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All Journal Jurnal Buana Informatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) ELINVO (Electronics, Informatics, and Vocational Education) Journal of Information System Sinkron : Jurnal dan Penelitian Teknik Informatika ILKOM Jurnal Ilmiah Jurnal Infomedia Progresif: Jurnal Ilmiah Komputer Buletin Ilmiah Sarjana Teknik Elektro Jambura Journal of Electrical and Electronics Engineering JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Infotek : Jurnal Informatika dan Teknologi Information System Journal (INFOS) Jurnal Pengabdian Masyarakat Indonesia Prima Abdika: Jurnal Pengabdian Masyarakat JTECS : Jurnal Sistem Telekomunikasi Elektronika Sistem Kontrol Power Sistem dan Komputer Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma SmartComp Dedikasi: Jurnal Pengabdian Pendidikan dan Teknologi Masyarakat Dedikasi: Jurnal Pengabdian Pendidikan dan Teknologi Masyarakat Tanggap Masyarakat untuk Aksi dan Sinergi
Jeki Kuswanto
Universitas Amikom Yogyakarta
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Public Health Social Sciences Other

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Sistem Pakan Cerdas Berbasis IoT Untuk Optimalisasi Peternakan Kambing Umbaran di Era Digital Farm Zahrowani, Rizal; Kuswanto, Jeki; Pramono, Eko
Jurnal Buana Informatika Vol. 16 No. 01 (2025): Jurnal Buana Informatika, Volume 16, Nomor 01, April 2025
Publisher : Universitas Atma Jaya Yogyakarta

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Abstract

This research aims to create a smart feeding system based on the Internet of Things (IoT) to enhance the efficiency of feed delivery in goat farming. The system automatically regulates the feed dispenser according to a predetermined schedule, making it easier for farmers to manage feed. System testing demonstrates its effectiveness in reducing feed delivery time and minimizing waste. The system features an LCD screen that displays the dispenser status, providing real-time information to farmers. This technology also allows for remote monitoring, enabling farmers to manage feed more effectively. The implementation of this system is expected to improve productivity and animal welfare while promoting modernization in farming practices in Indonesia. This innovation is anticipated to offer a sustainable solution to challenges in feed management, providing long-term benefits for farmers and the livestock industry.
Pengembangan Keterampilan Dasar Pemrograman bagi Siswa SMA N 2 Bantul sebagai Persiapan di Era Digital Putra, Andriyan Dwi; Nur'aini; Ashari, Wahid Miftahul; Sismoro, Heri; Kuswanto, Jeki
Tanggap Masyarakat untuk Aksi dan Sinergi Vol. 1 No. 02 (2025): Volume 01 Nomor 02 - Juni 2025
Publisher : TAM Global Insights - PT. Treeta Amanah Mandiri Group

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Abstract

Pelatihan Internet of Things (IoT) di SMA Negeri 2 Bantul dilaksanakan sebagai respons terhadap rendahnya literasi teknologi dan keterampilan digital siswa, serta keterbatasan tenaga pengajar dan sumber belajar di bidang IoT. Kegiatan ini bertujuan untuk meningkatkan kompetensi dasar siswa dalam memahami dan mengaplikasikan teknologi IoT melalui pendekatan pembelajaran interaktif, praktik langsung, serta pengembangan proyek mini. Metode pelaksanaan meliputi tahap persiapan, pelaksanaan inti, dan evaluasi, dengan dukungan modul pembelajaran cetak dan digital, video tutorial, serta sesi pendampingan intensif. Hasil evaluasi menunjukkan bahwa 68,3% siswa merasa puas dan 25,5% cukup puas terhadap pelatihan yang diberikan. Pelatihan ini terbukti mampu meningkatkan minat dan pemahaman siswa terhadap IoT, serta memperlihatkan pentingnya sinergi antara sekolah dan perguruan tinggi dalam mendukung transformasi pendidikan berbasis teknologi. Kegiatan ini diharapkan menjadi model pelatihan yang dapat direplikasi di sekolah lain untuk mendorong literasi teknologi sejak dini.
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.
Sistem Pakan Cerdas Berbasis IoT Untuk Optimalisasi Peternakan Kambing Umbaran di Era Digital Farm Zahrowani, Rizal; Kuswanto, Jeki; Pramono, Eko
Jurnal Buana Informatika Vol. 16 No. 01 (2025): Jurnal Buana Informatika, Volume 16, Nomor 01, April 2025
Publisher : Universitas Atma Jaya Yogyakarta

