Software Quality Measurement Analysis on Academic Information Systems

Measurement quantifies a process or product's extent, amount, size, capacity, or other characteristics. There are two types of measurement: direct and indirect [1, 2]. Direct measurement in software refers to tangible aspects such as expenses, labor, number of functions, memory size, documentation, inputs, outputs, lines of code, execution speed, and defects. Indirect measurement, such as assessing software quality, includes attributes like functionality, efficiency, reliability, and maintainability [3-5]. The measurement process begins with data collection, resulting in metrics-quantitative measures of an attribute's degree for an item, system, or process [6-8]. To evaluate software quality, these metrics must be transformed into indicators. An indicator is a statistic or a combination of metrics that provides comprehensive information about a product, assisting management in controlling the process and the resulting goods [9-11].

System is a collection of two or more components that constantly communicate and work together to achieve a specific goal [12]. Systems typically function as smaller subsystems that support larger, more complex systems [13, 14]. Effective systems require organization, structure, integration, and clear objectives [15, 16]. Thus, the author feels obligated to prepare a study under the heading "Analysis of Quality Improvement of Software Systems in Academic Information at Marsekal Suryadarma University."

While the methods for measuring software quality are extensively described [17-19], there is a need for detailed case studies to illustrate the practical application of these techniques. This research aims to bridge this gap by demonstrating the effectiveness of these measurement methods through case studies, comparing their application across different types of information systems within the academic context. By doing so, it will provide a deeper understanding of how these metrics and indicators can be used to improve software quality and assist university management in refining their information systems.

A globally accepted benchmark for software quality is ISO 9126. Software product quality is defined by ISO 9126, along with models, quality attributes, and related metrics that are used to assess and determine software product quality. Furthermore, management must also adhere to ISO standards. An ISO standard certificate cannot be issued for the job if the management does not adhere to the ISO standards. Six quality criteria are included in the ISO 9126 list of quality factors.

Software testing is one way to evaluate the quality of software, along with other metrics and techniques. ISO 9126 is a software quality benchmark developed by the International Electrotechnical Commission (IEC) and the International Organization for Standardization (ISO).

A globally accepted benchmark for software quality is ISO 9126. Software product quality is defined by ISO 9126, along with related metrics, models, and quality attributes that are used to assess and determine a software product's quality. Furthermore, management must also adhere to ISO standards. An ISO standard certificate cannot be issued for the job if the management does not adhere to the ISO standards. Six quality characteristics are included in the ISO 9126 list of quality criteria. They are as follows:

Usability. The capacity of software to fulfil user requirements and provide user satisfaction.

Dependability. The software's capacity to sustain a particular degree of functionality (e.g., precision, consistency, ease of use, and fault tolerance).

Practicality. Software should be easy to use, learn, understand, and appealing to users.

Effectiveness. The software's capacity to provide acceptable performance in relation to the quantity of resources consumed in the given situation (e.g., storage efficiency).

Reliability. software capacity for modification. Corrections, enhancements, or adjustments made in response to alterations in the environment, specifications, and functional needs are examples of modifications (ex: consistency).

Mobility. The software's capacity to change and adapt to different environments (e.g., self-documentation, organization) or specific uses.

The ISO 9126 model divides each software quality characteristic into many qualities sub-characteristics, which include:

(1) The functionality of ISO 9126.

(2) Dependability (ISO 9126).

(3) Usability (ISO 9126).

(4) The portability of ISO 9126.

3.1 Observation results

Based on the observations, the data as shown in Table 1 is obtained.

3.2 Numeric computation calculation

The numeric computation of the metric is that the function-oriented software metric is derived based on a functionality measurement delivered by the application as a normalized value. Since functionality cannot be measured directly, it must be derived indirectly from other direct measurements. The function-oriented metric created by Alan J. Albrecht (1979) is called a function point. Currently, there are many variations on how to calculate function points after this method was developed and revised by the International Function Point User Group (IFPUG) since 1986. However, in this research, the author will focus on using the function point created by Albrecth. Function points are derived using an empirical relationship based on direct measurement of the software's computable information domain and estimated software complexity. Function points are calculated using a rating scale as shown in Table 2.

3.3 Calculation of ISO 9126 quality indicators

After the data is collected, the next step is to look for ISO 9126 quality indicators, namely functionality, reliability, usability, efficiency, maintainability, and portability.

3.3.1 Functionality

Functionality indicators can be derived from function points. The function point calculation requires data in the form of user input, user output, user requests, files, and external interfaces. Each of these data must be assessed for complexity in general, namely simple, medium or complex. With this data and assessment, the function point calculation is as shown in Table 3.

3.3.2 Complexity modifier

The complexity modifier factor is obtained from the assessment of the fourteen attributes contained in the software. The fourteen attributes are used as factors to normalize the function point calculation. The calculation of the function point complexity variable factor is as shown in Table 4.

Table 1. Observation results

Table 2. Numeric computation and functional indicators

Unknown: Total=172

$\sum F i=30$            (1)

The formula for finding function points is as follows:

$\begin{gathered}\mathrm{FP}=\text { Total Number } \times\left(0.65+0.01 \sum F i\right) \\ F P=172 \times(0.65+(0.01 \times 30)) \\ F P=163.4 \\ F P M a x=1.35 \times \text { Total } \\ F P M a x=1.35 \times 163.4 \\ F P M a x=220.59\end{gathered}$           (2)

where, FP = Function Point; FPMax = Function Point Maximum; Total Sum = Total value of the information domain; ∑Fi = Sum of complexity adjustment prices.

