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All Journal Jurnal Sarjana Teknik Informatika Desimal: Jurnal Matematika BERDAYA: Jurnal Pendidikan dan Pengabdian Kepada Masyarakat InPrime: Indonesian Journal Of Pure And Applied Mathematics Jurnal Ilmiah Matematika Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi MATHunesa: Jurnal Ilmiah Matematika Smart Society: Community Service and Empowerment Journal MDP Student Conference Indonesian Journal of Applied Mathematics Jurnal Pengabdian Masyarakat Terapan Jurnal Ilmiah Teknologi dan Komputer (JITTER)
Christyan Tamaro Nadeak
Data Science Study Program, Sumatra Institute Of Technology
Humanities 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 Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Klasifikasi Multikelas Varietas Kacang Kering Menggunakan Metode Hybrid SVM Berbasis DAG Dinda Nababan; Christyan Tamaro Nadeak; Linda Rassiyanti; Fajri Farid
MDP Student Conference Vol 5 No 2 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i2.14094

Abstract

This study analyzes the performance of three conventional SVM strategies, namely One-vs-One (OvO), One-vs-Rest (OvR), and Directed Acyclic Graph OvO (DAG-OvO), compared with the hybrid approach Directed Acyclic Graph Rest-vs-Rest (DAG-RvR) in the context of multiclass classification using the Dry Bean Dataset. All models are evaluated based on accuracy and macro metrics to measure the consistency of predictions between classes. The results show that both conventional and hybrid methods achieve the same high level of accuracy, namely 0.92, with Precision, Recall, and F1-score Macro values ​​that were also identical between approaches. The main difference between the approaches lies in computational efficiency. OvO and DAG-OvO show the fastest training time, while DAG-RvR is the most efficient method in the inference stage. These findings confirm that the hybrid DAG-RvR structure can accelerate the prediction process without compromising accuracy, making it worthy of consideration for applications that require fast inference.
Klasifikasi Multikelas Support Vector Machine dengan Hibrida Directed Acyclic Graph One Vs One dan Rest Vs Rest pada Klasifikasi Tingkat Obesitas Daffa Ahmad Naufal; Christyan Tamaro Nadeak; Linda Rassiyanti; Fajri Farid
MDP Student Conference Vol 5 No 2 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i2.14097

Abstract

This research is focused on analyzing how well different multiclass Support Vector Machine (SVM) classification methods can predict obesity levels. It also presents a new hybrid Directed Acyclic Graph Rest-vs-Rest (DAG-RvR) method as a better option. The study utilizes a dataset called the Obesity Risk Prediction Cleaned, which has information on seven different obesity categories. The methods being assessed include One-vs-One (OvO), One-vs-Rest (OvR), DAG-One-vs-One (DAG-OvO), and the new DAG-RvR method. For fine-tuning the parameters, GridSearchCV and the RBF kernel were used. The findings reveal that DAG-RvR achieves an accuracy of 0.91, which is similar to OvO and DAG-OvO, but it trains much quicker, taking just 0.3422 seconds. Even though its precision, recall, and F1-score are a bit lower than the pairwise methods, DAG-RvR still maintains reliable multiclass performance. In summary, this method strikes a good balance between achieving high accuracy and being efficient in computations.
Klasifikasi Varietas Beras Menggunakan Hybrid SVM Berbasis DAG–OVO dan RVR Marleta Cornelia Leander; Christyan Tamaro Nadeak; Linda Rassiyanti; Fajri Farid
MDP Student Conference Vol 5 No 2 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i2.14108

