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International Journal of Management Science and Business Administration
Volume 6, Issue 4, May 2020, Pages 42-54

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The Effect of Motivation, Emotional and Spiritual Intelligence on Lecturer Performance

DOI: 10.18775/ijmsba.1849-5664-5419.2014.64.1004
URL: http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.64.1004

¹ Rosemarie S. Njotoprajitno, ² Rully Arlan Tjahjadi, ³ Nur,
⁴ Bram Hadianto, ⁵ Andre Sunjaya

^{1 2 3 4 5} Management Department of Economics Faculty, Maranatha Christian University, Indonesia

Abstract: Lecturers are individuals employed by the higher educational institutions to educate students based on their competency. The roles of lecturers are not limited to the education of students only but also include the activities related to the research and the service community. These three aspects are considered to be measures of lecturers’ performance. Consequently, the institutions must focus on the factors behind the performance of their lecturers to increase performance. By denoting the evidence of the previous study, the three determinants of performance are identified, namely, motivation, emotional and spiritual intelligence. Therefore, this study attempts to examine and analyze these determinants in the context of private university lecturers becoming active members of the Indonesia Management Forum. To collect the data, we utilize a simple random sampling and survey method. Also, we use a variance-based structural equation as the model to analyze the attained data. Overall, this study concludes that there is a positive effect of emotional intelligence on the performance of lecturers. On the other hand, the effect of motivation and spiritual intelligence is not confirmed.

Keywords: Emotional intelligence, Lecturer performance, Higher education institution, Spiritual intelligence

The Effect of Motivation, Emotional and Spiritual Intelligence on Lecturer Performance

1. Introduction

Human resources are considered to be the main organizational assets (Gabčanová, 2011). Therefore, maintaining their commitment is mandatory for achieving excellent performance (Rishipal and Manish, 2013) and ensuring organizational success (Vosloban, 2012). Similarly, such situations can be applied to lecturers in higher educational institutions. The lecturers and their achievement will determine the quality of these institutions, (Zahraini, 2014). In Indonesia, lecturers’ performance is measured by the three components, i.e., education and teaching; research, and community service (Muttaqiyathun, 2010; Pramudyo, 2010; Taruno, Thoyib, Zain, and Rahayu, 2012), and the Board of National Accreditation for Higher Education is authorized to perform the valuation for outcomes based on these three aspects.

To ensure their lecturers achieve excellent performance, the higher education institutions have to identify antecedents leading to superior performance. These include motivation (Muttaqiyathun, 2010; Pramudyo, 2010; Nur’aeni, 2011; Trisnaningsih, 2011; Taruno, Thoyib, Zain, and Rahayu, 2012; Faitullah, 2014; Anwar, 2017; Rina and Kusuma, 2017; Narasuci, Setiawan, and Noermijati, 2018), emotional (Muttaqiyathun, 2010; Faitullah, 2014), and spiritual intelligence (Muttaqiyathun, 2010; Anwar, 2017). Unlike the studies involving lecturers, some research finds that intrinsic motivation has no impact on employee performance in state-owned firms (Muogbo, 2013). Others suggest emotional intelligence decreases the enactment of the officers in educational and cultural departments (Bestyasamala, 2018), while it has previously been established that spiritual intelligence does not affect the performance of nurses (Haryono, Rosadi, and MdSaad, 2018). Based on two conflicting results, this study intends to test and analyze the effect of motivation and emotional and spiritual intelligence on the performance of lecturers.

2. Literature Review and Hypothesis Development

Motivation is the power to encourage employees to achieve outstanding results. Highly motivated employees can cooperate, assist, support, and inspire each other (Gibson, Ivancevich, Donnelly, and Konopaske, 2012). According to Muttaqiyatun (2010), motivation has a positive effect on lecturer performance. The result was supported by a number of studies, such as Pramudyo (2010), Nuraeni (2011), Trisaningsih (2011), Taruno et al. (2012), Faitullah (2014), Anwar (2017), Rina & Kusuma (2017), Narasuci et al. (2018). Therefore, the first hypothesis is declared as follows:

H1: Motivation has a positive effect on lecturer performance.

