**Nasyid Competition Assessment Using Fuzzy Evaluation Method**

\*\*This is a Double-blind review, please do not include authors information in this version \*\*

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**HIGHLIGHTS**

  - The Fuzzy evaluation method was used to evaluate the nasyid competition.

  - The primary data was collected from nasyid competition in Kedah.

  - This study evaluates a participant's performance based on several factors, including Voice, Music, Lyrics, and Performance.

**ABSTRACT**

*The nasyid competition evaluates a participant's performance based on several factors, including Voice, Music, Lyrics, and Performance. Participants in the nasyid competition are usually assigned a point value of 100, with each point representing a linguistic word such as “Perfect”, “Spectacular”, “Very Good” and so on. Evaluating participant performance is especially difficult because it involves human decision-making, which is imprecise, ambiguous, and unpredictable. This study employs the fuzzy evaluation method to assess participant performance at a nasyid competition held in Kedah. In this manner, the membership function graph was used to determine the membership value of each satisfaction level. When fuzzy numbers are used, the fuzzy markings are created more consistently. The satisfaction level of each participant’s mark would then be computed. At the end, the fuzzy markings with linguistic value would be obtained. The proposed assessment method has a bright future in evaluating those participants’ performance because it provides an alternative approach to assessing performance.*

***Keywords:** Fuzzy evaluation method, membership function, satisfaction level, nasyid competition*

# INTRODUCTION

The word nasyid is derived from the term ansyada, which means poetic melodies (Adil Johan, Mayco A. Santaella, 2021). The term ansyada also means to recite poetry and is connected to singing. When the Prophet Muhammad initially travelled from Mecca to Medina, the people of Medina greeted him with a nasyid. Nasyid is presently a type of Islamic devotional music with lyrics praising Allah or embracing other religious concepts such as universal love, good morals, or Islamic solidarity (Beng, 2007). They also campaigned for Islamic values and practices. The tunes were either sung a cappella or with frame drums such as the rebana or kompang accompanying them. Nasyid was already conducted organically by Islamic teachers and pupils in Malaysia at the end of World War II as a diversion during Quran reading sessions (Azniwati Abdul Aziz, Mohamed Akhiruddin Ibrahim, Mohammad Hikmat Shaker, Azlina Mohamed Nor, 2016). The Arabic language was first utilized, but Malay gradually took its place. Hence, it is easier to understand the meaning of the songs and more relatable for its audience.

Accompanied by musical instruments, nasyid undeniably became a popular medium for dakwah, meaning to preach in many mosques and religious events (Weintraub, 2011). Dakwah organizations like Darul Arqam promoted nasyid in the 1980s through live concerts by allied musical groups like Nada Murni and The Zikr. These non-profit organizations improved nasyid by including percussion instruments and releasing their own cassettes at Darul Arqam's cultural festivals. In the 1990s, the Prime Minister's Council's Islamic Affairs Ministry commissioned a plan to develop a modern age nasyid. This was in line with Dr. Mahathir Mohamed's new modernization narrative, Vision 2020, which he formulated at the time. In parallel to Vision 2020, Malaysia's road to modernization, psychological, religious, and ethical consciousness seem possible (Rafikul Islam, Yusof Ismail, 2011) & (Nur Azura Sanusi, Normi Azura Ghazali, 2014).

Islam plays an important role in accomplishing that vision. With influences from Darul Arqam's Nada Murni and post-modern nasyid, a new commercial version of nasyid called pop nasyid has emerged in Malaysia (Rahman Arifai, Ishak Saat, 2021). With the publication of their debut album Puji-Pujian, Raihan, the pioneer of commercial pop nasyid, soared to popularity. Since Raihan, several nasyid pop acts have emerged in Malaysia. Some of the most well-known groups include Hijjaz, Rabbani, In-Team, Waheeda, Mawi, Ramli Sarip, and many others. School children are developing their own bands as a response to the influence of pop nasyid. The Ministry of Education Malaysia (MOE) also organizes nasyid tournaments for public schools to compete in, to promote nasyid principles among students. The ministry organizes nasyid competitions at all levels of education, including primary, secondary, and higher education at public universities. This study is eager to investigate a method of evaluating nasyid participant performance in efficient way by adapting a fuzzy approach technique.

# METHODOLOGY

In the methodology, we will discuss how the fuzzy approach will be adapted in the evaluation process.

