC of 0.9715. LightGBM has an accuracy of 0.88, while CatBoost achieves an accuracy of 0.90. The research results show that XGBoost has the best ability to classify successful and unsuccessful MSMEs. The feature importance results also show that the success of MSMEs is influenced by a combination of several key factors. This research emphasizes that boosting algorithms are effectively used as predictive models to support the analysis of MSME success.
Co-Authors Aftuqa Sholikatur Rohmania Agus Fitri Yanto Andreas Tigor Oktaga, Andreas Bambang Widjanarko Susilo Siska Narulita Wesly Tumbur ML Tobing Yeremia Fransica Wisesa