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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences JPTK: Jurnal Pendidikan Teknologi dan Kejuruan Jurnal Teknik IPTEK The Journal for Technology and Science TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Edukasi dan Penelitian Informatika (JEPIN) ELINVO (Electronics, Informatics, and Vocational Education) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Applied Information System and Management Indonesian Journal of Electrical Engineering and Computer Science Lontara: Journal of Health Science and Technology Jurnal Algoritma International Journal of Community Service (IJCS) International Journal of Scientific Multidisciplinary Research (IJSMR) Lontara Journal Of Health Science And Technology Journal of Information Engineering and Technology

Fatchul Arifin

Universitas Negeri Yogyakarta

Author-ID : 232627

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy 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 Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Pengembangan Media Pembelajaran Kendali Fuzzy Logic Berbasis Arduino Nano Pada Mata Kuliah Praktik Sistem Kendali Cerdas Prabowo, Hernawan; Arifin, Fatchul
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 3 No. 1 (2018): May 2018
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Dewasa ini berbagai aplikasi dalam bidang industri yang canggih banyak menggunakan kecerdasan buatan. Mata kuliah praktik Sistem Kendali Cerdas di Jurusan Pendidikan Teknik Elektronika & Informatika FT UNY memerlukan sebuah media pembelajaran yang terintegrasi antara hardware dan software agar kualitas pembelajaran sesuai dengan tuntutan dunia Industri. Hasil penelitian ini untuk menghasilkan media pembelajaran kendali fuzzy logic yang teruji kinerja dan kelayakannya pada mata kuliah praktik Sistem Kendali Cerdas. Pendekatan penelitian menggunakan Research and Development dengan 9 tahapan prosedur pengembangan meliputi: (1) potensi dan masalah, (2) pengumpulan data, (3) desain produk, (4) validasi desain, (5) revisi desain, (6) ujicoba produk, (7) revisi produk, (8) ujicoba pemakaian, dan (9) revisi produk. Hasil penelitian diketahui bahwa: (1) media pembelajaran kendali fuzzy logic yang dirancang terdiri dari hardware berbasis Arduino Nano dilengkapi jobsheet dengan pemrograman menggunakan Arduino IDE dan library yang mudah untuk dipelajari, (2) Unjuk kerja media pembelajaran sudah berfungsi dengan stabil baik pada setiap bagian maupun secara keseluruhan, (3) Tingkat kelayakan media dan materi memperoleh nilai 86% dan 96%. Tingkat kelayakan pemakaian berdasarkan uji pemakaian kepada 15 mahasiswa diperoleh nilai 85% termasuk dalam kategori sangat layak. Hal ini berarti media pembelajaran ini sangat layak digunakan pada mata kuliah praktik Sistem Kendali Cerdas.

ASRO (Amphibious Spy Robot): Prototipe Robot Amfibi Pengintai dengan First Person View dan Sistem Navigasi berbasis Sensor Kompas Rajif, R. Amirur; Arifin, Fatchul
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 4 No. 2 (2019): November 2019
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Robots have an important role in all aspects of life, including the military field. The purpose of making this final project are building hardware and software of robot and to know the performance of robots. The method used in making the final project consists of identifying and analyzing requirements, designing and manufacturing hardware and software, and testing. The result of the performance of ASRO is that, the buoyancy force of the robot is greater than the weight of the object, namely Fa = 22,808 N and W = 15,696 N or Fa> W which makes the robot float while operate in the water field. The maximum range of control system robot is as far as 0-30 meters without obstacles and 0-15 meters with obstacles, while the monitoring system is as far as 0-75 meters without obstacles and 0-30 meters with obstacles. The Robot navigation system has a percentage of accuracy of reading 93.3% and the percentage response of the average robot when rotating 90â° is 100%, rotating 180â° is 100%, and rotating 270â° is 100%.

