Publication Search

This research is motivated by the phenomenon of decreasing number of customers at Emdee Easy Beauty Clinic Batam, which indicates the need for an evaluation of marketing strategies. The purpose of this study is to analyze the influence of price, promotion, brand image, and product quality on consumer satisfaction. The research method used is quantitative associative with a sample of 91 respondents taken using simple random sampling technique. Data were collected through questionnaires and analyzed using multiple linear regression. The results showed that simultaneously, price, promotion, brand image, and product quality had a significant effect on consumer satisfaction (F count 14.111 > F table 2.47). Partially, the variables of price, promotion, and brand image have a positive and significant influence, but product quality does not have a significant effect on consumer satisfaction in this study. The implication of these findings is that clinic management needs to prioritize competitive pricing strategies, strengthen promotional activities, and maintain a positive brand image to sustain and increase customer satisfaction.

The need for housing is increasingly pressing with population growth and urbanization, while affordability remains a challenge for single-income households. The purpose of this investigation is to assess the impact of price also location on home purchase decisions using a literature review. This approach involves reviewing, analyzing, and synthesizing various relevant literature sources, such as scientific journals, books, undergraduate theses, also previous investigation reports that discuss factors influencing home purchase decisions. The study concludes that price plays a positive also significant role in home purchase decisions, as consumers prefer homes with prices commensurate with their purchasing power and the quality offered. Location has also been shown to influence decisions, particularly when housing is conveniently situated at a key location  and the availability of public facilities. However, certain studies indicate that price and location are not always the primary determinants of decision-making, as other variables such as promotion, brand image, product quality, and lifestyle also play a role.

Investment decisions in pharmaceutical manufacturing companies listed on the Indonesia Stock Exchange (IDX) are influenced by fundamental analysis and stock price fluctuations. Stock prices reflect market perceptions shaped by profitability, liquidity, and capital structure. This study examines the effects of Return on Assets (ROA), Current Ratio (CR), and Debt-to-Equity Ratio (DER) on stock prices, both partially and simultaneously. Using a quantitative approach, the study analyzes secondary data from audited financial statements and stock prices of 12 pharmaceutical companies during 2022–2024, totaling 36 observations. Panel data regression with EViews 12 is applied. Results show that ROA and DER have positive and significant effects on stock prices, while CR has a negative but insignificant effect. Simultaneously, all three variables significantly influence stock prices, with an adjusted R² of 73%, indicating strong explanatory power. Profitability (ROA) is the most influential factor, followed by capital structure (DER), while liquidity (CR) shows no significant impact.

This study aims to analyze the effect of inflation and interest rates on the stock prices of banking companies listed in the IDX80 index on the Indonesia Stock Exchange for the 2019–2024 period. Research data were obtained from official reports of banking company stock prices as well as inflation and interest rate data from Bank Indonesia. The study used a quantitative approach with multiple linear regression methods through the SPSS application, and classical assumption tests were conducted as a requirement for analysis. The study population included all IDX80 banking companies, with a saturated sampling technique resulting in five banks that met the criteria during the study period. The results of the partial test indicate that inflation has a positive and significant effect on stock prices, while interest rates have a negative and significant effect on stock prices. This indicates that stable inflation can still improve the performance of the banking sector, while rising interest rates tend to depress stock prices due to increased borrowing costs and a shift in investment to other instruments. The results of the simultaneous test also show that inflation and interest rates together have a significant effect on the stock prices of IDX80 banking companies. The results show that inflation has a significant positive effect on stock prices with a significance value of 0.034, while interest rates have a significant negative effect with a significance value of 0.018. Simultaneously, inflation and interest rates have a significant effect on stock prices with a calculated F value of 14.549 > Ftable 2.70 and a significance of 0.000 < 0.05.

