Article Per Year (5 Year)
p-Index From 2021 - 2026
5.138
P-Index
This Author published in this journals
All Journal Jurnal Manajemen Teknologi Journal of Business and Management The Indonesian Journal of Business Administration KURVA S JURNAL MAHASISWA Gadjah Mada International Journal of Business EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi dan Bisnis The Asian Journal of Technology Management (AJTM) AGRIMOR Jurnal Mirai Management Jurnal Manajemen Indonesia Syntax Literate: Jurnal Ilmiah Indonesia Journal of Economic, Bussines and Accounting (COSTING) SEIKO : Journal of Management & Business International Journal of Supply Chain Management The International Journal of Business Review (The Jobs Review) Dinasti International Journal of Education Management and Social Science Al-Kharaj: Journal of Islamic Economic and Business Community Engagement and Emergence Journal (CEEJ) Journal of Economics and Business UBS Journal of Research in Social Science and Humanities International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS) The South East Asian Journal of Management International Journal of Management, Entrepreneurship, Social Science and Humanities (IJMESH) Eduvest - Journal of Universal Studies Amkop Management Accounting Review (AMAR) Jurnal Bisnis dan Pemasaran Digital Studi Akuntansi dan Bisnis Indonesia
Dermawan Wibisono
School Of Business And Management Institut Teknologi Bandung
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Neuroscience Social Sciences Transportation Other

Published : 61 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Syntax Literate: Jurnal Ilmiah Indonesia

 1 
Predicting Student Performance Using Machine Learning for Student Management in University (Study Case ABC University) Berlit Deddy Setiawan; Dermawan Wibisono
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (668.262 KB) | DOI: 10.36418/syntax-literate.v7i10.12791

Abstract

Higher education institutions play a vital role in providing quality education and producing skilled human resources. In Indonesia, there is a growing demand for higher education due to population growth and increasing awareness of its importance. ABC University, currently ranked 46-50 in Indonesia Uni Rank 2023, faces challenges in the rankings. To thrive in this competitive landscape, universities must be selective in admitting qualified students and ensure effective academic development processes. Machine learning capabilities can be leveraged to predict students' potential academic performance, facilitating timely interventions and support to enhance learning outcomes. However, there is currently no research available that focuses on creating a prediction model that integrates student profiles with academic performance. Highlights factors that contribute to student failure, including low academic ability, financial constraints, and geographical location. ABC University, with its limited database, requires a method to improve performance and predict students' academic performance. Machine learning techniques such as Educational Data Mining (EDM) and Random Forest can assist the university in understanding students' needs and developing effective educational policies. By leveraging these techniques, ABC University can remain competitive and enhance its students' academic performance. This research aims to establish a connection between the Random Forest algorithm theory and the prediction of students' potential academic performance. The objective is to develop an accurate and efficient method for managing student affairs at ABC University. The research employs both quantitative and qualitative approaches, with a focus on analyzing numerical data and generating classification predictions. The research process begins with a thorough analysis of the business situation to understand the university's environment and determine the research topic. The researcher then establishes research boundaries, prioritizes key issues, and constructs a research framework. A comprehensive literature review and Focus Group Discussions are conducted to identify research gaps and determine the factors that influence student performance. Data collection and processing take place, with the data processing phase encompassing tasks such as data cleaning, outlier removal, handling missing values, and variable transformation. The data modeling stage employs the Random Forest algorithm and the k-Folds cross-validation technique, dividing the data into training and testing sets. The evaluation stage involves assessing the model's performance using the testing data and performance metrics such as accuracy, precision, and recall. This study aims to investigate the completion rates of students at ABC University categorized as Fast (3 years), On Time (3.5-4 years), and Late (4.5-6 years) studies. The dataset includes both completed and uncompleted students, and a specific treatment is provided for those who have not completed their studies. Factors that influence student performance are identified through focus group discussions and correlation testing, enabling the identification of significant independent variables. The study analyzes the profiles of students who graduated in 2016-2017, combined with academic performance data. A regression test is conducted to determine the influence of 18 attributes on performance. Random Forest Machine Learning is compared to other techniques to identify the most accurate predictive model for students' academic performance. ABC University, the Random Forest model achieved a prediction rate of 89.60%.
Finding Conceptual Framework and Critial KPI’s For Performance Management System For Field Instrumentation Team of Private Ownership Construction Consultant: A Case Study Ahmad Kemal Arsyad; Dermawan Wibisono
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v7i10.13122

