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All Journal CogITo Smart Journal CSRID (Computer Science Research and Its Development Journal) Jurnal Ilmiah Sinus Jurnal Abdimas Mahakam Indonesian Journal of Data and Science Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Jurnal Ilmiah Dan Karya Mahasiswa International Journal of Artificial Intelligence in Medical Issues Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Hamada Zein
Universitas Muhammadiyah Kalimantan TImur
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Public Health Social Sciences

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Optimalisasi Sirkulasi Oksigen dan Monitoring Kualitas Air untuk Peningkatan Budidaya Perikanan di Desa Makarti Kutai Kartanegara Pranoto, Sigiet Haryo; Zein, Hamada; Agustina, Fitriyati; Arbansyah
Jurnal Abdimas Mahakam Vol. 9 No. 02 (2025): Juli
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/jam.v9i02.3619

Abstract

Kegiatan pengabdian kepada masyarakat ini dilaksanakan di Desa Makarti, Kabupaten Kutai Kartanegara, dengan tujuan untuk meningkatkan produktivitas budidaya ikan nila melalui penerapan teknologi tepat guna dan pemberdayaan masyarakat. Permasalahan utama yang dihadapi masyarakat adalah keterbatasan dalam mengelola kualitas air kolam serta kurangnya sarana pendukung budidaya. Untuk menjawab permasalahan tersebut, tim pengabdian merancang dan menerapkan sistem aerator berbasis Internet of Things (IoT) yang dilengkapi dengan sensor suhu dan pH, guna memantau kondisi air secara real-time. Selain itu, dilakukan pelepasan 1.500 ekor bibit ikan nila ke kolam warga sebagai bentuk dukungan nyata terhadap keberlanjutan budidaya. Hasil kegiatan menunjukkan bahwa suhu dan pH air kolam berada dalam kisaran optimal untuk pertumbuhan ikan nila, dan penggunaan teknologi monitoring berbasis IoT memberikan kemudahan bagi warga dalam melakukan kontrol kualitas air.
Penerapan Metode AHP-TOPSIS Dalam Menentukan Mahasiswa Lulusan Terbaik Pada Prodi Keperawatan UMKT Berbasis Web Raenald Syaputra; Hamada Zein; Ari Ahmad Dhani; Bulan Suci Cahayawati; Faldy Alfareza Pambudi; Siti Muawwanah; Raihan Nabil; Bima Satria; Hery Kurniawan; Vito Junivan Rivaldo; Manda Rela Istiantoko
Jurnal Ilmiah Dan Karya Mahasiswa Vol. 2 No. 1 (2024): FEBRUARI : JURNAL ILMIAH DAN KARYA MAHASISWA
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jikma.v2i1.1407

Abstract

This study utilizes the AHP-TOPSIS method to determine the best graduating students in the nursing program. Evaluation criteria include GPA, duration of study, achievements, and final projects. The results indicate that GPA and achievements significantly influence the assessment of graduates. The use of the AHP-TOPSIS method demonstrates consistency, yet it's important to note that similar results don't always guarantee equivalence between the two methods. This study confirms the reliability of the method in evaluation, however, suggestions for future research include expanding the sample size and considering additional factors to enhance validity and reliability.
Pemodelan AHP Dan AHP-SAW Dalam Menentukan Mahasiswa Terbaik Fakultas Ilmu Keperawatan Universitas Muhammadiyah Kalimantan Timur Highness Mailani Putri; Hamada Zein; Sri Mar’ati Sholikhah; Azelina Zahra Riadini; Seftiani Nur; Lilis Sagita; Ridha Anisa Soldzu Parnga
Jurnal Ilmiah Dan Karya Mahasiswa Vol. 2 No. 1 (2024): FEBRUARI : JURNAL ILMIAH DAN KARYA MAHASISWA
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jikma.v2i1.1419

Abstract

The best students are students who have excellence both in values and ethics. In the graduation ceremony every year, the selection of the best students is a reward and also as a motivation that will be a supporting material for a student to plunge into a wider layer of society. In determining the best students at the Faculty of Nursing, Muhammadiyah University of East Kalimantan, it is still done manually using Microsoft excel. So it is necessary to implement a computer-based information system that can support decision making by considering the criteria to be assessed. AHP and AHP-SAW methods are used in modeling this decision support system and comparing the two methods. The AHP-SAW method produces better results than the AHP method. This is because the AHP-SAW combined method combines the best of both methods.
Penerapan Metode AHP-SAW Berbasis Web Untuk Menentukan Lulusan Terbaik Di Prodi Profesi Ners UMKT Any Sawheri Gading; Hamada Zein; Khusnul Khotimah; Adia Lestari; Aulia Khofifah Syamsuri; Siti Patimah; Tri Wahyudi; Joni Saputra; Ilhan Firanda; Achmad Farid; Ferdi Iwanda
Jurnal Ilmiah Dan Karya Mahasiswa Vol. 2 No. 1 (2024): FEBRUARI : JURNAL ILMIAH DAN KARYA MAHASISWA
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jikma.v2i1.1427