Table 3. ISO 9126- Functionality

Table 4. Complexity modifier

Table 5. ISO 9126- Reliability

Based on function points and maximum function points, the level of achievement of SIAKAD software functionality is as follows:

$\begin{gathered}\text { Unknown: } F P=163.4 \\ \text { FPMax }=220.59 \\ \text { Functionality }=\frac{\text { FP }}{\text { FPMax }} \\ \text { Functionality }=\frac{\text { FP }}{\text { FPMax }}=0.7410\end{gathered}$            (3)

So, the SIAKAD software functionality value is 0.7410.

3.3.3 Reliability

Software reliability indicators are obtained from the rate of failure occurrence (ROCOF) metric. To calculate ROCOF, the variables function point (FP), and number of failures (Failure) are needed (Table 5).

Diketahui: FP=163.4

$\begin{gathered}\text { Failure }=5 \\ \text { ROCOF }=\frac{\text { Failure }}{\text { Function Point }} \\ \text { ROCOF }=\frac{5}{163.4}=0.0305\end{gathered}$                 (4)

Reliability can be derived using the following formula:

$\begin{gathered}\text { Reliability }=1-\text { ROCOF } \\ \text { Reliability }=1-0.0305 \\ \text { Reliability }=0.969\end{gathered}$                 (5)

Thus, the reliability of SIAKAD is 0.969. A value of 0.969 indicates that in 1,000 operations, it is estimated that the software of the SIAKAT application is able to work correctly for 969 times. In other words, in 1000 operations the application has been estimated to fail 31 times.

3.3.4 Usability

The software usability indicator is obtained from the speed of operation metric. The more the speed of operation approaches a value of 0, indicating that the usability is increasing. Conversely, the more the speed of operation approaches a value of 1, the more the usability decreases (Table 6).

Table 6. ISO 9126- Usability

Unknown: Function Point(FP)=163.4

$\begin{gathered}\text { User Input }=8 \\ \text { User Request }=10 \\ \text { Speed of Operation }=\frac{\text { User Input }+ \text { User Request }}{\text { Function Point }} \\ \text { Speed of Operation }=\frac{8+10}{163.4}=0.4895 \\ \text { Usability }=1-\text { Speed of Operation } \\ =1-0.4895=0.5105\end{gathered}$         (6)

3.3.5 Efficiency

Efficiency is related to performance, resources required, and savings gained from product use. To obtain efficiency indicators, several variables are needed to calculate them. These variables are total benefits, total costs, and effort required to build the software (Table 7).

Table 7. ISO 9126- Efficiency

Metric Approximation

$\begin{gathered}\text { Known: } F P=163.4 \\ E=-13.39+0.0545 F P \\ E=-13.39+(0.0545 \times 163.4) \\ E=4.4847 \text { person }- \text { month }\end{gathered}$            (7)

3.3.6 Maintenance

In software, the more changes that occur in the software indicate that maintenance will be more difficult to do. To find the value of maintainability, the metric used is the Software Maturity Index (SMI) metric. The more SMI approaches the value of 1, the more stable the product will be. Conversely, the more SMI moves away from the value of 1, the more unstable the product will be. The variables needed to find the SMI value are the current number of modules (MT), the number of added modules (Fa), the number of modules that have changed (Fc), and the number of modules that have been deleted since the initial design (Fd) (Table 8).

Table 8. ISO 9126- Maintainability

Unknown: MT=3

$\begin{gathered}F a=0 \\ F c=0 \\ F d=0 \\ S M I=\frac{M T-(F a+F c+F d)}{M T}=\frac{3-(0+0+0)}{3}=\frac{3}{3}=1\end{gathered}$           (8)

A maintenance indicator of 1 indicates that out of every 3 program modules, there is 1 module that is expected to be stable so that it does not require significant changes at maintenance time and 2 other modules that are expected to undergo changes at the maintenance stage.

3.3.7 Portability

After obtaining the six ISO 9126 quality indicators, namely functionality, reliability, usability, efficiency, maintainability, and portability, the last step is to generalize. The generalization in question is an overall assessment of the achievement of the quality of the SIAKAD system software the number of added modules (Fa), the number of modules that have changed (Fc), and the number of modules that have been deleted since the initial design (Fd) shown in Table 9.

The Table 10 lists different characteristics related to the quality of a software application, in this case, an SIAKAD application. Each characteristic has a value assigned to it. Here's a detailed explanation of each term: Functionality (Value: 0.74): This measures how well the software performs its intended functions. A value of 0.74 indicates a certain level of functionality provided by the software. Reliability (Value: 0.96): This measures the software’s ability to consistently perform its functions without failure. A value of 0.96 suggests high reliability. Usability (Value: 0.51): This measures how easy and user-friendly the software is. A value of 0.51 implies that usability could be improved. Efficiency (Value: 0.4): This measures how well the software utilizes resources (like memory and processing power) while performing its tasks. A value of 0.4 indicates that efficiency might need enhancement. Maintainability (Value: 1): This measures how easy it is to maintain and update the software. A value of 1 is the highest among the listed characteristics, indicating that the software is quite maintainable. Portability (Value: 2): This measures how easily the software can be transferred from one environment to another. A value of 2 suggests that portability is a strong point of the software.

Table 9. ISO 9126- Portability

Table 10. Portability

Total Quality (5.61): This is the sum of all the values assigned to the characteristics listed above.

$\begin{gathered}\text { Unknown: Maximum Quality }=6 \\ \text { Quality Achievement }=5.61 \\ \text { Percentage of Quality Achievement }=  \frac{\text { Quality Achievement }}{\text { Maximum Quality }} \times 100 \%  \quad=\frac{5.61}{6} \times 100 \%=93.5\end{gathered}$         (9)