Garuda - Garba Rujukan Digital

Analisis Regresi Linier pada Good Corparate Governance terhadap Kinerja LPD Dinata, Dewa Putu Gede Angga; Tristalina, Ni Luh Devi; Mariati, Ni Putu Ayu Mirah; Kumalasari, Putu Diah; Dewi, Ni Luh Putu Sandrya
Emasains : Jurnal Edukasi Matematika dan Sains Vol. 14 No. 1 (2025): Maret 2025
Publisher : Program Studi Pendidikan Matematika dan Pendidikan Biologi Universitas PGRI Mahadewa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59672/emasains.v14i1.4073

Kinerja merupakan suatu gambaran tentang kondisi keuangan suatu perusahaan yang dianalisis dengan alat-alat analisis keuangan, sehingga dapat diketahui mengenai baik buruknya keadaan keuangan suatu perusahaan yang mencerminkan prestasi kerja dalam periode tertentu. Kinerja perusahaan dikatakan baik saat penilaian keseluruhan aspek keuangan berpredikat sehat. Indikator yang digunakan dalam mengukur kinerja yaitu kinerja keuangan dan kinerja manajemen. Penelitian ini bertujuan untuk menguji dan memperoleh bukti empiris pengaruh good corporate governance terhadap kinerja LPD. Terpilih 100 LPD yang digunakan sebagai sampel penelitian. Teknik analisis data dalam penelitian ini menggunakan analisis regresi linear berganda. Variabel bebas (independen) dalam penelitian ini yaitu TR (Transparency), AC (Accountabilty), RN (Responsibility), IN (Independency), dan FS (Fairness), sedangkan untuk variabel terikat (dependen) yaitu KLPD (Kinerja lembaga perkreditan desa). Berdasarkan hasil penelitian yang telah dilakukan, dapat disimpulkan bahwa Transparency, Accountabilty, Responsibility, Independency, dan Fairness berpengaruh positif terhadap Lembaga Perkreditan Desa (LPD). Besarnya kontribusi antara Transparency, Accountabilty, Responsibility, Independency, dan Fairness terhadap KLPD (Kinerja lembaga perkreditan desa) adalah sebesar 78,20% sedangkan sisanya 21,80% dipengaruhi oleh faktor-faktor lain yang tidak dimasukkan ke dalam model.

Skrining Fitokimia serta Uji Aktivitas Antioksidan Ekstrak Etanol 96% Daun Kelor (Moringa Oleifera, Lam) dengan Metode DPPH (2,2-Difenil-1-Pikrilhidrazil) Ni Luh Putu Junita Kusuma Dewi; Ni Made sukma Sanjiwani; I Gusti Agung Ayu Kusuma Wardani; I Wayan Surya Rahadi; I Wayan Sudiarsa; Ni Putu Ayu Mirah Mariati
Akta Kimia Indonesia Vol. 10 No. 2 (2025): Desember 2025
Publisher : Chemistry Department

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/aki.v10i2.8870

All parts of the moringa plant, from the roots, seeds, stems to the leaves, are known to have medicinal properties. Its reported uses include anti-inflammatory, antioxidant, antibacterial, antifungal, and diuretic properties. This study focused on examining the presence of secondary metabolites and assessing the antioxidant potential of 96% ethanol extracts of moringa leaves (Moringa oleifera, Lam). The type of research conducted was a laboratory experiment. Moringa leaves were extracted using the Ultrasound-Assisted Extraction (UAE) method with 96% ethanol as the solvent. The resulting extract was then evaporated using a rotary evaporator to obtain a concentrated extract of 34.8 grams. The secondary metabolite content was evaluated through phytochemical screening, and the antioxidant activity was tested using the DPPH (2,2-diphenyl-1-picrylhydrazil) method. The antioxidant strength was determined by calculating the IC₅₀ value, which indicates the percentage of free radical scavenging by the test sample, and by the AAI value, which describes the antioxidant activity index of the extract. Based on the phytochemical screening results, the 96% ethanol concentrated extract of moringa leaves contained secondary metabolite compounds such as saponins, alkaloids, tannins, and steroids. The IC₅₀ value obtained from the extract was 75.428 ppm with an AAI of 0.530. As a comparison, ascorbic acid showed an IC₅₀ of 14.295 ppm and an AAI of 2.798.

