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All Journal (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana Jurnal Sistem dan Informatika Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Teknologi Dan Sistem Informasi Bisnis MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA
I Gede Teguh Satya Dharma
Politeknik Negeri Bali
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering

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Penemuan Pola Pengunjung Poliklinik Menggunakan Algoritma Apriori Dharma, Teguh Satya; Suhartana, I Ketut Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 2 (2020): JELIKU Volume 9 No 2, November 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v09.i02.p09

Abstract

Living in an information era, the presence of data is super important. With the data exponentially grows from decades to decades, it reflect the old saying that people today are so rich with data yet so poor on information. To dissect the information that contained within the large amount of data, a method is introduced called “Data Mining.” Data mining is a process of retriving a unique, unseen, and valuable information/insight from the data. Data mining comes with a lot of methods branches, one of those is pattern analysis, or also known as “Association Rules”. With the help of Association Rules, people can discover the relational pattern within the data, so people can make the best decision on the period of time. In this study, the writer is implementing Apriori Algorithm (one of the Association Rules algorithm) to see the pattern of a polyclinic visitor.
Lightweight CNN with wavelet-attention for fingerprint liveness detection Dharma, I Gede Teguh Satya; Astari, Ni Made Ayu Juli
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 15 No. 1 (2025): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v15i1.40-49

Abstract

Fingerprint authentication has been extensively employed as a biometric method in diverse applications, including smartphones and embedded systems. Despite its advantages, this technology is susceptible to spoofing attacks using materials such as gelatin, posing a significant security risk. Numerous solutions have been proposed, but deep learning-based approaches often face challenges due to their large model sizes, limiting deployment in resource-constrained environments. To address this issue, we developed a lightweight and efficient fingerprint liveness detection model by integrating wavelet-attention with inverted-bottleneck convolution. The proposed method balances computational efficiency with high accuracy, enabling its practical implementation on low-resource devices.The model was designed with only 874,000 parameters and a memory footprint of 4 MB, representing a significant reduction in size compared to conventional deep learning models. The use of wavelet-attention enhances feature extraction by focusing on multi-scale spatial details crucial for distinguishing live and spoof fingerprints. Extensive experiments were conducted on the LivDet dataset and a custom dataset, encompassing fingerprints captured from multiple sensors.The results demonstrated robust performance, achieving an average classification error (ACE) of 2.27 across various sensors, which is competitive with state-of-the-art methods. Additionally, the model exhibited consistent performance in scenarios with limited computational resources, highlighting its efficiency and scalability.These findings suggest that the proposed approach is a viable solution for enhancing the reliability of fingerprint liveness detection, particularly in applications requiring lightweight and resource-efficient models.
Implementasi Metode Agile untuk Meningkatkan Efisiensi Pengembangan Sistem Informasi Tabungan Koperasi Made Pradnyana Ambara; I Gede Teguh Satya Dharma; I Nyoman Suraja Antarajaya
Jurnal Sistem dan Informatika (JSI) Vol 19 No 1 (2025): Jurnal Sistem dan Informatika (JSI)
Publisher : Direktorat Penelitian,Pengabdian Masyarakat dan HKI - Institut Teknologi dan Bisnis (ITB) STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/jsi.v19i1.687

Abstract

Koperasi Simpan Pinjam (KSP) memiliki peran vital dalam memperluas akses layanan keuangan masyarakat Indonesia. Namun, sistem pencatatan manual yang masih banyak digunakan menyebabkan berbagai kendala, seperti rendahnya efisiensi operasional dan tingginya risiko kesalahan pencatatan. Penelitian ini bertujuan untuk mengembangkan Sistem Informasi Tabungan (SIT) dengan pendekatan metodologi Agile, yang memungkinkan tim pengembang merespons kebutuhan pengguna secara cepat dan fleksibel. Sistem ini dibangun menggunakan framework CodeIgniter dengan arsitektur Model-ViewController (MVC) dan memanfaatkan Bootstrap guna menghasilkan antarmuka yang responsif dan mudah digunakan. Evaluasi dilakukan melalui pengujian waktu pemrosesan, validasi fungsional menggunakan black-box testing, serta survei tingkat kepuasan pengguna. Hasil implementasi menunjukkan peningkatan efisiensi sebesar 72%, dengan waktu rata-rata 22,7 detik untuk transaksi dan 68,9 detik untuk pembuatan laporan bulanan. Pengujian fungsional terhadap lima modul utama mencatat tingkat akurasi 100%, sementara survei terhadap 45 pengguna menunjukkan skor kepuasan rata-rata 4,8 dari 5, berkat fitur pelacakan transaksi secara real-time yang meningkatkan transparansi.
Implementasi PPID Dalam Mendukung Transparansi Informasi di Politeknik Pariwisata Bali Wijaya, I Wayan Rizky; Gunawan, I Made Agus Oka; Dharma, I Gede Teguh Satya
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 4 (2025): Oktober 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i4.2244

