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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Language Literacy: Journal of Linguistics, Literature, and Language Teaching METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Informasi dan Teknologi Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Journal of Computer Networks, Architecture and High Performance Computing Yumary: Jurnal Pengabdian kepada Masyarakat Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Sains Teknologi dan Sistem Informasi International Journal of Research in Vocational Studies (IJRVOCAS) Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Pustaka Robot Sister Indonesian Journal of Emerging Trends in Community Empowerment Intelligent Computing and Advanced Data Science
Akbar Idaman
Informatika, Universitas Satya Terra Bhinneka, Medan, Indonesia,
Aerospace Engineering Agriculture, Biological Sciences & Forestry 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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Analysis of COPRAS and ORESTE in Determining Superior Website Pages of Universities in Medan City Akbar Idaman; Tar Muhammad Raja Gunung
Jurnal Informasi dan Teknologi 2024, Vol. 6, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v6i3.589

Abstract

This research aims to evaluate the quality of university web pages in Medan City using two decision-making methods, namely Complex Proportional Assessment (COPRAS) and Organization Rangement Et Syntest De Relatonnelles (ORESTE). University websites play a very important role in reflecting the identity, vision, and mission of the institution, as well as improving its reputation in today's digital era. However, not all universities in Medan have implemented optimal standards in managing their web pages. Therefore, the results of this study show that based on the COPRAS method, there are 3 top universities, namely Muhammadiyah University of North Sumatra (UMSU) ranked first with the highest score of 100.0000, followed by Quality University with a score of 93.7500 ranked second, and Harapan University Medan with a score of 91.4063 ranked third. Meanwhile, using the ORESTE method also ranked UMSU first with a score of 5.00, followed by Universitas Pembangunan Panca Budi in second place, and Santo Thomas Catholic University in third place with a score of 7.17. The similarity of the first rank between the two methods shows consistency in the recognition of the quality of the UMSU web page. However, differences were seen in the second and third rankings, where COPRAS ranked Universitas Quality and Universitas Harapan Medan, while ORESTE ranked Universitas Pembangunan Panca Budi and Universitas Katolik Santo Thomas. This difference reflects the different evaluation approaches of the two methods. The findings are expected to assist universities in Medan in developing more effective strategies for improving user experience and strengthening institutional reputation.
Enhancing Vocational High School Students’ Technological Competence through Python and Artificial Intelligence Mikha Dayan Sinaga; Zhafran Fatih Ananda; Akbar Idaman; Muhammad Irfan; Oswald Tobias Rafaello Siahaan
Yumary: Jurnal Pengabdian kepada Masyarakat Vol 6 No 4 (2026): Juni
Publisher : Penerbit Goodwood

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/yumary.v6i4.6407

Abstract

Purpose: This study aims to enhance the technological competence of vocational high school students through the introduction of Python programming and Artificial Intelligence (AI) to improve their digital literacy and computational thinking skills. Methodology: This study was conducted at Sekolah Menengah Kejuruan (SMK) Sultan Iskandar Muda, involving 44 tenth-grade vocational high school students. The program applied a quasi-experimental approach with a pretest–posttest design to measure students’ understanding before and after training. The training activities included lectures, demonstrations, and hands-on coding practice using Python 3.10, Google Colab, and Microsoft PowerPoint as learning tools. Data were collected through questionnaires, observations, and evaluation tests to measure the students’ knowledge of programming concepts and AI applications. Results: The results showed a significant improvement in students’ understanding after they participated in the training program. The average pretest score of 53.5 increased to 82.8 in the post-test. Students demonstrated better comprehension of Python programming concepts, including syntax, variables, data types, and input–output commands, as well as greater awareness of Artificial Intelligence applications in everyday life. Conclusions: The training program effectively improved students’ technological competence and increased their interest in learning programming and in emerging technologies. Limitations: The study was limited by the short training duration and differences in students’ initial knowledge levels. Contributions: This study contributes to vocational and technology education by providing a practical training model that can support the development of students’ digital literacy and readiness to face the challenges of the digital transformation era.
Banana Leaf Disease Classification Using HSV and LBP Feature Extraction with Support Vector Machine Novriza Rahayu; Farhan Muhammad; Sylvia Indri Yani; Agung Fadillah; Akbar Idaman
Journal of Intelligent Computing and Advanced Data Science Vol. 1 No. 2 (2026): July 2026
Publisher : Universitas Satya Terra Bhinneka