*Step 1: Normalizing the marks*

Table 1 shows the sample of normalized value calculated by using equation (1) as follow.

> \(\text{Normalized\ value}\left( \text{NV} \right) = \frac{Marks\ obtained\ (MO)}{Total\ marks\ (TM)}\) (1)

Table 1: The normalized value for each criterion in nasyid competition

| **CRITERIA** | **TOTAL MARK** | **MARK OBTAINED** | **NORMALIZED VALUE** |  |
| ------------ | -------------- | ----------------- | -------------------- |  |
|              |                |                   |                      |  |
| Voice        | 40             | 29                | 0.73                 |  |
| Music        | 30             | 28                | 0.93                 |  |
| Lyrics       | 20             | 16                | 0.8                  |  |
| Performance  | 10             | 9                 | 0.9                  |  |

*Step 2: Developing the graph of the fuzzy membership function*.

In order to perform the fuzzification process, the membership feature graph is developed as shown in Figure 1. In this step, the input value is transferred to the membership graph function to obtain the fuzzy membership value of the corresponding particular input value.

|                                               |
| --------------------------------------------- |
| ![graf](63f6f2ae1ad6a_media/media/image1.png) |

Figure 1: Membership function graph for satisfaction level of nasyid competition

Table 2 shows twelve degrees of satisfaction suggested by Daud et.al, 2011. The set of marks for each level of satisfaction is reflected by the degrees of satisfaction. The highest level of satisfaction is determined by the mapping function for the appropriate satisfaction standard, which is indicated by T(Xi), where T(Xi) is 0 to 1.

> Table 2: Satisfaction levels and the corresponding degrees of satisfaction

| SATISFACTION LEVEL (Xi)    | DEGREES OF SATISFACTION | MAXIMUM DEGREE OF SATISFACTION T(Xi) |  |
| -------------------------- | ----------------------- | ------------------------------------ |  |
|                            |                         |                                      |  |
| Perfect (PF)               | 80%-100% (0.8-1.0)      | 1                                    |  |
| Spectacular (ST)           | 75%-79% (0.75-0.79)     | 0.79                                 |  |
| Impressive (IS)            | 70%-74% (0.7-0.74)      | 0.74                                 |  |
| Very Good (VG)             | 65%-69% (0.65-0.69)     | 0.69                                 |  |
| Good (GD)                  | 60%-64% (0.6-0.64)      | 0.64                                 |  |
| Competent (CP)             | 55%-59% (0.55-0.64)     | 0.59                                 |  |
| Almost Competent (ACP)     | 50%-54% (0.5-0.54)      | 0.54                                 |  |
| Marginally Competent (MCP) | 45%-49% (0.45-0.49)     | 0.49                                 |  |
| Unpleasant (UP)            | 40%-44% (0.4-0.44)      | 0.44                                 |  |
| Bad (BD)                   | 35%-39% (0.35-0.39)     | 0.39                                 |  |
| Very Bad (VBD)             | 30%-34% (0.3-0.34)      | 0.34                                 |  |
| Extremely Bad (EBD)        | 0-29% (0-0.29)          | 0.29                                 |  |

*Step 3: Calculating the degree of satisfaction*

In this step, the degree of satisfaction which is denoted by *D*(*C<sub>i</sub>*) is evaluated by:

Degree of satisfaction *D*(*C<sub>i</sub>*) = \(\frac{y_{1}\left( Tx_{1} \right) + y_{2}\left( Tx_{2} \right)\text{...}y_{12}T(x_{12})}{y_{1} + y_{2} + ...y_{12}}\) (2)

where y = degree of membership value and *T(X)* = the maximum degree of satisfaction

*Step 4: Evaluating the Final mark*

For the final step, the final scores or marks are calculated using the equation (3) and will be presented in Table 3:

> \(F\left( S_{k} \right) = \frac{w_{1}D\left( C_{1} \right) + w_{2}D\left( C_{2} \right) + w_{3}D\left( C_{3} \right) + w_{4}D\left( C_{4} \right)}{w_{1} + w_{2} + w_{3} + w_{4}}\) (3)

where w is the sum of marks that reflects the number of criteria.

