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All Journal International Journal of Electrical and Computer Engineering PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Sinkron : Jurnal dan Penelitian Teknik Informatika Information System for Educators and Professionals : Journal of Information System Jurnal Sisfokom (Sistem Informasi dan Komputer) JurTI (JURNAL TEKNOLOGI INFORMASI) Krea-TIF: Jurnal Teknik Informatika E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Journal of Computer System and Informatics (JoSYC) Madaniya Jurnal Kajian Ilmiah Journal of Applied Computer Science and Technology (JACOST) Jurnal Atma Inovasia Prosiding University Research Colloquium INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Jurnal Informatika Polinema (JIP)
Muhammad Resa Arif Yudianto
Universitas Muhammadiyah Magelang
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Social Sciences Other

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Classification of Tangerines on Fruit Ripening Levels Using K-Nearest Neighbor Algorithm Rasyid, Irfan; Saputra, Imam; Suryanegara, Raden Kartika Satya; Yudianto, Muhammad Resa Arif; Maimunah, M
Prosiding University Research Colloquium Proceeding of The 15th University Research Colloquium 2022: Mahasiswa (Student Paper Presentation) B
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

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Abstract

This journal reviews the classification of the maturity level of tangerines based on HSV using the K-Nearest Neighbor (KNN) method. This study aims to make it easier for the public to distinguish ripe and unripe when choosing citrus fruits and also to avoid fruit shops selling unripe oranges so as not to harm sellers or buyers. We take the data sources used in this study ourselves. In this study, we use the K-Nearest Neighbors (KNN) method. This method is used in the image classification process by relying on the results of feature extraction that have previously been trained. This method selects the nearest neighbor from the training dataset, then determines the closest distance value or the smallest distance value that will produce the classification output. The results of the accuracy in using this method have reached 93% with a value of k=7.
Classification of Avocado Ripeness Levels using Naïve Bayes Method Nuryani, Ira; Fadli, Aldi Muhammad Nur; Saputri, Nadila Dwi; Fadhilah, Alfira Nisa; Yudianto, Muhammad Resa Arif; Maimunah, M
Prosiding University Research Colloquium Proceeding of The 15th University Research Colloquium 2022: Mahasiswa (Student Paper Presentation) B
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

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Abstract

During this time most people in determining the ripeness of avocados for personal consumption is not difficult because they can distinguish themselves but another case if used for production, which requires a lot of labor to group ripe and raw avocados. One of the innovations in information and communication technology in agriculture and plantations is the use of classification methods with naïve bayes algorithms. The formula of the problem in this study is how to do the classification on the ripeness of avocados and see the accuracy rate of the data. The purpose of this study is to classify avocado ripeness and to acquire intelligent systems, so that it becomes the first step towards the implementation stage. Based on the results and analysis that has been done, it can be concluded that the Naive Bayes method is considered capable in classifying avocado ripeness by using RGB color features. The accuracy in testing using Naïve Bayes method reached 83.34%. The performance obtained from this intelligent system is also effective and efficient so that the classification of avocado ripeness can be implemented.
Pengenalan Deteksi Wajah Artificial Intelligence dan Achievement Motivation Training untuk Siswa SMK Kuncup Samigaluh Sukmasetya, Pristi; Primadewi, Ardhin; Yudianto, Muhammad Resa Arif; Maimunah, Maimunah; Hasani, Rofi Abul; Nugroho, Setiya
Jurnal Atma Inovasia Vol. 4 No. 3 (2024)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jai.v4i3.9367

Abstract

— Artificial Intelligence (AI) is a field of computer science aimed at developing machines capable of performing tasks that typically require human intelligence. In recent years, the development of AI has shown significant progress, and its use has expanded across various sectors, including education. The application of AI in education offers various opportunities and challenges, such as personalized learning and enhancing students' skills, but also presents challenges in technological adaptation and ethical understanding. This paper discusses the utilization of AI-based facial recognition technology at SMK Kuncup Samigaluh, with the goal of enhancing students' competence in information technology. This community service activity involves a series of structured stages, including initial planning, activity implementation, discussion and Q&A, as well as evaluation and feedback. The results of this activity indicate a significant improvement in students' understanding of AI and facial recognition technology, as evidenced by the increase in post-test scores compared to pre-test scores. With an interactive demonstrative approach, this activity successfully provided a positive impact on students' knowledge and interest in AI, and broadened their horizons regarding career opportunities in information technology.
Peningkatan Kompetensi Digital Guru melalui Pelatihan Pembuatan Website dengan Google Sites di SMA Ma'arif 1 Yogyakarta Yudianto, Muhammad Resa Arif; Sari, Tika Novita; Nadhir Fachrul Rozam; Dzul Fadli Rahman; Masduki Zakarijah
Jurnal Atma Inovasia Vol. 5 No. 4 (2025)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jai.v5i4.11332

