Article Per Year (5 Year)
p-Index From 2021 - 2026
6.805
P-Index
This Author published in this journals
All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Information Technology and Computer Science (JOINTECS) Network Engineering Research Operation [NERO] Jurnal Sains dan Informatika Generation Journal Joutica : Journal of Informatic Unisla Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) NERO (Networking Engineering Research Operation) Jurnal Pengabdian Masyarakat Nusantara JISCOMP (Journal of Information System and Computer)
Julian Sahertian
Universitas Nusantara PGRI Kediri
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Transportation

Published : 75 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 75 Documents
Search

 1   2   3   4   5 
Penilaian Otomatis Cerdas Cermat Menggunakan Basis Data Sinonim Kata Dan Cosine Similarity Triosaputra, Johan Rizky; Sanjaya, Ardi; Sahertian, Julian
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 8 No. 1 (2024): PROSIDING SEMINAR NASIONAL INOVASI TEKNOLOGI TAHUN 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v8i1.4982

Abstract

Penelitian ini bertujuan untuk mengembangkan aplikasi 'Cerdas Cermat' yang dapat mengevaluasi jawaban siswa dengan mengukur kemiripan antara jawaban siswa dan kunci jawaban menggunakan metode cosine similarity dan database sinonim. Metode yang digunakan meliputi preprocessing teks, pengubahan kata menjadi sinonim, serta perhitungan cosine similarity berdasarkan ID sinonim yang diambil dari database. Hasil akhir yang dihasilkan adalah presentase kemiripan antara jawaban siswa dengan kunci jawaban menggunakan metode cosine similarity yang dibantu menangani variasi kata yang berbeda namun satu makna menggunakan proses basis data sinonim kata.
Prediksi Penjualan Rebana Al-Banjari Menggunakan Metode Least Square Maulana, Arfan; Sanjaya , Ardi; Julian Sahertian
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 8 No. 2 (2024): PROSIDING SEMINAR NASIONAL INOVASI TEKNOLOGI TAHUN 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v8i2.5022

Abstract

Di era digitalisasi, kebutuhan akan informasi mendorong perkembangan teknologi informasi dan komunikasi, yang penting bagi industri dalam mengelola rantai pasok. Pengrajin rebana Al-Banjari di Gresik, Jawa Timur, masih menggunakan sistem manual untuk menentukan stok penjualan.Oleh karena itu, penelitian ini bertujuan untuk merancang sistem prediksi penjualan dengan menggunakan metode Least Square. Metode ini dipilih karena mampu memprediksi penjualan secara objektif. Hasil penelitian menunjukkan bahwa sistem ini membantu pengrajin menentukan stok dengan tepat dan akurat berdasarkan data yang dihasilkan oleh sistem. Kesimpulannya, penerapan metode Least Square memudahkan pengrajin dalam menentukan stok dan pencatatan dengan lebih efisien. Penelitian selanjutnya disarankan untuk menambah data dan memperbaiki desain serta fitur sistem.
Implementasi Metode Forward Chaining Dalam Sistem Diagnosa Penyakit Pada Kucing Erlina Nasrinatun Ni’mah; Ardi Sanjaya; Julian Sahertian
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 8 No. 2 (2024): PROSIDING SEMINAR NASIONAL INOVASI TEKNOLOGI TAHUN 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v8i2.5035

Abstract

Kucing merupakan hewan yang cukup populer di kalangan masyarakat, Seperti halnya manusia, kucing bisa terjangkit penyakit yang dapat mempengaruhi kesehatan dan kualitas hidupnya. Diagnosa yang salah dan penanganan yang terlambat bisa berdampak buruk pada kucing. Berdasarkan uraian tersebut peneliti tertarik melakukan pembuatan sistem pakar yang dapat digunakan untuk mendiagnosa penyakit pada kucing. Sistem yang dibuat menggunakan metode Forward Chaining. Data yang digunakan pada penelitian ini yaitu 5 data penyakit dan 29 data gejala. Hasil akhir yang dihasilkan adalah penyakit yang dialami oleh kucing dan solusi penanganan untuk penyakit tersebut. Dalam proses perhitungan yang sudah dilakukan di peroleh hasil keakuratan 90%.
Sistem Controlling Pembuatan Pakan Ternak Silase Menggunakan ESP32 Berbasis IoT Annisa, Fera; Farida, Intan Nur; Sahertian, Julian; Yahya, Nisaa’ Husnia; Septiawan, Indra; Salsabila, Adinda Meylia; Setiawan, Bima
Generation Journal Vol 9 No 1 (2025): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/sdt1c007

