Purpose This study aims to examine the adoption of peer-to-peer (P2P) lending platforms to determine the factors that encourage SMEs to use P2P lending platforms in obtaining loans. Design/methodology/approach A sample of ten SMEs from a variety of backgrounds was taken in Bandung, Indonesia. Bandung has been awarded the title of “creative city” by UNESCO, as the city allows for the development of the creative economy. This research used a semi-structured interview. Coding method was then used for content analysis to establish which factors emerging from the interview were leading respondents to obtain a loan through the P2P lending platform. Findings The findings imply that loan processes, interest rates, loan costs, loan amounts and loan flexibility affect SMEs in obtaining a loan through P2P lending. Moreover, alternative payment schemes in the form of Sharia-based lending and profit-sharing schemes were found. These findings constituted the original findings of this study. Research limitations/implications The study offers findings on factors affecting SMEs in using the P2P lending platform as a form of alternative financing. Moreover, the theoretical framework provided can be used as literature in future research. As this study was conducted in Bandung, Indonesia, the findings may not be generalisable to other regions. Originality/value This study is one of the few studies that discusses P2P lending in Indonesia as the concept has been in practice only since 2015.

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Sky brightness measuring and monitoring are required to mitigate the negative effect of light pollution as a byproduct of modern civilization. Good handling of a pile of sky brightness data includes evaluation and classification of the data according to its quality and characteristics such that further analysis and inference can be conducted properly. This study aims to develop a classification model based on Random Forest algorithm and to evaluate its performance. Using sky brightness data from 1250 nights with minute temporal resolution acquired at eight different stations in Indonesia, datasets consisting of 15 features were created to train and test the model. Those features were extracted from the observation time, the global statistics of nightly sky brightness, or the light curve characteristics. Among those features, 10 are considered to be the most important for the classification task. The model was trained to classify the data into six classes (1: peculiar data, 2: overcast, 3: cloudy, 4: clear, 5: moonlit-cloudy, and 6: moonlit-clear) and then tested to achieve high accuracy (92%) and scores (F-score = 84% and G-mean = 84%). Some misclassifications exist, but the classification results are considerably good as indicated by posterior distributions of the sky brightness as a function of classes. Data classified as class-4 have sharp distribution with typical full width at half maximum of 1.5 mag/arcsec2, while distributions of class-2 and -3 are left skewed with the latter having lighter tail. Due to the moonlight, distributions of class-5 and -6 data are more smeared or have larger spread. These results demonstrate that the established classification model is reasonably good and consistent.

Due to its stable yet continuous growth, the beauty industry has intensely diversified both its marketing and managerial orientation toward consumer demands. The growth is in response to customer trends towards healthier lifestyles, where women aged within the range of 18 and 34 are concerned regarding the ingredients of the beauty products they purchase when it comes to selecting a specific cosmetic product. This study aims to measure the influence between consumption value (functional value, social value, conditional value, epistemic value, and emotional value) on motives in choosing natural cosmetics among 243 Indonesian Women specifically in Jabodetabek and Bandung. This research is conducted by questionnaire and analyzed using Confirmatory Factor Analysis in SmartPLS Software. The result of this research indicates that functional value, conditional value, epistemic value, and emotional value have positively influenced motives in choosing natural cosmetic products, where social value negatively influences motives in choosing natural cosmetics products. In applying the results of this research into marketing planning, natural cosmetics SMEs in Indonesia are advised to consider incorporating consumption values such as functional values, emotional values, conditional values, and epistemic values associated with the marketing of the product itself.