This study was conducted with the aim of identifying and analyzing the influence of price, innovation, and service quality variables on consumer decisions in using the Maxim online transportation service. The background of this research is the increasing competition in the online transportation industry in Indonesia, which encourages companies to continuously improve their marketing strategies to attract and retain customers. As one of the rapidly growing online transportation service providers, Maxim needs to understand the factors that influence consumer decisions in order to compete effectively. The method used in this research is a quantitative approach, with data collected through questionnaires distributed to 134 respondents who are active users of Maxim's transportation services. The data collected were analyzed using multiple linear regression to examine the effect of each independent variable (price, innovation, and service quality) on the dependent variable (consumer decision). Validity and reliability tests were also conducted to ensure the research instrument was appropriate for use.The results of the study show that all three independent variables—price, innovation, and service quality—have a positive and significant effect on consumer decisions. This means that the more competitive the price offered, the higher the level of innovation provided, and the better the perceived service quality, the more likely consumers are to choose and continue using the Maxim online transportation service.These findings provide practical implications for Maxim’s management in designing more targeted marketing strategies and service improvements, as well as strengthening the company’s position in facing market competition.

Local fashion businesses require accurate production cost calculations to ensure appropriate and sustainable pricing decisions. Problems often faced by small businesses is determining selling prices without comprehensive calculation of the cost of production. This study aims to analyze the calculation of the cost of production as the basis for determining the selling price at Voraya Wear, a student-based local fashion business developed through the Student Creativity Program (PKM). The research used a descriptive quantitative approach with direct practice methods. Data were collected through observation, documentation, and financial records, then analyzed using the full costing method to calculate the cost of production and the cost-plus pricing method to determine the selling price. The results show that the total production cost was Rp1,831,064 for 24 units, resulting in a unit cost of Rp65,757 for shirts and Rp86,832 for pants. By applying a profit margin of 30–40%, the business generated total revenue of Rp2,520,000 and a net profit of Rp688,936. These findings indicate that accurate cost calculation supports rational pricing decisions and ensures business profitability and sustainability.

The policy of increasing fuel prices is a strategic public policy that has broad implications for the lives of people in Indonesia. Fuel plays an important role in supporting economic activity, distribution of goods, and social mobility. This article aims to analyze the impact of the fuel price increase policy on public interests by emphasizing the current context in Indonesia and the empirical realities that arise in society. This study uses a qualitative approach through literature review and policy analysis. The results of the study show that the increase in fuel prices has a direct impact on the increase in the cost of living, a decline in people's purchasing power, and the emergence of social pressure, especially among low-income groups. Although the government views this policy as a rational step to maintain fiscal stability and the sustainability of energy subsidies, compensation and social protection policies remain key factors in ensuring that the public interest and the goal of community welfare are maintained.

This study aims to determine the effect of selling price and operational costs on fishermen’s income in Menawi Village, Angkaisera District, Kepulauan Yapen Regency. The population in this study consisted of all fishermen in Menawi Village, Angkaisera District, Kepulauan Yapen Regency. The research sample included 15 fishermen. The data collection technique used in this study was observation through interviews with fishermen, and the data were analyzed using multiple linear regression analysis with the assistance of SPSS 21.0 for Windows. The results of this study indicate that (a) there is a significant simultaneous effect of selling price and operational costs on fishermen’s income in Menawi Village, Angkaisera District, Kepulauan Yapen Regency; (b) there is a positive and significant partial effect of selling price and operational costs on fishermen’s income in Menawi Village, Angkaisera District, Kepulauan Yapen Regency, which can form the basis for economic policy and natural resource management in the fisheries sector. This research is expected to provide insight for policymakers in formulating strategies to increase fishermen's incomes through improved selling prices and more efficient operational cost management.

This study aims to determine the influence of price, product quality, and service quality on customer satisfaction at Salon Natayu. The approach used was quantitative, with data collection techniques through questionnaires distributed to Salon Natayu customers, with a total of 53 respondents (using census techniques). The data were analyzed using multiple linear regression analysis with the help of SPSS version 20. The results of the study show that the three independent variables (price, product quality, and service quality) simultaneously have a positive effect on customer satisfaction. However, partially, the price variable has the most dominant influence on customer satisfaction. The conclusion of this study shows that price is the most influential factor on customer satisfaction, followed by service quality, while product quality has the least influence. These findings indicate that a competitive pricing strategy is a crucial aspect for Salon Natayu in maintaining and improving customer satisfaction. In addition, continuous improvement of service quality is also necessary to create a better customer experience. This research is expected to be a reference for salon managers in formulating more effective marketing strategies as well as for future research that examines the factors that affect customer satisfaction in the beauty services industry.