Abstract

As a vocational higher education institution in the field of tourism, Politeknik Pariwisata Bali has an obligation to provide the public with access to information that is easy, fast, and accountable. This study discusses the implementation of the Public Information and Documentation Officer (PPID) as the main instrument to support information transparency at Politeknik Pariwisata Bali. The system was developed using the Waterfall method with PHP as the programming language and MySQL as the database. The testing process was carried out using the blackbox testing method to ensure that each system function operates as required. The implementation results show that the developed PPID system is capable of providing services for information requests, complaints, and public aspirations in a more effective and integrated manner.
Perbandingan Weighted Product Dengan AHP+WP Dalam Penentuan Pegawai Berprestasi Di Universitas XYZ Gunawan, I Made Agus Oka; Wijaya, I Wayan Rizky; Dharma, I Gede Teguh Satya
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025 (Naskah Accepted)
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3067

Abstract

The selection of outstanding employees is an important aspect of human resource management in higher education, requiring objective and accurate evaluation. This study compares two multi-criteria decision-making methods: Weighted Product (WP) and a combination of Analytic Hierarchy Process with WP (AHP+WP) in ranking high-performing staff at XYZ University. The evaluation uses Mean Absolute Percentage Error (MAPE) to measure the closeness of the method’s results to expert-based manual assessments. WP produced a MAPE of 16.86%, while AHP+WP yielded only 9.17%, indicating higher accuracy. The Wilcoxon signed-rank test resulted in a p-value of 0.0002 (< 0.05), indicating a significant difference. AHP+WP is superior due to its systematic and consistent weighting mechanism, compared to the more subjective WP. These findings align with previous studies recommending hybrid methods. AHP+WP is considered more appropriate for official implementation in employee performance assessment systems to support fair, transparent, and data-driven evaluation.Kata kunci: AHP; Weighted Product; outstanding employee; MAPE; Wilcoxon.   AbstrakPemilihan pegawai berprestasi merupakan bagian penting dalam manajemen sumber daya manusia di perguruan tinggi, yang memerlukan evaluasi objektif dan akurat. Penelitian ini membandingkan dua metode pengambilan keputusan multikriteria: Weighted Product (WP) dan kombinasi Analytic Hierarchy Process dengan WP (AHP+WP) dalam menentukan peringkat pegawai berprestasi di Universitas XYZ. Evaluasi menggunakan Mean Absolute Percentage Error (MAPE) untuk mengukur kedekatan hasil metode dengan penilaian manual oleh pakar. WP menghasilkan MAPE sebesar 16,86%, sementara AHP+WP hanya 9,17%, menunjukkan akurasi lebih tinggi. Uji Wilcoxon signed-rank memberikan nilai p = 0,0002 (< 0,05), mengindikasikan perbedaan signifikan. AHP+WP unggul karena mekanisme pembobotannya yang sistematis dan konsisten, dibandingkan WP yang lebih subjektif. Temuan ini sejalan dengan studi sebelumnya yang merekomendasikan metode hybrid. AHP+WP dinilai lebih layak untuk diimplementasikan secara resmi dalam sistem penilaian pegawai berprestasi, guna mendukung evaluasi kinerja yang adil, transparan, dan berbasis data. 
Weighted ANOVA and Mutual Information for Enhanced Intrusion Detection System I Gede Teguh Satya Dharma; I Wayan Rizky Wijaya; I Made Agus Oka Gunawan; Made Pradnyana Ambara
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 1, February 2026 (Article in Progress)
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i1.2448

Abstract

The rapid escalation in the sophistication of network attacks has exposed the limitations of traditional Intrusion Detection Systems (IDS). While machine learning has shown great promise in enhancing IDS performance, its success often hinges on the effectiveness of feature selection. Standard feature selection techniques, however, struggle in cybersecurity applications due to the highly imbalanced nature of network traffic datasets. In such settings, minority attack classes, though critical, are often overshadowed by majority classes, leading to reduced detection of rare intrusions. To address this challenge, we propose a hybrid feature selection framework that integrates Analysis of Variance (ANOVA) and Mutual Information (MI) with a novel class-frequency weighting mechanism. This weighting scheme adjusts the relevance score of each feature according to the distribution of classes, ensuring that features associated with rare attacks are more strongly emphasized during the selection process. We evaluate our method on the UNSW-NB15 dataset using a Support Vector Machine classifier. The results show that our approach achieves substantial gains in recall for underrepresented classes while simultaneously reducing feature dimensionality and maintaining efficiency. By improving the visibility of features tied to minority attacks, the proposed framework provides a more balanced and reliable solution for modern IDS. This contribution advances the detection of rare but impactful threats and highlights a scalable pathway for building more resilient cybersecurity defenses.
Co-Authors Astari, Ni Made Ayu Juli I Ketut Gede Suhartana I Made Agus Oka Gunawan I Nyoman Suraja Antarajaya I Wayan Rizky Wijaya Made Pradnyana Ambara, Made Pradnyana Wijaya, I Wayan Rizky