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All Journal International Journal of Electrical and Computer Engineering Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics JUITA : Jurnal Informatika Register: Jurnal Ilmiah Teknologi Sistem Informasi Bulletin of Electrical Engineering and Informatics Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Informatika Jurnal Teknik Komputer AMIK BSI Jurnal Khatulistiwa Informatika Paradigma Ekspektra: Jurnal Bisnis & Manajemen JITK (Jurnal Ilmu Pengetahuan dan Komputer) ILKOM Jurnal Ilmiah MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer SEINASI-KESI International Journal for Educational and Vocational Studies Jurnal Mantik Jurnal Teknik Informatika C.I.T. Medicom Journal of Intelligent Decision Support System (IDSS) Jurnal Bumigora Information Technology (BITe) Akrab Juara : Jurnal Ilmu-ilmu Sosial Jurnal Sistem Informasi IAIC Transactions on Sustainable Digital Innovation (ITSDI) Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Journal Software, Hardware and Information Technology International Journal of Basic and Applied Science Reputasi: Jurnal Rekayasa Perangkat Lunak Jurnal Sains Informatika Terapan (JSIT) INTERNATIONAL JOURNAL OF MECHANICAL COMPUTATIONAL AND MANUFACTURING RESEARCH Paradigma Indonesian Journal Computer Science (ijcs) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi International Journal of Enterprise Modelling International Transactions on Artificial Intelligence (ITALIC) Jurnal Teknoinfo
Mochamad Wahyudi
Universitas Bina Sarana Informatika
Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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Analisis Performa Open Shortest Path First Load Balancing dengan Metode Cost Manipulation Mochamad Wahyudi; Firmansyah Firmansyah
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 21 No. 3 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v21i3.1909

Abstract

Quality of Service (QoS) di dalam sebuah layanan jaringan menjadi faktor terpenting untuk memastikan kapasitas transfer paket data. Salah satunya pemilihan protokol routing yang akan digunakan. Routing Protokol Open Short Path First (OSPF) menggunakan metode Cost Manipulation mampu menjadi sebuah alternatif solusi untuk mamastikan QoS di dalam layanan jaringan dikarenakan metode Cost Manipulation mampu memilih jalan terbaik menuju network tujuan tanpa mempertimbangkan kembali metrik yang seharusnya, baik shortest path ke network tujuan ataupun bandwidth-nya. Hasil pengujian tracerroute sebelum pengimplementasian OSPF cost manipulation didapatkan hanya menggunakan 1 (satu) single line saja dan packet loss yang didapatkan saat terjadinya link failure dengan pengiriman 907 packet data adalah 1,4 packet loss. Sedangkan setelah pengimplementasi OSPF cost manipulation dapat menggunakan 2 (dua) dual line sebagai load balancing dan packet loss yang didapatkan menurun dengan hasil rata-rata sebesar 0,6 packet loss dan pengimplementasian cost manipulation mampu membagi transfer paket data dengan sama rata.
QUANTUM-ASSISTED FEATURE SELECTION FOR IMPROVING PREDICTION MODEL ACCURACY ON LARGE AND IMBALANCED DATASETS Safii, Safii; Wahyudi, Mochamad; Hartama, Dedy
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.7040

Abstract

One of the biggest obstacles to creating precise machine learning models is choosing representative and pertinent characteristics from big, unbalanced datasets. While too many features raise the risk of overfitting and computational expense, class imbalance frequently results in decreased accuracy and bias. The Simulated Annealing technique is used in this study to tackle a Quadratic Unconstrained Binary Optimization (QUBO) problem that is formulated as a quantum-assisted feature selection method to handle these problems. The technique seeks to reduce inter-feature redundancy and the number of selected features. There are 102,487 samples in the majority class and 11,239 in the minority class, totaling 28 characteristics in the experimental dataset. Nine ideal features were found during the feature selection method (12, 14, 15, 22, 23, 24, 25, 27, and 28). Ten-fold cross-validation was used to assess a Random Forest Classifier that was trained using an 80:20 split. With precision, recall, f1-score, and accuracy all hitting 1.00, the suggested QUBO+SMOTE method demonstrated exceptional performance. Comparatively, QUBO without SMOTE performed worse with accuracy 0.95 and minority-class f1-score of only 0.71, whereas a traditional Recursive Feature Elimination (RFE) approach obtained accuracy 0.97 with minority-class f1-score of 0.94. These findings indicate that QUBO can reduce dimensionality and address class imbalance which requires its integration with SMOTE. This study demonstrates how quantum computing can enhance the effectiveness and efficiency of machine learning, especially for large-scale imbalanced datasets
Quantum Computing Approach in K-Medoids Method for AIDS Disease Prediction Using Manhattan Distance Wahyudi, Mochamad; Sintagel br Sianipar, Imeldi; Pujiastuti, Lise; Solikhun, Solikhun; Kurniawan, Deny
ILKOM Jurnal Ilmiah Vol 17, No 1 (2025)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v17i1.2363.44-53

