Peran Gaya Kepemimpinan Transformasional Memoderasi Pengaruh Motivasi Intrinsik dan Kecerdasan Emosional terhadap Kinerja Guru (Studi Kasus pada SMA Negeri di Kecamatan Pati Kabupaten Pati)

This research is intended to examine the influence of motivation intrinsic and emotional intelligence to the state senior high school teachers\u27 work performance with the moderation of transformational leadership style. The specific purpose of this research is to examine the role of transformational leadership style moderates the influence of intrinsic motivation and emotional intelligence to the teachers\u27 work performance. The USAge of this research is to explain and expand the previous research about the role of transformational leadership style moderates the influence of intrinsic motivation and emotional intelligence to the teachers\u27 work performance. This research used the population of 116 teachers of state senior high school in Pati District, Pati Regency. The technique of sample collection used in this research is non-probability sampling with the purposive method. The analysis technique used in this research is regression model moderate quasi. Based on the research result can be conduded that: intrinsic motivation influences teachers\u27 work performance, emotional intelligence influences the teachers\u27 work performance, transformational leadership style do not moderate the influence of intrinsic motivation to teachers\u27 work performance, , transformational leadership style strengthen the influence of emotional intelligence to the teachers\u27 workperformance

Soft control performance (avg. Δ<i>θ</i>) for different <i>θ</i>_<i>s</i>, <i>M</i> and <i>ρ</i>_<i>n</i> in the <i>evolvable-heading-shill</i> scenario with <i>l</i> = 25.

<p>Soft control performance (avg. Δ<i>θ</i>) for different <i>θ</i>_<i>s</i>, <i>M</i> and <i>ρ</i>_<i>n</i> in the <i>evolvable-heading-shill</i> scenario with <i>l</i> = 25.</p

Main conclusions.

<p>Main conclusions.</p

How does the interaction radius affect the performance of intervention on collective behavior?

<div><p>The interaction radius <i>r</i> plays an important role in the collective behavior of many multi-agent systems because it defines the interaction network among agents. For the topic of intervention on collective behavior of multi-agent systems, does <i>r</i> also affect the intervention performance? In this paper we study whether it is easier to change the convergent heading of the group by adding some special agents (called shills) into the Vicsek model when <i>r</i> is larger (or smaller). Two kinds of shills are considered: fixed-heading shills (like leaders that never change their headings) and evolvable-heading shills (like normal agents but with carefully designed initial headings). We know that with the increase of <i>r</i>, two contradictory effects exist simultaneously: the influential area of a single shill is enlarged, but its influence strength is weakened. Which factor dominates? Through simulations and theoretical analysis we surprisingly find that <i>r</i> affects the intervention performance differently in different cases: when fixed-heading shills are placed together at the center of the group, larger <i>r</i> gives a better intervention performance; when evolvable-heading shills are placed together at the center, smaller <i>r</i> is better; when shills (either fixed-heading or evolvable-heading) are distributed evenly inside the group, the effect of <i>r</i> on the intervention performance is not significant. We believe these results will inspire the design of intervention strategies for many other multi-agent systems.</p></div

Soft control performance of different strategies in different scenarios based on two different models (the Vicsek model and the linearized Vicsek model) with non-periodic boundary.

<p><i>ρ</i>_<i>n</i> = 1, <i>M</i> = 15, <i>l</i> = 25, <i>v</i> = 0 and <i>η</i> = 0.02. (A) <i>Fixed-heading-shill</i> scenario for the Vicsek model. (B) <i>Evolvable-heading-shill</i> scenario for the Vicsek model. (C) <i>Fixed-heading-shill</i> scenario for the linearized Vicsek model. (D) <i>Evolvable-heading-shill</i> scenario for the linearized Vicsek model.</p

System size effect on soft control performance (avg. <i>T</i>) in the <i>fixed-heading-shill</i> scenario with <i>l</i> = 25.

<p>The system size is <i>n</i> = <i>ρ</i>_<i>n</i> <i>M</i>². (A) and (C) show how soft control performance (avg. <i>T</i>) change when <i>n</i> increases (by increasing <i>M</i> with fixed <i>ρ</i>_<i>n</i>); (B) and (D) show how soft control performance (avg. <i>T</i>) change when <i>n</i> increases (by increasing <i>ρ</i>_<i>n</i> with fixed <i>M</i>).</p

Examples of initial positions of adding 25 shills into a group of 225 normal agents inside a 15 × 15 square.

<p>Blue dots represent normal agents. Red stars represent shills. Short lines connected to the blue dots or red stars represent their headings. Here initial headings of all normal agents are set as <i>zero</i> and initial headings of shills are <i>π</i>/2. (A) <i>Centered</i> shills; (B) <i>Distributed</i> shills.</p

Comparisons of different soft control strategies in the <i>evolvable-heading-shill</i> scenario with <i>ρ</i>_<i>n</i> = 1 and <i>θ</i>_<i>s</i> = <i>π</i>/4.

<p>Comparisons of different soft control strategies in the <i>evolvable-heading-shill</i> scenario with <i>ρ</i>_<i>n</i> = 1 and <i>θ</i>_<i>s</i> = <i>π</i>/4.</p

System size effect on soft control performance (avg. <i>T</i>) in the <i>evolvable-heading-shill</i> scenario with <i>l</i> = 25.

<p>(A) and (C) show how soft control performance (avg. Δ<i>θ</i>) change when <i>n</i> increases (by increasing <i>M</i> with fixed <i>ρ</i>_<i>n</i>); (B) and (D) show how soft control performance (avg. Δ<i>θ</i>) change when <i>n</i> increases (by increasing <i>ρ</i>_<i>n</i> with fixed <i>M</i>).</p

Comparisons of different soft control strategies in the <i>fixed-heading-shill</i> scenario.

<p>Comparisons of different soft control strategies in the <i>fixed-heading-shill</i> scenario.</p