Emotional intelligence is comprised of emotional and social capabilities in all aspects of individual life (Tridhonanto & Agency, 2010). Someone who possesses and utilizes it on a daily basis will easily attain top performance (Agustian, 2007). According to Muttaqiyathun (2010) and Faitullah (2014), emotional intelligence positively influences lecturers’ performance. Anwar’s (2017) and Makkasau’s (2018) results confirm this conclusion. Therefore, the second hypothesis is declared as follows.

H2: Emotional intelligence will have a positive effect on lecturer performance.

Spiritual intelligence concentrates on the personality and is often associated with wisdom (Zohar & Marshall, 2007). This intelligence leads to revealing the truth, which then benefits the soul. People possessing this intelligence will make the better performance it and improve the quality of their life (Imawan, 2004). This type of intelligence contributes to performance in the face of substantial working strains because it brings about joyfulness and rationality (Noermijati, 2013). Muttaqiyathun (2010) and Makkasau (2018) support this explanation by affirming that the effect of spiritual intelligence on performance is positive. Therefore, the third hypothesis is declared as follows.

H3: Spiritual intelligence will have a positive effect on lecturer performance.

3. Methodology

3.1 Population and Samples

The private university lecturers who have become active members of Indonesia’s Management Forum before 2019 are study population. According to the information from the forum secretariat, the number of members is around 500. To get the total samples (n) that represent the total population (N), we used the Slovin formula cited in Suliyanto (2009), presented in equation 1 with the border of error (e) of 5%.

                   (1)

By this formula, the total samples calculated are To select 222 lecturers, furthermore, we utilize the simple random sampling method.

3.2 Data Collection Method

This research uses the primary data of respondents of the online survey carried out from March to April 2019. Unfortunately, not all respondents provided a full response. Only 100 lecturers filled the questionnaire completely. Therefore, the response rate is 100/222 x 100% = 45.05%. This rate is higher than 20%, which is the required response set by Sugiyanto et al. (2018). It means this level is still acceptable.

3.3 Determining Research Variables

The first variable is motivation, which has been measured with a scale adopted from Perwita et al. (2016) consisting of five items of intrinsic motivation (M1-M5) and extrinsic motivation (M6-M10) (see Table 1).

Table 1:  Indicators of motivation

The type of motivation	Indicator
Intrinsic motivation	M1: Working as a lecturer is interesting to me. M2: Working as a lecturer provides me with an opportunity to improve. M3: Working as a lecturer can improve my reputation. M4: Working as a lecturer encourages me to acquire some achievements. M5: Working as a lecturer stimulates me to fulfil my duties.
Extrinsic motivation	M6: My decision to be a lecturer is due to interpersonal relationships with other parties. M7: My decision to be a lecturer is due to conducive working conditions. M8: My decision to be a lecturer is due to quality supervision. M9: My decision to be a lecturer is due to a clear procedure for compensation. M10: M y decision to be a lecturer is for adequate financial compensation.

                                                  Source: Adopted from Perwita et al. (2017)

The second variable is emotional intelligence, where its measurements are denoting the study of Tjun, Setiawan, and Setiana (2017) consisting of five dimensions, namely, self-awareness (SA), self-control (SC), motivation (MOT), empathy (E), and social skills (SCL). Moreover, each indicator of these dimensions is in Table 2.