Abstract

This research proposes a hybrid Support Vector Machine (SVM) strategy for multiclass rice variety classification by combining Directed Acyclic Graph Rest-vs-Rest (DAG-RvR) with K-Means clustering. Five rice varieties were analyzed using 16 morphological and texture features extracted from the Rice Image Dataset. Three conventional SVM methods—One-vs-One (OvO), One-vs-Rest (OvR), and DAG-OvO—were evaluated as baselines. Two hybrid schemes were then developed: DAG-RvR K-Means–OvO and DAG-RvR K-Means–K-Means. Experimental results show that all methods achieve high accuracy of approximately 99%, indicating strong feature separability among rice varieties. However, the proposed DAG-RvR K-Means–OvO provides the most efficient performance, achieving the fastest training time while maintaining competitive testing speed and the highest accuracy of 0.99040. The findings demonstrate that integrating K-Means–based class partitioning with pairwise SVM classification improves computational efficiency without reducing predictive performance, making the hybrid approach suitable for fast and accurate multiclass classification tasks.
PELABELAN TOTAL (A,D)-SISI ANTIAJAIB SUPER PADA GRAF G + K_1 Christyan Tamaro Nadeak
MATHunesa: Jurnal Ilmiah Matematika Vol. 13 No. 02 (2025)
Publisher : Universitas Negeri Surabaya

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

Abstract

Let be a graph of order and size . A bijection is called -edge antimagic total labeling if the set of edge weight forms an arithmetic sequence with initial term a and difference d, or equals to the set . An -edge antimagic total labeling is called super -edge antimagic total labeling if the labelling of the vertex set is This study discuss a super -edge antimagic total labeling for graph .
Analisis Jaringan Sosial Pengguna Perpustakaan Institut Teknologi Sumatera Berbasis Peminjaman Buku menggunakan Algoritma Leiden Christyan Tamaro Nadeak
MATHunesa: Jurnal Ilmiah Matematika Vol. 13 No. 03 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v13n3.p307-313

Abstract

This study analyzes the interaction patterns between users of the Sumatra Institute of Technology (ITERA) Library through book borrowing data with a Social Network Analysis approach. A bipartite network was formed to describe the relationship between borrowers and books, then projected into two unipartite networks: the network between borrowers and between books. The network structure was analyzed using three centrality parameters, namely degree centrality, closeness, and relatedness. Community detection was performed using the Leiden algorithm, and community structure evaluation using the modularity metric. The results show a modularity value of 0.6646 in the borrower network and 0.6776 in the book network, indicating a strong community structure. These findings can be used to provide an overview of student reading tendencies in ITERA Library and a user behavior-based book recommendation system in higher education libraries.
Deteksi Komunitas Pasar Saham IHSG dengan Metode Hybrid Jaringan Kompleks dan Algoritma Leiden Christyan Tamaro Nadeak
MATHunesa: Jurnal Ilmiah Matematika Vol. 13 No. 03 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v13n3.p299-306

Abstract

The stock market is a complex system, with relationships between stocks that influence each other and form a dynamic network. In Indonesia, the Jakarta Composite Index (JCI) reflects the movement of the stock market as a whole. This study aims to detect the community structure of stocks in the JCI by sector using a hybrid approach that combines Random Matrix Theory (RMT), Complex Network (CN), and Leiden algorithm. The data used is the daily closing price of stocks in the JCI during the period January 2014 to January 2024. The methods applied include the formation of a correlation matrix between stocks, noise filtering using RMT, and community analysis using the Leiden algorithm. A multi-threshold correlation approach (0.7; 0.8; and 0.9) was used to evaluate the strength of the relationship between sectors. The results show that the combination of RMT, CN, and Leiden algorithm is effective in identifying stock communities with significant relationships. A higher correlation threshold results in a more stable community with a maximum modularity value of 0.72 at a threshold of 0.9. This approach makes an important contribution in understanding cross-sector interactions in the JCI stock market.
Workshop Pembuatan Sistem Monitoring Jaringan Sederhana Menggunakan Python bagi Siswa SMKN 4 Bandar Lampung M. Syamsuddin Wisnubroto; Yuliana Yuliana; Linda Rassiyanti; Ade Lailani; Fajri Farid; Christyan Tamaro Nadeak; Fitri Nurjanah; Indah Suciati; Rian Kurnia; Yusni Puspha Lestari; Dewi Indra Setiawan
BERDAYA: Jurnal Pendidikan dan Pengabdian Kepada Masyarakat Vol. 8 No. 2 (2026)
Publisher : LPMP Imperium

