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All Journal TEKNIK INFORMATIKA Reaktor Mechatronics, Electrical Power, and Vehicular Technology TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Journal of ICT Research and Applications Jurnal Agro Kultivasi JOIV : International Journal on Informatics Visualization Jurnal Sistem dan Manajemen Industri RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JRSI (Jurnal Rekayasa Sistem dan Industri) Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Mitra Manajemen Indonesian Journal of Information System Jurnal Kimia Terapan Indonesia Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURTEKSI Jurnal Sistem Cerdas Linguistik Indonesia Teknologi Indonesia International Journal of Advances in Data and Information Systems Journal of Data Science and Its Applications Jurnal Instrumentasi Jurnal Teknik Informatika (JUTIF) INVEST : Jurnal Inovasi Bisnis dan Akuntansi Charity : Jurnal Pengabdian Masyarakat Mechanical Engineering for Society and Industry Universitas Muhammadiyah Yogyakarta Undergraduate Conference Proceeding SENTRI: Jurnal Riset Ilmiah Jurnal Ilmiah Teknik Elektro eProceedings of Engineering Eduvest - Journal of Universal Studies SEMNASTERA (Seminar Nasional Teknologi dan Riset Terapan) SmartComp Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Polimesin Scientific Journal of Informatics Rekayasa Mekanika: Jurnal Ilmiah Teknik Mesin AQILA : Acceleration, Quantum, Information Technology and Algorithm Journal Journal of Production, Enterprise, and Industrial Applications IJoICT (International Journal on Information and Communication Technology) ITEJ (Information Technology Engineering Journals)
Fakhrurroja, Hanif
Telkom University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Neuroscience Public Health Social Sciences Transportation

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A Quantitative Comparative Analysis of NASA-TLX Workload between Staff and Non-Staff Employees in a Pharmaceutical Manufacturing Organization: Implications for Knowledge Management Rian Bimo Ankhal; Muharman Lubis; Hanif Fakhrurroja; Muhammad Fakhrul Safitra
Scientific Journal of Informatics Vol. 13 No. 3: August 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v13i3.54141

Abstract

Purpose: In pharmaceutical production, personnel may be exposed to different workload situations, since their job functions are affected by strict operational and regulatory standards. Non-personnel workers and personnel workers have different duties which can affect their perception of workload and their participation in knowledge sharing activities. However, empirical evaluations of the workload characteristics of these employee cohorts by means of the NASA Task Load Index (NASA-TLX) are still scarce. This study explores the perceived workload attributes of staff and non-staff workers on six modified NASA-TLX scales. The implications of the identified trends for knowledge management strategies are discussed. Methods: The method used for this research was quantitative, comparative and cross-sectional. The study’s data were collected using a structured questionnaire. The sample selected for the study was 30 staff and non-staff members of a pharmaceutical manufacturing company using purposive sampling. The tool assessed six modified NASA-TLX workload factors; Mental Demand, Physical Demand, Temporal Demand, Performance, Effort and Frustration Level using a five-point Likert scale. Dimension total Pearson correlation analysis and Cronbach’s alpha reliability test were performed to assess the instrument with the same data set. Descriptive analyses of the workload characteristics of staff and non-staff personnel were conducted using group mean scores and mean differences. No assertions regarding statistical significance were provided. Result: Non-staff personnel had higher mean scores than staff personnel in Mental Demand, Physical Demand, Temporal Demand, Effort and Frustration Level. For workload, the largest mean differences were found in Temporal Demand and Effort. Non-staff personnel also reported a higher Performance score. The Performance items, however, are positively worded and imply that higher scores reflect a more positive view of work accomplishment and quality, not a greater workload. The patterns shown here indicate that role-specific knowledge management practices can support continued improvement, learning and knowledge sharing activities. Novelty: This study presents the analysis of staff and non-staff employees according to their role and a complete workload analysis in the context of a pharmaceutical manufacturing environment with the modified NASA-TLX framework. The results provide a pragmatic basis for the development of knowledge management strategies relevant to the operational tasks and workload characteristics of each category of employees.
A Systematic Literature Review on Multi-Criteria Decision Analysis and Machine Learning for Decision-Making in Digital Payment Investment Rahmat Rambe; Lukman Abdurrahman; Hanif Fakhrurroja
Indonesian Journal of Information Systems Vol. 9 No. 1 (2026): August 2026
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v9i1.13797

