Article Per Year (5 Year)
p-Index From 2020 - 2025
3.146
P-Index
This Author published in this journals
All Journal PROSIDING SEMINAR NASIONAL Jurnal Ilmiah Mahasiswa FEB Jurnal sistem informasi, Teknologi informasi dan komputer Al-Jami'ah: Journal of Islamic Studies Nurani: Jurnal Kajian Syariah dan Masyarakat Edu Geography Format : Jurnal Imiah Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Khasanah Ilmu - Jurnal Pariwisata Dan Budaya IJISTECH (International Journal Of Information System & Technology) Jambura Journal of Educational Chemistry International Journal of Visual and Performing Arts Jurnal Ilmu Teknik dan Komputer Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Jurnal Abdidas Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences IJISTECH Masyarakat Indonesia Jurnal Pengabdian Kepada Masyarakat Patikala Jurnal Arsitektur, Sains Bangunan, Kota dan Pemukiman Tuturan: Jurnal Ilmu Komunikasi, Sosial dan Humaniora Jurnal Pengabdian Masyarakat Sultan Indonesia Journal Collabits
Mohamad Yusuf
Unknown Affiliation
Religion Arts Humanities 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 Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

Published : 28 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 28 Documents
Search

 1   2   3 
Penerapan Metode K-Means Untuk Rekomendasi Jenis Produk Barang Perkakas Bagi Pelanggan (Studi Kasus PT.ZXY) Agustianingsih, Putri; Yusuf, Mohamad
Jurnal Ilmu Teknik dan Komputer Vol 9, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jitkom.v9i1.006

Abstract

Penelitian ini membahas penerapan metode K-Means dalam data mining untuk merekomendasikan produk Pekakas kepada pelanggan, dengan studi kasus pada PT.ZXY. Tujuan dari penelitian ini adalah untuk memahami dan memprediksi volume penjualan produk perkakas menggunakan metode K-Means, dengan manfaat membantu perusahaan dalam pengadaan persediaan, perencanaan produksi, dan menyediakan informasi produk yang paling banyak dibeli oleh konsumen. Metode K-Means dipilih karena potensinya dalam menganalisis strategi promosi Perkakas. Studi ini juga mencakup konsep Penemuan Basis Data Pengetahuan (KDD), Indeks Davies Bouldin (DBI), dan RapidMiner. Hasil dari praproses, pemodelan, evaluasi dan penelitian dilakukan untuk memberikan pemahaman yang komprehensif tentang pola penjualan dan potensi perbaikan strategi penjualan alat produk pada PT. PT.ZXY. Oleh karena itu, dapat disimpulkan bahwa K optimal untuk pembentukan klaster terdapat pada percobaan keenam, yaitu nilai K = 3. Nilai ini dipilih karena K =3 menghasilkan nilai DBI terkecil yaitu 0 0.328. Dimana anggota klaster 0 berjumlah 1.389 data, klaster 1 berisi 1 data dan klaster 2 berisi 39 data sehingga totalnya berjumlah 1.429 data.
Utilization of Blockchain Technology for Digital Assets Case Study Makes a Comparison Algorithm for Bitcoin and Etherium Maesaroh, Siti; Mubarak, Roy; Yusuf, Mohamad; Daffa, Raihan Nur
Journal Collabits Vol 2, No 2 (2025)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i2.27189

Abstract

Rise of digital assets, such as cryptocurrencies, has heralded a new era in financial technology, where blockchain technology plays a fundamental role. This study conducts a comparative analysis of the blockchain algorithms underlying two of the most prominent digital assets, Bitcoin and Ethereum, to evaluate their efficacy and applicability in various use cases. Through a detailed examination of the consensus mechanisms, security features, and transaction handling capacities of both blockchains, this paper aims to provide insights into the distinct functionalities and potential scalability of each system. 
Installing the Haiku Operating System on Virtual Box and Implementing File Management Yusuf, Mohamad; Al Fatah, M Reza; Fami, Asrul; Pratama, Vemas Adi; Z, M Fauzan; Syadam, Muhammad
Journal Collabits Vol 2, No 2 (2025)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i2.26054