Table 2: Indicators of the dimensions of emotional intelligence

Dimension	Indicator
Self-awareness	SA1: I like myself. SA2: I know my strength. SA3: I exist for a reason. A4: I am angry with reason. SA5: I never doubt my ability. SA6: I can do something. SA7: I am not worried about my future. SA8: I dare to be different from my friends. SA9: I can get what I want. SA10: I will finish the job, although I do not like its responsibility.
Self- control	SC1: I am patient with other people. SC2: I easily recover quickly after feeling disappointed. SC3: I think of what I want before acting. SC4: I remain calm in situations making other people angry. SC5: I can control my life. SC6: I am calmer than others. SC7: I am not quickly bored and tired of doing things. SC8: Tight competition does not reduce my enthusiasm. SC9: To achieve another larger goal, I can delay the satisfaction of my momentary pleasure. SC10: I immediately finish the work I plan without wasting time.
Motivation	MOT1: I know the purpose of my life. MOT2: I like trying new things. MOT3: I always try the same job again until I am successful. MOT4: I join various information and ideas. MOT5: I am happy to face challenges to solve problems. MOT6: If I encounter obstacles to reach a goal, I will turn to another one. MOT7: I do not easily surrender when doing difficult tasks. MOT8. The hope of success influences me more than the fear of failure. MOT9: I am interested in work requiring me to give new ideas. MOT10: I often introspect to rediscover the important one in my life.
Empathy (E)	E1: I own a lot of close friends from various backgrounds. E2: I can usually find out how other people feel about me. E3: I feel that my friend does not drop me. E4: I easily understand others’ point. E5: I am confident when talking to people I don’t know. E6: I can make people I don’t know talk about themselves. E7: I can convey something that attracts other people’s attention during the meeting. E8: I can feel that people are hurt, although they do not tell it. E9: I am a source of advice for my friends with problems. E10: I can put myself in someone else’s position
Social skills (SS)	SS1: I can accept critiques with an open mind as long as they can be justified. SS2: I easily come up with the topic of conversation with others. SS3: I easily become friends with people. SS4: Ethics guides me when I deal with others. SS5: My problems do not affect my relationships with others. SS6: I can feel the mood of a group. SS7: I joy and do not talk too much when I am among people.

Source: Adopted from Tjun, Setiawan, and Setiana (2009)

The third variable is spiritual intelligence, with indicators adopted from King (2008) as well as Anwar & Osman-Gani (2015). It covers 24 question items distributed into four dimensions: critical existential thinking (7 items), personal meaning production (5 items), transcendental awareness (7 items), conscious state expansion (5 items).

Table 3: Indicators of the dimensions of spiritual intelligence

Dimension	Indicator
Critical existential thinking	CET1: I often ask the question and reflect on the characteristics of reality. CET2: I use the time to reflect on the reason for my existence. CET3: I can deeply reflect on something that happened after death. CET4: I have developed my theory about things like life, death, reality, and existence. CET5: I often reflect on the meaning of events in my life. CET6: I often contemplate the relationship between humans and the whole universe CET7: I think about unlimited power.
Personal meaning production	PMP1: I can find meaning and purpose in life so that it helps me adapt to stressful situations. PMP2: I can define goals or reasons for my life. PMP3: When I failed, I was still able to find meaning in my failure. PMP4: I can make decisions according to the purpose of my life. PMP5: I can find meaning and purpose in my daily experience.
Transcendental awareness	TA1: I recognize aspects of myself better than my physique. TA2: I easily feel beyond tangible items. TA3: I realize a deeper relationship between me and others exists. TA4: I define myself deeper than my physique. TA5: I have a high awareness of non-physical aspects of life. TA6: I recognize the quality of people more meaningful than their body, personality, or emotion. TA7: Recognizing aspects of non-physical life helps me concentrate.
Conscious state expansion	CSE1: I can achieve a high level of consciousness. CSE2: I can control myself when entering a higher level of consciousness. CSE3: I can freely move between levels of consciousness CSE4: I often see problems and choices clearly when a high awareness exists. CSE5: I can develop techniques to enter higher awareness.

Source: Adopted from Anwar & Osman-Gani (2015)

The fourth variable is the lecturer’s performance. We define it as the success of the lecturer to perform the activities related to research, community service, and teaching. Furthermore, three aspects become the dimension of the performance. The indicators used in this study for each dimension refer to the relevant content of the accreditation instrument version 4 for the study program. For the research performance dimension, the indicators are as follows.

