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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Edukasi dan Penelitian Informatika (JEPIN) Sinkron : Jurnal dan Penelitian Teknik Informatika Creative Information Technology Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Martabe : Jurnal Pengabdian Kepada Masyarakat Informatik : Jurnal Ilmu Komputer Jurnal Riset Informatika CCIT (Creative Communication and Innovative Technology) Journal Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Kepada Masyarakat Patikala ABDIKOM
I Wayan Rangga Pinastawa
Univeristy Pembangunan Nasional Veteran Jakarta, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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REACH: A Reinforcement Learning-Based Protocol for Adaptive Cluster Head Selection in Wireless Sensor Networks Hadi, Novi Trisman; Supriyanto, Supriyanto; Pinastawa, I Wayan Rangga; Setyadinsa, Radinal
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.4754

Abstract

Wireless Sensor Networks (WSNs) are widely used in critical applications such as environmental monitoring and the Internet of Things (IoT), where energy efficiency and minimal latency are critical for network robustness and effectiveness. Conventional clustering and routing methods often struggle to adapt to fluctuating network conditions, resulting in suboptimal energy usage and increased latency. This study introduces REACH, an adaptive clustering and routing algorithm that leverages reinforcement learning to optimize energy consumption and reduce latency in WSNs. The proposed protocol dynamically selects cluster heads based on real-time network characteristics, including node density and energy levels, enhancing adaptability and robustness. Simulation results using MATLAB show significant improvements, with energy consumption reduced by 35% and latency reduced by 40% compared to traditional protocols such as LEACH and HEED. These findings suggest that reinforcement learning can significantly improve the performance of WSNs by extending the network lifetime and minimizing data transmission delay. This research contributes to the development of intelligent network protocols, offering practical insights into the integration of reinforcement learning for sustainable and scalable WSN design.
PENERAPAN KONSEP COMPUTATIONAL THINKING MELALUI KOMPETENSI PEDAGOGIK GURU DALAM PEMBELAJARAN DI SD NEGERI 032 TILIL BANDUNG MELALUI MEDIA GAME Adrezo, Muhammad; Galih Pradana, Musthofa; Niqotaini, Zatin; Pinastawa, I Wayan Rangga; Maulana, Nurhuda; Alvionita Simanjuntak, Anni; Devira Ayu Martini, Ni Putu
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 7, No 11 (2024): MARTABE : JURNAL PENGABDIAN MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v7i11.4901-4910

Abstract

Salah satu kemampuan yang penting saat ini adalah pemecahan masalah serta pemikiran logis dan sistematis dengan menguraikan masalah menjadi bagian-bagian kecil sehingga mudah untuk dijalankan sesuai dengan konsep dari Computational Thinking. Kemampuan ini yang sangat berguna di banyak aspek dalam menjalankan kehidupan, baik dalam kehidupan sehari-hari maupun secara profesional. Dalam konteks Pendidikan di Sekolah Dasar, stimulus untuk berpikir secara logis dan rasional dapat membantu untuk menyiapkan siswa yang siap untuk mempersiapkan masa depan yang menuntut kemampuan pemecahan masalah yang baik. Keterkaitan konsep Computational Thinking dengan kondisi pembelajaran di SDN 032 Tilil Bandung berdasarkan observasi dan wawancara awal dengan pihak sekolah yang menyatakan belum ada proses pembelajaran yang menstimulus konsep dan cara berpikir komputasional. Pihak sekolah menyatakan juga bahwa membutuhkan proses penyelarasan konsep Computational Thinking dalam pembelajaran, hal ini merupakan salah satu hal yang ingin diterapkan untuk mampu mewujudkan salah satu misi yang telah dicanangkan yaitu dengan melatih pola pikir anak agar mampu menumbuhkan kreativitasnya. Dalam rangka perwujudan misi SDN 032 Tilil ini dapat dilakukan dalam kegiatan pelatihan pembuatan game sederhana menggunakan game Scratch sebagai media ajar dalam proses penerapan dan integrasi konsep Computational Thinking. Kegiatan ini akan ditargetkan dalam pelatihan kepada guru yang diharapkan nantinya guru dapat memberikan pengajaran pembuatan game sederhana kepada murid dalam penerapan dan integrasi Computational Thinking.
Mobile App for Child Learning with Task Reminders and Performance Statistics Setyadinsa, Radinal; Pinastawa, I Wayan Rangga; Razaqa, Dhi'Fan; Sebayang, Axel Putra Bintang Syahkuala
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol. 11 No. 3 (2025): Volume 11 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v11i3.98826