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

Abstract

Banana leaf diseases are one of the primary factors contributing to the decline in the quality and productivity of banana plants, as manual identification remains time-consuming, subjective, and prone to misclassification due to the similarity of symptoms among different diseases. This raises the question of whether a combination of Hue, Saturation, Value (HSV) and Local Binary Pattern (LBP) feature extraction can provide an effective alternative for banana leaf disease classification using a Support Vector Machine (SVM). While previous studies have relied on deep learning methods or combined HSV with Histogram of Oriented Gradients (HOG) features for this task, the combination of HSV and LBP for banana leaf disease classification remains largely unexplored. Using the Banana Leaf Spot Diseases (BananaLSD) dataset, comprising four classes (Cordana, Healthy, Pestalotiopsis, and Sigatoka), the original images were first divided into training and testing sets using an 80:20 ratio to prevent data leakage, after which data augmentation was applied exclusively to the training set. All images were center cropped before HSV and LBP features were extracted, combined, and classified using an SVM with a Radial Basis Function (RBF) kernel. On an independent test set of original, non-augmented images, the proposed model achieved an accuracy of 87.30%, precision of 89.06%, recall of 87.30%, and F1-score of 87.80%, with consistent results confirmed through Stratified Group 5-Fold Cross-Validation and an ablation study showing that the HSV and LBP combination outperformed either feature type alone. These findings indicate that combining HSV and LBP features offers a reliable, feature based alternative to deep learning for automated banana leaf disease identification.
Integrasi Multi Factor Evaluation Process (MFEP) Untuk Prioritisasi Kanal Pemasaran Digital UMKM Akbar Idaman; Muit Sunjaya; Tar Muhammad Raja Gunung; Febry Aurlani
Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Vol. 5 No. 2 (2026): EDISI MARET 2026
Publisher : STMIK Triguna Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jursi.v5i2.12328

Abstract

Penelitian ini mengintegrasikan Multi Factor Evaluation Process (MFEP) sebagai kerangka evaluasi multikriteria untuk prioritisasi kanal pemasaran digital UMKM pada konteks Indonesia yang ditandai keterbatasan anggaran, SDM, dan kompetensi digital. Lima kriteria inti digunakan, yaitu Reach–Fit, efisiensi biaya/CPA, potensi konversi, kecepatan dampak (time-to-result), serta kemudahan eksekusi & pengukuran. Data mencakup 13 alternatif kanal yang dinilai pada skala 1–5 dan dibobotkan sesuai skema penelitian. Capaian utama menunjukkan 7 kanal melampaui ambang kelulusan TNE ≥ 3,50, yaitu: TikTok Ads (3,95), Facebook Local Awareness Ads (3,85), Influencer Mikro (3,85), Instagram Feed Ads Conversion (3,60), WhatsApp Click-to-Chat (3,55), Instagram Reels Organic + Light Ads (3,50), dan Marketplace Ads (3,50); kanal lain berada pada rentang 2,85–3,30 dan direkomendasikan sebagai pendukung/optimalisasi. Hasil ini menegaskan bahwa keputusan yang menimbang kelima kriteria lebih konsisten, hemat, dan actionable dibanding pemilihan berbasis intuisi, karena langsung diturunkan menjadi urutan eksekusi, alokasi anggaran awal, dan fokus peningkatan kapabilitas tim. Kerangka MFEP yang diusulkan bersifat sederhana, transparan, dan dapat dijelaskan, sehingga layak diadopsi sebagai sistem pendukung keputusan bagi pendampingan UMKM.
Sistem Pakar Adaptif Berbasis Case-Based Reasoning untuk Monitoring dan Deteksi Kecanduan Game Free Fire pada Remaja Ningtyas, Alyiza Dwi; Raja Gunung, Tar Muhammad; Odang, Diana Kemala; Idaman, Akbar; Lubis, Siti Sahara
Jurnal Pustaka Robot Sister (Jurnal Pusat Akses Kajian Robotika, Sistem Tertanam, dan Sistem Terdistribusi) Vol 4 No 2 (2026): Jurnal Pustaka Robot Sister (Pusat Akses Kajian Robotika, Sistem Tertanam, dan Si
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakarobotsister.v4i2.2148