Abstract

The growth of financial technology has strengthened the role of digital payments indriving the digital economy and influencing investment decision-making. This developmentcreates both opportunities and challenges for investors in evaluating digital payment investments.Multi-Criteria Decision Analysis (MCDA) supports structured evaluation across multiple criteria,while Machine Learning (ML) enhances predictive capabilities using historical and market data.However, studies integrating MCDA and ML remain limited and unsystematic. This studyconducts a systematic literature review (SLR) based on the PRISMA framework, analyzingpublications from 2019 to 2024 related to the application of MCDA and ML in digital paymentinvestment and decision-making. The results indicate an increasing research trend, with commonlyapplied MCDA methods such as AHP, TOPSIS, and PROMETHEE, and ML algorithms includingSupport Vector Machine and Gradient Boosting. This review identifies research gaps and providesdirections for future studies and practical investment strategies in the digital payment sector. Keywords: Digital Payment; Investment; MCDA; Machine Learning; Systematic Literature Review.
Co-Authors Abdullah Ridwan Adi Sutrisno Adi Waskito Agus Sutanto Agustiana, Nathifa Ahmad Musnansyah Andry Alamsyah Andy Victor Pakpahan Anindya Prameswari Putri Djakaria Anto Tri Sugiarto Arif Abdul Aziz Aris Munandar Asriana Asriana, Asriana Azwar Farrel Wirasena Betty Natalie Fitriatin Binashir Rofi’ah Bismar Fadli Carmadi Machbub Cindy Septiani Hudaya Deden Witarsyah Deni Kurnia Denis Gresan Yubelas Deris Stiawan Dermawan, M Farhan Hussaini Derry Destian Didit Adytia Dimas Jaya Kusuma Dina Angela Dini Dwi Andayani Dita Pramesti Dita, Limbong Agatha Dita Djakaria, Anindya Prameswari Putri Edi Triono Nuryatno Edy Tanu Elsa Melati Nurrachmat Emma Trinurani Sofyan Erlangga, Gilang Faishal Mufied Al Anshary Faishal Mufied Al-Anshary Fauziah, Nicky Oktav Firdaus, M Ridwan Fitri Widiantini Ghifari, Raden Faqih Hilmiy Hakim, Aqil Rahman Hans Melkisedek Simanjuntak Hariyadi , Hendri Hestiawan Joniko Joniko Karina M., Rahma Kemahyanto Exaudi Lidanta, Fairuz Zahirah Lovely Son, Lovely Lukman Abdurrahman Made Marshall Vira Deva Mahardiono, Novan Agung Marno Marno Mimin Muhaemin Mohammad Tyas Pawitra Muhammad Fakhrul Safitra Muhammad Fauzan Nur Adillah Muharman Lubis Nabiel Muhammad Al Ghazali Nathifa Agustiana Nopendri Nopendri Novan Agung Mahardiono Novan Agung Mahardiono Novan Agung Mahardiono Nuryatno, Edi Triono Oktariani Nurul Pratiwi Orvalamarva, Orvalamarva Permatasari, Yessy Prahastiwi, Narita Ayu Prima Audina Wibowo Puspitasari, Devi Ambarwati Putra Perdana Prasetyo, Aditya Putri Utami Rukmana Rahayu, Indah Sari Rahma Karina M. Rahman, Jodi Rizki Rahmat Budiarto Rahmat Mulyana Rahmat Rambe Rais, Muhammad Haidar Ramdhani, Fiqri Rian Bimo Ankhal Rian Bimo Ankhal Rimba Pratama Putra Riverinda Rijadi, Safara Cathasa Sadewa, Rizki Salsabila, Syifa Aria Sandy, Muhammad Dwi Hary Sarmayanta Sembiring Sendhitasari, Aulia Ferina Seno Adi Putra Setyorini Setyorini Sinung Suakanto Sudaryati Cahyaningsih Sugiono, - Sutoyo, Edi Tanu, Edy Tatang Mulyana Tien Fabrianti Kusumasari Triwangsa, Mochamad Cory Sakti Tualar Simarmata Utama, Muhammad Hasbi Juri V. Luvita Veithzal Rivai Zainal Veny Luvita Veny Luvita Wibowo, Jony Winaryo Wibowo, Nanang Roni Widianto Soekarnen Wijaya, I Made Darma Putra Wira Guna, Tezar Yolanda, Mitra Marlina Zuhdi, Hafidh