Abstract

This journal aims to explore the installation process of the Haiku operating system, utilizing VirtualBox and implementing effective file management techniques. Haiku, as an open-source operating system, showcases an innovative user interface and high performance. The study assesses the practicality of Haiku in virtualization through the use of the VirtualBox application. The journal presents step-by-step instructions on installing the Haiku operating system and deploying it within the VirtualBox application. Additionally, it delves into various aspects of file management in the Haiku system, including creation, deletion, and data viewing within files
RANCANG BANGUN APLIKASI MOBILE ANALISIS KESEHATAN KUKU MENGGUNAKAN AI GENERATIF DENGAN ALUR KERJA OTOMATIS Yusuf, Mohamad; Prayuda, Sendy; Indra Lesmana, Bagas; Rayhan Maulana, Jericho; Aditiya, Eka; Alam, Syamsir
Jurnal Sistem Informasi, Teknologi Informatika dan Komputer Vol 15 No 3 (2025): Volume 15 No 3, Mei Tahun 2025
Publisher : Universitas Muhammadiyah Jakarta

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

Abstract

Heatlh conditions can often be detected though external indicators such as fingernails, yet access to rapid expert analysis is frequently a barrier. This research aims to design and build a mobile health application capable of providing automated preliminary analysis of nail conditions using AI techonology. The system integrates a frontend application built with flutter with a backend architecture that utilizes Google Apps Script, Google Sheets as a trigger, and Google Drive for storage. The core functionality relies on an automated workflow built on the n8n platform, which processes user-uploaded nail images through the generative AI model, Google Gemini 1.5 Flash, to produce a visual analysis. The result of this research is a functional and efficient system where users can receive the analysis in the form of an Al-annotated nail image directly on their mobile device. The resulting application was then validated through a series of functional tests to ensure each stage of the automated workflow performed as expected. The testing showed the system successfully processed user input to generate analysis output accurately, thus deeming the application viable for use.
Analysis of the Influence of Learning Strategies on the Academic Achievement of Gen-Z Students with Data Visualization Using Matplotlib in Python Salsabila, Yovi Naila; Lutfansa, Nabila Aulia; Fadiyah, Fitri Nur; Qurotaani, Nazwa Nurul; Safira, Dessi Adelia; Yusuf, Mohamad
Journal Collabits Vol 2, No 1 (2025)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v2i1.28450

Abstract

This research examines the influence of learning strategies on the Grade Point Average (GPA) of Generation Z (Gen- Z) students. The background of this research is to understand how the learning strategies used by Gen-Z students affect their GPA. The research aims to analyze the influence of various learning strategies, identify the most effective ones, and demonstrate the use of the Matplotlib library in Python for data visualization. This research is quantitative in nature using statistical methods to evaluate the results. Data was collected through a questionnaire distributed to students, including the frequency of using learning strategies such as reading books, watching YouTube tutorials, doing practice questions, taking private lessons/online tutoring, and participation in training/seminars/workshops. Data analysis was carried out using Python and the Matplotlib library to visualize the data and provide a clear picture of the effectiveness of the learning strategy implemented. The research results show that active and technology- integrated learning strategies have a significant influence on increasing the academic achievement of Gen-Z students. Specifically, strategies such as watching YouTube tutorials and doing practice questions had a positive correlation with improving students' GPAs. These findings indicate the importance of adapting learning methods that suit the characteristics and learning preferences of Gen-Z students.
Optimizing DBSCAN Parameters for Depth-Based Earthquake Clustering Using Grid Search Rushendra, Rushendra; Wijaya, Ody Octora; Yusuf, Mohamad; Setiyaji, Andri; Prabowo, Djoko
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025 (in progress)
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6521

Abstract

This study addresses the challenge of accurately clustering earthquake events based on depth to better understand seismic activity patterns in Sulawesi from 2019 to 2023. Traditional clustering algorithms often fail to capture the complex spatial and depth-based structures of earthquake data. To overcome this, we employed the DBSCAN algorithm, which is well-suited for identifying irregularly shaped clusters and handling noise in spatial datasets. A key focus of this research is the systematic optimization of DBSCAN’s parameters—epsilon (ε) and minimum samples (min_samples)—using a grid search approach. Epsilon values varied from 0.1 to 0.5, and min_samples ranged from 6 to 60. The optimal parameters, determined using the Calinski-Harabasz (CH) index, were ε = 0.4 and min_samples = 54. Compared with previous heuristic settings, the optimized configuration produced better separated and more interpretable clusters. Using the optimized parameters, nine distinct clusters were identified, capturing meaningful patterns in both depth and magnitude. The results revealed that shallow earthquakes (0–20 km) tend to exhibit greater magnitude variation, with some clusters averaging magnitudes up to 3.7. This suggests a higher seismic hazard potential associated with brittle crustal activity. The findings contribute to seismic hazard analysis by providing a more robust understanding of three-dimensional earthquake distribution, aiding regional risk assessment and disaster preparedness efforts. These insights can support agencies such as BMKG and BPBD in hazard mapping, sensor deployment, and contingency planning for high-risk zones.
Peningkatan Kreativitas Anak dengan Implementasi Augmented Reality Pembelajaran Hewan Berbasis Android Kusmawan, Dicky; Aryani, Diah; Yusuf, Mohamad
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.007