Abstract

Perkembangan pesat game online berbasis mobile, khususnya Free Fire, telah memberikan dampak signifikan terhadap perilaku remaja, termasuk meningkatnya risiko kecanduan. Penelitian ini bertujuan untuk mengembangkan sistem pakar adaptif berbasis case-based reasoning yang mampu melakukan monitoring dan deteksi dini kecanduan game secara efektif. Data penelitian diperoleh melalui kuesioner, observasi, serta data penggunaan (user usage) dan statistik permainan (in game statistics) seperti jumlah permainan, jumlah kill, rata-rata jarak tempuh, rata-rata waktu hidup, dan win rate. Metode case-based reasoning digunakan untuk menghitung tingkat kemiripan antara kasus baru dengan kasus dalam basis pengetahuan guna menentukan tingkat kecanduan pengguna. Hasil penelitian pada pengguna dengan username Dvin DVZ menunjukkan bahwa tingkat kemiripan tertinggi berada pada kategori severe addiction sebesar 60%, diikuti oleh moderate addiction sebesar 31%, sedangkan kategori non addicted dan mild addiction menunjukkan nilai 0%. Temuan ini mengindikasikan bahwa pengguna yang dianalisis cenderung berada pada tingkat kecanduan yang tinggi. Sistem yang dikembangkan terbukti mampu memberikan diagnosis yang akurat serta rekomendasi penanganan, seperti pembatasan durasi bermain, pengaturan aktivitas harian, dan peningkatan interaksi sosial. Dengan demikian, sistem pakar ini diharapkan dapat menjadi alat bantu yang efektif dalam mengidentifikasi serta mengurangi dampak negatif kecanduan game pada remaja.
Sistem Pendukung Keputusan Prioritas Implementasi Pendidikan Inklusif Menggunakan Integrasi Metode Entropy-WASPAS Idaman, Akbar; Egani Sitepu, Sengli; Muhammad Raja Gungung, Tar; Putri Mulyadi, Iriene
Jurnal Pustaka Robot Sister (Jurnal Pusat Akses Kajian Robotika, Sistem Tertanam, dan Sistem Terdistribusi) Vol 4 No 2 (2026): Jurnal Pustaka Robot Sister (Pusat Akses Kajian Robotika, Sistem Tertanam, dan Si
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakarobotsister.v4i2.2265

Abstract

Pendidikan inklusif memerlukan prioritas implementasi yang jelas karena sekolah dan pemangku kebijakan sering menghadapi keterbatasan sumber daya, kapasitas guru, infrastruktur, teknologi bantu, dan dukungan kelembagaan. Penelitian ini bertujuan mengembangkan model sistem pendukung keputusan untuk menentukan prioritas strategi pendidikan inklusif bagi peserta didik penyandang disabilitas menggunakan integrasi metode Entropy dan Weighted Aggregated Sum Product Assessment (WASPAS). Penelitian menggunakan pendekatan kuantitatif berbasis Multi-Criteria Decision Making dengan mengevaluasi delapan alternatif strategi berdasarkan sepuluh kriteria. Data diperoleh dari penilaian tiga pakar dan diagregasi menjadi matriks keputusan. Metode Entropy digunakan untuk menghasilkan bobot objektif berdasarkan keragaman data, sedangkan WASPAS digunakan untuk menentukan peringkat alternatif melalui kombinasi Weighted Sum Model dan Weighted Product Model. Kebaruan penelitian ini terletak pada formulasi model prioritisasi pendidikan inklusif yang mengintegrasikan pembobotan objektif, pemeringkatan multikriteria, dan pengujian kestabilan hasil dalam satu kerangka pengambilan keputusan. Hasil menunjukkan bahwa risiko implementasi memperoleh bobot tertinggi sebesar 0,3110, diikuti biaya implementasi sebesar 0,3055. Strategi penguatan kolaborasi antara sekolah, orang tua, dan komunitas disabilitas menjadi prioritas utama dengan nilai sebesar 0,9693, diikuti pelatihan guru sebesar 0,9125, adaptasi kurikulum dan asesmen sebesar 0,8494, serta peningkatan sistem identifikasi kebutuhan peserta didik sebesar 0,8043. Analisis sensitivitas pada nilai ? 0,00–1,00 menghasilkan urutan peringkat yang identik tanpa rank reversal, sehingga model stabil dan robust terhadap perubahan proporsi WSM dan WPM. Kontribusi ilmiah penelitian ini berupa model komputasional yang objektif, transparan, dan dapat direplikasi sebagai dasar pengembangan aplikasi sistem pendukung keputusan pendidikan inklusif.
Penerapan Algoritma Sorting dalam Penentuan Pekerja Pada Aplikasi Cari Kerja Oleh dan Untuk Warga Satu Kelurahan Dataran Tinggi Binjai Manutur Pandapotan Siregar; Abwabul Jinan; Akbar Idaman Prince Peter S. Siagian
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp294-300

Abstract

The current job search process often involves posting an announcement on paper or a banner on a notice board, or in front of the company’s location. Another common method is through job search applications, such as JobStreet and others. The first method has a drawback because people may not know when the job posting is published. Meanwhile, with the second method, many people hesitate to use these applications as they feel their skills may not be sufficient. To address these issues, an Android or web-based job search application is proposed to facilitate job sharing and job seeking within a nearby area, specifically within a single subdistrict. This application is targeted at individuals with a high school education level or lower, and the jobs shared are typically daily work requiring minimal skills, such as construction work, electrical repairs, gardening, cleaning, and similar tasks. A sorting algorithm will be implemented to help select the nearest and most suitable candidate for each job. To access the application, users must first register, enabling employers to post jobs and workers to find suitable positions.
ANALISIS MULTI OBJECTIVE OPTIMIZATION ON THE BASIS OF RATIO ANAYSIS (MOORA) DALAM MODEL REKOMENDASI EKSTRAKURIKULER SISWA Akbar Idaman; Muhammad Imam Zarkasyi; Febry Aurlani; Hamjah Arahman
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4665