Prototipe Kursi Roda Elektrik dengan Kendali Joystick dan Smartphone Junior, Andy Sadewa; Arifin, Fatchul
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 4 No. 1 (2019): May 2019
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Wheelchairs are one of the walking aids for people with disabilities and also for people who are unable to move from one place to another. The purpose of this research was to build hardware and software into a wheelchair prototype that can be controlled with joysticks and smartphones and to know its performance. The method in making the final project consists of the stages of need identification, requirements analysis, system design, tool making, tool testing and data collection. Based on the testing that has been done, the results are obtained that the control input from the smartphone through the application and also the joystick produces the output of the wheelchair prototype movement according to the instructions that have been set as input. The maximum distance of the control system from the smartphone is 0-10 meters either with obstacles or without obstacles. The response of the wheelchair prototype device has an average error of 0.024. Smartphone applications that are used as controls can be installed on the latest Android version "Nougat" and 4 versions of Android below. The speed of the wheelchair prototype on the joystick control matches the value of the resistance issued by the joystick module.

Pengembangan Media Pembelajaran Berbasis Role Playing Game (RPG) Untuk Siswa Kelas X SMK Negeri 3 Yogyakarta Swadyaya, Putu Yana; Arifin, Fatchul
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 4 No. 2 (2019): November 2019
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

The purpose of this study is to develop a game like learning media program about resistor's color code reading and simple resistor circuits made in RPG Maker MV game engine for grade X vocational school student. The developed learning media includes: learning media program, student workbook, and a complementary module book. The method of research and development is used in this study. Descriptive analysis was used on the feasibility analysis of learning media. Result of experts and users test validation stated that the developed learning media is in the feasible category based on all validated and tested aspects. First educational expert's assessment shows feasibility level of 93.04% (Very Feasible). Second educational expert's assessment shows feasibility level of 72.17% (Feasible). First media expert's assessment shows feasibility level of 86.65% (Very Feasible). Second media expert's assessment shows feasibility level of 89.29% (Very Feasible). User trial assessment shows feasibility level of 78.52% (Feasible)

Classification of Organic and Inorganic Waste Types Based on Neural Networks Arifin, Fatchul; Habiburrahman, M.; Gusti, Wahyu Ramadhani
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 8 No. 1 (2023): Mei 2023
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.v8i1.53284

Garbage is the residue of unused industrial production and household consumption. In Indonesia, waste is divided into 2 types, namely organic and inorganic waste. The two types of waste can be recycled in diverse ways, so they must be separated. So far, it is often difficult for the community to sort waste. This paper presents the process of recognizing and sorting waste automatically by utilizing Artificial Intelligence technology, especially Artificial Neural Networks (ANN). The ANN architecture used in this study consists of 4 layers. The number of neurons in each layer consists of 3 neurons in the input layer, 4 neurons in the hidden layer-1, 4 neurons in the hidden layer-2 and 1 neuron in the output layer. The ANN model that has been designed is trained, so that the best weight and bias model will be obtained, which in turn gives the ANN the ability to be able to sort waste properly. The best weights and biases will then be implanted into the Arduino UNO Microcontroller hardware. In this developed system, the microcontroller is given input obtained from 3 kinds of sensors, namely capacitive proximity, inductive proximity, and photodiode. While the input consists of 2 pieces of organic or in organic waste conditions. From the test results, it was found that the system has 100% training accuracy and 100% test accuracy.