1. I can publish my research results in reputable international and national journals (RP1)
2. I can publish my research results in the proceeding of international and national conferences or seminars (RP2).
3. I can publish my research results in international and national media that can be accessed by the public (RP3).
4. I can get external funds from abroad or domestic to finance the research (RP4).
5. I can obtain an intellectual property right based on the results of my research (RP5).
6. I can produce books with ISBN based on the results of my research (RP6).

For the community service performance dimension, the indicators are as follows.

1. I can publish the activity related to the service for the community in the related journals and proceedings (CSP1)
2. I can obtain an intellectual property right based on the activities of the service for the community (CSP2).
3. I can obtain an intellectual property right based on the activities of the service for the community (CSP3).
4. I can produce books with ISBN based on the results of the service community (CSP4).

For the teaching performance dimension, the indicators are as follows.

1. I can mix the results of my research into the learning materials for the students (TP1).
2. I can mix the results of my service community into the learning materials for the students (TP2).

3.4 Validity and Reliability Test

Although the instruments are already designed based on existing literature, testing the data validity and reliability is still vital. The validity and reliability test intends to prove the accuracy and consistency of respondents’ answers, respectively.

• This research uses confirmatory factor analysis (CFA) as the validity test, by comparing the loading factor value of each indicator with the 0.5. If its value exceeds 0.5, the answer of respondents is valid. If it has a value below 0.5, it should be removed (Sholihin and Ratmono, 2013).
• This research utilizes the Cronbach Alpha (CA) analysis as the reliability test after all respondents’ answers of indicators are valid. This analysis is conducted by comparing the CA value with 0.7. A collection of convincing indicators is reliable if the CA is higher than 0.7(Ghozali, 2016).

3.5 Data Analysis Method

Examining the effect of motivation (M), emotional intelligence (EI), and spiritual intelligence (SI) on lecturer performance (LP) requires for a method variance-based structural equation model to analyze data. This is because these variables are not directly observed, and the number of respondents is between 30 and 100 (Ghozali, 2014). Additionally, this model is exhibited in equation two.

LP = β₀ + γ₁.M + γ₂.EI + γ₃. SI + ζ                                                               (2)

4. Result and Discussion

4.1 The Statistics of the Demographic Characteristics

The statistic used is the frequency to capture the total lecturers categorized by gender, functional position, the study field, working duration, work status, academic degree. Table 4 presents the number of lecturers by gender. Of the 100, 66 females (66%) and 34 males (34%) participate in this survey.

Table 4: The Total Lecturers categorized by gender

Gender	The number of lecturers	Percentage
Male	34	34%
Female	66	66%
Total	100	100%

Source: Processed Survey Data

Table 5 exhibits the number of lecturers joining this survey, categorized by their functional position. The number of the expert assistants is 25 (25%),  the senior lecturer is  45%, the associate professors are 27 (27%), and there are 3 professors (3%).

Table 5: The Total Lecturers categorized by Functional Position

Functional Position	The number of lecturers	Percentage
Expert Assistant	25	25%
Senior Lecturer	45	45%
Associate Professor	27	27%
Professors	3	3%
Total	100	100%

Source: Processed Survey Data

Table 6 illustrates the number of lecturers categorized by the field of their study. This table informs that the number of lecturers from the management field is 88, from the accounting field is 2, from the business administration field and industrial engineering field is 2. There is one lecturer from Islamic economics and finance field, the economics of development field, and information system field, respectively.

Table 6: The total number of lecturers  categorized by  the field of study

The Field of Study	The number of lecturers	Percentage
Business administration	2	2%
Accounting	5	5%
Islamic economics and finance	1	1%
Economics of development	1	1%
Management	88	88%
Information system	1	1%
Industrial engineering	2	2%
Total	100	100%

Source: Processed Survey Data

Table 7 displays the number of lecturers by their tenure. This table shows that the number of lecturers having a tenure less than 10 years is 19, between 10 and 20 is 44, between 21 and 30 is 30, over 30 is 7.