Academic stress is a common type of stress experienced by students, which greatly affects their self-esteem. This study aims to determine the relationship between self-esteem and academic stress levels among students. This study used a quantitative design with a cross-sectional approach and probability sampling technique. The sample consisted of 101 respondents from a total of 132 students. Data analysis was performed using Spearman's rank correlation test. The results showed a weak and negative relationship between self-esteem and academic stress levels with a p-value of 0.000 (p˂ 0.05) and a correlation coefficient (r) = -0.385. There is a relationship between self-esteem and academic stress levels in students, where low self-esteem is associated with higher academic stress levels.

Stock price prediction remains a complex challenge due to the dynamic and non-linear nature of financial markets, especially for banking stocks like PT Bank Negara Indonesia (Persero) Tbk (BBNI). This study aims to optimize BBNI stock price forecasting by integrating an automated Extract, Transform, Load (ETL) pipeline with the Long Short-Term Memory (LSTM) algorithm within a data engineering framework. Historical data from 2019 to 2025 were processed through a structured ETL sequence—including data cleaning, feature engineering, and MinMaxScaler normalization—to ensure high data quality. The dataset was partitioned into 80% for model training and 20% for testing to ensure rigorous evaluation. The results demonstrate that the systematic ETL approach significantly enhances model stability and predictive accuracy compared to conventional methods. The LSTM model effectively captured long-term temporal dependencies, providing reliable trend forecasts with an impressive test accuracy, achieving a Root Mean Squared Error (RMSE) of 0.0354. This research underscores that integrating robust data engineering practices with deep learning is essential for building resilient financial decision-support systems.

This study examines the development of a Crude Palm Oil (CPO) price forecasting model using an artificial neural network algorithm, specifically the backpropagation algorithm. As one of Indonesia’s main export commodities, CPO has a significant economic impact and influences the income of oil palm farmers. The CPO price data used in this study were obtained from CIF Rotterdam, covering the period from January 2019 to December 2023. The research methodology consists of several stages, including data collection, preprocessing, model design, and model implementation using Python programming. The training results of the backpropagation algorithm show an error value of 0.537829578 after 1,000 epochs, while the evaluation using Mean Squared Error (MSE) indicates an MSE of 0.022709 during the training process and 0.017604 during the testing process. The model also produces CPO price predictions for the next three months, namely 932.578 for the first month, 949.568 for the second month, and 774.855 for the third month. These findings indicate that the developed model is capable of predicting future CPO prices with adequate accuracy, which can assist companies in making better financial decisions and managing risks associated with CPO price fluctuations.

The dynamic fluctuations in stock prices present a major challenge for investors in making informed decisions. To anticipate such uncertainties, forecasting methods that can provide accurate predictions are required. This study compares two time series forecasting methods Autoregressive Integrated Moving Average (ARIMA) and Double Exponential Smoothing (Holt) in predicting the stock prices of PT Telkom Indonesia (TLKM). The dataset consists of monthly closing prices from January 2018 to December 2023. The performance of each model is evaluated using three error metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). The results show that the ARIMA(1,1,1) model yields higher predictive accuracy than the Holt method, with MAE of 787.71, MSE of 771,844.2, and RMSE of 878.55. In contrast, the Holt method records a MAE of 837.19, MSE of 878,393.4, and RMSE of 937.23. These findings confirm that ARIMA is superior in capturing the complex patterns of stock price movements and is more effective in volatile market conditions such as the stock exchange.

