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The purpose of this study include analyzing the conformity between the General Guidelines for the Governance of the Indonesian Sharia Entities (GGG-ISE) and the implementation in the field and proposing a model of corporate governance for Islamic property developers.

This research uses a qualitative method with a case study approach. The researcher used a structured interview method and chose a purposive technique to determine the interviewees. This study has seven interviewees representing three Islamic property developer companies in Jember Regency, East Java, Indonesia. Data collection was conducted from June to July 2023, with a duration of about 60 min for each interviewee. The interviews were conducted face-to-face in each interviewee’s residential office.

The results showed that the companies had implemented several principles of GGG-ISE, namely, ethical and responsible actors, risk management, internal control, compliance, disclosure and transparency by making financial reports, shareholder rights and stakeholder rights, both internal and external stakeholders. Furthermore, this study found that GGG-ISE does not comply with the components of the organizing organ group. This study also found that governance reports have not been implemented in GGG-ISE components. In addition, this study identified a new component that must be present and not found in GGG-ISE, namely, a statement of the use of contracts for mudharib owners and between mudharib owners and stakeholders. Based on these findings, this study proposes a governance model for Islamic property developer companies called the GGG-IPDE.

This research is a pioneer in proposing a corporate governance model for Islamic property developers.

On the one hand, this paper is to further understand the residents' differentiated power consumption behaviors and tap the residential family characteristics labels from the perspective of electricity stability. On the other hand, this paper is to address the problem of lack of causal relationship in the existing research on the association analysis of residential electricity consumption behavior and basic information data.

First, the density-based spatial clustering of applications with noise method is used to extract the typical daily load curve of residents. Second, the degree of electricity consumption stability is described from three perspectives: daily minimum load rate, daily load rate and daily load fluctuation rate, and is evaluated comprehensively using the entropy weight method. Finally, residential customer labels are constructed from sociological characteristics, residential characteristics and energy use attitudes, and the enhanced FP-growth algorithm is employed to investigate any potential links between each factor and the stability of electricity consumption.

Compared with the original FP-growth algorithm, the improved algorithm can realize the excavation of rules containing specific attribute labels, which improves the excavation efficiency. In terms of factors influencing electricity stability, characteristics such as a large number of family members, being well employed, having children in the household and newer dwelling labels may all lead to poorer electricity stability, but residents' attitudes toward energy use and dwelling type are not significantly associated with electricity stability.

This paper aims to uncover household socioeconomic traits that influence the stability of home electricity use and to shed light on the intricate connections between them. Firstly, in this article, from the perspective of electricity stability, the characteristics of the power consumption of residents' users are refined. And the authors use the entropy weight method to comprehensively evaluate the stability of electricity usage. Secondly, the labels of residential users' household characteristics are screened and organized. Finally, the improved FP-growth algorithm is used to mine the residential household characteristic labels that are strongly associated with electricity consumption stability.

1. The stability of electricity consumption is important to the stable operation of the grid.

2. An improved FP-growth algorithm is employed to explore the influencing factors.

3. The improved algorithm enables the mining of rules containing specific attribute labels.

4. Residents' attitudes toward energy use are largely unrelated to the stability of electricity use.

The stability of electricity consumption is important to the stable operation of the grid.

An improved FP-growth algorithm is employed to explore the influencing factors.

The improved algorithm enables the mining of rules containing specific attribute labels.

Residents' attitudes toward energy use are largely unrelated to the stability of electricity use.