Komparasi Beberapa Algoritma Machine Learning untuk Klasifikasi Sentimen Pengguna X (Twitter) Terkait Isu Kabur Aja Dulu Ramadhan, Rayhan Dwi; Arifin, Fatchul
Journal of Information Engineering and Technology Vol. 3 No. 2 (2025): September 2025
Publisher : Department of Electronics and Informatics Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jiety.v3i2.2160

Penelitian ini bertujuan untuk menganalisis sentimen pengguna media sosial X (Twitter) terhadap isu “Kabur Aja Dulu” serta membandingkan performa beberapa algoritma machine learning dalam mengklasifikasikan sentimen tersebut. Penelitian ini menggunakan pendekatan kuantitatif dengan kerangka kerja SEMMA (Sample, Explore, Modify, Model, Assess). Data dikumpulkan melalui teknik crawling menggunakan tools Tweet Harvest dan diproses melalui tahapan preprocessing seperti pembersihan data, normalisasi, tokenisasi, dan stemming. Pelabelan sentimen dilakukan dengan pendekatan lexicon-based menggunakan InSet Lexicon, sementara proses ekstraksi fitur menggunakan Term Frequency–Inverse Document Frequency (TF-IDF). Untuk mengatasi ketidakseimbangan kelas, diterapkan metode Synthetic Minority Oversampling Technique (SMOTE). Enam algoritma diuji, yaitu Support Vector Machine (SVM), Logistic Regression, Naive Bayes, Random Forest, Decision Tree, dan K-Nearest Neighbors (KNN). Hasil penelitian menunjukkan bahwa mayoritas sentimen bersifat negatif. Algoritma SVM menghasilkan akurasi terbaik sebesar 80%, diikuti oleh Logistic Regression (77%) dan Random Forest (75%). Temuan ini menunjukkan bahwa SVM paling efektif digunakan dalam klasifikasi sentimen terkait isu sosial, dan dapat menjadi acuan dalam pengembangan sistem pemantauan opini publik.

Optimizing VR-UX: analysis and adaptive recommendations for enhancing immersion and reducing motion sickness Aji Purnomo, Fendi; Arifin, Fatchul; Surjono, Herman Dwi
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1181-1191

This study presents an adaptive recommendation framework to enhance comfort and immersion in virtual reality (VR) by actively reducing motion sickness. Unlike prior research that views VR user experience (UX) as static, this approach integrates statistical analysis with dynamic system design. Using a Kaggle dataset of 1,000 entries, we applied descriptive statistics, Spearman correlation, Kruskal-Wallis tests, and regression to explore relationships among session duration, motion sickness, immersion, headset type, and user demographics. Findings show that session duration alone does not significantly predict motion sickness or immersion (R²=0.00, p>0.05), but certain user profiles, such as individuals over 30 using PlayStation VR, are more prone to discomfort. These insights inform a four-module framework: user profiling, real-time duration monitoring, rule-based adaptation logic (such as slowing navigation speed or adding a virtual nose for visual stability), and personalized in-VR recommendations. The system is compatible with Unity and Unreal Engine and integrates with commercial headset software development kits (SDKs). Future validation will use A/B testing, standardized questionnaires, simulator sickness questionnaire /immersion presence questionnaire (SSQ/IPQ), and physiological metrics. This work shifts VR design toward personalized, responsive systems that prioritize user well-being and immersive engagement.

Pengembangan Nutri-Bumil dengan Model APPED Berbasis Website Terintegrasi Chatbot sapina, Sapina; Mashoedah; Dwi Kurniawan, Prabowo; Arifin, Fatchul; Syaiful Rijal, Bait
Jurnal Teknik Vol 23 No 2 (2025): Jurnal Teknik
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37031/jt.v23i2.731

This study aims to develop the Nutri-Bumil System, a web-based nutrition intake monitoring service for pregnant women integrated with a chatbot. The system development employed a Research and Development (R&D) approach using the APPED model (Analysis, Planning, Production, Evaluation, and Distribution). The research instruments included validation by content experts and media experts using a 4-point Likert scale, which was converted into percentages to assess the system’s feasibility based on the ISO/IEC 25010 software quality standards in the aspects of Usability, Functional Suitability, and Performance Efficiency. The validation results showed that content experts rated the system at 80.71% for Usability, 82.65% for Functional Suitability, and 76.78% for Performance Efficiency, which fall into the categories of Feasible and Fairly Feasible. Meanwhile, media experts provided scores of 80%, 85.41%, and 87.5%, all of which are categorized as Feasible. These findings indicate that the developed Nutri-Bumil system meets the software quality aspects in terms of ease of use, functional suitability, and performance efficiency. Overall, the system is declared Feasible for use as an adaptive, accurate, and efficient digital nutrition service supporting the needs of pregnant women and nutrition professionals.