> Table 3: Fuzzy grade sheet

| NO. | CRITERIA | FUZZY MEMBERSHIP VALUE | DEGREE OF SATISFACTION | FINAL MARK |    |     |     |    |    |    |    |    |    |       |       |  |
| --- | -------- | ---------------------- | ---------------------- | ---------- | -- | --- | --- | -- | -- | -- | -- | -- | -- | ----- | ----- |  |
|     |          |                        |                        |            |    |     |     |    |    |    |    |    |    |       |       |  |
|     |          | EBD                    | VBD                    | BD         | UP | MCP | ACP | CP | GD | VG | IS | ST | PF |       |       |  |
| 1   | C1       |                        |                        |            |    |     |     |    |    |    |    |    |    | D(C1) | F(S1) |  |
|     | C2       |                        |                        |            |    |     |     |    |    |    |    |    |    | D(C2) |       |  |
|     | C3       |                        |                        |            |    |     |     |    |    |    |    |    |    | D(C3) |       |  |
|     | C4       |                        |                        |            |    |     |     |    |    |    |    |    |    | D(C4) |       |  |

**FINDINGS AND DISCUSSIONS**

The scores obtained from each school participant would be normalized and used as an input value for this evaluation as shown in Table 4. We must divide the overall maximum mark by the mark received from each criterion.

> **Table 4: Samples of normalized value for nasyid competition**

| No. | School            | Criteria   | Total Marks | Marks Obtained | Normalized Value |
| --- | ----------------- | ---------- | ----------- | -------------- | ---------------- |
| 1   | SK SUNGAI LAYAR   | VOICE      | 40          | 28             | 0.7              |
|     |                   | MUSIC      | 30          | 27             | 0.9              |
|     |                   | LYRICS     | 20          | 18             | 0.9              |
|     |                   | PERFOMANCE | 10          | 8              | 0.8              |
| 2   | SK TELOK WANG     | VOICE      | 40          | 27             | 0.68             |
|     |                   | MUSIC      | 30          | 26             | 0.87             |
|     |                   | LYRICS     | 20          | 13             | 0.65             |
|     |                   | PERFOMANCE | 10          | 8              | 0.8              |
| 3   | SK PINANG TUNGGAL | VOICE      | 40          | 29             | 0.73             |
|     |                   | MUSIC      | 30          | 28             | 0.93             |
|     |                   | LYRICS     | 20          | 16             | 0.8              |
|     |                   | PERFOMANCE | 10          | 9              | 0.9              |
| 4   | SK IBRAHIM        | VOICE      | 40          | 31             | 0.78             |
|     |                   | MUSIC      | 30          | 25             | 0.83             |
|     |                   | LYRICS     | 20          | 18             | 0.9              |
|     |                   | PERFOMANCE | 10          | 10             | 1                |

Figure 1 represents the satisfaction levels of impressive and spectacular, which reflect the degree of membership for normalized value of 0.73 from the first criteria for SK Pinang Tunggal. The samples for degree of satisfaction and final marks are calculated as follows using equation (2) and (3).

> **Table 5: Samples of calculation for degree of satisfaction and final score for each participant**

