The purpose of the study is to evaluate the efficiency of Islamic Rural Banks (BPRS) and analyze the factors that determine them using a two-stage approach to Data Envelopment Analysis (DEA). DEA in this study focuses on the production, intermediation, and inefficiency causes. This research was done on BPRS across Indonesia. The data were taken from a financial report for the 2013-2021 period. The source of the data was a publication from the Financial Services Authority of Indonesia. The data were analyzed using the non-parametric approach with a two-stage DEA method. The input variables were personnel costs, fixed assets, and third-party funds. The result shows that Revenue Sharing, ROA, and Growth have a significant positive effect on DEA. BOPO and inflation have a positive but insignificant effect on DEA. While NPF and FDR have negative but insignificant effects on DEA. Then CAR has a negative and not significant effect on DEA. It also shows that the variables of Revenue Sharing, NPF, ROA, CAR, FDR, BOPO growth, and inflation have a simultaneous effect on DEA.

A pine tree, namely Pinus merkusii is an indigenous species from Indonesia which grows extensively in the Island of Java, Sumatera, and Sulawesi. This plant produces both timber and non-timber forest products (TFP and NTFP). Resin or oleum pine resin, as the main NTFP of Pinus merkusii, becomes the raw material for the gum rosin and turpentine oil industry. Globally, Indonesia is ranked 3rd as a producer of pine products after China and Brazil, in which Perhutani as a State Owned Forestry Enterprise plays a major role in this industry. On average, Perhutani manufactures 65,000 tons of gum rosin and 14,000 turpentine oil per year. Entire volume of both pine products is produced by nine factories with various maximum capacities. Therefore, this research aims to measure efficiency and/or inefficiency score of each factory using data envelopment analysis (DEA) method, which is then complemented by a single bootstrap technique with 2.000 iterations to eliminate bias scores. Cost of raw material, labour, energy, and general affairs are employed as input variables, while the output variables are total revenue and production volume. As result, 27.3% inefficiency (efficiency score = 72.7%) is generally found in all Perhutani’s pine chemical factories. To resolve this inefficiency issue, analytical hierarchy process (AHP) pairwise comparison questionnaire is distributed to 13 expert respondents to determine prioritized operational capability to focus on in optimizing efficiency of production performance. Dimensions of Cost, Quality, Flexibility, Innovation, and Sustainability are selected to construct the AHP questionnaires.

Stock is one of the investment assets that has its charm for investors. It is very liquid and has a high rate of return, but it has a high risk. The strategy commonly used to minimize investment risk is to diversify through portfolio formation. A good allocation of funds must be determined in forming an optimal portfolio. In addition, the method of stock selection needs to be considered so the stocks are well diversified and the portfolio developed has good performance. This study aims to compare stock selection between K-Means and Average Linkage clustering approaches in forming an investment portfolio. Clustering analysis is used to group IDX80 stocks based on their attributes. In forming a portfolio with the Mean-VaR model, the stock selection decision criteria used are by selecting stocks with the highest positive returns from each cluster. As a result, the two clustering techniques show the superiority of the Silhouette score for a certain number of clusters, but there are still more advantages in Average Linkage. The portfolio approached by Average Linkage resulted in a better performance than the portfolio approached by K-Means. Therefore, Average Linkage clustering can be used as a better recommendation in decision-making to select stocks so as to produce optimal portfolio performance.

This study analyzes the vulnerability of the power relations between the Indonesian National Armed Forces and the Indonesian National Police (TNI-Polri power relations) post-1998 Reform. This article employed exploratory sequential mixed methods in answering the research problem. Analytical Hierarchy Process (AHP) and System Dynamics methods were utilized in the study. Based on the research results, the variables of Socio-Economic (SE) Vulnerability and Adaptive Capacity (AC) have the highest weight value of 0.329. Meanwhile, the variable of Institutional Vulnerability has the lowest weight, 0.142. Overall, the vulnerability value of TNI-Polri power relations post-1998 Reform was still in the Low Vulnerability category with a value of 1,699 (33.97%). The vulnerability value of TNI-Polri power relations in the next five years will increase from a score of 1.66 in 2022 to 1.74 in 2027 so that it will increase by 5% with the same category level, namely Low Vulnerability. This study is expected to strengthen TNI-Polri power relations in maintaining national political stability.

The property is a unique product that cannot be contrasted with other commercial products due to pricing conditions. Property price determination is one of the crucial aspects of property development activities because of the profit margin made by the developer and the purchasing preferences. This study attempts to extend the literature that has largely focused on factors of housing prices in developed markets and provided recent evidence of housing price determinants in two countries (i.e., Indonesia and Malaysia). Thus, this study examines the factors affecting housing prices in Jakarta Metropolitan Region and Greater Kuala Lumpur. A quantitative approach was used involving two countries, namely Indonesia and Malaysia. The data was collected using a survey questionnaire through purposive sampling. A total of 100 respondents (Indonesia) and 134 respondents (Malaysia) participated in this study. The data was analyzed using descriptive (frequency) and inferential statistics (chi-square test and multinomial regression). The results indicated that housing location, property funding, and health have a significant effect on residential property prices in Indonesia. Besides that, the results displayed that housing physical design, home design and construction, developer and real estate products, development concepts, housing location, property funding, social status, health, law provisions, and external factors do not affect residential property price in Malaysia. Despite being neighbors, Indonesia and Malaysia have distinct economic and landscape characteristics. Furthermore, considering Indonesia has a higher number of Covid-19 cases than Malaysia, significant information on how the pandemic has affected the demand, cost, and pricing of residential housing in Jakarta and Kuala Lumpur will be provided. The findings of this study will provide recommendations to investors, buyers, and policy about the residential housing industry's prospects for growth in emerging nations following the pandemic.