This study aims to analyze the effect of price on purchasing decisions of broiler chicken production inputs (sapronak) among partner farmers of PT Sejahtera Abadi Unggas, Kediri Unit. A quantitative approach with a causal research design was employed. The research sample consisted of 104 active partner farmers, selected using purposive sampling. Data were collected through structured questionnaires using a five-point Likert scale. The collected data were analyzed using validity and reliability tests, classical assumption tests, and simple linear regression analysis with the assistance of SPSS software. The results indicate that price has a positive and significant effect on purchasing decisions. The regression analysis produces the equation Y = 2.103 + 0.940X, with a significance value of 0.000, confirming that an increase in positive price perception significantly enhances purchasing decisions. Furthermore, the coefficient of determination (R²) of 0.699 shows that price explains 69.9% of the variation in purchasing decisions, while the remaining 30.1% is influenced by other factors not examined in this study. These findings highlight that competitive, fair, and value-based pricing strategies play a crucial role in strengthening long-term partnerships and sustaining purchasing behavior among broiler farmers. The study provides empirical evidence that can support managerial decision-making in developing effective pricing strategies within the agribusiness sector.

This study aims to analyze the influence of price, product quality, and promotion on purchasing decisions of fashion products on the Shopee marketplace (Case Study: Students of STIE Dharma Putra Semarang). Data were collected using a questionnaire, with respondents selected through purposive sampling. The sample consisted of 50 students from STIE Dharma Putra Semarang who had previously purchased fashion products on Shopee. Based on hypothesis testing, the first hypothesis shows that price has a positive and significant effect on purchasing decisions (t = 2.638 > t-table = 1.678; regression coefficient β₁ = 0.252; significance = 0.011 < α = 0.05). The second hypothesis indicates that product quality has a positive and significant effect on purchasing decisions (t = 4.233 > t-table = 1.678; regression coefficient β₂ = 0.434; significance = 0.001 < α = 0.05). The third hypothesis reveals that promotion has a positive and significant effect on purchasing decisions (t = 3.924 > t-table = 1.678; regression coefficient β₃ = 0.341; significance = 0.001 < α = 0.05). Therefore, it can be concluded that the more competitive the price, the better the product quality, and the more attractive the promotions offered, the higher the purchasing decision for fashion products among students on the Shopee marketplace.

Pricing is a critical factor determining the success of small and medium-sized enterprises (SMEs) in the market. This study investigates the pricing strategy implemented by Kebab Ajo Lubeg, a culinary SME located near Universitas Putra Indonesia YPTK Padang. The research aims to analyze how pricing methods are applied, the factors considered in price determination, and their influence on consumer purchasing decisions and business strategy. A qualitative descriptive approach was employed, with data collected through semi-structured interviews with the owner and employees, direct observation, and documentation of product offerings and pricing. Findings indicate that Kebab Ajo applies a combination of cost-based pricing, competition-based pricing, and product-based price variation to balance production costs, consumer purchasing power, and market competition. The pricing strategy significantly affects consumer satisfaction, repeat purchases, perceived value, brand image, and business competitiveness. This study provides practical insights for other SMEs in setting appropriate prices while maintaining customer loyalty and profitability, and it contributes to the academic discourse on marketing management and pricing strategies in the culinary sector.

Business competition in the culinary sector continues to increase along with changes in people's consumption patterns towards ready-to-eat food. One product that is quite popular is fried dim sum, which is known for its variety of flavors and relatively affordable prices. In this competitive environment, understanding how consumers perceive product price and quality is crucial for businesses to maintain and increase customer interest in purchasing goods. Consumer perceptions of product price and quality when they choose fried dim sum are the subject of this study. Informants were selected purposively in this study, which used a qualitative and descriptive approach, namely consumers who have purchased and consumed fried dim sum products. Data collection methods included comprehensive interviews, direct observation, and supporting documentation. The collected data were analyzed using an interactive analysis model developed by Miles and Huberman through steps such as data reduction, data presentation, and discovery. The results show that consumers view price as an indicator related to the affordability and suitability of the product value. Price is considered acceptable if it is commensurate with perceived quality. In addition, product quality, including taste, texture, cleanliness, and packaging, is a primary factor considered before making a purchase. Positive perceptions of product quality increase customer trust and encourage repeat purchases. This study concluded that customer perceptions or opinions about price and product quality influence fried dim sum purchasing decisions. Therefore, culinary businesses need to prioritize proportional pricing and maintain consistent product quality to enhance business competitiveness.