Production of Solid Soap from Arabica Coffee Grounds (Coffea arabica L.) with Antibacterial Properties Sanjiwani, Ni Made Sukma; Ariani, Komang; Sunadi Putra, I Made Agus; Rahadi, I Wayan Surya; Mirah Mariati, Ni Putu Ayu; Sudiarsa, I Wayan; Udayani, Ni Nyoman Wahyu
Journal of Food and Pharmaceutical Sciences Vol 14, No 1 (2026): J.Food.Pharm.Sci
Publisher : Integrated Research and Testing Laboratory (LPPT) Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jfps.25035

Coffee shops are now a favourite hangout for people of all ages, so many entrepreneurs are developing coffee shop businesses because of their high profit potential. Arabica coffee is the type of coffee most commonly used in coffee shops. The coffee-making process produces waste in the form of coffee grounds. Coffee grounds can be used as an ingredient in beauty products such as soap. Soap is the result of saponification, which is a reaction between a base or alkali and fatty acids, which acts as a skin cleanser. This study aims to examine the presence of secondary metabolite compounds in Arabica coffee grounds (Coffea arabica L.), test the physical quality of solid soap made from Arabica coffee grounds (C arabica L.), and assess the soap's ability to inhibit the growth of Staphylococcus aureus bacteria. Arabica coffee grounds were first analysed through qualitative phytochemical screening tests using test tubes and various reagents, then formulated into solid soap with different concentrations, namely 4%, 7%, and 9%. After that, physical properties testing and antibacterial activity evaluation against Staphylococcus aureus were carried out using the disc diffusion method. The research results data were presented using descriptive analysis. The tests revealed that Arabica coffee residues contain secondary metabolites in the form of alkaloids, flavonoids, tannins, saponins, and triterpenoids. Solid soap made from Arabica coffee grounds meets the physical quality test standards in accordance with SNI 3532:2021 and that solid soap made from Arabica coffee grounds with a percentage of 7% (formula 2) and 9% (formula 3) has the potential to inhibit the activity of Staphylococcus aureus bacteria with a moderate category. It can be concluded that Arabica coffee grounds contain secondary metabolites such as alkaloids, flavonoids, tannins, saponins, and triterpenoids. Solid soap with Arabica coffee grounds as an ingredient meets the physical quality requirements in accordance with SNI 3532:2021. Soap formulas with a coffee grounds concentration of 7% (F2) and 9% (F3) have the potential to inhibit the growth of Staphylococcus aureus with moderate efficacy.

Production of Solid Soap from Arabica Coffee Grounds (Coffea arabica L.) with Antibacterial Properties Sanjiwani, Ni Made Sukma; Ariani, Komang; Sunadi Putra, I Made Agus; Rahadi, I Wayan Surya; Mirah Mariati, Ni Putu Ayu; Sudiarsa, I Wayan; Udayani, Ni Nyoman Wahyu
Journal of Food and Pharmaceutical Sciences Vol 14, No 1 (2026): J.Food.Pharm.Sci
Publisher : Integrated Research and Testing Laboratory (LPPT) Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jfps.25035

Coffee shops are now a favourite hangout for people of all ages, so many entrepreneurs are developing coffee shop businesses because of their high profit potential. Arabica coffee is the type of coffee most commonly used in coffee shops. The coffee-making process produces waste in the form of coffee grounds. Coffee grounds can be used as an ingredient in beauty products such as soap. Soap is the result of saponification, which is a reaction between a base or alkali and fatty acids, which acts as a skin cleanser. This study aims to examine the presence of secondary metabolite compounds in Arabica coffee grounds (Coffea arabica L.), test the physical quality of solid soap made from Arabica coffee grounds (C arabica L.), and assess the soap's ability to inhibit the growth of Staphylococcus aureus bacteria. Arabica coffee grounds were first analysed through qualitative phytochemical screening tests using test tubes and various reagents, then formulated into solid soap with different concentrations, namely 4%, 7%, and 9%. After that, physical properties testing and antibacterial activity evaluation against Staphylococcus aureus were carried out using the disc diffusion method. The research results data were presented using descriptive analysis. The tests revealed that Arabica coffee residues contain secondary metabolites in the form of alkaloids, flavonoids, tannins, saponins, and triterpenoids. Solid soap made from Arabica coffee grounds meets the physical quality test standards in accordance with SNI 3532:2021 and that solid soap made from Arabica coffee grounds with a percentage of 7% (formula 2) and 9% (formula 3) has the potential to inhibit the activity of Staphylococcus aureus bacteria with a moderate category. It can be concluded that Arabica coffee grounds contain secondary metabolites such as alkaloids, flavonoids, tannins, saponins, and triterpenoids. Solid soap with Arabica coffee grounds as an ingredient meets the physical quality requirements in accordance with SNI 3532:2021. Soap formulas with a coffee grounds concentration of 7% (F2) and 9% (F3) have the potential to inhibit the growth of Staphylococcus aureus with moderate efficacy.