Abstract

Acquired Immunodeficiency Syndrome (AIDS) caused by the Human Immunodeficiency Virus (HIV) is one of the deadliest infectious diseases in the world. Understanding its spread and epidemiological characteristics is crucial for developing and preventing more effective treatments. This study uses the K-Medoids method with a quantum computing approach to predict AIDS based on clinical and demographic data. K-Medoids is chosen to group large amounts of data using a clustering technique that determines the center point (medoid) of each cluster, minimizing the overall distance between data in a cluster. The Manhattan distance is used because it is easier to process data. The quantum computing approach is used to overcome the limitations of classical computing when processing large-scale medical data. This study shows that the application of quantum algorithms to the K-Medoids method allows for faster and more accurate predictions in the diagnosis of AIDS. The tests carried out showed that the prediction accuracy of classical and quantum methods was comparable, namely 85%. The results support the great potential of quantum computing to improve the efficiency of medical predictions. The research involves converting data into quantum format, processing it with the K-Medoids algorithm, and evaluating its performance based on metrics such as intercluster distance and computation time. The research will also identify patterns and risk factor for the spread of AIDS that can be used to develop more effective health interventions. The conclusion of the research is that integrating the K-Medoids techniques can only increase the speed of data processing but also provide competitive accuracy compared to traditional techniques. This research opens up new possibilities in medical data analysis, especially when managing large and complex data sets. The bottom line is that these findings can help make better medical decisions and strategically support AIDS prevention and treatment efforts.
Co-Authors Abdurrachman, Qais Ade Budiman, Ade Adi Supriyatna Akbar, Habibullah Alfiah Khoirunisa Ali Haidir Alpha Ariani, Alpha Andri Amico Atrinawati, Lovinta Happy Azis, Munawar Abdul Azkia, Farah Diba Barreto Jose da Conceição Budiman, Ade Surya Dedi Triyanto Dedi Triyanto Dedi Triyanto Deni Kurniawan, Deni Dennis Gunawan, Dennis DENY KURNIAWAN Deny Kurniawan Dewi, Revinta Arrova Dimas Trianda Doni Purnama Alam Syah, Doni Purnama Dwi Arum Ningtyas Efendi, Syahril Faiz Djarot, Raihan Jamal Fajar Akbar Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Freshtiya Beby Larasati Fristi Riandari Fuad Nur Hasan Ganda Wijaya Ganda Wijaya, Ganda Gerhard-Wilhelm Weber Givan, Bryan Hartama, Dedy Hengki Tamando Sihotang Herman Mawengkang Husain Husain Husain Husain Ihsan Daulay Ikhwan, Subaiki Imam Sutoyo Indra Chaidir, Indra Khoirun Nisa KHOIRUN NISA Kotjek, Rafie Laksono, Andriansyah Tri Lestari Yusuf Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Lise Pujiastuti Merio Hengki Muhammad Safii Muhammad Zarlis Mukhtar, Mukhneri Noviyanto Nurajijah Nurajijah Nurhasanah Halim Oktaviany, Venny Pricillia Pujiastuti , Lise Pujiastuti, Lise Rachmat Adi Purnama Rahmansyah Siregar, Muhammad Rani, Maulidina Cahaya Retno Dwigustini Reynaldi , Reynaldi Rifani Haikal Riska Aryanti Riski Wulandari Rugaiyah Safii Safii Sfenrianto Sfenrianto Sintagel br Sianipar, Imeldi Siregar, Muhammad Rahmansyah Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun, Solikhun Sumanto Sumanto Sunu Sugi Arso Susilawati Susilawati Sutarman Sutarman Syarifah Putri Agustini Tantrisna, Ellen Vinsensia, Desi Vivi Meilinda Wijaya, Filzah Yahya Mara Ardi Yosua Chandra Simamora Yudha, Satria Wira Yuni Eka Achyani, Yuni Eka Zidan, Muhammad