Abstract

Penelitian ini mengembangkan sistem controll pembuatan pakan ternak silase berbasis Internet of Things (IoT) menggunakan ESP32. Sistem ini dirancang untuk memantau suhu, kelembapan, dan pH secara real-time dengan memanfaatkan sensor DHT21 dan sensor pH tanah, yang terhubung ke Firebase sebagai database. Sistem dilengkapi antarmuka berbasis web dan LCD, sehingga memudahkan peternak dalam memantau kondisi pakan dari jarak jauh. Proses produksi silase dilakukan selama 19 hari dengan hasil grade yang diukur berdasarkan nilai pH, menunjukkan tingkat keberhasilan produksi berada pada Grade C (rendah). Functional testing, usability testing, dan blackbox testing memastikan sistem bekerja sesuai kebutuhan dengan nilai rata-rata usability sebesar 88,2%, termasuk kategori "Baik Sekali." Hasil pengujian menunjukkan bahwa sistem ini mampu memberikan data yang akurat dan stabil, meskipun memerlukan kalibrasi berkala. Tegangan dari aki motor 12V berhasil diturunkan menjadi 5V menggunakan modul stepdown untuk menjaga keandalan perangkat. Sistem ini juga menawarkan notifikasi otomatis saat terjadi kondisi abnormal, sehingga tindakan korektif dapat segera dilakukan. Sistem ini terbukti efektif dalam membantu peternak memantau proses fermentasi silase dan mengurangi risiko kegagalan produksi. Namun, peningkatan stabilitas sensor, optimasi komposisi pakan, dan koneksi internet yang lebih kuat diperlukan untuk meningkatkan hasil produksi dan kualitas pakan. Dengan demikian, sistem ini memberikan solusi inovatif bagi peternak dalam memproduksi pakan ternak secara efisien, andal, dan berkelanjutan
Ekstraksi Fitur Pada Aksara Kawi Moh Imam Yusuf Mustofa; Resty Wulanningrum; Julian Sahertian
JUKOMPSI (Jurnal Komputer dan Sistem Informasi) Vol 1 No 2 (2023): Juni
Publisher : Teknik Komputer Fakultas Teknik Universitas Islam Kadiri (UNISKA)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The Kawi script is a derivative of the post-palawa language. Kawi itself in Sanskrit means poet. The Kawi script itself is found in many ancient manuscripts from ancient times. Kawi script itself nowadays is no longer used, many people don't know Kawi script. In this modern era, where everything is digital, it needs preservation, one of which is by using computers to recognize kawi script patterns. Before identifying characters, it is necessary to have digital image information, one of which is the extraction process. This research will create a feature extraction system for the kawi script which will later be used as input for the classification of the kawi script. This study uses data sourced from books and in this research, the data taken is only 6 types of data. In the process of making this system using the Matleb application. In the testing phase, the GLCM (Gray Level Co-Occurrence Matrix) feature extraction will be used which includes Contrast, Correlation, Energy, and Homogeneity, then identification will be processed. The results of this study produce values ​​from the GLCM method, namely values ​​from Contrast, Correlation, Energy, and Homogeneity. It is expected that the values ​​of the 4 features can be used as input data from the classification from in further research.
EKSTRAKSI CIRI BENTUK PADA AKSARA JAWA KAWI MENGGUNAKAN METODE L*A*B dan K-Means Clustering Achmad Iqbal Maulana; Resty Wulanningrum; Julian Sahertian
JUKOMPSI (Jurnal Komputer dan Sistem Informasi) Vol 1 No 2 (2023): Juni
Publisher : Teknik Komputer Fakultas Teknik Universitas Islam Kadiri (UNISKA)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kawi Javanese script is one of the many cultural assets belonging to Indonesia that must be preserved and protected, one of which is by introducing it with a computer-based system, namely pattern recognition. In pattern recognition, shape extraction is a process that identifies and extracts shape features in digital images which can then be used as the initial classification process. This study aims to create a form extraction system for Kawi Javanese script which can then be used to classify Kawi Javanese script images so that they can be used for the process of reading Kawi Javanese script. Data collection in this study was taken from books using Javanese Kawi script with as many as 6 characters. In making this system using Matlab R2020a. Testing is carried out by processing 6 character images using the L*A*B and K-Means Clustering methods which will produce segmentation values ​​and then take shape feature values ​​including Area, Perimeter, Metric, and Eccentricity which can then be processed using the Artificial Neural Network method for classification. It is hoped that the values ​​of these parameters can be used as input values ​​for the classification of the Kawi Javanese script.
Ekstraksi Ciri Bentuk pada Huruf Kawi Cholid Ilham Isniawan; Resty Wulanningrum; Julian Sahertian
JUKOMPSI (Jurnal Komputer dan Sistem Informasi) Vol 1 No 2 (2023): Juni
Publisher : Teknik Komputer Fakultas Teknik Universitas Islam Kadiri (UNISKA)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The Javanese kawi script is basically an ancient script that appeared in the 18th to 16th centuries. Which the kawi script is also a derivative of the Pallawa script, considering the very importance of the Kawi language because previous texts mainly used the history of Hindu texts still using the Kawi language. (Surada, 2018). And to preserve the kawi language, it can be developed through a kawi identification system. For image identification, shape feature extraction is used for the identification system to find information from digital images (Herdiansah, 2022). In this study, an image identification system was created by extracting shape features to get the initial value of the shape of the Kawi letters and then going through a classification process so that they could recognize Kawi letters. There was some data collected from 2 data sources with a total of 6 data collected. In this manufacture using the matlab application (Prayoga, 2019) by conducting tests to process image data that has been obtained using shape feature extraction with metric and eccentricity parameters which are then processed using an artificial neural network method. From the results of this study it is hoped that the extraction value of shape features with these parameters can be used for the next step for classifying kawi letters.
Deteksi dan Klasifikasi Kue Tradisional Indonesia Menggunakan YOLOv8 Mustofa, Arin Ayu Silvyani; Wulanningrum, Resty; Sahertian, Julian
NERO (Networking Engineering Research Operation) Vol 10, No 1 (2025): Nero - 2025
Publisher : Jurusan Teknik Informatika Fakultas Teknik Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/nero.v10i1.30177