ADAPTIVE MULTIRESOLUTION SEMIPARAMETRIC MODEL INTEGRATING TRUNCATED SPLINE AND WAVELET TO BALINESE VILLAGE CREDIT INSTITUTIONS (LPD) Mariati, Ni Putu Ayu Mirah; Sudiarsa, I Wayan; Kumalasari, Putu Diah
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 10 No. 2 (2026): Volume 10, Nomor 2, April 2026
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v10i2.53877

In this research, an adaptive multiresolution semiparametric regression approach is proposed to examine the financial performance of Lembaga Perkreditan Desa (LPD) in Bali, Indonesia. In the research, the problem that arises from the inadequacy of traditional regression techniques in accounting for the nonlinear pattern in the data and the financial instability is overcome by introducing the truncated spline and wavelet components into the semiparametric regression analysis.This research utilizes a quantitative method based on secondary financial information collected for 50 LPDs between 2015 and 2024, providing around 500 observations. In order to obtain a more consistent dataset, the purposive sampling method will be used. Return on Assets (ROA) is chosen as the dependent variable, and explanatory variables include interest rates, the number of customers, capital adequacy ratio (CAR), total assets, and non performing loans (NPL). The model will be estimated using the penalized least squares with iterative backfitting estimation technique and will be assessed using the RMSE, MAE, and R² criteria based on Kfold cross validation. As it can be seen from the results, the hybrid model significantly improves the predictive power of traditional linear and spline methods, providing smaller error rates and better fit quality. Spline functions help to determine long term trends, whereas wavelets capture short term effects. This shows that multiresolution modeling increases predictability and interpretability. The model has practical utility for financial management and regulation through adaptive risk management and decision-making processes in microfinance firms.

A Hybrid Semiparametric Regression Approach Using Truncated Spline–Wavelet Estimators for Modeling Nonstationary Financial Performance: Evidence from Village Credit Institutions in Bali Ni Putu Ayu Mirah Mariati; I Wayan Sudiarsa; Putu Diah Kumalasari
Inferensi Vol 9 No 1 (2026)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v9i1.9460

This research proposes a novel semiparametric regression framework, integrating truncated spline and wavelet estimators in the modeling of dynamic relationships among CG, IC, and institutional performance in Bali's Village Credit Institutions (LPDs) in Indonesia. The robustness of this estimator is initially tested by a Monte Carlo simulation under various conditions of nonstationarity. From these, it becomes quite clear that the proposed hybrid spline-wavelet model has produced the least MSE (MSE = 0.0076) and greatest coefficient of determination (R² = 0.968). However, the specific penalized estimation method used ensures an appropriate bias variance tradeoff, allowing the proper modeling of global smooth trends and local short term variations. Latent CG and IC constructs obtained through Partial Least Squares Structural Equation Modeling were applied as covariates to the hybrid regression model by using a longitudinal database from 86 LPDs over the period 2016-2023. From the empirical findings, it was manifested that CG and IC significantly influence institutional performance and account for as much as 78% of its variation. The time varying component depicted three phases: reform growth from 2016 to 2019, the pandemic contraction in 2020-2021, and post recovery stabilization in 2022-2023. In general, this hybrid spline-wavelet estimator showed superior precision, decreasing MSE by up to 31% compared to single basis models, and provided a novel methodological contribution to nonstationary financial and econometric modeling.

Title

Found 26 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 26 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 26 Documents
Search