Abstract

The rapid development of mobile technology has opened significant opportunities to support education, particularly in monitoring children"™s learning activities. Common challenges faced include poor time management among children, limited parental supervision, and the absence of an integrated system for task reminders and performance analysis. This research aims to develop a mobile application for Child Learning Monitoring, featuring task reminders based on notifications and performance statistics in graphical form. The study employed a Research and Development (R&D) method using the Software Development Life Cycle (SDLC) approach, which consists of requirement analysis, interface design, application implementation, testing, and evaluation. The application was developed using Android Studio with Java programming language. The task reminder feature utilizes the AlarmManager to display notifications according to the scheduled time, while performance statistics are visualized using a Pie Chart to represent the number of completed and pending tasks. Implementation results indicate that the application runs smoothly on Android devices. Functional testing using the Black Box Testing method proved that all features operate as designed. A limited user trial involving children and parents revealed that more than 80% of users found the application easy to use, beneficial, and effective in improving children"™s learning discipline. Therefore, this application serves as an innovative solution to assist children in managing their daily learning activities while providing parents with an easier way to monitor progress.
DIGITAL IMAGE PROCESSING FOR BRAIN TUMOR CLASSIFICATION IN HUMANS USING CONVOLUTIONAL NEURAL NETWORKS Muhammad Dimas Romero Yusuf Daywin; Naufal Rasyad Muhammad; Kevin Yosia; Danendra Satya Purwoko; I Wayan Rangga Pinastawa
Jurnal Riset Informatika Vol. 8 No. 3 (2026): Juni 2026
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v8i3.536

Abstract

The rapid development of digital technology has encouraged its utilization in various aspects of life, including the medical field. One significant application is digital image processing, which is used to enhance the quality and utility of medical imagery such as MRI and CT scans. This technology is highly relevant in diagnosing brain diseases, particularly brain tumors, which require high precision given the organ's complexity. This research focuses on the classification of brain tumor diseases using MRI images through the Convolutional Neural Network (CNN) method. CNN was selected due to its ability to extract essential features from MRI images, enabling it to identify complex patterns that are difficult for the human eye to recognize. With proper training, the CNN model is capable of distinguishing between healthy brain MRI images and those with tumors with an accuracy of 80%. These results demonstrate great potential in accelerating and improving the accuracy of the diagnostic process, which in turn assists in determining appropriate and effective treatment steps. This study provides a significant contribution to the development of medical diagnostic technology, specifically in brain tumor classification. Through the application of advanced digital image processing technology, it is expected that more efficient and accurate diagnostic tools can be created, thereby improving the quality of healthcare and patient treatment outcomes.
Penguatan UMKM Ramah Lingkungan melalui Sinergi Inovasi Produk dan Transformasi Digital Musthofa Galih Pradana; I Wayan Rangga Pinastawa; Retno Dwi Nyamiati; Fadhli Suko Wiryanto; Ryan Setya Budi; Nurul Afifah Arifuddin; Muhammad Adrezo; Zatin Niqotaini
Jurnal Pengabdian kepada Masyarakat Bidang Ilmu Komputer Vol 4 No 1 (2025): Jurnal Pengabdian Kepada Masyarakat Bidang Ilmu Komputer (ABDIKOM)
Publisher : Universitas Pembangunan Nasional "Veteran" Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/abdikom.v4i1.12855

Abstract

Kawasan Industri Sentolo merupakan lokasi yang strategis bagi UMKM Jangkang Indah Craft, produsen kerajinan berbahan serat agel yang merupakan sumber daya alam khas Kabupaten Kulon Progo. Memasuki tahun 2025, UMKM ini dihadapkan pada dua tantangan utama, yaitu kesiapan melakukan pemasaran internasional secara mandiri serta penerapan teknik pewarnaan ramah lingkungan guna mendukung keberlanjutan ekosistem dan meminimalkan dampak ekologis. Menjawab kebutuhan tersebut, kegiatan Pengabdian kepada Masyarakat dirancang untuk memperkuat kapasitas pengelolaan usaha secara holistik. Program ini menerapkan metode Participatory Action Research meliputi sosialisasi, pendampingan, dan praktik langsung pada beberapa aspek kunci, yakni peningkatan manajemen pemasaran melalui pelatihan digital marketing berbasis website serta pemanfaatan platform e-Bay. Di sisi lain, peserta juga menerima pelatihan teknis mengenai teknik pewarnaan berkelanjutan, seperti pemanfaatan spirulina untuk menghasilkan warna hijau serta penggunaan ekstrak warna kuning dengan kandungan kimia yang lebih rendah. Pendampingan dilakukan dalam tiga sesi, dan hasil evaluasi melalui kuesioner menunjukkan tingkat kepuasan rata-rata 4,27 dari skala 1 - 5, yang mencerminkan kategori penilaian baik. Temuan ini sejalan dengan perkembangan positif dari pendampingan tahap sebelumnya, di mana keberadaan website terbukti meningkatkan branding awal UMKM dan membantu menjalin sejumlah kemitraan melalui kemudahan akses informasi.
Security and Performance Analysis of PRESENT, SPECK, and ASCON Lightweight Cryptographic Algorithms in MQTT-Based IoT Environments I Wayan Rangga Pinastawa; Susanto Susanto; Khoironi Khoironi
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13189