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Abstract

Penelitian ini bertujuan untuk mengembangkan sistem pakan cerdas berbasis Internet of Things (IoT) yang dirancang untuk meningkatkan efisiensi pemberian pakan di peternakan kambing umbaran. Sistem ini secara otomatis mengatur dispenser pakan sesuai dengan jadwal yang telah ditentukan, sehingga memudahkan peternak dalam manajemen pakan. Pengujian sistem menunjukkan efektivitas dalam mengurangi waktu pemberian pakan dan meminimalkan pemborosan. Selain itu, sistem dilengkapi dengan layar LCD yang menampilkan status dispenser, memberikan informasi real-time kepada peternak. Teknologi ini juga memungkinkan pemantauan jarak jauh, sehingga peternak dapat mengelola pakan dengan lebih baik. Dengan penerapan sistem ini, diharapkan dapat meningkatkan produktivitas dan kesejahteraan ternak, serta mendorong modernisasi dalam praktik peternakan di Indonesia. Inovasi ini diharapkan menjadi solusi yang berkelanjutan untuk tantangan dalam manajemen pakan, memberikan manfaat jangka panjang bagi peternak dan industri peternakan secara keseluruhan. 
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.
Co-Authors Abdulloh, Ferian Fauzi Aditia, Amar Ali Mustopa Alva Hendi Muhammad Arvin Claudy Frobenius Ashari, Wahid Miftahul Asharudin, Firman Baihaqi, Muhammad Aziz Banu Santoso Bernadhed, Bernadhed Dimas Pratama, Rifqi Dwi Nurani, Dwi Dwi Putra, Andriyan Eko Pramono Fania Ellysabeth Fauzi, Moch Farid Febrian Putra Pratama Firman Asharudin Frobenius, Arvin Claudy Hakim, Muhamad Nauval Hamid, Nadila Ibnu Hadi Purwanto Imananda, Eldiva Tegar Kaleb, Setiawirawan Valerian Khamzah , Khaerul Koprawi, Muhammad Kurniawan , Hendra Kusrini, Kusrini Mahananing Puri, Fiyas Martisa Fiorentina, Rinda Melwin Syafrizal Moch Farid Fauzi Muhammad Abdul Ghofur Muhammad Irfan Annas Muhammad Koprawi Muktafin, Elik Hari Nenden Ranuma Ratri Nugraha, Anggit Ferdita Nur Asyifa Nur'aini Nurcholis, Muhammad Tofa Praditya, A.G. Arvin Pratama, Rifqi Dimas Putra, Andriyan Dwi Putra, Wahyu Sukestyastama Rahman, M. Ardafi Sulchia Ria Andriani Riasasi, Widiyana Rifda Faticha Alfa Aziza Rina Pramitasari Rivan Ardiansyah Setiani, Rina Setyaji, Ghalih Anung Setyanto, Nurcahyo Fajar Sismoro, Heri TONNY HIDAYAT Tri Atmaja Ramadhani, Surya Wasiso, Ichsan Wicaksono, Wahyu Enggar Widatama, Krisna Wisnu Yudo Untoro wisnu yudo untoro, wisnu Wiwi Widayani, Wiwi Yossy Ariyanto Yusuf Amri Amrulloh Zahrowani, Rizal