Abstract

Perkembangan teknologi digital saat ini menuntut semua sektor, termasuk pendidikan, untuk beradaptasi dan memanfaatkannya dalam proses belajar mengajar. Salah satu bentuk pemanfaatan teknologi di lingkungan pendidikan adalah kemampuan guru dalam membangun identitas profesional melalui website pribadi yang juga dapat digunakan sebagai media pembelajaran. Kegiatan pengabdian masyarakat ini dilakukan di SMA Ma’arif 1 Yogyakarta dan bertujuan untuk memberikan pelatihan kepada para guru dalam membuat website pribadi menggunakan platform Google Sites. Materi pelatihan meliputi konsep pembelajaran digital, perencanaan konten, serta praktik langsung membuat dan menyusun struktur website. Selain menjadi sarana branding diri, website yang dibuat juga diharapkan mampu menjadi repositori materi pembelajaran yang dapat diakses oleh siswa kapan saja dan di mana saja. Peserta pelatihan terdiri dari guru berbagai mata pelajaran, dan sebagian besar belum memiliki pengalaman membuat website sebelumnya. Hasil kegiatan menunjukkan peningkatan pengetahuan dan keterampilan guru dalam mengelola konten digital, serta antusiasme yang tinggi dalam mengikuti pelatihan. Kegiatan ini diharapkan dapat menjadi langkah awal dalam mendorong transformasi digital di sekolah, khususnya dalam memperkuat peran guru sebagai fasilitator pembelajaran berbasis teknologi. Kata Kunci—kompetensi digital, pelatihan guru, Google Sites, media pembelajaran, website pribadi
Implementasi Metode Dempster-Shafer Untuk Deteksi Kesehatan Mental Pada Mahasiswa Berbasis Web Jalaluddin, Alif; Arumi, Endah Ratna; Sasongko, Dimas; Pinilih, Sambodo Sriadi; Yudatama, Uky; Arif Yudianto, Muhammad Resa
Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i2.4830

Abstract

Mental health is a person's soul condition to budaptasi in its environment to feel happy or get the comfort of life, so as not to experience mental disorders. Often mental health is ignored by most people because it is different from physical health that can be seen directly with the eyes and can be identified easily. Lack of awareness of mental health in the life of the people of Indonesia and the assumption that a person who goes to psychologists is a person inseasonable, often the individual who actually undergoes mental health problems reluctant to get help from experts or deny that he does not have mental health problems. Limitations of time and costs are also one of the constraints of a student reluctant to get help from experts like psychologists. Therefore, a web-based expert system is built with a dempster-shafer method to use as detection on the student and allows the user to know whether the user has a tendency of the problem on its mental health or not before the official consultation is required from the expert. Testing Accuracy Comparison System between the results of the system and experts by using 100 correspondents from students at Muhammadiyah Magelang University (UNIMMA) 89% know mental health and 65% have experienced mental disorders. The results of the SRQ29 data used and were spread among campus students, this study has used 20 sample data and produces 70% expert suit compliance. From the results of expert suitability obtained from the calculation of the system by selecting symptoms and automatically the system will calculate the accuracy of the existing Belief Valident in every symptom. Then the system will take decisions based on the results of the largest calculation value.
Co-Authors Acihmah Sidauruk Aldi Muhammad Nur Fadli Alfira Nisa Fadhilah Arazka Firdaus Anavyanto Ardhin Primadewi Arham Rahim Arif Dwi Laksito Arya Prayoga Bayu Agustian Burhanudin, Nazil Ilham Darmawan, Briga Devi Oktaviani Dimas Sasongko Dzul Fadli Rahman Ema Utami Endah Ratna Arumi, Endah Ratna Fadhilah, Alfira Nisa Fadli, Aldi Muhammad Nur Febriyanto, Yusril Hanif Al Fatta Hanif Al Fatta Hasani, Rofi Abul Imam Saputra Imam Saputra Ira Nuryani Irfan Rasyid Irfan Rasyid Jalaluddin, Alif Kusrini Kusrini Kusrini, Kusrini Lusi Nurlatifah Maimunah Maimunah Maimunah, M Maimunah, Maimunah Masduki Zakarijah Meidar Hadi Avizenna Nadhir Fachrul Rozam Nadila Dwi Saputri Nuryani, Ira R Arri Widyanto Raden Kartika Satya Suryanegara Rahmi, Alfie Nur Rasyid, Irfan Rofi Abul Hasani Sambodo Sriadi Pinilih Saputri, Nadila Dwi Setiya Nugroho Sukmasetya, Pristi Suryanegara, Raden Kartika Satya Tika Novita Sari Tuessi Ari Purnomo Tuessi Ari Purnomo Uky Yudatama, Uky Yusril Febriyanto