Abstract

Indonesian traditional cakes are part of the cultural heritage, characterized by their rich flavors, unique forms, and significant historical value. However, the lack of recognition among younger generations necessitates a new approach to preservation efforts. This study aims to develop an image processing-based detection system for traditional cake types using the YOLOv8 algorithm. The five types of cakes identified in this research are lumpur cake, lapis cake, wingko cake, dadar gulung cake, and putu ayu cake. The image dataset was obtained through a combination of direct image capture and public datasets, and was manually annotated using the Roboflow platform. The model was trained using the PyTorch framework and evaluated based on precision, recall, F1-score, and mean Average Precision (mAP) metrics. Experimental results show that the system achieved an average mAP of 89.9% and an F1-score of 86.5%, with a relatively low classification error rate. These findings indicate that the YOLOv8 algorithm is effective in detecting visually similar objects and holds significant potential for application in the digital preservation of culinary heritage. The system can also be further developed as a technology-based educational medium to support the conservation of Indonesia’s local culinary wealth.Keywords: YOLOv8, Object Detection, Cake Traditional, Image Processing, Computer Vision
Deteksi dan Klasifikasi Kue Tradisional Indonesia Menggunakan YOLOv8 Mustofa, Arin Ayu Silvyani; Wulanningrum, Resty; Sahertian, Julian
NERO (Networking Engineering Research Operation) Vol 10, No 1 (2025): Nero - 2025
Publisher : Jurusan Teknik Informatika Fakultas Teknik Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/nero.v10i1.30177

Abstract

Indonesian traditional cakes are part of the cultural heritage, characterized by their rich flavors, unique forms, and significant historical value. However, the lack of recognition among younger generations necessitates a new approach to preservation efforts. This study aims to develop an image processing-based detection system for traditional cake types using the YOLOv8 algorithm. The five types of cakes identified in this research are lumpur cake, lapis cake, wingko cake, dadar gulung cake, and putu ayu cake. The image dataset was obtained through a combination of direct image capture and public datasets, and was manually annotated using the Roboflow platform. The model was trained using the PyTorch framework and evaluated based on precision, recall, F1-score, and mean Average Precision (mAP) metrics. Experimental results show that the system achieved an average mAP of 89.9% and an F1-score of 86.5%, with a relatively low classification error rate. These findings indicate that the YOLOv8 algorithm is effective in detecting visually similar objects and holds significant potential for application in the digital preservation of culinary heritage. The system can also be further developed as a technology-based educational medium to support the conservation of Indonesia’s local culinary wealth.Keywords: YOLOv8, Object Detection, Cake Traditional, Image Processing, Computer Vision
Hand Gesture Recognition Untuk Interaksi Anak Autis Dengan Algoritma Convex Hull Anwarruddin, Muhammad Tri; Sanjaya, Ardi; Sahertian, Julian
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 4 No. 2 (2020): PROSIDING SEMNAS INOTEK Ke-IV Tahun 2020
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v4i2.110