Table 7: The number of lecturers categorized by the working duration

Working duration	The number of lecturers	Percentage
< 10 Year	19	19%
10 – 20 Years	44	44%
21 -30 Years	30	30%
>30 Years	7	7%
Total	100	100%

Source: Processed Survey Data

Table 8 shows the number of lecturers categorized by their status. This table shows that the number of lecturers without and with the additional managerial assignment is 53 and 47, respectively.

Table 8: The number of lecturers categorized by the work status

Status of work	The number of lecturers	Percentage
Lecturer without the additional managerial assignment	53	53%
Lecturer with additional managerial assignments	47	47%
Total	100	100%

Source: Processed Survey Data

Table 9 displays the number of lecturers categorized by academic degrees of master of 54 and doctor of 46, respectively.

Table 9:  The number of lecturers categorized by the academic degree

Academic Degree	The number of respondents	Percentage
Master	54	54%
Doctor	46	46%
Total	100	100%

Source: Processed Survey Data

4.2 The Output of Validity and Reliability Test and Interpretation

This study uses confirmatory factor analysis  (CFA) to test the data validity. For motivation, the first result is illustrated in Table 10A. As seen in this table, M6 is the invalid indicator because the loading factor value is 0.298, lower than 0.5. Hence, removing M6 is essential.

Table 10A: The beginning CFA result: The Loading Factor Values of Motivation Indicators

Indicator	Loading factor	Interpretation	Indicator	Loading factor	Interpretation
M1	0.613	Valid	M6	0.298	Invalid
M2	0.729	Valid	M7	0.672	Valid
M3	0.581	Valid	M8	0.665	Valid
M4	0.740	Valid	M9	0.645	Valid
M5	0.664	Valid	M10	0.749	Valid

Source: Modified Warp PLS Output

After removing M6, CFA was conducted again, and the result is in Table 10B. As seen in this table, all the indicators are valid because all the loading factors are above 0.5.

Table 10B: The final CFA Result: The Loading Factor Values of Motivation Indicators

Indicator	Loading factor	Interpretation	Indicator	Loading factor	Interpretation
M1	0.629	Valid	M7	0.659	Valid
M2	0.739	Valid	M8	0.648	Valid
M3	0.588	Valid	M9	0.649	Valid
M4	0.748	Valid	M10	0.734	Valid
M5	0.678	Valid

Source: Modified Warp PLS Output

For self-awareness as the first dimension of emotional intelligence, SA3, SA4, SA7, and SA10 are the invalid indicators because their loading factor values are 0.257, 0.268, 0.476, 0.426, respectively, lower than 0.5 (see Panel A of Table 11A). For motivation as the second dimension of motivation, MOT1 and MOT6 are invalid because their loading factors are 0.319 and 0.064, respectively, lower than 0.5 (see Panel B of Table 11A). For empathy and social skill as the third and fourth dimensions, all the indicators are valid because these loading factor values are higher than 0.5 (see Panel C and D of Table 11A).

Table 11A: The beginning result of CFA: The Loading Factor Values of Self-Awareness, Self-Control, Motivation, Empathy, and Social Skill Indicators

