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All Journal Jurnal TIMES Al Ishlah Jurnal Pendidikan International Journal of Artificial Intelligence Research Jurnal Studi Komunikasi SEIKO : Journal of Management & Business JURIKOM (Jurnal Riset Komputer) Jurnal Telematika JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Robotics and Control (JRC) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Journal of Applied Science, Engineering, Technology, and Education TIN: TERAPAN INFORMATIKA NUSANTARA JINAV: Journal of Information and Visualization ARRUS Journal of Social Sciences and Humanities INCODING: Journal of Informatics and Computer Science Engineering Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Ceddi Journal of Information System and Technology (JST) Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) BISMA: Bimbingan Swadaya Masyarakat
Robbi Rahim
Sekolah Tinggi Ilmu Manajemen Sukma
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Beyond Compensatory Benchmarking: A Robust Multi-Criteria Decision Support Framework for Regional Digital Economy Performance Leroy Samy Uguy; Esther Kembauw; Rahim, Robbi
ARRUS Journal of Social Sciences and Humanities Vol. 6 No. 1 (2026)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/soshum4682

Abstract

The multi-dimensional nature of the digital economy is such that there is a need to develop new methodologies to overcome the limitations of existing methods of measuring regional digital economy performance beyond composite indicators. The existing methods of benchmarking, which are based on compensatory aggregation, may mask structural problems in key governance areas. The research aims to develop an integrated multi-criteria decision support system to evaluate regional digital economy performance by applying the Analytical Hierarchy Process (AHP) with the geometric mean method for determining the weight of each criterion and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking. The quantitative approach to multi-criteria decision-making (MCDM) has been used to develop the decision support system. The results of the research indicate that the digital economy’s cybersecurity and digital trust are the most influential factors in determining digital economy performance. The results of the TOPSIS analysis indicate that there is a clear stratification of digital economy performance across regions, with the best-performing regions having well-developed digital infrastructure, human capital readiness, and cybersecurity. The results of the sensitivity analysis indicate that the ranking of digital economy performance is robust across all scenarios. The research contributes to theory by providing a new approach to measuring digital economy performance. The research contributes to the practical applications of digital economy research by providing an integrated approach to decision support. The research contributes to the methodological approach to multi-criteria decision-making by providing an integrated approach to decision support. The research contributes to the practical applications of digital economy research by providing an integrated approach to decision support. The research contributes to the practical applications of digital economy research by providing an integrated approach to decision support.
Multi-Criteria Decision Support for Smart Manufacturing Innovation Ecosystems Toward Industry 6.0 Saputra, Dhanar Intan Surya; Sutiksno, Dian Utami; Rahim, Robbi
JINAV: Journal of Information and Visualization Vol. 7 No. 1 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The transition towards Industry 6.0 demands the evolution of intelligent manufacturing systems beyond automation and digitalization towards integrated, human-centric, and resilient innovation ecosystems. The assessment of ecosystem readiness in the face of such complexity is essentially a multi-criteria decision problem with conflicting objectives and structural risk constraints. This study proposes a non-compensatory multi-criteria decision support system using the ELECTRE method to evaluate the readiness of Smart Manufacturing Innovation Ecosystems in Indonesia. Seven industry 6.0-oriented criteria are considered, including technology infrastructure readiness, digital connectivity, human capital capability, sustainability, governance, cybersecurity, and investment costs. The structured decision matrix is normalized, weighted, and processed using concordance-discordance analysis to obtain an outranking dominance relationship between the decision alternatives. The results show that ecosystem readiness varies, with regions with balanced digital, governance, and cybersecurity readiness exhibiting structural dominance, while regions with lower digital readiness but lower investment costs are vetoed due to non-compensatory decision rules. Sensitivity analysis shows that the ranking of decision alternatives remains robust with moderate weight/threshold changes. The ELECTRE-based non-compensatory decision approach is more appropriate than compensatory approaches in evaluating strategic industrial constraints pertinent to the industry 6.0 transition. The study’s contribution is the operationalization of industry 6.0 principles within a decision support system framework, providing policy-relevant prioritization results pertinent to the smart manufacturing development strategy in Indonesia.
Rental Housing Recommendation System Model Based on Multi-Criteria Decision Making and Machine Learning with Technology Acceptance Model Integration Rahim, Robbi; Nath, Vijay
Ceddi Journal of Information System and Technology (JST) Vol. 5 No. 1 (2026): April
Publisher : Yayasan Cendekiawan Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v5i1.164