Perkembangan kecerdasan buatan (AI) mendorong inovasi dalam analisis keuangan, termasuk prediksi harga saham yang fluktuatif. Penelitian ini bertujuan memprediksi harga saham PT Garudafood Putra Putri Jaya Tbk menggunakan model ARIMA dengan penanganan Outlier sebagai pendekatan awal menuju sistem prediksi yang lebih adaptif. Data harga penutupan harian dari Yahoo Finance dianalisis melalui uji stasioneritas, identifikasi model ARIMA, deteksi Outlier berbasis log-return, serta evaluasi performa menggunakan RMSE, MAE, dan MAPE. Hasil penelitian menunjukkan bahwa ARIMA Outlier memberikan performa lebih baik dibandingkan ARIMA dasar. ARIMA standar menghasilkan MAPE 1.32% dan AIC –899.46, sedangkan ARIMA dengan tiga dummy Outlier mencapai MAPE 1.16% dan AIC –900.37. Peramalan 14 hari ke depan menunjukkan pola yang stabil pada kisaran Rp 370–371. Pada data uji, ARIMA dasar memberikan akurasi terbaik pada pertengahan Agustus, sedangkan ARIMA Outlier mencapai akurasi tertinggi pada akhir Agustus dengan prediksi Rp 370.2 yang sangat dekat dengan harga aktual Rp 370.4. Hasil ini menunjukkan bahwa penanganan Outlier meningkatkan ketepatan model, sehingga ARIMA Outlier dapat digunakan sebagai fondasi awal menuju pengembangan sistem prediksi keuangan berbasis AI.

This study examines the price elasticity of fresh cow’s milk on the demand for raw materials at Anisa Yoghurt Company using a demand theory approach. Milk is the main input in yoghurt production, making price fluctuations potentially influential on production decisions. The objective of this research is to analyze the responsiveness of raw milk demand to price changes and to identify the elasticity characteristics of milk demand in a small-scale food processing business. This study employs a quantitative case study method using primary data collected through weekly observations of milk prices and quantities purchased over a three-month period, from September to November. The analysis applies the midpoint elasticity formula to measure price elasticity of demand. The findings indicate that the demand for raw milk is consistently inelastic across the observed periods, as shown by elasticity values with absolute magnitudes less than one. Both price decreases and increases result in relatively small changes in the quantity demanded, indicating low sensitivity of demand to price fluctuations. These results suggest that raw milk is an essential production input, and purchasing decisions are driven more by production needs than by short-term price changes. The study implies that yoghurt producers should prioritize supply stability and production efficiency rather than adjusting purchase volumes in response to minor price changes. This research contributes empirical evidence on demand elasticity in dairy-based agro-industries, particularly at the small enterprise level.

The relatively high volatility of Robusta coffee prices creates uncertainty for farmers, business actors, and policymakers in making economic decisions. This study aims to analyze the price movement patterns of Robusta coffee, determine the most appropriate Autoregressive Integrated Moving Average (ARIMA) model, and conduct short- to medium-term price forecasting for Robusta coffee. The data used consist of monthly Robusta coffee price data from January 2023 to September 2025, sourced from the World Bank Commodity Price Data. The analytical method employed is ARIMA using EViews software, beginning with stationarity testing using the Augmented Dickey-Fuller (ADF) test, model identification through ACF and PACF, parameter estimation, and residual diagnostic testing. The results show that Robusta coffee price data are non-stationary at the level but become stationary at the first difference, indicating integration of order one I(1). Based on model identification and diagnostic testing, the ARIMA (0,1,0) model is found to be the most appropriate and satisfies the white noise assumption. Forecasting results indicate that Robusta coffee prices are projected to remain relatively stable with a moderate upward trend through December 2026. These findings are expected to serve as a reference for decision-making by farmers, business actors, and the government in responding to Robusta coffee price dynamics.