Panel A. Dimension of self-awareness
Indicator	Loading factor	Interpretation	Indicator	Loading factor	Interpretation
SA1	0.589	Valid	SA6	0.776	Valid
SA2	0.660	Valid	SA7	0.476	Invalid
SA3	0.257	Invalid	SA8	0.730	Valid
SA4	0.268	Invalid	SA9	0.766	Valid
SA5	0.730	Valid	SA10	0.426	Invalid
Panel B. Dimension of self-control
Indicator	Loading factor	Interpretation	Indicator	Loading factor	Interpretation
SC1	0.787	Valid	SC6	0.865	Valid
SC2	0.624	Valid	SC7	0.629	Valid
SC3	0.708	Valid	SC8	0.761	Valid
SC4	0.817	Valid	SC9	0.805	Valid
SC5	0.793	Valid	SC10	0.683	Valid
Panel C. Dimension of motivation
Indicator	Loading factor	Interpretation	Indicator	Loading factor	Interpretation
MOT1	0.319	Invalid	MOT6	0.064	Invalid
MOT2	0.660	Valid	MOT7	0.740	Valid
MOT3	0.774	Valid	MOT8	0.560	Valid
MOT4	0.670	Valid	MOT9	0.830	Valid
MOT5	0.831	Valid	MOT10	0.677	Valid
Panel D. The Dimension of Empathy
Indicator	Loading factor	Interpretation	Indicator	Loading factor	Interpretation
E1	0.583	Valid	E6	0.739	Valid
E2	0.622	Valid	E7	0.678	Valid
E3	0.645	Valid	E8	0.688	Valid
E4	0.763	Valid	E9	0.789	Valid
E5	0.680	Valid	E10	0.757	Valid
Panel E. The Dimension of Social Skill
Indicator	Loading factor	Interpretation	Indicator	Loading factor	Interpretation
SS1	0.777	Valid	SS5	0.817	Valid
SS2	0.758	Valid	SS6	0.615	Valid
SS3	0.585	Valid	SS7	0.584	Valid
SS4	0.864	Valid

Source: Modified Warp PLS Output

After eliminating the invalid indicators of SA3, SA4, SA7, SA10, MOT1, and MOT6, the CFA is conducted again, and the result is shown in Table 11B. As illustrated by this table, all the indicators of each dimension of emotional intelligence are valid since these loading factor values are higher than 0.5.

Table 11B: The final result of CFA: The Loading Factor Values of Self-Awareness and Motivation

Panel A. Dimension of self-awareness
Indicator	Loading factor	Interpretation	Indicator	Loading factor	Interpretation
SA1	0.635	Valid	SA6	0.788	Valid
SA2	0.730	Valid	SA8	0.726	Valid
SA5	0.762	Valid	SA9	0.741	Valid
Panel B. Dimension of motivation
Indicator	Loading factor	Interpretation	Indicator	Loading factor	Interpretation
MOT2	0.668	Valid	MOT7	0.741	Valid
MOT3	0.776	Valid	MOT8	0.553	Valid
MOT4	0.687	Valid	MOT9	0.824	Valid
MOT5	0.844	Valid	MOT10	0.662	Valid

Source: Modified Warp PLS Output

Once the indicators are valid, determining the validity status of each dimension, reflecting emotional intelligence is required. The result is listed in Table 11C. Dimensions are valid because their loading factor is higher than 0.5.

Table 11C:.The final result of CFA: The Loading Factor Value of The Emotional Intelligence Dimensions

Dimension	Loading Factor	Interpretation
Self-awareness	0.735	Valid
Self-control	0.875	Valid
Motivation	0.883	Valid
Empathy	0.824	Valid
Social skill	0.870	Valid

Source: Modified Warp PLS Output

Table 12A shows the loading factor values of the indicators of the dimensions of spiritual intelligence. Because these values are higher than 0.5, the validity test on these indicators is achieved.

Table 12A: The CFA result: The Loading Factor Indicators Values of Dimensions of Spiritual Intelligence

Panel A. Dimension of Critical Existential Thinking			Panel C. Dimension of transcendental awareness
Indicator	Loading factor	Interpretation	Indicator	Loading factor	Interpretation
CET1	0.859	Valid	TA1	0.765	Valid
CET2	0.881	Valid	TA2	0.747	Valid
CET3	0.868	Valid	TA3	0.844	Valid
CET4	0.650	Valid	TA4	0.856	Valid
CET5	0.853	Valid	TA5	0.887	Valid
CET6	0.932	Valid	TA6	0.825	Valid
CET7	0.813	Valid	TA7	0.869	Valid
Panel B. Dimension of personal meaning production			Panel D. Dimension of conscious state expansion
Indicator	Loading factor	Interpretation	Indicator	Loading factor	Interpretation
PMP1	0.826	Valid	CSE1	0.822	Valid
PMP2	0.905	Valid	CSE2	0.918	Valid
PMP3	0.896	Valid	CSE3	0.946	Valid
PMP4	0.865	Valid	CSE4	0.909	Valid
PMP5	0.887	Valid	CSE5	0.927	Valid

Source: Modified Warp PLS Output

After determining the validity of all indicators, deciding the validity status of each dimension, reflecting spiritual intelligence is essential. Results are illustrated in Table 12B. In this table, the loading factor value exceeds 0.5. Therefore, the five dimensions reflecting spiritual intelligence are valid.