Abstract

The rapid growth of the Internet of Things (IoT) has increased the demand for lightweight cryptographic algorithms capable of providing adequate security while maintaining low computational overhead on resource-constrained devices. This study aims to analyze and compare the ASCON, PRESENT, and SPECK algorithms in MQTT-based IoT environments using the MQTT-IoT-IDS2020 dataset as a source of communication payloads. The evaluation was conducted using a Python-based framework with security and randomness metrics, including Avalanche Effect, Strict Avalanche Criterion (SAC), Bit Independence Criterion (BIC), Shannon Entropy, Approximate Entropy, Hamming Distance, Monobit Test, and Runs Test. Performance was evaluated using execution time, throughput, memory usage, and CPU usage. The validity of the results was strengthened through statistical analysis using 95% confidence intervals, One-Way ANOVA, and Tukey HSD. The results indicate that all three algorithms exhibit strong diffusion and randomness characteristics, with Avalanche Effect values close to the ideal value of 50% and ciphertext randomness metrics that satisfy the applied statistical tests. SPECK achieved the best performance with an execution time of 0.000238 seconds and a throughput of 2,199,891 bits/s, while PRESENT demonstrated the lowest memory consumption at 2.85 KB. Based on the calculated Security Score and Efficiency Score, PRESENT achieved the highest Security Score of 0.692, while SPECK achieved the highest Efficiency Score of 0.993, respectively. Statistical analysis revealed that significant differences among the algorithms primarily occurred in diffusion-related and computational performance metrics. Therefore, within the scope of the evaluated diffusion, randomness, and performance metrics, SPECK provides the most favorable balance between security-related characteristics and computational efficiency among the evaluated algorithms for MQTT-based IoT environments.
Comparative Analysis of RSA-2048, ECDSA-P256, and Ed25519 Digital Signatures in Document Authentication Systems I Wayan Rangga Pinastawa; Khoironi; Tomi Tri Sujaka
Informatik : Jurnal Ilmu Komputer Vol 22 No 2 (2026): August 2026
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v22i2.14719

Abstract

Digital signatures are widely used to ensure the authenticity, integrity, and non-repudiation of digital documents. This study aims to compare the performance of RSA-2048, ECDSA P-256, and Ed25519 algorithms in digital document authentication. The dataset consisted of 500 text documents with file sizes ranging from 1 KB to 10 MB. The evaluation was conducted based on key generation time, signing time, verification time, signature size, and tampering detection capability. Each signing and verification process was repeated 10 times, resulting in a total of 15,000 observations. The experimental results show that Ed25519 achieved the fastest signing time of 0.000027 seconds and the smallest signature size of 64 bytes. RSA-2048 achieved the fastest verification time of 0.000025 seconds, while ECDSA P-256 provided intermediate performance between the two algorithms. Tampering detection tests demonstrated that all algorithms successfully detected document modifications with a 100% detection rate. Statistical analysis using the Kruskal–Wallis and Mann–Whitney U tests confirmed significant performance differences among the evaluated algorithms, with a very large effect size (η² = 0.682). Based on the obtained results, Ed25519 was found to be the most efficient algorithm for digital document authentication systems requiring high performance and compact signature sizes.
Co-Authors Anni Alvionita Simanjuntak Budi, Ryan Setya Danendra Satya Purwoko Deny Fardiansyah Putra Ema Utami Fadhli Suko Wiryanto Izzety, Aurel Kevin Yosia Khoironi Khoironi Khoironi Khoironi Khoironi Khoironi, Khoironi M. RUDYANTO ARIEF MARTINI, NI PUTU DEVIRA AYU Muhamad Ridwan Muhammad Adrezo Muhammad Dimas Romero Yusuf Daywin Musthofa Galih Pradana Naufal Rasyad Muhammad Niqotaini, Zatin Novi Trisman Hadi Nurhajar Anugraha Nurhuda Maulana Nurul Afifah Arifuddin Nyamiati, Retno Dwi Razaqa, Dhi'fan Ryan Setya Budi Sebayang, Axel Putra Bintang Syahkuala Setiawan, Deandra Satriyo Setyadinsa, Radinal Susanto Susanto Tomi Tri Sujaka Wahit Desta Prastowo