Today, the economic resilience in Indonesia measures using the index approach, but it does not consider the effect of the disturbance and causes meaningless. The index is essentially an average, and the average is not a model that captures the relationship between variables. This research differs significantly from earlier studies that used the index to measure economic resilience. The crucial step in assessing the economic resilience of a city is to determine the economic resilience decision variable itself. If a variable significantly correlates with the disturbance factors in each relationship pattern, it is considered suitable as an economic resilience variable. This study evaluates variable Z as an economic resilience variable with a significant relationship to its disturbance variable. The evaluation method is conducted in-depth by studying Indonesia's cities over five years (2015-2019). Z, the ratio of Original Local Government Revenue (PAD) to the number of poor people in a city as a cost centre, will be evaluated as a prospective decision variable for economic resilience. The statistical relationship between Z and 9 disturbance variables is examined using piecewise linear regression analysis. All 514 cities in Indonesia were observed extensively for identification during a five-year observation period. Rosenbrock pattern search estimation was used to estimate the model parameters. The following results were obtained by analysing the data with the STATISTICA software. As determined by parsimonious analysis, the price of Pertalite fuel and the US dollar foreign exchange are two disturbance factors that are crucial to the fall in the resilience variable Z. The joint effect of these two variables on the decline in the resilience measure Z is 73.63 percent. The study concludes that Z is a city-level economic resilience decision variable that applies to all 514 cities in Indonesia and is measured as the ratio of PAD to the number of poor people. This study's novel contribution to Indonesian policymakers is Z as a new economic resilience decision variable that can be used to assess cities' relative economic resilience.

Intrinsic leadership is a new concept of leadership and is built based on philosophically and psychologically of the intrinsic meaning. The basic philosophy of its development is a holistic leadership philosophy that integrates cognitive, affective, conative, and spiritual as the core of leadership. The purpose of developing intrinsic leadership is to create a vision and value congruence, empower cooperation between all stakeholders and especially build an organization like a family so that it creates attachment, trust, a motivation that has an impact on organizational performance. Intrinsic leadership is conceptually different from the previous concept of leadership that only rests on one or several elements that the leader has as a human. Development of measurement scales and validity testing provides a foundation that facilitates quantitative research in intrinsic leadership. There are three studies carried out, the first is scale development and testing the content validity of intrinsic leadership measurements. Testing the content validity is accomplished by analyzing and calculating the content validity index (CVI) and Kappa coefficient data are obtained from a panel expert consisting of eight experts. The second study is related to testing construct validity of intrinsic leadership using EFA from 186 data collected from owner-managers of SMEs. The results show that there are twenty-six indicators extracted into eight factors that are intrinsic leadership measurement scale. The third study aims to test empirically or confirm measurement model of intrinsic-leadership using CFA.

The purpose of this study is to identify and analyze the interaction between customer satisfaction and trust in a structural model. Sample consists of 210 Suzuki motor bikes’ users, aged 17-64, domiciled in Medan. Structural equation model approach is used to process raw data. Respondents' opinions were taken proportionally throughout the Medan city sub-districts. Questionnaires were submitted accidentally. The results show that customer satisfaction and trust partially had positive and significant effect on brand equity and repurchase intention. Brand equity did not show any indirect causal relationship mediator of the three exogenous variables to repurchase intention. Programs related to customer satisfaction and trust better increase brand equity and repurchase intention directly. Interaction variable existence in research model increases Chi-Square probability, decreases standard deviation, and increases t-value. Interaction variable creates synergy on the influence of customer satisfaction and trust to increase brand trust. Any programs to increase brand equity through customer satisfaction and trust should be implemented, simultaneously. The two exogenous variables will bring out the synergy that comes from this interaction.

The objective of this study is to analyze the effect of entrepreneurial experience and social entrepreneurship orientation on social entrepreneurship performance. This survey research was conducted on waste bank entrepreneurship activists in the city of Semarang. Thirty-five respondents were taken using the accident sampling method. Partial Least Square Structural Equation Model (PLS-SEM) is used as an analysis technique. The results showed that entrepreneurial experience and social entrepreneurship orientation had a positive and significant effect on the performance of social entrepreneurship. The contribution of the concept of human capital and the concept of entrepreneurial orientation is needed in building social entrepreneurship. The Semarang government is requested to give more attention to developing waste banks due to their contribution to social, economic, and environmental.

The purpose of this study was to examine the role of environmental consciousness and green intellectual capital (GIC) for green competitive advantage. The association between environmental consciousness and each component of GIC—green human capital, green relational capital, green structural capital—is tested in this study. Tests are also carried out to examine the association of each GIC element with green competitive advantage. Data were collected using an online questionnaire. A total of 237 questionnaires were sent to the CEOs of medium manufacturing companies in Bali Province, Indonesia. There were 72 returned questionnaires that could be analyzed (a 30.37% usable response rate). Data analysis was performed using variance-based structural equation modelling with the partial least square (SEM-PLS) approach with WarpsPLS 7.0. The findings show that there is a positive and significant association between environmental consciousness and each component of GIC: environmental consciousness with green human capital, environmental consciousness with green relational capital and environmental consciousness with green structural capital. The findings also demonstrate that each component of GIC has a significant positive association with green competitive advantage: green human capital with green competitive advantage, green relational capital with green competitive advantage and green structural capital with green competitive advantage. This research implies that going green through the adoption of green practices can contribute to green competitive advantage.