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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Teknoif Teknik Informatika Institut Teknologi Padang
Syaifur Rohman, Muhammad
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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PERANCANGAN APLIKASI PERHITUNGAN BEBAN KERJA DOSEN TERINTEGRASI DENGAN PENDEKATAN WATERFALL Ratmana, Danny Oka; Syaifur Rohman, Muhammad; Firdausillah, Fahri; Wilujeng Saraswati, Galuh
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 12 No 2 (2024): TEKNOIF OKTOBER 2024
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2024.V12.2.139-148

Abstract

Digital transformation in higher education emphasizes the importance of information technology in enhancing management efficiency, including the management of lecturers' workloads. This study aims to design a Full-Time Equivalent Teaching Load (EWMP) calculation system integrated with the Integrated Resource Information System (SISTER), implemented by the Ministry of Education, Culture, Research, and Technology (KEMDIKBUDRISTEK). The application was developed using the Waterfall methodology and leverages the SISTER Application Programming Interface (API) to automate the collection of lecturer activity data at Universitas Dian Nuswantoro Semarang (UDINUS). By integrating the workload calculation application into the internal management system, this solution streamlines data recording, reduces manual errors, and enhances accuracy in the evaluation of lecturer performance. The test results indicate that the application successfully synchronizes data with SISTER in an accurate and real-time manner, supporting more effective workload management for lecturers. Additionally, the system provides reports and analyses of lecturer workloads, facilitating resource planning and allocation. This application is expected to contribute to a more transparent, accurate, and quality-driven human resource management process in higher education.
Optimizing earthquake damage prediction using particle swarm optimization-based feature selection Anisa Sri Winarsih, Nurul; Anggi Pramunendar, Ricardus; Fajar Shidik, Guruh; Widjajanto, Budi; Syaifur Rohman, Muhammad; Oka Ratmana, Danny
Bulletin of Electrical Engineering and Informatics Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i1.8421

Abstract

Earthquakes have destroyed the economy and killed many people in many countries. Emergency response actions immediately after an earthquake significantly reduce economic losses and save lives, so accurate earthquake damage predictions are needed. This research looks at how machine learning (ML) techniques are used to predict damage from earthquakes. The ML algorithms used are k-nearest neighbors (KNN), decision tree (DT), random forest (RF), and Naïve Bayes (NB). Feature selection is necessary, it needs to select the most relevant features from big data. One of the most commonly used algorithms to optimize ML is particle swarm optimization (PSO). PSO is also suitable for feature selection. This research compares various of PSO. Based on research, the RF algorithm with Phasor PSO has the highest fitness score. This process succeeded in reducing features from 38 features to 14 features. Based on the process after feature selection, it was found that the KNN, DT, and RF algorithms had improved. RF obtained the best accuracy, namely 72.989%. The processing time in DT, RF, and NB is faster than before. In conclusion, the ML algorithm can be combined with PSO feature selection to create a classification model that provides better performance than without feature selection.
PERANCANGAN APLIKASI PERHITUNGAN BEBAN KERJA DOSEN TERINTEGRASI DENGAN PENDEKATAN WATERFALL Ratmana, Danny Oka; Syaifur Rohman, Muhammad; Firdausillah, Fahri; Wilujeng Saraswati, Galuh
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 12 No 2 (2024): TEKNOIF OKTOBER 2024
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2024.V12.2.139-148

Abstract

Digital transformation in higher education emphasizes the importance of information technology in enhancing management efficiency, including the management of lecturers' workloads. This study aims to design a Full-Time Equivalent Teaching Load (EWMP) calculation system integrated with the Integrated Resource Information System (SISTER), implemented by the Ministry of Education, Culture, Research, and Technology (KEMDIKBUDRISTEK). The application was developed using the Waterfall methodology and leverages the SISTER Application Programming Interface (API) to automate the collection of lecturer activity data at Universitas Dian Nuswantoro Semarang (UDINUS). By integrating the workload calculation application into the internal management system, this solution streamlines data recording, reduces manual errors, and enhances accuracy in the evaluation of lecturer performance. The test results indicate that the application successfully synchronizes data with SISTER in an accurate and real-time manner, supporting more effective workload management for lecturers. Additionally, the system provides reports and analyses of lecturer workloads, facilitating resource planning and allocation. This application is expected to contribute to a more transparent, accurate, and quality-driven human resource management process in higher education.
Co-Authors Anggi Pramunendar, Ricardus Anisa Sri Winarsih, Nurul Budi Widjajanto Fahri Firdausillah Fajar Shidik, Guruh Oka Ratmana, Danny Ratmana, Danny Oka Wilujeng Saraswati, Galuh