Article Per Year (5 Year)
p-Index From 2021 - 2026
3.069
P-Index
This Author published in this journals
All Journal Jurnal Informatika dan Teknik Elektro Terapan INFORMAL: Informatics Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Pengembangan Riset dan Observasi Teknik Informatika Jurnal RESISTOR (Rekayasa Sistem Komputer) Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika AGROMIX Jurnal Informatika Global Jurnal Teknologi Informasi dan Multimedia JATI (Jurnal Mahasiswa Teknik Informatika) Soeropati: Journal of Community Service Jurnal Cahaya Mandalika Best : Journal of Applied Electrical, Science and Technology Jurnal Mandiri IT Nusantara Journal of Computers and its Applications
Moch. Lutfi
Universitas Yudharta Pasuruan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Social Sciences Other

Published : 26 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 26 Documents
Search

 1   2   3 
Detection of Sugarcane Leaf Disease Using Pre-Trained Feature Extraction and SVM Method Izza, Mufidatul; Lutfi, Moch.
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10626

Abstract

Sugarcane (Saccharum officinarum) is an important commodity in the sugar industry, but it is vulnerable to leaf diseases such as Red Rot, Rust, Yellow Leaf, and Mosaic, which can significantly reduce the quality and quantity of yields. Manual identification is time-consuming and prone to subjective errors, therefore an automatic detection method based on digital images is required. This study proposes a combination of VGG16 pre-trained as a feature extractor with Support Vector Machine (SVM) as a classifier. The dataset used is the Sugarcane Leaf Disease Dataset from Kaggle, consisting of 2,521 images of five classes, which were then balanced through augmentation in the form of rotation, zoom, and flipping to a total of 3,000 images (600 per class). The preprocessing stage includes resizing the images to 224×224 pixels and normalization using the preprocess_input function. Three model scenarios were tested, namely SVM, VGG16, and VGG16+SVM. Evaluation was carried out using two methods, namely an 80:20 train–test split and 10-fold cross-validation, with metrics of accuracy, precision, recall, F1-score, G-Mean, and AUC. The experimental results show that VGG16+SVM provides the best performance with an accuracy of 99.60% on the 80:20 scheme, while on 10-fold cross-validation the average accuracy is 80.76%. This value surpasses the baseline SVM and VGG16 + Softmax, proving that the integration of VGG16 feature extraction with SVM classification can produce stable and accurate performance. This research contributes to the development of image-based plant disease detection systems to support precision agriculture and fast decision-making.
Comparison of MobileNetv2 and MobileNetv3 architectures in rice leaf disease classification using transfer learning Mifthauddin, Adlim; Lutfi, Moch.; Saadah, Zulfatun Nikmatus
Jurnal Mandiri IT Vol. 14 No. 2 (2025): Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i2.459

Abstract

Rice is of the main food commodities in Indonesia that is susceptible to various leaf diseases, one of which is Bacterial Blight, Brown Spot, and Leaf Smut. Manual identification by farmers is often less accurate and time-consuming, thus requiring a technology-based detection system. The objective of this research is to categorize rice leafdiseases through the use of deep learning with a transfer learning approach based on MobileNetV2 and MobileNetV3 architectures. The dataset, comprising 4,684 rice leaf images, was divided into training and validation sets using an 80:20 ratio. Preprocessing included resizing images to 224×224 pixels, normalization, and augmentation to increase data variation. Training was carried out across 30 epochs with a mini-batch size set to 32. while applying an EarlyStopping mechanism to reduce the likelihood of overfitting. The result of the experiment indicate that MobileNetV2 reached an 96% accuracy, while MobileNetV3 outputperformed is with an accuracy of 99%. Therefore, MobileNetV3 is more effective for rice leaf disease classification.
IMPLEMENTASI PEMANFAATAN TEKNOLOGI IOT DAN BLOCKCHAIN PADA SISTEM LOGISTIK CABE Sofyan asaury; Moch. Lutfi
Jurnal Cahaya Mandalika ISSN 2721-4796 (online) Vol. 4 No. 2 (2023)
Publisher : Institut Penelitian Dan Pengambangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/jcm.v4i2.2106

Abstract

This research aims to develop a chili logistics system that utilizes the Internet of Things (IoT) and blockchain technology. This system is designed to improve the efficiency and transparency of the chili logistics process from collection, delivery, to distribution using a smartphone. IoT is used to monitor environmental conditions for storing and transporting chilies, such as temperature and humidity, so as to prevent damage to chilies. Meanwhile, blockchain technology is used to optimize transparency and security in the chili logistics process by ensuring the authenticity of products and data recorded on the blockchain. The methodology used in this study uses the prototyping method. Implementation of IoT technology with an average temperature of 30 ֯ C and 40% humidity. Also, the blockchain system in the chili logistics system can be an effective solution in increasing efficiency, transparency and security in sending chilies.
IMPLEMENTASI QR CODE PADA APLIKASI ABSEN SANTRI TERINTERGRASI WHATSAPP GATEWAY DI PONDOK PESANTREN NGALAH Mustofa, Aldi Ahmad; Lutfi, Moch.; Fahamsyah Havy, Ahmad Zulham
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5229

