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All Journal Journal of Innovation Research and Knowledge Knowbase : International Journal of Knowledge in Database
Rakhmi Khalida
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Health Professions Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : Knowbase : International Journal of Knowledge in Database

 1 
Business Intelligence Dashboard Human Resource Capacity to Increase the Capacity City of Bekasi Prio Pamungkas, R Wisnu; Rakhmi Khalida
Knowbase : International Journal of Knowledge in Database Vol. 4 No. 2 (2024): December 2024
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v4i2.8764

Abstract

Bekasi City with qualified and evenly distributed human resources will be better able to meet dynamic and complex development needs. Effective data visualization can simplify complex information related to HR capacity, such as education levels, skills distribution, and the number of workers in various sectors, making it easier for policy makers to design strategies including identifying the distribution of filling several positions based on gender and identifying areas of need for educational facilities, children's health, and other infrastructure that supports the growth and development of the younger generation, and developing more effective policies to improve the overall capacity of the city. This research aims to develop a human resource capacity data visualization model as a tool in improving city capacity. This research uses Google Looker Studio as a data visualization platform, data integration is done by Extract, Transform, Load (ETL) method, the data starts from Excel then cleaned, adjusted the format and loaded into Google Sheets. The data used includes key variables that describe the characteristics of human resources in the Bekasi city area, such as education, age group, gender, and demographic distribution. The results show that based on the dashboard visualization, the Bekasi City government can increase 10% representation of the number of women in supervisory and administrator positions in 2 years and the number of only 5% at the S2 or S3 education level requires an increase in education to support the optimization of HR for strategic positions
Business Intelligence Dashboard Human Resource Capacity to Increase the Capacity City of Bekasi Prio Pamungkas, R Wisnu; Rakhmi Khalida
Knowbase : International Journal of Knowledge in Database Vol. 4 No. 2 (2024): December 2024
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v4i2.8764

Abstract

Bekasi City with qualified and evenly distributed human resources will be better able to meet dynamic and complex development needs. Effective data visualization can simplify complex information related to HR capacity, such as education levels, skills distribution, and the number of workers in various sectors, making it easier for policy makers to design strategies including identifying the distribution of filling several positions based on gender and identifying areas of need for educational facilities, children's health, and other infrastructure that supports the growth and development of the younger generation, and developing more effective policies to improve the overall capacity of the city. This research aims to develop a human resource capacity data visualization model as a tool in improving city capacity. This research uses Google Looker Studio as a data visualization platform, data integration is done by Extract, Transform, Load (ETL) method, the data starts from Excel then cleaned, adjusted the format and loaded into Google Sheets. The data used includes key variables that describe the characteristics of human resources in the Bekasi city area, such as education, age group, gender, and demographic distribution. The results show that based on the dashboard visualization, the Bekasi City government can increase 10% representation of the number of women in supervisory and administrator positions in 2 years and the number of only 5% at the S2 or S3 education level requires an increase in education to support the optimization of HR for strategic positions
Implementation of Genetic Algorithm for Automatic Course Scheduling Optimization Rakhmi Khalida; Situmorang; Dwi; Setiawati, Siti
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i2.10260

Abstract

Course scheduling in vocational high schools (SMK) constitutes a complex combinatorial optimization problem involving multiple hard and soft constraints related to teacher availability, class allocation, and time-slot distribution. Although Genetic Algorithms (GA) have been extensively applied in educational timetabling, existing studies largely emphasize standalone optimization or desktop-based solutions, with limited analytical evaluation of refinement strategies and system-level applicability. This study addresses this gap by empirically evaluating a hybrid GA–Local Search (LS) approach embedded within a web-based scheduling framework. GA is utilized as a global search mechanism to generate feasible schedules that satisfy all hard constraints, while LS is applied as a post-optimization phase to improve solution quality by reducing soft constraint violations. Experiments were conducted using real scheduling data from SMK Yadika 13 Bekasi, involving 3 subjects, 3 teachers, 4 classes, and 12 time slots within a single-day scenario. Although limited in scale, this configuration was deliberately selected to enable transparent analysis of the optimization dynamics and refinement impact of the proposed hybrid approach. The results show that the pure GA produces five soft constraint violations, mainly due to suboptimal placement of cognitively demanding subjects and uneven subject distribution. After applying LS, violations were reduced to two cases, with the fitness value improving from 0.873 to 0.946 and only a marginal increase in computation time (5–7 seconds). These findings demonstrate that local refinement significantly enhances schedule quality beyond conflict-free feasibility. This study contributes scientifically by providing an empirical assessment of GA–LS hybridization for soft-constraint optimization and by establishing a scalable web-based framework that supports future extensions to full-week scheduling and adaptive academic systems
Co-Authors Andy Achmad Hendharsetiawan Dwi Kustanto , Prio Mayadi, Mayadi Prio Pamungkas, R Wisnu SITI SETIAWATI Situmorang