Abstract

Abstract: This research applies the Multi Objective Optimization On the Basis of Ratio Analysis (MOORA) method to determine the appropriate extracurricular activity recommendations at XYZ School, aiming to facilitate data-driven decision-making in selecting extracurricular activities that align with students' interests and talents. The methodology includes data collection through observation and interviews, followed by the application of the MOORA method to process data on students' interests, talents, creativity, and potential involvement in extracurricular activities. The results show that the application of the MOORA method produces objective and systematic rankings of the available extracurricular activities based on the established criteria. The Scouting activity, with the highest value (Yi = 0.4821), was found to be the most suitable activity for students' profiles, followed by Arts and Paskibra. The MOORA method proves effective in providing more accurate and efficient extracurricular activity recommendations, addressing issues in previous subjective and ad-hoc decision-making processes. This study concludes that the application of MOORA can enhance the quality of decisions in selecting extracurricular activities, potentially enriching students' experiences and skill development. Keyword: MOORA; Extracurricular recommendations; Decision-making; Decision support system; Education. Abstrak: Penelitian ini mengaplikasikan metode Multi Objective Optimization On the Basis of Ratio Analysis (MOORA) untuk menentukan rekomendasi kegiatan ekstrakurikuler yang tepat di Sekolah XYZ, dengan tujuan untuk mempermudah pengambilan keputusan berbasis data mengenai kegiatan ekstrakurikuler yang sesuai dengan minat dan bakat siswa. Metodologi penelitian ini melibatkan pengumpulan data melalui observasi dan wawancara, serta penerapan metode MOORA untuk mengolah data mengenai minat, bakat, kreativitas, dan potensi keterlibatan siswa dalam kegiatan ekstrakurikuler. Hasil penelitian menunjukkan bahwa penerapan metode MOORA dapat menghasilkan peringkat yang objektif dan sistematis terhadap kegiatan ekstrakurikuler yang tersedia, berdasarkan kriteria yang ditetapkan. Kegiatan Pramuka, dengan nilai tertinggi (Yi = 0,4821), dinilai sebagai kegiatan yang paling sesuai dengan profil minat dan bakat siswa, diikuti oleh Kesenian dan Paskibra. Metode MOORA terbukti efektif dalam memberikan rekomendasi kegiatan ekstrakurikuler yang lebih tepat dan efisien, mengatasi masalah pemilihan yang sebelumnya bersifat subjektif dan ad-hoc. Penelitian ini menyimpulkan bahwa penerapan MOORA dapat meningkatkan kualitas keputusan dalam pemilihan kegiatan ekstrakurikuler, yang berpotensi memperkaya pengalaman dan pengembangan keterampilan siswa. Kata kunci: MOORA; Rekomendasi ekstrakurikuler; Pengambilan keputusan; Sistem pendukung keputusan; Pendidikan.
Co-Authors Abdul Muis ABDUL MUIS Abdul Muis Abwabul Jinan Agung Fadillah Agung Prabowo Al Khowarizmi Alifia Restu Selvanda Amrullah Amrullah Amrullah Amrullah Ananda, Zhafran Fatih Aurlani, Febry Egani Sitepu, Sengli Eldo, Handry Farhan Muhammad Febry Aurlani Hamjah Arahman Handry Eldo Handry Eldo Hirzi, M Fakhrul Lubis, Siti Sahara Manutur Pandapotan Siregar Monika, Eka Syafrina Muhammad Imam Zarkasyi Muhammad Imam Zarkasyi Muhammad Irfan Muhammad Raja Gungung, Tar Muit Sunjaya Mutiasanita Nasution, Guslila Sari Ningtyas, Alyiza Dwi Novriza Rahayu Odang, Diana Kemala Oswald Tobias Rafaello Siahaan Purnomo, Nopi Putri Mulyadi, Iriene Raja Gunung, Tar Muhammad Ramadhona, M. Rifqi Rika Rosnelly Riko Muhammad Suri Riris Agustin Roslina, Roslina Ryan Rinaldi Hadistio Sabila, Puji Chairu Simamora, Windi Saputri Simanjuntak, Peter Jaya Negara Simatupang, Septian Sinaga, Mikha Dayan Siregar, Manutur Pandapotan Siti Sarah Harahap Sukartara, Nirwansyah Suri, Riko Muhammad Sylvia Indri Yani Tar Muhammad Raja Gunung Tar Muhammad Raja Gunung Vicky Rolanda Vicky Rolanda, Vicky Windi Saputri Simamora Zarkasyi, Muhammad Imam