Abstract

Pengelompokan data dalam satu manajemen adalah proses sistematis untuk pengumpulan data dari berbagai sumber yang dikelola. Pondok Pesantren Ngalah di Kecamatan Purwosari, Kabupaten Pasuruan, menghadapi tantangan dalam mengelola absensi santri di asrama karena proses absensi manual sering kali menyebabkan kesalahan penulisan, hilangnya data, dan kesulitan dalam menyampaikan informasi kepada walisantri. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem absensi berbasis QR Code yang terintegrasi dengan Whatsapp Gateway guna meningkatkan akurasi dan efisiensi absensi. Sistem ini dirancang dengan menggunakan teknologi QR Code, sehingga setiap santri cukup memindai kode unik untuk melakukan absensi, serta memungkinkan penyampaian informasi absensi secara real-time kepada penyelia melalui integrasi dengan Whatsapp Gateway. Penelitian ini menggunakan metode deskriptif dengan pendekatan kualitatif, yang melibatkan pengamatan, wawancara, dan analisis dokumen untuk mendapatkan pemahaman lebih rinci tentang kebutuhan dalam pengelolaan absensi di Pondok Pesantren Ngalah. Dengan demikian, hasil dari sistem pengelompokan data dalam satu manajemen ini tidak hanya meningkatkan kualitas manajemen absensi, tetapi juga memperkuat komunikasi antara pihak pondok dan walisantri, serta mendukung transparansi dan akuntabilitas dalam pengelolaan kehadiran santri. Keywords: QR-Code,  Absen Santri, Manajemen Absensi, Whatsapp Gateway
GAME EDUKASI PENGENALAN ALAT MUSIK TRADISIONAL 3D UNTUK ANAK USIA DINI Jariyah, Riza Ainun; Lutfi, Moch.
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5286

Abstract

Karena kurangnya penggunaan teknologi untuk melestarikan alat musik tradisional, generasi muda tidak memiliki banyak informasi tentang musik tradisional. Pendidikan seni budaya di sekolah tingkat dasar adalah salah satu cara untuk mempertahankan budaya alat musik tradisional tetap hidup. Namun, kurangnya pengetahuan tentang alat musik tradisional menyebabkan banyak guru kesenian kesulitan menyampaikan materi pembelajaran. Terdapat dua faktor yang dapat menyebabkan pengetahuan tentang alat musik tradisional semakin terkikis, yang pertama kurangnya pemahaman tentang alat musik tradisional, dan yang kedua adalah terbatasnya fasilitas yang terkait dengan alat musik tradisional. Hal tersebut melatarbelakangi peneliti untuk merancang dan mengembangkan game edukasi pengenalan alat musik tradisional 3D. Game ini dibangun dengan menggunakan software Unity 3D sebagai game engine, multimedia development life cycle (MDLC) sebagai metode, dan pengkodingan menggunakan bahasa pemrograman C#. Hasil dari game edukasi ini membuat belajar mengenal alat musik tradisional lebih mudah dengan menggunakan teknologi augmented reality. Kata-kata kunci: Game Edukasi, Augmented Reality, Alat Musik Tradisional, Unity3D
Rancang Bangun Aplikasi Sistem Monitoring Kupon Makan Di Pondok Pesantren Ngalah Menggunakan KTS (Kartu Tanda Santri) Berbasis RFID Arrosidi, Shoffi; Lutfi, Moch.
Jurnal Ilmiah Informatika Global Vol. 14 No. 2
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v14i2.3212

Abstract

Along with the growth of the contemporary era, where technological advances occasionally experience rapid development and have provided many conveniences for mankind in everyday life. It promotes and facilitates human control of each system and can facilitate human work, including security-related tasks. One of the boarding schools in Pasuruan Regency is the Ngalah Islamic Boarding School. Pondok Ngalah was built on August 30, 1985 AD, or to coincide with Friday Pahing, the 14th of Dzulhijjah in 1405 Hijriyah, by its founder KH. M. Sholeh Bahruddin Kalam. Meal coupons are one of the most important cultures in the world of Islamic boarding schools. The meal coupon is proof that the student can take rice at the dormitory canteen. The student coupons are distributed in each dormitory and each student gets 60 coupons that can be used to collect rice within one month. In terms of each dormitory, coupons are used in one day, up to 2 coupons, but there are students who do not pay attention to the rules, and what's even worse, there are students who photocopy coupons to increase the number of coupons. Follow up with the student. Therefore, a coupon security system is needed that can be monitored by the parties concerned, namely using a tool that is already based on the Internet of Things by making a coupon security tool using KTS (Santri Identity Card). This electronic tool is designed to find out the availability of student meal coupons using RFID which produces a scanned program that can be printed in pdf format. The expected result of this test is to be able to find out the availability of student meal coupons every day.
Co-Authors Achmad Saiful Rizal Adi Winarno Ahmad Rif’an Firdaus Ahmad Zulham Fahamsyah Havy Ajid Husain, Muhammad Arief Tri Arsanto Arrosidi, Shoffi Arum Virnanda, Karisma Cahya Bagus Sanjaya Cintya Nada Anjali Elmaida Khoirotuzzuhria Indrasetianingsih, Artanti Izza, Mufidatul Jariyah, Riza Ainun Lukman Hakim Mifthauddin, Adlim Mochamad Hasyim Mohamad Ilham Mohammad Gugus Azhari Muhammad Faishol Amrulloh Muhammad Imron Rosadi Mustofa, Aldi Ahmad Nath, Gourab Rahmad Zainul Abidin Saadah, Zulfatun Nikmatus Sofyan asaury Ummi Kulsum