Table 12B: Loading Factor Value of Dimensions of Spiritual Intelligence

Dimension	Loading Factor	Interpretation
Critical existential thinking	0.814	Valid
Personal meaning production	0.761	Valid
Transcendental awareness	0.855	Valid
Conscious state expansion	0.815	Valid

Source: Modified Warp PLS Output

Table 13A shows the loading factor values of the dimensions of lecturer performance. Since these values are higher than 0.5, the validity test on these dimensions gets achieved.

Table 13A: The CFA result: The Loading Factor Indicator Values of Dimensions of Lecturer Performance

Panel A. Dimension of research performance
Indicator	Loading factor	Interpretation
RP1	0.612	Valid
RP2	0.596	Valid
RP3	0.638	Valid
RP4	0.728	Valid
RP5	0.751	Valid
RP6	0.731	Valid
Panel B. Dimension of community service performance
Indicator	Loading factor	Interpretation
CSP1	0.830	Valid
CSP2	0.841	Valid
CSP3	0.863	Valid
CSP4	0.854	Valid
Panel C. Dimension of teaching performance
Indicator	Loading factor	Interpretation
TP1	0.947	Valid
TP2	0.947	Valid

Source: Modified Warp PLS Output

Once all the indicators are valid, determining the validity status of each dimension, reflecting lecturer performance is vital. Results are shown in Table 13B. Because these values are higher than 0.5, the validity test on these dimensions gets achieved.

Table 13B: Loading Factor Value of Dimensions of Lecturer Performance

Dimension	Loading Factor	Interpretation
Research Performance	0.895	Valid
Community Service Performance	0.853	Valid
Teaching Performance	0.675	Valid

Source: Modified Warp PLS Output

This study uses the Cronbach Alpha (CA) analysis to determine the reliability of the valid indicators for motivation and dimension of emotional and spiritual intelligence, as well as lecturer performance. The result is in Table 14. Because all coefficients of CA are higher than 0.7, the reliability test stand reached.

Table 14: Cronbach Alpha’s Coefficient of The Valid Indicators

Latent Variable/ Dimension	Measurement Status	Total valid Indicators	The name of valid indicators	Cronbach Alpha
Motivation	Latent variable	9	M1, M2, M3, M4, M5, M7, M8, M9, M10	0.851
Emotional intelligence (EI)/self-awareness	Dimension	6	SA1, SA2, SA5, SA6, SA8, SA9	0.825
EI/self- control	Dimension	10	SC1, SC, SC3, SC4, SC5, SC6, SC7, SC8, SC9, SC10	0.912
EI/motivation	Dimension	8	MOT2, MOT3, MOT4, MOT5, MOT7, MOT8, MOT9, MOT10	0.867
EI/ empathy	Dimension	10	E1, E2, E3, E4, E5, E6, E7, E8, E9, E10	0.881
EI/social skill	Dimension	7	SS1, SS2, SS3, SS4, SS5, SS6, SS7	0.841
Spiritual intelligence (SI)/ critical existential thinking	Dimension	7	CET1, CET2, CET3, CET4, CET5, CET6, CET7	0.929
SI/personal meaning production	Dimension	5	PMP1, PMP2, PMP3, PMP4, PMP5	0.924
SI/ transcendental awareness	Dimension	7	TA1,  TA2, TA3, TA4, TA5, TA6, TA7	0.923
SI/ conscious state expansion	Dimension	5	CSE1, CSE2, CSE3, CSE4, CSE5	0.944
Lecturer Performance (LP)/ Research Performance	Dimension	6	RP1, RP2, RP3, RP4, RP5, RP6	0.764
LP/ Community Service Performance	Dimension	4	CSP1, CSP2, CSP3, CSP4	0.869
LP/ Teaching Performance	Dimension	2	TP1, TP2	0.885

Source: Modified Warp PLS Output

4.3 The Estimation Result of Structural Equation Model

After testing the validity and reliability of the data, estimating the variance-based structural equation model (SEM) is the subsequent step, and the result is in Table 15.