Abstract

Monitoring works is considered have significant impact on the office's internal processes, the propper PMS is needed. This study aims to manage the organizational performance of PT XYZ company using Knowledge Based Performance Management System (KBPMS) framework approach developed by Wibisono (2006). The proposed model was developed by combining a literature review and a case study approach applied to construction companies especially from previous studies in Indonesia. The data is analyzed to assess the suitability of the company's strategy with the current PMS used in the company, and to determine suitable performance indicators to be used in the proposed model. The analysis was carried out using a qualitative approach and multi-criteria decision-making with an analytical hierarchy process (AHP) approach from experts at the managerial level of the company. The research shows that there are at least 16 aspects and 20 performance measurement variables proposed for the monitoring division to support PT XYZ's performance. The development of this model is still in a stage that needs to be developed further. Evaluation and improvement of the PMS implementation will be planned in the future.
Performance Management System Using Balanced Scorecard Framework and Analytical Hierarchy Process A Case Study In Indonesia Manufacturing Company Hadiyanto, Haris; Wibisono, Dermawan
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v10i1.11730

Abstract

Improving an increasingly competitive environment such as how easy it is for customers to get cheap and quality products from the import process pressures manufacturing companies to always increase their competitive advantage. It is important for a company to be able to anticipate threats and continuously update its strategy in order to maintain the performance of the company. This paper aims to identify, analyze, and define key performance indicators (KPI) for one of the manufacturing companies in Indonesia with the first step being to design the right performance management system (PMS) for the company. The integration of the Balanced Scorecard (BSC) and the Analytical Hierarchy Process (AHP) introduces a structured, data-driven approach to prioritizing key performance indicators (KPIs), enabling manufacturing companies like PT ABCD to align strategic objectives with operational performance more effectively, thereby enhancing decision-making accuracy and competitive advantage in a highly dynamic market. The balanced scorecard approach was used in this research to determine the right KPIs and were determined through focus group discussions with top management. The KPIs that have been set are then analyzed using the Analytical Hierarchy Process (AHP) to determine how the relationships between these KPIs are. The finding of this paper is to provide KPIs that companies can use as a first step in measuring the performance of manufacturing companies in Indonesia.
Co-Authors , Akhiyar , Akhyar . Meiliza, . Adrian Pasca Agung Sukma Hardana agus Purwadi Ahmad Kemal Arsyad Alpha Nur Setyawan Pudjono Alpha Pudjono Amanah Pasaribu Anugia, Zakie Arief Andhella Aries F Firman Asbah, Zuhwan Assydik, Muhammad Handeriyan Bagus Budianto Bangun, Madju Yuni Ros Berlit Deddy Setiawan Binti Hassan, Radiah Chairuna, Dina Cornell, Axel William Darusulistyo, Sidik Durio Etgar Durio Etgar Firmanto, Andri Budhiman Habsoro, Moh Akhim Bayu Hadiyanto, Haris Halim, Didi Kurniadi Harimukti Wandebori Hasibuan, Fabian Zaki Geraldy Herry Hudrasyah Hibban, Laksamana Naufal Hoa, Hong Mee Husodo, Widodo Kukuh Sujatmiko I Nyoman Sardjana Ima Fatima Ima Fatima Ima Fatima, Ima Izhar Rahman Dwiputra Jonathan, Ivan Kaff, Ahmad Auva Nadiyyi Kukuh M Rahardjo Lase, Putri Vaerina Maulanda, Fadrian Dwiki Meita Annisa Nurhutami Mohammad Wisaksono Mohammad Zaki Mubarok, Mohammad Zaki Mohammed K. Khan Mohammed K. Khan Muhammad Handeriyan Assydik Muhammad Shidqi, Roza Mursyid Hasan Basri Mustika Sufiati Purwanegara Mustika Sufiati Purwanegara Nabilla, Faradhina Astri Nanda Ravenska Oktorius Kosasih Priyanto, Rohmat Putri, Aghnia Nadhira Aliya Rahmat Hidayat Rahmawati, Isadora Raihan, Maudy Farras Raka Achmad Inggis, Raka Achmad Ramadhan, Dimas Rizki M. Ratih Siti Rachmawati Reni Sri Rahayu Reno Renaldi Tibyan Rhanni Apriani Wirdhawan Rhanni Apriani Wirdhawan Riansa, Muhamad Danindra Rizki Utama Romi Setiawan Roza Muhammad Shidqi Santi Novani Setiawan, Romi Setiawan, Steven Nathanael Shihran, Reza Setiadi Siallagan, Manahan Parlindungan Saragih Sonia, Veren Sulaeman, Dwi Rian Taufik Faturohman Untea, Pungkas Utama, Rizki Wirdhawan, Rhanni Apriani Zulfikar, Prananda Septian