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36407/berdaya.v8i2.1810

Abstract

This community service program was conducted to strengthen vocational students' competencies in network monitoring using Python. The partner school's main challenge was that networking lessons were still centered on hardware-oriented tools such as Mikrotik and Cisco, while software-based monitoring skills had not been introduced systematically. The program took the form of a workshop at SMKN 4 Bandar Lampung on 24 September 2025 and combined short lectures, demonstrations, guided practice, and mini projects. The training module covered basic networking concepts, connectivity and server status, bandwidth and latency, Python fundamentals, and the use of requests, psutil, socket, subprocess, and pandas to build a simple network monitoring system. Evaluation was conducted descriptively using pre-tests, post-tests, and practical assessment. The results showed that the mean pre-test accuracy of 46% from 32 participants increased to 64% in the post-test completed, representing an 18 percentage-point gain. All students also completed the assigned Python-based monitoring practice successfully. The outputs included a training module, poster, short video, and press release to support sustainability and dissemination.
Pengenalan dan Implementasi Sistem Smart Lighting Berbasis IoT melalui Aplikasi App Inventor sebagai Media Edukasi Teknologi bagi Siswa SMA Vidia Vidia; Ronal Ronal; Fajri Farid; Rohmi Dyah Astuti; Christyan Tamaro Nadeak; Rizki Yustisia Sari; Sofyan Fauzi Dzaki Arif; Eggi Satria; Randa Andriana Putra; Danang Hilal Kurniawan
Jurnal Pengabdian Masyarakat Terapan Vol 2 No 3 (2025): JUPITER Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jupiter.2.3.83

Abstract

Internet of Things (IoT), sebagai konsep penghubung perangkat fisik melalui internet secara otomatis, membuka peluang signifikan untuk peningkatan efisiensi dan produktivitas di berbagai sektor. Meskipun relevansinya tinggi, literasi digital di kalangan pelajar masih terbatas. Untuk mengetasi kesenjangan ini dan meningkatkan pemberdayaan siswa, kegiatan pengabdian masyarakat ini dilaksanakan selama satu hari di SMA Al Huda Jati Agung, bekerja sama dengan Kepala Sekolah dan guru. Kegiatan ini berfokus pada pengenalan dan demonstrasi implementasi sederhana teknologi IoT pada konsep Smart Lighting menggunakan App Inventor. Metode yang digunakan adalah presentasi interaktif diikuti demonstrasi langsung perangkat. Dampak kegiatan dievaluasi melalui Pre-test dan Post-test, yang secara statistik (Uji Paired Sample T-Test, ) menunjukkan peningkatan signifikan pemahaman siswa, dengan rata-rata kenaikan skor sebesar 14%. Keberhasilan ini tidak hanya menumbuhkan minat, tetapi secara efektif meletakkan dasar bagi pengembangan keterampilan digital siswa, berkontribusi pada kesiapan mereka menghadapi tantangan era digital, dan mendukung keberlanjutan pemanfaatan teknologi untuk solusi kehidupan sehari-hari.
Co-Authors Ade Lailani Ade Lailani Daffa Ahmad Naufal Danang Hilal Kurniawan Dewi Indra Setiawan Dinda Nababan Eggi Satria Fajri Farid Fajri Farid Fajri Farid Fajri Farid Farid, Fajri Fitri Nurjanah Indah Suciati Linda Rassiyanti Linda Rassiyanti Linda Rassiyanti Luluk Muthoharoh M. Syamsuddin Wisnubroto Marleta Cornelia Leander Mika Alvionita Sitinjak Putri, Lutfia Aisyah Randa Andriana Putra Rassiyanti, Linda Rian Kurnia Rizki Yustisia Sari Rohmi Dyah Astuti Rohmi Dyah Astuti Ronal Ronal Siahaan, Arielva Simon Sihombing, Natanael Oktavianus Partahan Sofyan Fauzi Dzaki Arif Surya, Annisa Cahyani Tirta Setiawan Vidia Vidia Yuliana Yuliana Yusni Puspha Lestari