| 1                | SK SUNGAI LAYAR                                                                  |                  |                                                                                                                                                                                                                         |
| ---------------- | -------------------------------------------------------------------------------- | ---------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| D(C<sub>1</sub>) | \(\frac{\left( 0.2 \right)\left( 0.79 \right) + (0.8)(0.74)}{0.2 + 0.8}\) = 0.75 | F(S<sub>1</sub>) | \(\frac{\left( 40 \right)\left( 0.75 \right) + \left( 30 \right)\left( 1.00 \right) + \left( 20 \right)\left( 1.00 \right) + (10)(1.00)}{100}\) = 0.900                                                                 |
| D(C<sub>2</sub>) | \(\frac{\left( 1.0 \right)\left( 1.00 \right) + (0)(1.00)}{1.0 + 0}\) = 1.00     |                  |                                                                                                                                                                                                                         |
| D(C<sub>3</sub>) | \(\frac{\left( 1.0 \right)\left( 1.00 \right) + (0)(1.00)}{1.0 + 0}\) = 1.00     |                  |                                                                                                                                                                                                                         |
| D(C<sub>4</sub>) | \(\frac{\left( 1.0 \right)\left( 1.00 \right) + (0)(1.00)}{1.0 + 0}\) = 1.00     |                  |                                                                                                                                                                                                                         |
| 2                | SK TELOK WANG                                                                    |                  |                                                                                                                                                                                                                         |
| D(C<sub>1</sub>) | \(\frac{\left( 0.2 \right)\left( 0.69 \right) + (0.8)(0.74)}{0.2 + 0.8}\) =0.73  | F(S<sub>2</sub>) | \(\frac{\left( \text{40} \right)\left( \text{0.73} \right)\text{+}\left( \text{30} \right)\left( \text{1.00} \right)\text{+}\left( \text{20} \right)\left( \text{0.70} \right)\text{+(10)(1.00)}}{\text{100}}\) = 0.832 |
| D(C<sub>2</sub>) | \(\frac{\left( 1.0 \right)\left( 1.00 \right) + (0)(1.00)}{1.0 + 0}\) = 1.00     |                  |                                                                                                                                                                                                                         |
| D(C<sub>3</sub>) | \(\frac{\left( 0.2 \right)\left( 0.74 \right) + (0.8)(0.69)}{0.2 + 0.8}\) = 0.70 |                  |                                                                                                                                                                                                                         |
| D(C<sub>4</sub>) | \(\frac{\left( 1.0 \right)\left( 1.00 \right) + (0)(1.00)}{1.0 + 0}\) = 1.00     |                  |                                                                                                                                                                                                                         |
| 3                | SK PINANG TUNGGAL                                                                |                  |                                                                                                                                                                                                                         |
| D(C<sub>1</sub>) | \(\frac{\left( 0.2 \right)\left( 0.74 \right) + (0.8)(0.79)}{0.2 + 0.8}\) = 0.78 | F(S<sub>3</sub>) | \(\frac{\left( 40 \right)\left( 0.78 \right) + \left( 30 \right)\left( 1.00 \right) + \left( 20 \right)\left( 1.00 \right) + (10)(1.00)}{100}\) = 0.912                                                                 |
| D(C<sub>2</sub>) | \(\frac{\left( 1.0 \right)\left( 1.00 \right) + (0)(1.00)}{1.0 + 0}\) = 1.00     |                  |                                                                                                                                                                                                                         |
| D(C<sub>3</sub>) | \(\frac{\left( 1.0 \right)\left( 1.00 \right) + (0)(1.00)}{1.0 + 0}\) = 1.00     |                  |                                                                                                                                                                                                                         |
| D(C<sub>4</sub>) | \(\frac{\left( 1.0 \right)\left( 1.00 \right) + (0)(1.00)}{1.0 + 0}\) = 1.00     |                  |                                                                                                                                                                                                                         |
| 4                | SK IBRAHIM                                                                       |                  |                                                                                                                                                                                                                         |
| D(C<sub>1</sub>) | \(\frac{\left( 0.2 \right)\left( 0.79 \right) + (0.8)(1.00)}{0.2 + 0.8}\) = 0.96 | F(S<sub>4</sub>) | \(\frac{\left( 40 \right)\left( 0.96 \right) + \left( 30 \right)\left( 1.00 \right) + \left( 20 \right)\left( 1.00 \right) + (10)(1.00)}{100}\) = 0.984                                                                 |
| D(C<sub>2</sub>) | \(\frac{\left( 1.0 \right)\left( 1.00 \right) + (0)(1.00)}{1.0 + 0}\) = 1.00     |                  |                                                                                                                                                                                                                         |
| D(C<sub>3</sub>) | \(\frac{\left( 1.0 \right)\left( 1.00 \right) + (0)(1.00)}{1.0 + 0}\) = 1.00     |                  |                                                                                                                                                                                                                         |
| D(C<sub>4</sub>) | \(\frac{\left( 1.0 \right)\left( 1.00 \right) + (0)(1.00)}{1.0 + 0}\) = 1.00     |                  |                                                                                                                                                                                                                         |

Based on the final mark, the participant from SK Pinang Tunggal is assign a fuzzy linguistic term of perfect at 1.0 (PF = 1.00). This figure is taken from the graph of the membership function.

Table 6: Result of fuzzy grade sheet

| No | Criteria    | Fuzzy Membership Value | Degree of Satisfaction | Final Mark |    |     |     |    |    |    |     |     |     |      |       |
| -- | ----------- | ---------------------- | ---------------------- | ---------- | -- | --- | --- | -- | -- | -- | --- | --- | --- | ---- | ----- |
|    |             | EBD                    | VBD                    | BD         | UP | MCP | ACP | CP | GD | VG | IS  | ST  | PF  |      |       |
| 1  | Voice       | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | 0.2 | 0.8 | 0.75 | 0.9   |
|    | Music       | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | \-  | 1   | 1    |       |
|    | Lyrics      | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | \-  | 1   | 1    |       |
|    | Performance | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | \-  | 1   | 1    |       |
| 2  | Voice       | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | 0.2 | 0.8 | \-  | 0.73 | 0.832 |
|    | Music       | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | \-  | 1   | 1    |       |
|    | Lyrics      | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | 0.2 | 0.8 | \-  | 0.7  |       |
|    | Performance | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | \-  | 1   | 1    |       |
| 3  | Voice       | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | 0.2 | 0.8 | \-  | 0.78 | 0.912 |
|    | Music       | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | \-  | 1   | 1    |       |
|    | Lyrics      | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | \-  | 1   | 1    |       |
|    | Performance | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | \-  | 1   | 1    |       |
| 4  | Voice       | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | 0.2 | 0.8 | \-  | 0.96 | 0.984 |
|    | Music       | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | \-  | 1   | 1    |       |
|    | Lyrics      | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | \-  | 1   | 1    |       |
|    | Performance | \-                     | \-                     | \-         | \- | \-  | \-  | \- | \- | \- | \-  | \-  | 1   | 1    |       |

The final comparison section will provide a performance study of the results produced using the fuzzy and non-fuzzy evaluation methods. Table 7 displays the results of both approaches for 16 competitors of various schools during nasyid competition in Kedah for year 2015.

Table 7: Results for 16 participants of nasyid competition obtained from fuzzy and non-fuzzy method

| School | Non-Fuzzy Method | Fuzzy Evaluation Method |            |                                    |
| ------ | ---------------- | ----------------------- | ---------- | ---------------------------------- |
|        | Final Mark       | Linguistic Term         | Final Mark | Linguistic Term                    |
| 1      | 81               | Perfect                 | 0.9        | Perfect at 1.0                     |
| 2      | 74               | Impressive              | 0.832      | Perfect at 1.0                     |
| 3      | 82               | Perfect                 | 0.912      | Perfect at 1.0                     |
| 4      | 84               | Perfect                 | 0.984      | Perfect at 1.0                     |
| 5      | 78               | Spectacular             | 0.89       | Perfect at 1.0                     |
| 6      | 86               | Perfect                 | 1          | Perfect at 1.0                     |
| 7      | 68               | Very Good               | 0.79       | Perfect at 1.0                     |
| 8      | 65               | Very Good               | 0.712      | Spectacular 0.4, Impressive at 0.6 |
| 9      | 80               | Perfect                 | 0.892      | Perfect at 1.0                     |
| 10     | 77               | Spectacular             | 0.818      | Perfect at 1.0                     |
| 11     | 80               | Perfect                 | 0.912      | Perfect at 1.0                     |
| 12     | 78               | Spectacular             | 0.877      | Perfect at 1.0                     |
| 13     | 68               | Very Good               | 0.805      | Perfect at 1.0                     |
| 14     | 69               | Very Good               | 0.755      | Perfect 0.2, Spectacular at 0.8    |
| 15     | 78               | Spectacular             | 0.878      | Perfect at 1.0                     |
| 16     | 77               | Spectacular             | 0.872      | Perfect at 1.0                     |

**CONCLUSION AND RECOMMENDATIONS**

In conclusion, an evaluation is essential to provide a greater understanding of how well one's performance is and helps to determine what works well and can be improved (Aziz et al., 2021). This study shows that the fuzzy approach with the help of the membership function graph and the fuzzy grade sheet as an alternative evaluation score to determine a result for nasyid competition. Previously, the commonly used method for obtaining the discussed competition’s scores was unsatisfactory as a result would be ambiguous and debatable amongst competitors, leaving the judges displeased. Moreover, the use of linguistic terms on the membership function graph is practical for judges to refer when providing constructive feedback for each performance as it is straightforward and explainable. Consequently, it motivates competitors to work harder to achieve the highest level of performance while also competing with other rivals in future competition.

**REFERENCES**

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[An evaluation of students' performance in poster presentations using fuzzy evaluation method](https://scholar.google.com/scholar?oi=bibs&cluster=16869437643719898791&btnI=1&hl=en)

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