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Decision Support System for Selecting the Best Head of Study Program Using the MOORA and MOOSRA Methods Karim, Abdul; Hidayatullah, Muhammad; Kurniawan Nasution, Muhammad Bobbi; Esabella, Shinta
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8928

Abstract

The Head of the Study Program is one of the most important parts of a university. The Head of the Study Program is also the highest leader within the study program structure. The role of the Head of the Study Program is as an organizational unit that is responsible for the administration of the study program they lead. The Head of the Study Program is tasked with coordinating all study program activities, as well as managing lecture schedules, practicum schedules, and lecture evaluation results. The selection of the Head of the Study Program requires precise accuracy to avoid errors in the selection process. The stability of a study program heavily depends on the role and reputation of its lecturers, especially the lecturer responsible for the core courses of that study program. Therefore, the participation of lecturers is highly necessary in the selection of the Head of the Study Program. Since the higher education management is also interested in the selection process, methodological assistance is needed to accommodate the aspirations of the lecturers and the interests of the university management. The reward system is a crucial element for motivation toward a better direction, aiming to further increase performance. This reward system is expected to encourage the performance of the Head of the Study Program to be more productive, so that the vision and mission for achieving the development of a university can be properly attained and implemented.
Implementation of MOORA and MOORSA Methods in Supporting Computer Lecturer Selection Decisions Zulham Sitorus; Abdul Karim; Asyahri Hadi Nasyuha; Moustafa H. Aly
JURNAL INFOTEL Vol 16 No 3 (2024): August 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i3.1184

Abstract

The selection of computer science lecturers is an important process for educational institutions, requiring a balanced assessment of various criteria to find the most suitable candidates. This paper examines the implementation of Multi-Objective Optimization based on Ratio Analysis (MOORA) and its variant, namely Multi-Objective Optimization based on Ratio Analysis with a Subjective Attitude (MOORSA), as a tool to support decision making. in this case. This selection process is often complex, requiring consideration of various criteria, such as academic qualifications, teaching experience, research capabilities, and others. This research was conducted to support the decision-making process. by developing a Decision Support System (DSS) using the Multi-Objective Optimization on The Basic of Ratio Analysis (MOORA) and MOORSA methods. Many methods are used, such as SAW, AHP, Topsis and others. based on the calculation of the MOORA method, the highest result has been achieved by A1 worth 0.651819 and similarly, in the MOOSRA method the highest alternative result is A1 worth 0.592177.
Pemanfaatan Teknologi AI untuk Mengembangkan Strategi Digital Marketing Berbasis Data bagi UMKM Desa Karim, Abdul; Syahrizal, Muhammad; Diansyah, Tengku Mohd.
Jurnal Pengabdian Masyarakat Inovasi Vol. 5 No. 1 (2026): February 2026
Publisher : Sekolah Tinggi Ilmu Manajemen Sukma Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35126/jpmi.v5i1.999

Abstract

This community service program aims to enhance the capacity of micro, small, and medium enterprises (MSMEs) in Aek Pamingke Village in utilizing artificial intelligence (AI) for data-driven digital marketing strategies. The activities were conducted through several stages, including needs analysis, intensive training, practical implementation, and evaluation. The initial analysis revealed that most MSME participants had limited knowledge and skills in digital marketing, with 60% categorized as having low understanding before the program. After the training, significant improvement was recorded, with 50% of participants reporting being very satisfied and 35% satisfied. The program’s impact was evident in the participants’ improved ability to design more effective data-driven marketing strategies. The main limitations of this program were the relatively small number of participants and the limited implementation time, indicating the need for extended programs with broader coverage in the future.
Peningkatan Pengarahan Beam dan Estimasi Sudut Kedatangan Berbasis CNN untuk Sistem Antena MIMO Cerdas Karim, Abdul; Purnama, Iwan; Ernawati, Andi
Explorer Vol 6 No 1 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v6i1.2592

Abstract

This study proposes a Convolutional Neural Network (CNN)–based approach to enhance the intelligence of MIMO antenna systems in Internet of Things (IoT) environments, particularly for modeling the relationship between wireless channel characteristics and achievable communication capacity. Modern MIMO systems face complex challenges due to dynamic channel conditions such as noise, path loss, and multipath fading, which significantly affect data transmission quality. In this research, channel-related features are processed through a structured preprocessing stage before being fed into a CNN model to learn nonlinear relationships among channel parameters. The developed model is designed to predict achievable channel capacity accurately as part of an adaptive and intelligent wireless communication framework. Experimental results show that the proposed CNN model achieves a Test Loss of 0.0317 and a Mean Absolute Error (MAE) of 0.1267 on unseen test data. Visualization of actual versus predicted values indicates that the model demonstrates good generalization across most data ranges, although some deviations remain at extremely high capacity values. Compared to conventional approaches, the CNN-based method shows superior capability in capturing complex correlations among MIMO channel parameters. Therefore, this approach contributes to the development of adaptive and efficient intelligent antenna systems, supporting the growing demands of next-generation IoT communication networks.
Sistem Pendukung Keputusan Pemilihan Kepala Desa Terbaik Menerapkan Metodethe Extended Promethee II (EXPROM II) Nurlela Nurlela; Muhammad Syahrizal; Fadlina Fadlina; Abdul Karim
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 1 No. 3 (2020): Mei 2020
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v1i3.2151

