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All Journal Efisiensi : Kajian Ilmu Administrasi Jurnal Ilmu Komputer Jurnal Ilmiah Kursor Telematika SMATIKA Jurnal Informatika Upgris JURNAL MEDIA INFORMATIKA BUDIDARMA InComTech: Jurnal Telekomunikasi dan Komputer JURNAL ILMIAH INFORMATIKA JCES (Journal of Character Education Society) SINTECH (Science and Information Technology) Journal Martabe : Jurnal Pengabdian Kepada Masyarakat JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Tekno Insentif IJISTECH (International Journal Of Information System & Technology) The IJICS (International Journal of Informatics and Computer Science) JUTEKIN (Jurnal Manajemen Informatika) JUMANJI (Jurnal Masyarakat Informatika Unjani) KOMPUTIKA - Jurnal Sistem Komputer Jurnal Manajemen Informatika Jurnal Sistem Cerdas Jurnal Tekno Kompak MULTINETICS Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JISKa (Jurnal Informatika Sunan Kalijaga) bit-Tech Dinasti International Journal of Education Management and Social Science Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika JATI (Jurnal Mahasiswa Teknik Informatika) Dharma Raflesia : Jurnal Ilmiah Pengembangan dan Penerapan IPTEKS Journal of Computer System and Informatics (JoSYC) JIKA (Jurnal Informatika) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Merpati JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Algoritma JOMLAI: Journal of Machine Learning and Artificial Intelligence Malcom: Indonesian Journal of Machine Learning and Computer Science Competitive Jurnal Informatika: Jurnal Pengembangan IT Jurnal Ilmiah Sistem Informasi The Indonesian Journal of Computer Science JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Smatika Jurnal : STIKI Informatika Jurnal
Prianto, Cahyo
Universitas Logistik Dan Bisnis Internasional
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Transportation Other

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Prediksi harga FCPO Bursa Malaysia Menggunakan Support Vector Regression Berbasis Particle Swarm Optimization: FCPO Malaysia Stock Exchange Price Prediction Using Particle Swarm Optimization-Based Support Vector Regression Fatwa Fatahillah Fatah; Roni Andarsyah; Cahyo Prianto
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 3 (2026): MALCOM July 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i3.2257

Abstract

Crude Palm Oil (CPO) merupakan komoditas minyak nabati strategis yang harganya dipengaruhi oleh dinamika penawaran dan permintaan global serta kebijakan perdagangan. Fluktuasi yang cepat dan sulit diprediksi ini berdampak pada seluruh rantai pasok dari petani hingga industri pengolahan dan pembuat kebijakan, sehingga dibutuhkan model prediksi yang akurat dan adaptif berbasis sinyal pasar harian. Penelitian ini membangun model Support Vector Regression (SVR) yang ditingkatkan menggunakan Particle Swarm Optimization (PSO), serta membandingkannya dengan SVR tanpa optimasi. Data yang digunakan dalam penelitian ini meliputi informasi harga harian minyak sawit (FCPO) di BURSA Malaysia Derivatives dari tahun 2020 hingga 2025. Hasil menunjukkan PSO menemukan konfigurasi yang efektif, dengan biaya minimum MSE = 0,018675, dan PSO-SVR melampaui SVR default, baik secara visual maupun secara metrik. Pada skala asli diperoleh MAE = 83,939, MAPE = 1,84%, RMSE = 119,881, dan R² = 0,9818. Hasil ini menunjukkan bahwa PSO-SVR mampu meningkatkan kinerja prediksi dibandingkan dengan SVR standar. Namun, nilai R² yang sangat tinggi perlu diinterpretasikan secara hati-hati mengingat karakteristik harga CPO yang volatil serta potensi risiko overfitting. Dengan demikian, PSO-SVR dapat dipertimbangkan sebagai pendekatan pendukung untuk prediksi harga CPO berbasis data pasar harian, dengan tetap memerlukan validasi berkala sebelum diterapkan dalam pengambilan keputusan operasional.
Web-Based Qr-Code System In The Library Data Processing Process At State Senior High School 1 Bangkinang City Khairyzal Khairyzal; Cahyo Prianto
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 9 No. 1 (2026): Jurnal Teknologi dan Open Source, June 2026
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v9i1.5316

Abstract

The school library plays an important role in supporting the learning process. However, the library data processing at SMA Negeri 1 Bangkinang Kota is still conducted manually, which may lead to problems such as data recording errors, slow services, and difficulties in generating reports. Therefore, an information system is needed to improve the effectiveness and efficiency of library data management. This study aims to design and develop a Web-Based Library Information System integrated with QR-Code technology. The system is designed to manage book data, member data, borrowing and returning transactions, and automated report generation. The system development method used in this study is the Waterfall method, which consists of requirements analysis, system design, implementation, testing, and maintenance stages. The result of this study is a web-based library application that is able to accelerate transaction processes through the use of QR-Code technology, reduce data input errors, and facilitate librarians in managing and generating library reports. Based on the results of testing using the Black Box Testing method, the developed system operates according to functional requirements and can be implemented as a solution to improve the quality of library services at SMA Negeri 1 Bangkinang Kota.
Model Switching Hybrid Untuk Menangani User dan Item Cold-Start Muhammad Ilman Aqilaa; Muhammad Yusril Helmi Setyawan; Cahyo Prianto
Jurnal Teknik Informatika dan Sistem Informasi Vol 12 No 1 (2026): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v12i1.12779

