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All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) Jurnal Konseling dan Pendidikan Jurnal Momentum Al Ishlah Jurnal Pendidikan INVOTEK: Jurnal Inovasi Vokasional dan Teknologi Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Teknologi Informasi dan Pendidikan Journal of Applied Engineering and Technological Science (JAETS) Ranah Research : Journal of Multidisciplinary Research and Development Journal of Innovative and Creativity Jurnal Penelitian Pendidikan Indonesia
Muhammad Anwar
Universitas Negeri Padang
Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Transportation Other

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PROTOTYPE RICE DRYER UNTUK OPTIMALISASI PRODUKTIVITAS PASCAPANEN Tika Rukmana; Muhammad Anwar
Journal of Innovative and Creativity Vol. 5 No. 2 (2025)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v5i2.3059

Abstract

Drying is a critical stage in the post-harvest process of rice to maintain the quality and shelf life of the grain. In Indonesia, traditional sun-drying methods are still widely used, which are highly dependent on weather conditions and require significant time and labor. These limitations often lead to grain moisture levels exceeding the ideal range set by the Indonesian National Standard (SNI 6128:2020), which is 13–14%, thereby reducing the quality and market value of the rice. This study aims to design and implement a semi-automatic rice dryer system based on the Arduino Mega 2560 microcontroller to regulate temperature, humidity, and grain moisture levels automatically. The system utilizes DS18B20 sensors for temperature, DHT22 for humidity, and a grain moisture sensor, while controlling fans, heaters, and agitators through programmed logic. Test results show that the prototype can reduce grain moisture levels more efficiently and consistently than traditional methods, with sensor readings falling within acceptable accuracy tolerances. This tool is expected to provide an effective solution for improving rice drying quality and supporting overall farmer productivity
Implementasi Algoritma Fuzzy Tsukamoto Dalam Sistem Pendeteksi Gejala Social Anxiety Disorder Pada Mahasiswa Musfara Zahra Nadien; Muhammad Anwar; Dony Novaliendry; Randy Proska Sandra
Journal of Innovative and Creativity Vol. 5 No. 3 (2025)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v5i3.4578

Abstract

Social Anxiety Disorder (SAD) atau gangguan kecemasan sosial yang ditandai oleh rasa takut berlebihan dalam situasi sosial. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem pendeteksi gejala Social Anxiety Disorder pada mahasiswa menggunakan algoritma Fuzzy Tsukamoto berbasis web. Sistem ini memanfaatkan data hasil kuesioner berdasarkan indikator gejala kecemasan sosial yang diadaptasi dari instrumen Hamilton Anxiety Rating Scale (HARS). Proses inferensi dilakukan melalui tahapan fuzzifikasi, pembentukan rule base, inferensi fuzzy, dan defuzzifikasi untuk menghasilkan nilai crisp yang menunjukkan tingkat kecemasan sosial. Metode pengembangan yang digunakan adalah Waterfall, yang meliputi tahap analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Pengujian sistem dilakukan terhadap 20 responden mahasiswa. Hasil implementasi menunjukkan bahwa sistem mampu mengklasifikasikan tingkat kecemasan, yaitu tidak ada kecemasan, ringan, sedang, berat, dan sangat berat. Berdasarkan hasil validasi, diperoleh tingkat kesesuaian sebesar 90% antara hasil sistem dan hasil penilaian manual menggunakan metode HARS. Dengan demikian, sistem ini dapat digunakan sebagai alat bantu deteksi dini gangguan kecemasan sosial pada mahasiswa secara mandiri serta sebagai media pendukung pemantauan kesehatan mental di lingkungan kampus.
Effectiveness of STEM-Oriented Project-Based Learning Modules in Visual Communication Design to Support Science and Technology Skills in Vocational Education Deliana; Muhammad Anwar
Jurnal Penelitian Pendidikan IPA Vol 11 No 4 (2025): April
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i4.10542

Abstract

This study aims to develop and evaluate the effectiveness of a STEM-oriented entrepreneurship-based learning module using a Project-Based Learning (PjBL) model in the Basic Principles of Design and Visual Communication subject at SMK Negeri 2 Guguak. The research used the Research and Development (R&D) method with the 4D model (Define, Design, Develop, Disseminate). Data were collected through observations, expert validations, and pretest-posttest experiments involving teachers and students. The module received high feasibility ratings from media experts (4.87) and material experts (4.89). Practicality tests showed very practical results from both teachers (97.38) and students (87.11). Effectiveness was confirmed through a Paired Samples Test with significant improvements in student learning outcomes (Sig < 0.005; t-value > t-table). In conclusion, the developed module is valid, practical, and effective in improving learning outcomes and integrating STEM-based competencies in vocational education.
A Aplikasi Web untuk Klasifikasi dan Deteksi Penyakit Daun Tomat Menggunakan Model CNN dan YOLO Dony Novaliendry; Fachri Rizal; Muhammad Anwar; Dedy Irfan
Jurnal Teknologi Informasi dan Pendidikan Vol. 19 No. 1 (2026): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v19i1.1073

Abstract

This study developed a web-based application for the classification and detection of tomato leaf diseases using Convolutional Neural Network (CNN) and You Only Look Once (YOLO) models. The research followed a Research and Development approach that consisted of requirement analysis, system design, implementation, model training, and testing. The CNN model was trained to classify tomato leaf images into specific disease categories, while the YOLO model was designed to detect and localize diseased areas in real time. Both models were integrated into a Flask-based web system to provide accessible and interactive functionality through standard web browsers. Testing results showed that the CNN model achieved an accuracy of 96.1%, effectively identifying disease types such as Early Blight and Bacterial Spot. The YOLO model reached a mean Average Precision (mAP) of 87.3% for real-time detection, successfully locating and labeling infected regions on tomato leaves. The integration of CNN and YOLO models demonstrated strong classification and detection performance, offering an efficient and scalable solution to support early disease diagnosis and digital transformation in precision agriculture.
Co-Authors Ali Basrah Pulungan ARIF KURNIAWAN Dedy Irfan Deliana Delvi Sonda Dony Novaliendry Dwi Suryani Alfa Dwiprima Elvanny Myori Elsa Sabrina Fachri Rizal Fahmi Rizal Fakhrur Rozi Fitria, Yanti Habbieb Abdullah Hamdani Hamdani Hanifa Hanifa Hastuti Hastuti Ika Puspa Yulistiowarno Lena Susianti Mery Sumiati Muhammad Azisan Muhammad Irsyad Musfara Zahra Nadien Nikhel Purnama Delfa Nurul Syafika Oktavia Delvira Oktavia Suci Rahma Qotrun Nada Fitri Adisva Randy Proska Sandra Regina Aprilia Rimo Handriyatma Sri Ardiyanti Tika Rukmana Waskito Yasdinul Huda Yeka Hendriyani Zhafranul Nafis Zulhijra Rahma Dia