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All Journal Indonesian Journal of Pharmaceutical Science and Technology Multifinance
Galih, Wening
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Computer Science & IT Economics, Econometrics & Finance Medicine & Pharmacology

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BEHAVIORAL FINANCE: THE IMPACT OF HERDING BEHAVIOR ON INVESTMENT DECISIONS: The Case Of Companies Listed In The Lq-45 Index In The Indonesian Stock Exchange (BEI) For The Period 2018-2020 Khalingga, Muhammad Ariq; Galih, Wening; Risnanto, Slamet; Abimanyu, Ketut
Multifinance Vol. 2 No. 2 (2024): Multifinance
Publisher : PT. Altin Riset Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61397/mfc.v2i2.253

Abstract

The purpose of this study is to describe and analyze the effect of herding behavior on investment decisions in companies included in the LQ-45 index of the Indonesia Stock Exchange (IDX) for the period 2018-2022 Research method will use descriptive verification method. To test the hypothesis to determine the influence or causal relationship of the hypothesis that has been proposed. In this study, the verification method is used to determine how much influence herding behavior has on investment decisions.  Findings show the results of hypothesis testing that, the independent variable herding behavior has a positive and significant effect on investment decisions, which means that with the panic of investors over the unclear sources of information and market conditions that will affect portfolio performance or can be said to be informational cascades conditions cause the loss of objectivity of an investor and lead to an irrational attitude so that investment decisions are made by following signals and information owned by other investors who are considered high skilled to be used as a reference for portfolio performance.  Value, according to the test results that have been carried out, the herding behavior variable results in a coefficient value of 1.61 with a significance level of 0.0198 <0.05, and the test results for the Coefficient of Determination in this study, show an RSquare value of 0.081119, meaning that 8.1% of the dependent variable Investment Decision can be explained by the independent variable, namely Herding Behavior. For 91.9% can be explained by other factors outside of Herding Behavior.
Development and Validation of Analytical Method for Piperine in Phytopharmaceutical Product Containing Cabe Jawa Fructus by HPLC Galih, Wening; Permana, Benny; Damayanti, Sophi
Indonesian Journal of Pharmaceutical Science and Technology Vol 12, No 1 (2025)
Publisher : Indonesian Journal of Pharmaceutical Science and Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/ijpst.v12i1.46348

Abstract

Cabe Jawa fruit (Retrofractii fructus) has empirically known to have effects such as anti-inflammatory and analgesic due to the presence of piperine. The maximum daily dose for piperine is 0.300–0.540 mg/kg/person/day. A reliable analytical method is required to ensure that phytopharmaceutical preparation is safe. This study developed and validated a piperine analysis method using phytopharmaceutical samples containing Cabe Jawa. A Shimadzu prominence HPLC SIL-20A Prominence autosampler and an X-Bridge C18 column (5 m x 250 mm x 4.6 mm) were used in the research devices. The OFAT method optimised the mobile phase, instrument systems, and sample preparation. The instrument system was optimized for acetonitrile:1% glacial acetic acid (48:52), 40°C, and a 1 mL/min flow rate. Each solid and liquid sample was prepared using the multilevel methanol dilution and water-dichloromethane liquid-liquid extraction (LLE) method. The results of validating the analytical procedures for solid and liquid samples were LOD and LOQ of 1.290 g/mL and 4.300 g/mL, 1.310 g/mL and 4 g/mL, respectively. Precision: 0.157% and 1.174%. Accuracy for three different concentrations were 94.232±1.050%, 95.387%±0.176%, and 96.272±1.043%; 88.801±0.428%, 89.473 ±0.252%, and 89.338 ±0.052% respectively. The analysis of the sample's piperine revealed that this method met the criteria for the validation parameters.
Co-Authors Ketut Abimanyu Munastha Khalingga, Muhammad Ariq Permana, Benny Slamet Risnanto Sophi Damayanti