Abstract

In the nursing profession study program, has an important role in producing quality graduates and is ready to compete in the world of work. This research has a high urgency because it can make a real contribution in improving the quality of graduates of the UMKT Ners professional program. The main objective of this research is to implement a web-based AHP-SAW method to determine the best graduates in the UMKT Nursing Profession Program. The data collection method uses secondary data. Secondary data is obtained based on data from related agencies and sources, including the data that has been collected. This research uses multi-criteria, namely GPA, Study Period, Achievement, and Final Project KIAN. The AHP method is used to determine weights based on many criteria or multi criteria. The results of this study concluded that the implementation of the AHP-SAW method can help determine the best graduates in the UMKT Ners Professional Study Program. This system is equipped with features that can display all calculations in detail, this system also has a database that makes it easy for users to access LifeTime, other advantages can overcome the possibility of lost data. the author hopes that this system will be developed to be dynamic so that it can be used on all devices. As for the appearance of the system which is still basic, it can be developed to be more attractive, but still has to adjust the purpose of using the system.
Ensemble Learning Using KNN and Decision Tree for Virus Infection Classification in Mouse Study Dataset Wahyu Murdiyanto, Aris; Tarigan, Thomas Edyson; Zein, Hamada
International Journal of Artificial Intelligence in Medical Issues Vol. 3 No. 1 (2025): International Journal of Artificial Intelligence in Medical Issues
Publisher : Yocto Brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijaimi.v3i1.359

Abstract

In this study, we propose an ensemble learning approach to classify viral infection presence in mice using the Mouse Viral Infection Study Dataset. The dataset includes two numerical features—volumes of two administered medications—and a binary label indicating viral presence. To improve prediction performance, we combined K-Nearest Neighbor (KNN) and Decision Tree (DT) classifiers within a soft voting ensemble framework. Standardization was applied as a preprocessing step to ensure fair feature contribution, especially for the distance-sensitive KNN. The ensemble model underwent hyperparameter optimization using GridSearchCV with 5-fold cross-validation to fine-tune the number of neighbors for KNN and depth-related parameters for DT. The experimental results demonstrated that the ensemble classifier achieved perfect performance, with 100% accuracy, precision, recall, and F1-score on the test set. The confusion matrix showed no misclassifications, and the Receiver Operating Characteristic (ROC) curve achieved an Area Under Curve (AUC) of 1.00, indicating excellent separability between classes. These results suggest that the proposed ensemble effectively leverages the strengths of both KNN and DT, making it suitable for biomedical classification tasks where interpretability and reliability are critical. Although the model performed exceptionally well, the simplicity of the dataset, including balanced classes and clear feature boundaries, may have contributed to the ideal performance. Thus, while the findings are promising, further validation is necessary using more complex or noisy datasets. This study contributes a practical, interpretable, and effective ensemble learning framework for binary classification problems in experimental virology, and opens pathways for further research in preclinical biomedical data analytics using hybrid classification systems.
Co-Authors Abdul Rahim Achmad Farid Adia Lestari Admojo, Fadhila Tangguh Angriani, Husni Any Sawheri Gading Arbansyah Ari Ahmad Dhani Aris Wahyu Murdiyanto Aulia Khofifah Syamsuri Azdy, Rezania Agramanist Azelina Zahra Riadini B, Isdayani Bima Satria Bobi Zinaidin Zidan Bulan Suci Cahayawati Dian Hafidh Zulfikar Effan Najwaini Erfan Tongalu Fajri Harits Muzaki Faldy Alfareza Pambudi Farhan Akbar Febri Ananda Chairi Ferdi Iwanda Fitriyati Agustina Hery Kurniawan Highness Mailani Putri Ilhan Firanda izmy alwiah musdar Jimmy H Moedjahedy Joni Saputra Khusnul Khotimah Kusrini Kusrini Kusrini, Kusrini Lidya Sari Lilis Sagita M. Syukri Mustafa Manda Rela Istiantoko Maria, ⁠⁠Eny Melisa Nur Aini Muhamad Wahyu Tirta Muhammad Aditya Pratama Muhammad Fariz Ijlal Rafi Muhammad Khumaidi Nursyarif Muhammad Taufiq Sumadi Mukminatul Munawaroh Naswin, Ahmad Novia Hidayati Ramadhani Poetro, Bagus Satrio Waluyo Prasetio, Dimaz Arno Priyambada, Galih Radhitya, Made Leo Raenald Syaputra Raihan Nabil Reyka Luna Karalo Ridha Anisa Soldzu Parnga Ririn Wahyuni Rita Yulfani Rudi Setiawan Seftiani Nur Sigiet Haryo Pranoto Sinra, A. Siti Muawwanah Siti Patimah Siti Puspita Hida Sakti MZ Sri Mar’ati Sholikhah Sulistyowati Sulistyowati Supriatin Supriatin Tarigan, Thomas Edyson Taruk, Medi Tri Wahyudi Vito Junivan Rivaldo