Article Per Year (5 Year)
p-Index From 2021 - 2026
2.447
P-Index
This Author published in this journals
All Journal Jupiter Insect (Informatics and Security) : Jurnal Teknik Informatika Jurnal Abdimas Mandiri JATI (Jurnal Mahasiswa Teknik Informatika) Reswara: Jurnal Pengabdian Kepada Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Nasional Ilmu Komputer Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pengembangan Sistem Informasi dan Informatika Golden Ratio of Mapping Idea and Literature Format Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi Jurnal Software Engineering and Computational Intelligence International Journal of Advances in Artificial Intelligence and Machine Learning
Rudi Heriansyah, Rudi
Unknown Affiliation
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
Implementasi Single Sign-On Menggunakan Protokol Openid Connect (OIDC) Pada Virtual Private Server (VPS) Sahrin, Muhammad Aditya; Heriansyah, Rudi; Sartika, Dewi
Jurnal Nasional Ilmu Komputer Vol. 5 No. 2 (2024): Jurnal Nasional Ilmu Komputer
Publisher : Training and Research Institute Jeramba Ilmu Sukses (TRI - JIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jurnalnik.v5i2.1748

Abstract

Single Sign-On (SSO) is an authentication method that allows users to access multiple website services using one account and one login process. OpenID Connect (OIDC) is a protocol based on OAuth 2.0 and provides user identity information through JWT (JSON Web Token) tokens. Virtual Private Server (VPS) is a service that can be configured according to user needs. Internet users have many accounts needed to access various online services such as email, social media, online shopping, and many more. Each online service usually has a different username and password. Users often find it difficult to remember each password needed. In addition, using the same password on each online service is also not recommended because it can increase security risks. Based on this problem, an SSO system is needed that is useful for helping users in logging in. The SSO system will be tested with two Dummy Students and Dummy Elearning clients using Black Box Testing with the Equivalence Partitioning technique. From the test results, it was obtained that the SSO system showed that 83% of the test scenarios were successfully carried out
Klasifikasi Kinerja Teknisi Pada Pt. Telkom Menggunakan Metode K-Nearest Neighbor Amidhan, Muhammad; Heriansyah, Rudi; Permatasari, Indah
Jurnal Nasional Ilmu Komputer Vol. 4 No. 3 (2023): Jurnal Nasional Ilmu Komputer
Publisher : Training and Research Institute Jeramba Ilmu Sukses (TRI - JIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jurnalnik.v4i3.1751

Abstract

Productivity is expected to support the company's goal of achieving high profits. Technician performance assessment still relies on subjective assessment from the team leader, causing difficulties in objective evaluation. This research aims to improve the appraisal of technician performance at PT Telkom by proposing using the k-nearest Neighbor (k-NN) method as a classification method. The k-NN method was chosen because of its robustness to training data and effectiveness on large training data. The classification process includes finding the distance between two points using the Euclidean equation, sorting the lowest value as the nearest neighbor, calculating the number of neighbors based on the 5 (five) nearest neighbors for the classification of "Dissatisfied", "Quite Satisfied,", "Satisfied", and "Very Satisfied". Based on calculations carried out using a confusion matrix, this algorithm has an accuracy rate of 74%, precision of 80%, and recall of 80%, so it can be recommended to PT Telkom to know the actions to be taken, whether a technician can be retained or not in the company
Pemberdayaan UMKM Kain Tenun Songket dan Kain Jumputan Binaan LPP-PEKKA Yayasan Masjid Agung Palembang untuk Meningkatkan Skala Produksi dan Pewarna Alami S.Si., M.Kom, Dr. Shinta Puspasari,; Setiawan, Herri; Viatra, Aji Windu; Yustini, Tien; Dhamayanti; Heriansyah, Rudi; Alie, Marzuki
Jurnal Abdimas Mandiri Vol. 7 No. 3
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jam.v7i3.3477

Abstract

Program Pembinaan Usaha Mikro Kecil dan Menengah (UMKM) Berbasis Kemitraan ini memiliki tujuan pembinaan, pemberdayaan, dan pemanfaatan bahan alami pewarna bahan kain di LPP-PEKKA Yayasan Masjid Agung Palembang. Program yang dirancang meliputi pelatihan Digital Marketing, Pelatihan Branding dan Packaging Produk, Pelatihan Manajemen Keuangan, dan Pelatihan Ketrampilan Produksi Pewarna Alami yang diikuti oleh 50 peserta UMKM LPP-PEKKA yang merupakan para pengerajin kain jumputan dan kain tenun songket Palembang. Metode pelatihan berupa penyampaian materi oleh narasumber, praktek langsung oleh para peserta, dan evaluasi kegiatan dengan pengisian kuesioner oleh peserta pelatihan. Hasil kegiatan menunjukkan adanya peningkatan pemberdayaan mitra yang mengalami peningkatan pengetahuan terkait materi pelatihan yang diberikan. Skor rata-rata peningkatan pengetahuan peserta sebesar 10%. Capaian luaran kegiatan PkM juga diukur dari peningkatan penerapan Iptek yang mendukung mitra UMKM LPP-PEKKA untuk memasarkan produk secara digital. Program ini diharapkan dapat meningkatkan skala produksi dan pewarna alami kain tenun songket dan kain Jumputan sebagai produk budaya tradisional Palembang sekaligus sebagai usaha untuk pelestarian budaya daerah. Dengan peningkatan pengelolaan keuangan dan peluang pasar produk hasil UMKM melalui pemasaran digital yang mampu menjangkau pasar global diharapkan dapat berdampak pada peningkatan perekonomian anggota UMKM LPP-PEKKA serta kelestarian lingkungan dengan pemanfataan pewarna alami yang ramah lingkungan dan aman bagi masyarakat
Performance Comparison of Adam and SGD Optimizers in Transfer Learning Based CNN for Banana Leaf Disease Classification Mair, Zaid Romegar; Heriansyah, Rudi; Sagala, La Ode Hasnuddin S.
Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi Vol. 5 No. 1 (2026)
Publisher : Department of Informatics Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/snati.v5.i1.43901