Abstract

Decision Support System is a system that can help management in making the right decision, which is needed at a management level. Likewise at the Lubuk Pakam Sub-District Office in selecting the best village head. So far, the Camat Office has never determined the best village head in Lubuk Pakam Subdistrict, so that it encounters obstacles in choosing the village head election. SPK is able to provide alternative solutions to semi / unstructured problems for individuals or groups and in a variety of decision making processes and styles, SPK uses data, databases and analyzes of decision models. Seeing this, researchers are interested in conducting research by applying the Extended Promethee II (EXPROM II) method to elect the best village head in a decision support system. It is expected that the results of the research can help the Lubuk Pakam sub-district
Co-Authors Afrendi, Mohammad Agus Perdana Windarto Agustina Sidabutar Agustina, Asri Widya Ahyuna Ahyuna, Ahyuna Aldiansyah, Ferry Alfarisi Pasaribu, Ahmad Ambiyar, Ambiyar Andi Ernawati Andi Ernawati Andriani, Titi Aritonang, Putri Armasari, Selly Arridha Zikra Syah Asyahri Hadi Nasyuha Awfa, Qifari Bangun, Budianto Bernadus Gunawan Sudarsono Bobbi Kurniawan Nasution, Muhammad Cheylani Lukito, Salwa Christiorenfa Br Haloho, Agatha Daulay, Nelly Khairani Dayu Sari, Arini Dhea Ananda, Tasya Dito Putro Utomo Dwika Asrani Dwika Assrani Efendi Hutagalung, Jhonson Efendi, Safri Erlin Windia Ambarsari Fadli, Muhammad Bagus Fadlina Fahmi Rizal Febriani, Budi Fifto Nugroho Garuda Ginting Guidio Leonarde Ginting Harahap, Armyka Pratama Hasibuan, Awaludin Heni Pujiastuti Hersatoto Listiyono Hidayatullah, Muhammad I Wayan Sugianta Nirawana Imam Saputra Indah Sari, Leni Indrayani, Puput Iwan Purnama Iwan Purnama Jahril Jeperson Hutahaean Kraugusteeliana Kraugusteeliana Kurniawan Nasution, Muhammad Bobbi Kusmanto Kusmanto Kusmanto Kusmanto M. Rafi Mardinata, Erwin Marha As, Pawa Niassa Meryance Viorentina Siagian Mesran, Mesran Mhd Ali Hanafiah Mhd Bobbi Kurniawan Nasution Moustafa H. Aly Muhammad Bobbi Kurniawan Nasution Muhammad Hamka Muhammad Syahrizal Nababan, Dosmaida Nasution, Mhd Bobbi Kurniawan Nasution, Muhammad Bobbi Kurniawan Natalia Silalahi Nona Oktari Nurlela Nurlela Nurliadi Pane, Rahmadani Pane, Siddik Pohan, Tatang Hidayat Poningsih Pratama, Armyka Prayetno, Sugeng Prayetno, Sugeng Prayetno Purba, Elvitrianim Purba, Elvitrianim Putra Juledi, Angga Putri, Nathania Rahman, Ben Rizal, Chairul Rohani Rohani Roslidar Saidi Ramadan Siregar Saludin Muis Sartika Br Siregar, Amanda Sempurna, Teguh Shinta Esabella Siagian, Yessica Siddik Siregar, Anwar Sinulingga, Raja Ingata Siregar, Feby Khairunnisya Siti Sahara Nasution Soeb Aripin Suha Alvita Suhada, Karya Sundari Retno Andani Supiyandi Supiyandi Suryadi, Sudi Sutrino Dwi Raharjo Syahputra Harahap, Hasmi Syahrial Tengku Mohd Diansyah, Tengku Mohd Triana, Dewi Trianovie, Sri Trianovie, Sri Unung Verawardina Uswatun Hasanah Vita S. Siregar, Siony William Ramdhan Wilson, Eric Yessica Siagian Yulizar, Isma Ahmad Yuwaldi Away Zebua, Yuniman Zulham Sitorus Zulkifli Zulkifli Zuly Budiarso