Abstract

The selection of rental housing is a multi-criteria decision-making problem involving factors such as price, location, facilities, security, and environment, making it difficult for prospective tenants to determine the option that best suits their needs. This study aims to develop a rental housing recommendation system model by integrating Multi-Criteria Decision Making (MCDM), Machine Learning, and Technology Acceptance Model (TAM). The Analytical Hierarchy Process (AHP) is used to determine the criteria weights. In contrast, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used to rank rental housing alternatives. Furthermore, a Machine Learning approach using the Random Forest algorithm is applied to predict user preferences from historical data. System evaluation is carried out by comparing recommendation performance between AHP–TOPSIS and Simple Additive Weighting (SAW), testing the performance of the Machine Learning model, and analysing user acceptance using Structural Equation Modelling based on Partial Least Squares (SEM-PLS) within the Technology Acceptance Model framework. The results show that the AHP–TOPSIS model outperforms SAW in recommendation performance, achieving 89.4% compared to 84.7%. The Random Forest-based Machine Learning model also demonstrated good performance in predicting user preferences. The SEM results showed that perceived ease of use significantly influenced perceived usefulness and behavioural intention; perceived usefulness significantly influenced behavioural intention; and behavioural intention significantly influenced actual use, with p-values < 0.05. The R-square value of 0.67 indicated that the model had strong explanatory power for user acceptance. This study developed a rental housing recommendation system model that not only objectively provides the best alternative but also adjusts its recommendations to user preferences, achieving high acceptance. This model has the potential to be applied in the development of recommendation systems in the housing sector and artificial intelligence-based decision support systems.
Co-Authors Abdul Latif Abdul Latif Abdul Rahman Abroza, Ahmad Ada Adoley Allotey Adri Lundeto Agus Riyanto Agus Widodo, Hendro Ahmar, Ansari Saleh Ahmed Ramadhan Al-Obaidi Ahyuna Ahyuna Akbar Iskandar Amiruddin, Erwin Gatot Andrei Widjanarko Anggia Arif Arfianto, Afif Zuhri Baringbing, Elsinta Karolina Br Belinda Lai Berman Hutahaean Claudia Ann Rutland Darwis Robinson Manalu Desi Eka Nuryanti Dhanar Intan Surya Saputra Dwi Yuny Sylfania ELIHAMI, ELIHAMI Ellisa Agustina Elsayed T.Helmy Enos Lolang Ernie C Avila Ernie C Avila Ernie C. Avila Erwin L. Rimban Ester Rajagukguk Esther Kembauw Fahmi Sulaiman Fajriana, Fajriana Fransiskus Panca Juniawan GS , Achmad Daengs Guellica Agnesia Claudia Thanos Hafsah, Hafni Hardisal, Hardisal Harfawan Matturungan Harjanti, Trinugi Wira Hasan, Nonce Hashim, Raja Intan Zarina Binti Raja Zaki Hendro Agus Widodo Herry Rachmat Widjaja I Gede Iwan Sudipa Imam Saputra Indriyani Indriyani Intan Nurrachmi Ira Modifa Tarigan Irfan Ahmad Iswahyu Pranawukir Iswanto Suwarno Iswanto Suwarno Iwan Adhicandra Iwan Adhicandra Iwan Adicandra Jacomina Vonny Litamahuputty Jassim Alhamid Jimmy H Moedjahedy Kraugusteeliana Kraugusteeliana Kunal Kunal Kunal Kunal Kunal, Kunal Laksono Trisnantoro Lase, Delipiter Lela Khartishvili Leon Andretti Abdillah Leroy Samy Uguy Lestari, Veronika Nugraheni Sri LITAMAHUPUTTY, JACOMINA VONNY Lusy Tunik Muharlisiani M. Aldi Hidayat Lamdho Mamadiyarov, Zokir Mansyur Mansyur Manvender Kaur Sarjit Singh Manvender Kaur Sarjit Singh Maret Sitanggang Mary Puthern Matturungan, Harfawan Meithiana Indrasari Mohamad Sudi Mohammad Aljanabi Muhammad Ade Kurnia Harahap Muhammad Ahmad Baballe Muqarranah Sulaiman Kurdi Musyarrafah Sulaiman Kurdi Mutmainnah, Muthia Nabila Turahma Niah Butarbutar Nia Maharani Raharja Nia Maharani Raharja Nofirman, N Novarezi, Wendi Tri Nur Mistari Nurhalimah Nurhalimah Nurhayati Nurhayati Nurmawati Nurmawati Omar Tanane Omar Tanane Prisma Megantoro Raditya Argananta Churyanto Rahmat Hidayat Ramadhani Prayoga Raudatul Innayah Restu Diyah Pramesti restu Rispa Ngindana Rosmawita Ningrum Rushendra, Rushendra S Suwarni Sahyunu Sahyunu Sanco Simanullang Santri W Pasaribu Sapinah, Sapinah Satria Prayudi Siewe Pougoue E.B. Siregar, Yulia Rahma Slamet Riyadi Suhanda, Yogasetya Sujatmiko, Dedi Sulaiman, Jihan Susatyo Adhi Pramono, Susatyo Adhi Sutiksno, Dian Utami Syafrizaldi Syamsu Rijal T.Helmy, Elsayed Tasya Noorhaliza Toha Ardi Nugraha Toong Hai Sam Ursula Hadimeri Usanto S Usanto S Victor Jiménez-Díaz-Benito Vijay Nath, Vijay Virro I. Wajdi, Muh Barid Nizarudin Widjanarko, Andrei Widyatmike Gede Mulawarman Wim Winowatan Wulandari, Ike Yuni Yaya Finayani Yoga Ihsan Rianto Yoga Ihsan Rianto Yuaniko Paramitra