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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Sistemasi: Jurnal Sistem Informasi CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Network Engineering Research Operation [NERO] Jurnal Teknoinfo Jurnal Tekno Kompak Building of Informatics, Technology and Science TIN: TERAPAN INFORMATIKA NUSANTARA Mattawang: Jurnal Pengabdian Masyarakat Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Ilmiah Infrastruktur Teknologi Informasi Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Telematics and Information Technology (TELEFORTECH) Jurnal Ilmiah Edutic : Pendidikan dan Informatika Jurnal Media Borneo CHAIN: Journal of Computer Technology, Computer Engineering and Informatics Journal of Data Science and Information System Journal of Artificial Intelligence and Technology Information Jurnal Media Jawadwipa Swarnadwipa JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Pasaribu, A. Ferico Octaviansyah
Fakultas Teknik Dan Ilmu Komputer, Universitas Teknokrat Indonesia
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RAM-MEREC (Root Assessment Method - Method based on Removal Effects of Criteria): A Synergistic Approach to Weight Derivationand Alternative Ranking in the Selection of the Best Intern Employees Permata, Permata; Wang, Junhai; Setiawansyah, Setiawansyah; Pasaribu, A. Ferico Octaviansyah; Wahyudi, Agung Deni
TIN: Terapan Informatika Nusantara Vol 5 No 11 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i11.7198

Abstract

An effective intern selection process requires an objective and systematic approach to decision-making, especially when it involves multiple assessment criteria. This study proposes a combined approach of RAM-MEREC, which is a combination of Method based on Removal Effects of Criteria (MEREC) and Root Assessment Method (RAM), as a method to improve accuracy and reliability in the best internal selection. MEREC is used to objectively determine the weight of criteria based on the impact of the elimination of each criterion on the overall outcome. Meanwhile, RAM is used to generate alternative rankings by considering the root impact of value changes on each candidate's performance. The results of the application of this method show that RAM-MEREC is able to provide a more representative weighting and a more stable and consistent final ranking. The results of the application of this method show that RAM-MEREC is able to provide a more representative weighting and a more stable and consistent final ranking. The results of the calculation of the total score of all alternatives using the evaluation method that has been determined, obtained that Alternative 10 is the best candidate with the highest score of 1.4378, followed by Alternative 6 with a score of 1.4375 and Alternative 3 with a score of 1.4375. This approach not only improves the quality of decision-making, but also minimizes subjectivity and bias in the selection process.
Implementasi Kombinasi LOPCOW dan Operational Competitiveness Rating Analysis Dalam Rekomendasi Tempat Wisata Indoor Setiawan, Gde Denny; Octaviansyah Pasaribu, A. Ferico
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol. 9 No. 2 (2024): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v9i2.1914

Abstract

Indoor attractions offer an exciting and comfortable holiday experience, especially for those who want to avoid extreme weather or want indoor comfort. The selection of indoor attractions is often faced with various problems involving distance, price, rating, and cleanliness. All these factors must be carefully considered to ensure that the chosen indoor attraction can provide a satisfying and enjoyable experience. The application of a combination of Logarithmic Percentage Change-Driven Objective Weighting (LOPCOW) and Operational Competitiveness Rating Analysis (OCRA) in the performance evaluation of business alternatives offers an innovative and robust approach to decision making. LOPCOW allows objective determination of criteria weighting based on logarithmic percentage changes, emphasizing the dynamics of relative performance changes between criteria. Integration with OCRA, which evaluates operational competitiveness through efficient ratio analysis. The ranking results showed that the first best rank was obtained by Puncak Mas with a final value of 1.2596, the second-best rank was obtained by Wira Garden with a final value of 1.1607, the third best rank was obtained by Lampung Walk with a final value of 1.0289. The combination of these two methods increases the accuracy and reliability of ranking results, assisting decision makers in choosing truly superior alternatives based on relevant and up-to-date data. By utilizing data-driven analysis and robust methodologies, the decision-making process becomes more efficient and can be done faster, saving time and resources.
Co-Authors Ade Dwi Putra ade rahman Ade Surahman Ade Surahman Adhie Thyo Priandika Adi Sucipto, Adi Agus Irawan Ahmad Ari Aldino Aldi Bagus Prasetyo Amik Herningsih Andi Nurkholis Arif Febriansyah Arifin Nur Dedi Darwis Dedi Darwis Dedi Irawan Depriansah Depriansah Donaya Pasha Eka Shintya Pratiwi Fachrul Kurnia Adam Farid Jack Hendri Farid Jeck Fikri Hamidy Fredy Hermawan Gufran Umar, M. Kasyif Habib Rizki A.Siregar Imam Ahmad Irna Puspasari Kadek Dwi Riska Santi Kiki Septiani Leny Meilisa M. Rizky Fadhilah Mahdalena Serumpun Maria Ainun Nazar Maulana Aziz Assuja Muhammad Al Khusnul Rizki Nita Afriani Novi Eka Wati Nurfitria Ningsi Nuroji Nuroji Nuroji Nuroji Oprasto, Raditya Rimbawan Permata, Permata Prasetyo, Aditya Dwi Purnomo Aji Renaldy Hermanto Renaldy Hermanto Riska Aryanti Riskiono, Sampurna Dadi Sampurna Dadi Riskiono Sanriomi Sintaro Saputra, Febrian Eko Setiawan, Gde Denny Setiawansyah Setiawansyah Shinta Bela Siti Romlah Sumanto, Sumanto Surahman, Ade Vera Nadita Very Hendra Saputra vista anestiviya Wahyudi Wahyudi Wahyudi, Agung Deni Wang, Junhai YOHANA TRI UTAMI, YOHANA TRI Yopita Anggela Yuri Rahmanto Yusra Fernando Yusra Fernando