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All Journal Jurnal Sains dan Teknologi Techno.Com: Jurnal Teknologi Informasi Sistemasi: Jurnal Sistem Informasi JURNAL PENGABDI MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Informasi dan Multimedia Jurnal Bumigora Information Technology (BITe) Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Minfo Polgan (JMP) MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) INCOME: Indonesian Journal of Community Service and Engagement Bakti Sekawan : Jurnal Pengabdian Masyarakat Explore Prosiding Seminar Nasional CORISINDO
Syahrir, Moch.
Universitas Bumigora
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Health Professions Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Social Sciences Other

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Penerapan Metode Simple Additive Weigthed Dan Analitical Hierachy Proces Untuk Penentuan Dosen Penguji Skripsi Rijaldi, Rian Maulana; Syahrir, Moch
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 4 (2025): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i4.750

Abstract

The selection of thesis examiners is a crucial process for student academic success, yet it is often based on unstructured subjective considerations. This study aims to address this issue by designing and implementing a Decision Support System (DSS) to provide objective lecturer recommendations. The system integrates the Analytical Hierarchy Process (AHP) method for consistent criteria weighting and the Simple Additive Weighting (SAW) method to rank 10 lecturer alternatives based on four main criteria: Academic Qualification (K1), Time Availability (K2), Total Guidance (K3), and Structural Position Workload (K4). The AHP analysis results indicate that Academic Qualification (K1) is the highest priority criterion with a weight of 0.449 and a highly valid consistency ratio (CR = 0.04). Subsequently, the SAW calculation yielded three candidates who ranked at the top with a maximum preference score of 1.000. This study concludes that the hybrid AHP-SAW model provides an objective, transparent, and efficient framework for the lecturer selection process, successfully delivering accountable recommendations to assist decision-making within the academic environment.
Association Rule Integrasi Pendekatan Metode Custom Hashing dan Data Partitioning untuk Mempercepat Proses Pencarian Frekuensi Item-set pada Algoritma Apriori Moch. Syahrir; Fatimatuzzahra Fatimatuzzahra
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 20 No. 1 (2020)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v20i1.833

Abstract

Data mining dengan peran asosiasi sudah banyak digunakan oleh dunia usaha, salah satu algoritma yang sering digunakan untuk aturan asosiasi adalah apriori. Namun apriori memiliki kelemahan dalam hal performa, karena pada setiap penentuan frequent k-itemset harus melakukan scan database. Hal ini akan menjadi masalah apabila kandidat k-itemset memiliki dimensi yang banyak. proses scan database yang besar akan memakan waktu yang lama dan berpengaruh pada penggunaan memori dan prosesor. Apriori sudah sering dikembangkan, salah satu yang populer adalah Frequent Pattern (fp-growth), apriori dan fp-growth sama-sama merupakan algoritma untuk aturan asosiasi, hanya saja fp-growth menggunakan pendekatan yang berbeda dengan apriori yakni menggunakan pendekatan Frequent Pattern Tree (fp-tree). Meski fp-growth memiiki performa yang bagus ketika scan database namun rules yang di hasilkan oleh fp-growth tidak sebaik yang di hasilkan oleh apriori. Alternatif lain yang bisa digunakan adalah metode hashing, hal ini bisa menjadi solusi untuk mengatasi masalah dalam proses pencarian dan penentuan frequent k-itemset, sehingga proses scan database bisa lebih cepat. Tujuan penelitian adalah memperbaiki kinerja apriori dalam proses pencarian frekuensi itemset sehingga waktu scan database bisa lebih cepat
Intelligent System for Internet of Things-Based Building Fire Safety with Naive Bayes Algorithm Ni Gusti Ayu Dasriani; Sirojul Hadi; Moch Syahrir
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i1.3581

Abstract

Population growth is increasing every year. Population growth causes an increase in population density in a country. The largest population density is in urban areas. Fires in a city with a high population density will potentially cause greater damage. Material and non-material losses due to fire can be caused by not functioning maximally early warning systems, especially fire detection. In addition, other factors, such as system errors in detecting fires, can potentially cause fires. This research aims to build an intelligent system that can minimize building fire detection errors to reduce user material losses. The intelligent system can classify fire potential into four classifications, namely ”very dangerous,” ”dangerous,” ”alert,” and ”safe.” The method used in this research is Research and Development (R&D) with artificial intelligence using the Na¨ıve Bayes method, which has been integrated with the Internet of Things (IoT). This research shows that the Na¨ıve Bayes algorithm can be used to classify fire potential, proven by the overall system testing accuracy of 93.33% with an error of 6.77%.
Co-Authors Ahmad Ahmad Ahmat Adil Andi Sofyan Anas Anthony Anggrawan Apriani Apriani Augustin, Kartarina Ayu Dasriani, Ni Gusti Azhar, Lalu Zazuli Azhar, Raisul Bukran Cahyablindar, Ayu Darma, I Made Yadi Darmawan, I Made Angga Wahyu Fatimatuzzahra Fatimatuzzahra Galih Hendro Martono Hairani Hairani Hammad, Rifqi Hariyadi, I Putu I Nyoman Switrayana Kartarina, Kartarina Kurniadin Abd Latif Lely Kurniawati Lilik Widyawati M. Hidayatullah Mardedi, Lalu Zazuli Azhar Mardedi, Lalu Zazuli Azhar Melati Rosanensi Mudawil Qulub Muhamad Azwar Muhamad Azwar, Muhamad Muhammad Azwar Muhammad Zulfikri Muhammad Zulfikri Neny Sulistianingsih Ningsih, Neny Sulistia Ondi Asroni Pahrul Irfan Qulub, Mudawil Ria Rismayati Rifqi Hammad Rijaldi, Rian Maulana Riosatria, Riosatria Rismayanti, Ria Rizki, M Santoso, Heroe Sirojul Hadi Tri Sujaka, Tomi Wicaksono, Moh Arief Widayat, Windy Zulfikri, Muhammad Zulkipli Zulkipli