http://repository.president.ac.id/xmlui/handle/123456789/11088 2026-04-09T03:37:45Z 2026-04-09T03:37:45Z Anggraini, Lydia; et al http://repository.president.ac.id/xmlui/handle/123456789/11748 2024-01-25T03:27:28Z 2022-01-01T00:00:00Z

Homogenization of Green SiO2 from Rice Husk Burn through Potassium Hydroxide Solid-Liquid Extraction Anggraini, Lydia; et al In the agricultural countries, rice husk is an abundant waste, especially as one of the largest sources of silica (SiO2) production that can be produced. By complete combustion, to about 87% - 97% SiO2 content can be produced from rice husks. Alkaline solution is used as a solvent in the solid-liquid extraction process of rice husk ash. The mass of 10 grams of rice husk ash was weighed for the extraction process added with 80 ml of potassium hydroxide (KOH) solution with 10%, 15% and 20% various concentration for 60 minutes to extract the SiO2 content. The solution was added with 1 N hydrochloric acid (HCl) solution to precipitate the SiO2, after the extraction process was complete. The SiO2 formed is then separated from the rest of the solution by filtration. Next step is the drying process which aims to remove the moisture content of the resulting SiO2. In a systematic study, for 60 minutes the rice husks were soaked and washed using HCl and then heated in a muffle furnace. The results of this study showed that all samples are succeeded in homogenizing SiO2 with a purity close to 90%. Furthermore, through X-Ray Fluorescence (XRF) analysis was proven these results obtained through solid-liquid extraction of KOH from rice husks. Green SiO2, known as biosilica, is useful and has potential in reinforcing compounds, including applications as filler in tires and natural rubber compounds. Journal of Physics: Conference Series (2022); p. 1-6.

2022-01-01T00:00:00Z Lembah, Gebby Maurizka Jony Oktavian Haryanto http://repository.president.ac.id/xmlui/handle/123456789/11707 2023-09-05T04:08:07Z 2022-01-01T00:00:00Z

THE INFLUENCE OF THE STORE ATMOSPHERE TOWARDS CONSUMER ATTITUDES ON HYPERMART STORES Lembah, Gebby Maurizka; Jony Oktavian Haryanto The aim of this study is to examine how store atmosphere can influence Hypermart consumers’ satisfaction, which then forms a repurchase intention and generates word of mouth. This study used data from 170 respondents obtained using the Purposive Sampling technique. The research data were analyzed using the Structural Equation Modeling (SEM) method with Lisrel 8.8 software. The results showed that music had a positive influence on store atmosphere and word of mouth. In addition, the store atmosphere has a positive influence on consumer satisfaction and repurchase intention. Afterward, consumer satisfaction has a positive influence on repurchase intention, and repurchase intention has a positive influence on word of mouth. The managerial implication in this study is that marketers should create an attractive store atmosphere to achieve consumer satisfaction to make consumers interested in repurchasing and in an effort to retain consumers to continue to generate abundant profits. The 6th International Conference on Family Business and Entrepreneurship, 2022. p.240-254.

2022-01-01T00:00:00Z Permatasari, Anggraeni Wawan Dhewanto Dina Dellyana http://repository.president.ac.id/xmlui/handle/123456789/11562 2023-06-05T08:48:38Z 2022-01-01T00:00:00Z

CREATIVE SOCIAL ENTREPRENEURIAL ORIENTATION OF TRADITIONAL WOVEN SMES Permatasari, Anggraeni; Wawan Dhewanto; Dina Dellyana The 6th International Conference on Family Business and Entrepreneurship, 2022. p. 188-194.

2022-01-01T00:00:00Z Medellu, Juliano Victor Christian Edwin Setiawan Nugraha http://repository.president.ac.id/xmlui/handle/123456789/11219 2023-04-18T07:29:44Z 2022-01-01T00:00:00Z

TEA PRODUCTION FORECASTING IN INDONESIA’S LARGE PLANTATION BY USING ARIMA MODELS Medellu, Juliano Victor Christian; Edwin Setiawan Nugraha Indonesia is known for its outstanding agricultural sector and natural wealth. Tea is one of the plantation sectors that are mostly consumed all over the world and has been one of Indonesia’s mainstay commodities that has already been listed as one of the 10 export commodities with a big amount of production. Tea production data have a fluctuating pattern and characteristic. Therefore, it is really important to know the projection of tea production for planning and management purposes. The ARIMA (Autoregressive Integrated Moving Average) model is one of the methods that can be used to predict future productions. The ARIMA (4,1,0) is found to be the most suitable model to be used with a MAPE of 29.9%. The forecasting process shows the production will have an uptrend pattern for ten months from March 2018. The Tea production forecast data will be useful for future planning and production control. The 6th International Conference on Family Business and Entrepreneurship 2022.

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