Abstract

Banana leaf diseases significantly reduce crop productivity, yet automated detection systems based on deep learning often rely on limited datasets, where training stability and generalization become critical challenges. Although Convolutional Neural Networks (CNNs) have been widely applied for plant disease classification, systematic comparisons of optimization algorithms under small dataset conditions remain limited, particularly for banana leaf disease identification. This study addresses this gap by comparing the performance of Adaptive Moment Estimation (Adam) and Stochastic Gradient Descent (SGD) optimizers within a transfer learning–based CNN framework. Six pre-trained architectures VGG16, VGG19, ResNet50, DenseNet121, MobileNet, and NASNetMobile were evaluated using 1,652 annotated banana leaf images classified into Sigatoka, Cordana, Pestalotiopsis, and healthy leaves. Both optimizers were trained under identical experimental settings to ensure a fair comparison. Experimental results show that VGG19 achieved the highest accuracy, reaching 85% with Adam and 83% with SGD, while lightweight architecture exhibited lower performance due to underfitting. The findings demonstrate that optimizer selection plays a crucial role in improving CNN performance for banana leaf disease classification, especially when data availability is limited.
Penerapan Algoritma A-Star sebagai Metode Pathfinding pada Game Lokasi Logika Cerdas untuk Non-Player Character Gibran, Kevin; Heriansyah, Rudi; Romegar Mair, Zaid
Insect (Informatics and Security): Jurnal Teknik Informatika Vol. 12 No. 01 (2026): Maret 2026
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/insect.v12i01.5508

Abstract

Perkembangan game simulasi modern menuntut sistem navigasi Non-Player Character (NPC) yang efisien dan adaptif dalam lingkungan virtual yang kompleks. Algoritma A-Star (A*) banyak digunakan dalam pathfinding karena mengombinasikan biaya aktual dan estimasi heuristic untuk menghasilkan jalur optimal. Namun, performanya dipengaruhi oleh jenis heuristic yang digunakan. Penelitian ini bertujuan mengimplementasikan A* pada sistem navigasi NPC berbasis Roblox Studio serta menganalisis kinerja Manhattan Distance dan Euclidean Distance. Metode yang digunakan adalah eksperimen komputasional pada tiga tingkat kompleksitas map (25×25, 50×50, dan 75×75 node) dengan dua mode pergerakan, yaitu 4-arah dan 8-arah. Parameter evaluasi meliputi waktu pencarian, panjang jalur, dan tingkat optimalitas. Hasil menunjukkan bahwa Manhattan Distance lebih efisien dalam waktu pencarian, terutama pada map Level 3 mode 8-arah (1.220,1 ms dibandingkan 6.990,5 ms pada Euclidean Distance). Sebaliknya, Euclidean Distance menghasilkan jalur lebih pendek dan optimal pada mode 8-arah (99 node dibandingkan 106 node pada Manhattan Distance). Temuan ini menunjukkan adanya trade-off, yaitu tidak bisa mendapatkan semuanya sekaligus secara maksimal antara efisiensi waktu dan kualitas jalur. Penelitian ini memberikan dasar empiris dalam pemilihan heuristic yang sesuai untuk sistem navigasi NPC tiga dimensi.
Co-Authors Aji Windu Viatra Alie, Marzuki Amidhan, Muhammad Budi Setiawan DEWI SARTIKA Dhamayanti Dwi Kurniawan, Budi Džakula, Nebojša Bačanin Fadly Fadly Fajri Munawar, Muhammad Ferano, Dwi Asa Gibran, Kevin Herri Setiawan Imelda Saluza, Imelda Indah Permatasari Irfani, Muhammad Hafiz JABAR, Tri Ahmad Jabar Jambak, Muhammad Ikhwan Kanaka, Nayaka Al Syahreal La Ode Hasnuddin S. Sagala Lestari, Sylvia Dwi Pameka, Aplea Purnamasari, Evi Ramadhan, Mustafa Remustin, Rivky Riyanti, Rizki S.Si., M.Kom, Dr. Shinta Puspasari, Sahrin, Muhammad Aditya Shinta Puspasari Tien Yustini, Tien Widya Astuti, Lastri