Abstract

Beberapa anak pengidap sindrom autisme kesulitan untuk melakukan interaksi secaraverbal maupun fisikal, bahkan pada penggunaan perangkat komputasi untuk kegiatan edukasi. Pada penelitian ini diterapkan pengenalan isyarat tangan (hand gesture) sebagai pendekatan alternatif interaksi manusia dengan komputer, khususnya bagi anak pengidap autisme. Metode convex hull digunakan untuk menemukan titik masing-masing jari pada tangan. Setelah tangan terdeteksi pada tiap frame citra, koordinat tangan dipakai guna melakukan kontrol terhadap mouse untuk berinteraksi dalam mengoperasikan game edukasi bernama GCompris. Penelitian ini menunjukkan bahwa objek berupa isyarat tangan manusia mampu dikenali dengan hasil akurasi sebesar 80% pada kondisi pencahayaan yang cukup dan warna background gelap serta polos.
Co-Authors Achmad Iqbal Maulana Adhitia, Riswandha Ahmad Bagus Setiawan Ahmad Robet Nailul Author Alexander, Kevin Rio Amanda, Novia Anandra, Yayan Anardha, Danuar Aditya Anifiatiningrum Anwar, Muhammad Choirul Anwarruddin, Muhammad Tri Aqharabah, Bhisri Hafi Ardi Sanjaya Astutik, Eka Yulia Sri Ayu Meudea, Prita Azmi, Muhamad Ulul BIMA SETIAWAN Cholid Ilham Isniawan Christofel Wicaksono, John Danang Wahyu Widodo Daniel Swanjaya Darmawan, Reza Depi, Alisa Sintiya Diansyah, Alex Rahma Dipa Perwira, Mohammad Askar Doni Abdul Fatah Dusea Widyadara, Made Ayu Erlina Nasrinatun Ni’mah Erwanto, Elga Asfa Fera, Annisa Fery Setiawan Frans Rega Agista Hari Setiawan Ibnu Al Ikrom Indra Septiawan Intan Nur Farida Irawan, Rony Hery Juli Sulaksono Khotmuniza, Muzan Ihda Kumalasari, Ratih Kurniawan, Candra Mega Adi Kurniawati, Desi Dwi Luluk Indah Safitri Made Ayu Dusea Widyadara - Universitas Nusantara Kediri, Made Ayu Dusea Widyadara Mahdiyah, Umi Mahmudi, Aris Majid, Moh. Lukky Abdul Marjuni, Mohamad Marzuki, Moh. Ismail Maulana, Arfan Moh Imam Yusuf Mustofa Muhammad Vicko Putra Ardiansyah Mulya, Leon Prasetya Mustofa, Arin Ayu Silvyani Muzan Ihda Khotmuniza Natasha, Sonya Niska Shofia, Niska Niswatin , Ratih Kumalasari Novianto, Alfian Dwi Nugroho, Alindro Septo Nur Farida Nurarinda, Terry Anda Putra Nurul Mahpiroh Odhianto, Yosan Pandie, Risky Vridel Eduard Patmi Kasih Pramudita, Yosua Yonnas Prasetyo, Mochammad Bima Pratama Putra, Septiandy Adibya Pratama, Tutus Lusni Raharjo, Yulianto Dwi Ramadhanu, Ilham Khefi Ratih Kumalasari Niswatin Resty Wulanningrum Risa Helilintar Rizakatama, Moh. Rohman Rizal, Muhamad Helmi Khoirur Rohman, Ahmad Andi Fatkhur Rony Heri Irawan Rony Hery Irawan Saiful Akbar Salsabila, Adinda Meylia Santoso, Christa Witta Putra Saputro, Aryo Widodo Satria Bijaksana Satrio Damara, Moch. Deifa Sholahuddin, Muhammad Resandi Subiyantoko, Rizki Suraju, Ghovin Triosaputra, Johan Rizky Umami, M. Rizal Utama, Yoga Putra WAHYU FIRMANSYAH Wahyuniar , Lilia Sinta Wulaningrum, Resty Yahya, Moh. Zakariya Yahya, Nisaa’ Husnia Yuprastiwi, Yessy Zuhri, Mohamad Farkhan Fahmi