The Statistics and Quality Management Laboratory is one of the academic laboratories within the field of Industrial Engineering that focuses on the development of competencies, research, and the application of statistics, quality control, quality management, and data-driven decision-making. This laboratory serves as an academic platform for lecturers and students in supporting education, research, community service, and collaboration with industry and other relevant stakeholders.
1. Background
The increasingly competitive development of the industrial sector requires every organization to produce high-quality, efficient, consistent products and services that meet user needs. In this context, statistical approaches and quality management play an important role in assisting organizations in performance measurement, process control, variation analysis, quality improvement, and data-based decision-making.
The Statistics and Quality Management Laboratory was established as a supporting facility for the implementation of the Three Pillars of Higher Education, particularly in strengthening Industrial Engineering knowledge in the areas of applied statistics, quality control, quality engineering, quality management, Six Sigma, Total Quality Management, experimental design, and industrial data analysis. This laboratory also supports the development of students’ abilities to understand and apply quantitative methods in solving real problems in manufacturing, services, education, healthcare, logistics, and government sectors.
Through this laboratory, students, lecturers, and researchers are expected to develop analytical skills, systematic thinking, and the ability to design continuous quality improvement solutions. The laboratory also functions as a center for academic studies and consultation in the fields of statistics and quality management for both internal university stakeholders and external partners.
2. Laboratory Members
The organizational structure of the Statistics and Quality Management Laboratory consists of a Head of Laboratory and laboratory members who possess academic competence and expertise in statistics, quality management, optimization, operations management, industrial systems, and data-based decision-making.
Head of Laboratory:
Prof. Dr. Ir. Syamsul Bahri, M.Si., IPU., ASEAN.Eng
Laboratory Members:
- Ir. Kifayah Amar, S.T., M.Sc., Ph.D., IPU., ASEAN.Eng
- Ir. Armin Darmawan, S.T., M.T., Ph.D., IPU., ASEAN.Eng
- Dr. Eng. Ir. Farid Mardin, S.T., M.T., IPM., ASEAN.Eng
3. Supporting Facilities
The Statistics and Quality Management Laboratory is supported by various facilities that assist learning activities, practicums, research, simulations, training, data processing, and quality analysis. These facilities are designed to help lecturers and students understand statistical concepts and the practical application of quality management.
The supporting facilities include:
- SPSS Software
SPSS software is used to support statistical analysis, research data processing, validity and reliability testing, regression analysis, correlation analysis, multivariate analysis, and various quantitative data processing needs for undergraduate and master’s students. - Laboratory Computers
Laboratory computers are used as the main facilities for data processing, statistical analysis, simulation, practicum report preparation, research model development, and data visualization. These facilities support students and lecturers in completing academic and research activities based on data analysis. - Laboratory and Academic Discussion Room
The laboratory room is used for practicum activities, academic assistance, research discussions, final project consultations, proposal preparation, laboratory meetings, and other academic activities that support learning and research processes. - Supporting Software for Data and Quality Analysis
In addition to SPSS, the laboratory may also support the use of other relevant software such as Microsoft Excel, Minitab, R, Python, or other data processing applications to support statistical analysis, quality control, experimental design, and data visualization.
4. Research Roadmap
The research roadmap of the Statistics and Quality Management Laboratory is directed toward supporting the development of Industrial Engineering knowledge oriented toward quality improvement, process efficiency, variation control, and data-based decision-making. This roadmap is arranged progressively so that laboratory research activities have a clear, sustainable direction and remain aligned with industrial needs and technological developments.
In general, the laboratory research roadmap can be divided into the following stages:
5. Standard Operating Procedures
The Standard Operating Procedures of the Statistics and Quality Management Laboratory are established to ensure that all laboratory activities are conducted in an orderly, safe, effective, and academically appropriate manner. These procedures serve as guidelines for lecturers, students, laboratory assistants, and all laboratory users in utilizing facilities and carrying out learning, research, and community service activities.
In general, the laboratory SOP includes the following provisions:
