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Optimizing 4-ary Huffman Trees and Normalizing Binary Code Structures to Minimize Redundancy and Level Reduction Hidayat, Tonny; Kurniawan , Hendra; Mustopa , Ali; Kuswanto, Jeki
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 10 No. 1 (2025): May 2025
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v10i1.78722

Abstract

Since the present data expansion and increase are occurring at an increasingly rapid pace, the solution of adding storage space is not sustainable in the long run. The growing need for storage media can be addressed with lossless compression, which reduces stored data while allowing complete restoration. Huffman remains a potent method for data compression, functioning as a "back end" process and serving as the foundational algorithm in applications, among others, Monkey's PKZIP, WinZip, 7-Zip, and Monkey's Audio. Lossless compression of 16-bit audio requires binary structure adjustments to balance speed and optimal compression ratio. The use of a 4-ary Huffman tree (4-ary) branching procedure to generate binary code generation and to insert a maximum of 2 dummy data symbol variables that are given a binary value of 0 with the condition that if the number of MOD 3 data variables = remaining 2, then two dummy data are added, if the result is the remainder 0 = 1 dummy data, and if the remainder = 1 then it is not required. This process effectively maintains a high ratio level while speeding up the 4-ary Huffman code algorithm's performance in compression time. The results show that the efficiency reaches 95.94%, the ratio is 38%, and the comparison is 1/3 of the Level based on calculations, testing, and comparison with other generations of the Huffman code. The 4-ary algorithm significantly optimizes archived data storage, reducing redundancy to 0.124 and achieving an entropy value of 2.91 across various data types.
Pemberdayaan Peternak Kambing Umbaran di Bantul Berbasis IoT untuk Meningkatkan Produktivitas Kuswanto, Jeki; Riasasi, Widiyana; Dewi, Melany Mustika; Wasiso, Ichsan
Prima Abdika: Jurnal Pengabdian Masyarakat Vol. 5 No. 3 (2025): Volume 5 Nomor 3 Tahun 2025
Publisher : Program Studi Pendidikan Guru Sekolah Dasar Universitas Flores Ende

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37478/abdika.v5i3.5438

Abstract

The development of Internet of Things (IoT) technology offers new opportunities for managing small-scale livestock farming, including goat farming. The partner of this program, the Umbaran Goat Farmers Group in Bantul, still faces several challenges such as a high mortality rate (12%), inefficient manual feeding, limited digital record-keeping, and marketing that relies solely on local collectors. This community service program aims to improve farm productivity through the application of IoT integrated with a digital farm management system. The implementation method included socialization, workshops, theoretical and practical training, and the deployment of technologies such as a web-based farm management platform, RFID identity tags, and an automatic feeding device. A seven-day trial of the automatic feeder resulted in a total feed distribution of 67 kg, with an average of 9.57 kg/day, and demonstrated a feed saving of approximately 12.99% compared to manual methods. The system also successfully maintained feeding schedule consistency twice a day with 100% accuracy. The results indicate improved efficiency, regularity in feeding patterns, and support for digital transformation in livestock management. Therefore, the implementation of IoT in goat farming not only reduces operational costs but also opens opportunities for developing sustainable business models through the integration of digital systems and online marketing.
Optimalisasi Engine Optimalization On-Page untuk Meningkatkan Kinerja Situs Berita Digital Menggunakan Analisis CTR dan UX Martisa Fiorentina, Rinda; Miftahul Ashari, Wahid; Kuswanto, Jeki
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2377

Abstract

This study analyzes the application of Search Engine Optimization (SEO) strategies on the Radar Jogja website to increase its visibility on search engines. With internet penetration in Indonesia reaching 78.19% in 2023, digital platforms have become an important necessity for media companies. Radar Jogja faces the challenge of competing for top positions on Google's search engine results pages (SERPs), where most users only access the first two pages. This study uses a descriptive-analytical method to evaluate key SEO elements such as titles, URLs, internal link structure, and page performance. Test results show that CTR increased from 2% to 4.75% and average position improved from 12th to 6th. In addition, dwell time increased to 2.25 minutes and bounce rate decreased, indicating a significant improvement in user experience. The results of this study contribute to content-based SEO strategies for local media to increase digital competitiveness and gain better visibility on search engines.
Kalibrasi Regresi Linier untuk Peningkatan Akurasi Load Cell pada Kursi Roda Cerdas Hakim, Muhamad Nauval; Miftahul Ashari, Wahid; Kuswanto, Jeki
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.3023

Abstract

Smart wheelchairs are an innovation designed to facilitate user mobility while monitoring their condition in real time. One of the main features developed is an integrated weight reading system. However, the accuracy of the sensor is still affected by sitting posture, body position, and surrounding environmental conditions. This study aims to improve the accuracy of the weighing system on smart wheelchairs by applying linear regression analysis as a sensor calibration method. Data collection was conducted under four conditions of use, namely sitting upright, sitting tilted, walking while sitting upright, and walking while sitting tilted, which represent variations in user load distribution. The calibration model was constructed using the average sensor reading data and evaluated using the R², MAE, and MAPE parameters. The results showed a significant improvement in accuracy with an R² value of 1.0000, MAE of 0.0687 kg, and MAPE of 0.111%, as well as a decrease in the average error from ±1.2 kg to ±0.07 kg after the calibration process. The linear regression method proved to be effective in improving the accuracy of sensor readings with light computational calculations. This study also demonstrates the potential of linear regression as an efficient lightweight calibration method for IoT-based medical systems, particularly on devices such as ESP32 or Arduino that display real-time, high-precision body weight measurements.
Improving Machine-Learning Malware Detection Through IQR-Based Feature Reduction Setyanto, Nurcahyo Fajar; Pramitasari, Rina; Kuswanto, Jeki
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15634

Abstract

Malware detection is a significant challenge in cybersecurity due to the complex and evolving nature of threats. This study evaluates the effectiveness of machine learning algorithms, specifically XGBoost and LightGBM, in detecting malware. The approach includes data cleaning, normalization, feature selection, and the use of the Interquartile Range (IQR) technique to select relevant features. The initial dataset contained 21,752 files, evenly split between malicious and benign files. After data cleaning, the number of samples decreased to 19,256 files, with numerous features that were reduced after applying IQR. Results show that XGBoost outperforms other algorithms, achieving 99.20% accuracy, an improvement over the 98.99% accuracy without IQR. The IQR technique enhances data quality by filtering out features with significant differences between malware and benign files, improving model performance. Additionally, reducing the feature set helps prevent overfitting and strengthens the model's generalization ability. The study concludes that machine learning, particularly with algorithms like XGBoost and LightGBM, can effectively improve malware detection. By using IQR in feature selection, model performance is enhanced, leading to reduced false positives and increased detection efficiency. The research highlights the importance of feature selection techniques like IQR in boosting the predictive power of machine learning models, making them more efficient in identifying malware. Future work will explore additional feature selection methods to further improve malware detection accuracy.
Smart Fish Farm Budidaya Ikan Nila Menggunakan NodeMCU Terintegrasi Berbasis Internet Of Things Kuswanto, Jeki; Ashari, Wahid Miftahul; Asharudin, Firman
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 12, No 1 (2023): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v12i1.5061

Abstract

Teknologi budidaya ikan yang digabungkan dengan pertanian saat ini berkembang  pesat banyak muncul sistem yang cocok untuk menggabungkan antara media tanam dan juga budidaya ikan salah satunya yaitu media tanam vertikultur  yang mana sistem budidaya pertanian ini dilakukan secara vertikal atau bertingkat  pada ruang lingkup indoor maupun outdoor. beberapa proses yang dilakukan masih secara manual yaitu  melakukan penyiraman tanaman,  pengecekan PH air, memberi makan ikan, pengecekan suhu air dalam kolam,  mengontrol tingkat kelembaban tanah, ini dikerjakan secara manual. Oleh sebab itu Smart fish Farm dibutuhkan sistem  sistem ini dibuat otomatisasi berbasis iot (internet of thing)  dibutuhkan untuk mengatasi beberapa apa permasalahan tersebut, dengan memanfaatkan  NodeMCu sebagai mikrokontroler yang akan dihubungkan dengan sensor kelembaban tanah, sensor suhu, PH meter,  motor DC maka kontrol dan pemantauan  penyiram tanaman, pemberian makan ikan, kondisi air air dapat dilakukan secara otomatis. smart fish Farm budidaya ikan nila dan tanaman  vertikultur  berbasis iot (internet of thing)  dapat menampilkan data yang sesuai melalui  aplikasi mobile yang dapat dilihat oleh pengguna, mulai dari tingkat kelembaban tanah menampilkan hasil kadar pH dari 1 sampai dengan 10 kadar pH dan menampilkan suhu kolam ikan dari rentan 15 sampai dengan 32 derajat Celcius serta Aplikasi mobile  dapat mengontrol sistem pakan ikan.
PENGEMBANGAN EKOWISATA WATER BYUR PONJONG MELALUI EDUKASI DAN DIGITALISASI Septi Kurniawati Nurhadi; Atika Fatimah; Jeki Kuswanto; Dera Milyarta; Marcelinus Erix Nugroho; Muhammad Zakyul Fikri; Anita Kusumaning Tyas
Jurnal Abdi Insani Vol 13 No 2 (2026): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v13i2.3553

Abstract

Water Byur Ponjong merupakan destinasi wisata air yang terdiri atas kolam renang dan wahana permainan air yang terletak di Kabupaten Gunung Kidul, Yogyakarta. Kawasan wisata ini memiliki dua site yakni Site 1 (lokasi titik mata air) dan Site 2 (zona publik dan area parkir). Namun tata ruang di kawasan ini masih belum terkonsep dengan baik dan terdapat rencana pengembangan area Kawasan Wisata Water Byur, dengan tujuan dapat menarik wisatawan lebih banyak lagi untuk berkunjung. Selain itu, terdapat kerusakan pada beberapa fasilitas karena tidak adanya dana perbaikan, sementara pendapatan kawasan wisata yang berasal dari penjualan tiket ini terbilang besar. Berdasarkan latar belakang tersebut, perlu adanya kegiatan pelatihan peningkatan kualitas SDM seperti pelatihan perhitungan gaji dan retribusi jasa usaha serta pelatihan peningkatan kualitas kawasan melalui penataan kawasan dengan konsep ekowisata. Selanjutnya untuk pengembangan wisata alam yang berkelanjutan, akan menggunakan fasilitas pengelolaan air melalui inovasi sistem pintar. Hasil dari pengabdian ini yaitu : (1) Masterplan kawasan wisata, (2) Sistem pintar irigasi lahan (SIPILAH), (3) Aplikasi penggajian dan perhitungan tiket masuk wisata, (4) Peningkatan pemahaman masyarakat terkait penggajian dan perhitungan tiket masuk wisata, serta penggunaan aplikasi SIPILAH. Kegiatan ini menunjukkan adanya perubahan positif bagi pengembangan ekowisata Water Byur Ponjong.