Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Metode : Jurnal Teknik Industri Tibuana : Journal of Applied Industrial Engineering
Alfani, Musaddad
Unknown Affiliation
Control & Systems Engineering Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Analisis Risiko Pada Usaha Mebel Menggunakan House of Risk Rubik, Filimon Erno; Alfani, Musaddad
Metode : Jurnal Teknik Industri Vol. 11 No. 2 (2025): Jurnal Metode
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/mt.v11i2.4945

Abstract

The furniture industry is one of the manufacturing sectors that makes a significant contribution to the economy. However, the complexity of the production process, ranging from raw material procurement to product distribution, makes this industry vulnerable to various internal and external risks. If not properly managed, these risks may hinder production targets, reduce product quality, and weaken the company’s competitiveness. This study aims to identify and design risk mitigation strategies in a furniture business in Yogyakarta using the House of Risk (HoR) method. Data were collected through observation and questionnaires to assess risk events and risk agents. The HoR phase 1 analysis identified nine risk events and twenty-two risk agents, with five priority risk agents, namely raw material shortages due to poor planning, suboptimal maintenance, limited raw material stock from suppliers, delays in machine spare parts procurement, and lack of worker skills. Subsequently, HoR phase 2 produced five main mitigation strategies, including improving raw material requirement calculations, establishing clear maintenance schedules, expanding supplier networks, enhancing interdepartmental coordination, and providing worker training and certification. The findings indicate that the application of the HoR method can assist furniture companies in prioritizing risk sources and formulating more systematic and targeted mitigation strategies.
Mental Workload Analysis of Student Members of the Mosque Management Committee at Campus X Using NASA-TLX Alfani, Musaddad; Wicaksono, Mahruri Arif; Syafnijal, Frieska Ariesta; Qalbi, Putri Aysha
Tibuana Vol 9 No 1 (2026): Tibuana
Publisher : UNIPA PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/tibuana.9.1.10911

Abstract

Students who serve as administrators of campus mosques often face dual responsibilities: fulfilling academic obligations while simultaneously managing various religious activities on campus. Balancing these roles can lead to a considerable mental workload. This study aims to assess the level of mental burden experienced by students actively involved as campus mosque administrators. The research was conducted at a university mosque located in Yogyakarta. Mental workload was measured using the NASA-TLX instrument, which evaluates six key dimensions of cognitive load. Findings revealed an average mental workload score of 71.14, categorized as high. A total of 80% of participants reported experiencing high to very high levels of mental stress. The most prominent contributing dimensions were mental demand, effort, and perceived performance. These results highlight the need for effective workload management strategies, including equitable task distribution, engagement of external volunteers, stress and time management training, and promoting awareness of the importance of balancing academic and organizational commitments.
Customer Segmentation in a Campus-Area Convenience Store Using K-Means Clustering Alfani, Musaddad; Qalbi, Putri Aysha
Tibuana Vol 9 No 02 (2026): Tibuana
Publisher : UNIPA PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/tibuana.9.02.11641

Abstract

Customer segmentation is an important strategy for understanding differences in customer characteristics and supporting more targeted marketing decisions. In campus areas, convenience store customers generally consist of students with diverse demographic, economic, and accessibility characteristics, resulting in different purchasing behaviors. This study aims to identify customer segments of a convenience store located in the Campus X area of Yogyakarta using the K-Means Clustering algorithm. The study employed a quantitative approach with data mining techniques using customer data from students. The variables analyzed included age, income, shopping intensity, and residential distance from the store. The optimal number of clusters was determined using the Elbow Method before applying the K-Means algorithm. The results identified three customer segments with distinct characteristics. The largest segment consisted of customers living relatively close to the store and exhibiting high shopping intensity, while another segment was characterized by lower purchasing activity and greater residential distance. The smallest segment showed the highest income level and more diverse product preferences. Furthermore, differences in customer characteristics were reflected in product purchasing patterns across the identified segments. These findings indicate that accessibility and economic factors play important roles in shaping customer purchasing behavior in campus-area convenience stores. The results can serve as a reference for developing more targeted promotional and product management strategies.
Co-Authors Frieska Ariesta Syafnijal Qalbi, Putri Aysha Rubik, Filimon Erno Wicaksono, Mahruri Arif