Abstract

This study aims to address challenges in early childhood education, which are often caused by regulations, limited educator readiness, and inadequate interactive learning media. Augmented Reality (AR) technology offers a solution by integrating the virtual and real worlds, enabling children to experience 3D objects immersively using smartphones. The research was conducted at SD Bedahan 01 with third-grade students learning Natural Science (IPA) topics about animals, including their characteristics, classifications, habitats, and benefits. Initial observations showed the average student score was 78, meeting the Minimum Competency Criteria (KKM) but requiring improvement to optimize learning outcomes. To address this, an AR-based learning media application for Android was developed using the Multimedia Development Life Cycle (MDLC) method, integrating 3D visuals, audio, and interactive features to create an engaging and immersive learning experience. The results demonstrated that the use of AR technology increased students’ interest and understanding of the material, as well as their ability to recall and apply concepts. This study highlights the potential of AR as an effective educational tool and contributes to the development of innovative and interactive learning media for elementary education, particularly in subjects requiring visualization. Future research may explore expanding AR features to include gamification and advanced interactivity for broader educational applications.
Evaluation of the Effectiveness of Hybrid Learning Based on Linear Algebraic Hybrid Model in the Online-Offline Lecture System in the Digital Era Ritonga, Andre Meyro; Sulistio, Nicholas; Anggriawan, Guruh Pandhu; Yusuf, Mohamad
Journal Collabits Vol 2, No 2 (2025)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v2i2.32548

Abstract

Optimal class division is a crucial aspect of academic planning to ensure the effectiveness of the learning process. The main challenges in class division lie in the limited capacity of space, balanced distribution of students, and the fulfillment of varied academic needs. This study proposes a Linear Programming-based approach to optimize class division by considering various constraints, such as the maximum capacity of the room, the number of students, and the distribution of subjects according to curriculum needs. The developed applications are designed to produce optimal solutions that minimize student distribution gaps and ensure efficient classroom utilization. A case study is applied to an educational institution to evaluate the performance of the application in real situations. The results of the experiment show that this approach is able to improve the efficiency of classroom allocation, reduce imbalances in the distribution of students, and optimize the use of educational facilities. Thus, this research contributes to more effective and data-based academic management in decision-making related to class division.
Co-Authors Abdul Karim Aditiya, Eka Aditya Rizki Rinaldi Afiyati, Afiyati Agustianingsih, Putri Al Fatah, M Reza Anggriawan, Guruh Pandhu Ansari, Isa Awang, Nungky Budiana, Kelik Carl Sterkens Carl Sterkens Citron S Payu Daffa, Raihan Nur Diah Aryani, Diah Esa Esa Fadiyah, Fitri Nur Fahreza, Muhammad Rizky Fami, Asrul Fernando, Henky Hadi Santoso Indra Lesmana, Bagas Irwan Irwan Kusmawan, Dicky Languju, Indri Kristin Lukman Hakim Lutfansa, Nabila Aulia Moh. Muhrim Tamrin Naimah, Faaza Nia Agustina Prabowo, Djoko Pratama, Vemas Adi Prayuda, Sendy Qurotaani, Nazwa Nurul Ramlani Lina Sinaulan Rayhan Maulana, Jericho Ritonga, Andre Meyro Rushendra, Rushendra Sabily, Inna Safira, Dessi Adelia Salsabila, Yovi Naila Setiyaji, Andri Siti Maesaroh ST. HAISAH Sulistio, Nicholas Suranti, Meliana Syadam, Muhammad Syamsir Alam Tofik Yanuar Chandra Wijaya, Ody Octora Z, M Fauzan