Table 15: The Estimation Result of Variance-based SEM for The Effect of Motivation, Emotional and Spiritual Intelligence on Lecturer Performance

The determinant of lecturer performance	Path Coefficient	Standard error	t-statistic	Probability Value
Motivation	0.140	0.140	1.000	0.160
Emotional Intelligence	0.361	0.141	2.560	0.006
Spiritual Intelligence	0.160	0.137	1.168	0.122

Source: Modified Warp PLS Output

4.4 The Test Result of the Hypotheses

The first research hypothesis states that motivation has a positive effect on lecturer performance; it becomes the first alternative hypothesis. Moreover, we test the null hypothesis by comparing the probability value of t-statistic for motivation with a significance level (α) of 5%. In Table 15, this value is 0.160. Since this value is higher than α, the null hypothesis stating motivation does not affect the lecturer’s performance is accepted.

The second research hypothesis states that emotional intelligence has a positive effect on lecturer performance; it becomes the second alternative hypothesis. Moreover, we tested the null hypothesis by comparing the probability value ​​of t-statistic for emotional intelligence with a significance level (α) of 5%. In Table 15, this value is 0.006. Since this value is lower than α, the null hypothesis is rejected. Instead, the alternative hypothesis is accepted.

The third research hypothesis states that spiritual intelligence has a positive effect on lecturer performance. Moreover, we test the null hypothesis by comparing the probability value ​​of t-statistic for spiritual intelligence with a significance level (α) of 5%. In Table 15, the probability value is 0.122. Since this value is higher than α, the null hypothesis, declaring spiritual intelligence does not affect the lecturer’s performance, is recognized.

4.5 Discussion

In this research, motivation does not have a positive effect on lecturer performance. Even when lecturers are well encouraged, this does not impact on their performance. According to Robescu & Iancu (2016), this is due to the difficulty of tasks have to accomplish. In the context of this study, the responsibilities of lecturers encompass publishing their articles in a reputable international journal and resulting in useful outcomes based on their research.

Moreover, this research displays that emotional intelligence has a positive effect on the lecturers’ performance. This intelligence enables lecturers to collaborate when they teach a team of students and design the contents of subjects for improving the curriculum, execute the research and service community activity and publish their results in the related average journal to get the various forms of intellectual property rights. Therefore, this research confirms the study of Muttaqiyathun (2010), Faitullah (2014), Anwar (2017), and Makkasau (2018).

Furthermore, this research shows that spiritual intelligence does not affect lecturer performance. This means that spiritual intelligence cannot contribute to working performance. Therefore, this research affirms the study result of Haryono et al. (2018).

5. Conclusion

The goal of this research is to examine and analyze the impact of motivation, emotional, and spiritual intelligence on lecturer performance by SEM based on variance.  Based on the executed analysis, this study implies two things.

1. Motivation and spiritual intelligence do not affect lecturer performance.
2. Emotional intelligence has a positive effect on lecturer

Evidence has both practical and theoretical suggestions.

• As a practical implication, achieving an excellent performance requires the training of emotional intelligence. Therefore, higher education institutions can facilitate this training for their lecturers to increase the ability to control their emotions and to cooperate in the teamwork.
• As a theoretical implication, the next researchers can do two things. Firstly, employing the other determinants of lecturer performance like intellectual intelligence, compensation, work environment, leadership, organizational citizenship behaviour, and stress. Secondly, treating spiritual intelligence as a moderating variable of the causal relationship between stress and performance.

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