Abstract

Recommender systems face significant challenges under cold-start conditions, where information about users or items is still limited. This study proposes a hybrid switching approach that adaptively combines Content-Based Filtering (CBF), User-Based Collaborative Filtering (CF), and Item-Based CF based on the number of user and item interactions. The evaluation was conducted through cold-start scenario testing for a single user, accuracy measurement using RMSE and MAE with 5-Fold Cross-Validation, and adaptivity testing under varying levels of cold-start conditions (5%, 20%, and 50%). Experimental results show that the hybrid model effectively handles all cold-start scenarios by falling back to CBF or CF User-Based when data is insufficient, and opting for CF Item-Based when sufficient information is available. The model achieved the best performance with an average RMSE of 0.8165 and MAE of 0.6592, along with low standard deviations, indicating stable performance across folds. Furthermore, the hybrid system demonstrated dynamic adaptability to data completeness levels, with a gradual shift in fallback algorithm usage as cold-start severity increased. Therefore, the hybrid switching approach not only excels in accuracy but also offers flexibility and robustness, making it an effective solution for improving the quality of recommender systems in scenarios with incomplete data.
Model Prediksi Risiko Kanker Serviks dengan Pendekatan Support Vector Machine Juwita Stefany Hutapea; Nisa Hanum Harani; Cahyo Prianto
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 11 No. 1 (2026): January 2026
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.5445

Abstract

Cervical cancer is one of the leading causes of death in women, especially in developing countries due to delays in early diagnosis. Developing a risk prediction model based on the Support Vector Machine (SVM) algorithm is one way to support a more accurate and efficient early detection process. The research object is medical records of female patients obtained from hospitals in Medan City, with a total of 164 patient data. The development process was carried out through the CRISP-DM stages, which include data cleaning, feature transformation, class balancing with SMOTE, and dimensionality reduction using PCA. The evaluation results showed that the best model was obtained with a PCA configuration with 9 principal components (90% variance) and a test size of 80:20, resulting in an accuracy of 88%, a precision of 88%, a recall of 84%, and an F1-score of 86%. Cross-validation evaluation with 5 folds provided the best average performance and the smallest standard deviation, indicating model stability. The final model was implemented in a web-based system to facilitate digital early detection. This study shows that SVM with the SMOTE and PCA approaches is effective in predicting cervical cancer risk accurately and efficiently.
Co-Authors Adiningrum, Nur Tri Ramadhanti Adiningrum, Nur Tri Ramadhanti Al Novianti Ramadhani Sulaksono Al Novianti Ramadhani Sulaksono Alfadian Owen Amalia, Fahriza Rizky Aminuyati Andarsyah, Roni Andi Tenri Wali Andri Fajar Sunandhar Arjun Yuda Firwanda Azzahra, Fedhira Syaila Putri Burhanudin Zuhri Dellavianti Nishfi Ilmiah Huda Dian Markuci Fahira Fahira Fatwa Fatahillah Fatah Fedhira Fikri Aldi Nugraha Firwanda, Arjun Yuda Habib Abdul Rasyid Hanna Theresia Siregar Hanum, Nisa Harani, Nisa Hanum Harun Ar-Rasyid Helmi Azhar Hutabarat, Rizkyria Angelina Pandapotan Ilyas Tri Khaqiqi, M Indra Firmansyah Juwita Stefany Hutapea Kamaluddin, Rendy Kezia Tirza Naramessakh Kezia Tirza Naramessakh Khairyzal Khairyzal Kishendrian, Hanan M Ilyas Tri Khaqiqi Mariana Rospilinda Siki Markuci, Dian Mohamad Nurkamal Fauzan Mohamad Nurkamal Fauzan Mubassiran Mubassiran, Mubassiran Muh Kusnadi Muhammad Ibnu Choldun Muhammad Ilman Aqilaa Muhammad Nazhim Maulana Muhammad Rifqi Daffa Ulhaq Muhammad Yusril Helmi Setyawan Muhammad Yusril Helmi Setyawan Muhammad Yusuf, Hadi Nawaf Naofal Nico Ekklesia Sembiring Nisa Hanum Nisa Hanum Harani Nisa Hanum Harani Nisa Hanum Harani Nisa Hanum Harani Nisa Hanum Harani Nisa Hanum Harani Nisa Hanum Harani Nurkamal Fauzan, Mohamad Nurul Izza Hamka Nurul Izza Hamka Nurul Lutfiasih Oktaviami Manullang Oktaviami Manullang Pertiwi, Aryka Anisa Rahayu, Woro Isti Rd Nuraini Rd.Nuraeni Siti Fatonah Riza, Noviana Rolly Maulana Awangga Rolly Maulana Awangga, Rolly Maulana Roni Andarsyah Roni Andarsyah Roni Andarsyah Roni Andarsyah Roni Andarsyah Rukmi Juwita Setiadi, Hilman Setyawan, Muhammad Yusril Helmi Shinta Amelia Shinta Amelia Sulaksono, Al Novianti Ramadhani Supriady, Supriady Syafrial Fachri Pane Syafrial Fachri Pane Syafrial Fachri Pane, Syafrial Fachri Syahra, anita alfi Vegita, Yola Zian Asti Dwiyanti Zuhri, Burhanudin