Reviewing The Combination of Case-Based Reasoning and Machine Learning for Improving a Decision Support System Hendri Maradona; Fatchul Arifin; Sri Andayani
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v9i1.48904

This study investigates the integration of case-based reasoning (CBR) with machine learning (ML) to enhance decision support systems. Due to the inadequate synthesis of empirical data in this domain by previous research, we undertook a systematic review of 46 indexed journal articles published between 2019 and 2024. The review adhered to PRISMA principles to ensure a transparent and rigorous selection and analysis procedure. We analyzed integration architectures and documented performance results, application areas, and persistent implementation challenges. The research indicates that hybrid CBR-ML systems typically surpass single-method systems in accuracy, precision, and flexibility, with an average improvement of approximately 7% over CBR-only systems. Sequential and ensemble approaches typically demonstrate effectiveness, though weighted hybrid designs often achieve superior precision and recall, particularly in complex problem domains such as healthcare and finance where accuracy is critical. Researchers based in Asia authored the majority of the reviewed studies, with contributions from Europe and Africa following. These regions concentrated high-impact applications in healthcare, finance, manufacturing, and environmental management. Notwithstanding these developments, several enduring challenges persist, including substantial computational demands, vulnerability to variations in data quality, and the continuing scarcity of clearly articulated evaluation protocols, which hinder the effective implementation of high-impact applications across these regions. Overall, existing findings suggest that integrating reasoning-oriented approaches with learning-based methods can yield a balanced trade-off between predictive accuracy and interpretability.

Implementasi SMOTE pada Klasifikasi Email Spam Menggunakan Algoritma Machine Learning Berbasis TF-IDF Moh Ali Aljauhari; Fatchul Arifin
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3246

Class imbalance is a major challenge in email spam detection, causing classification models to be biased toward the majority class. This study examines the effectiveness of the Synthetic Minority Over-sampling Technique (SMOTE) on six machine learning algorithms—Naive Bayes, SVM, KNN, Logistic Regression, Random Forest, and XGBoost—using TF-IDF feature representation. Test results show that synthetic data balancing successfully improved the sensitivity of linear models (SVM and Logistic Regression) with a recall value exceeding 49.1%, overcoming the failure to predict the minority class in the original dataset. KNN recorded the highest F1-score (0.436), while Random Forest provided the best class separation stability with an AUC-ROC of 0.601. The main contribution of this study is to demonstrate that although SMOTE improves minority class detection capabilities, its effectiveness on high-dimensional text data remains limited by feature sparsity constraints that trigger class overlap.

Co-Authors Agus Setyawan Al Matiin, Muhammad Azril Haidar Alam Rahmatulloh Alfath, Muhammad Rofiq Banu Ali Sophian Ali Sophian Anggun Winursito Anis Nurashikin Nordin Ardy Seto Priambodo Aris Nasuha Arselan Ashraf Arselan Ashraf Bekti Wulandari Caryn, Femilia Hardina Dessy Irmawati Dwi Kurniawan, Prabowo Dwi Marlina Dyah Muslihah Erman Agusta, Gino Faisal Ahmed Assaig Fauziah, Khasna Nur Fendi Aji Purnomo Gunawan, Rohmat Gunawan, Teddy Surya Gusti, Wahyu Ramadhani Habiburrahman, M. Hazlan, Mohamed Alfian Al-Zikry Hendri Maradona, Hendri Herjuna Artanto Herman Dwi Surjono Indradewa, Rhian Iskandar, Ranu Jonas de Deus Guterres Junior, Andy Sadewa Kartiwi, Mira Lahiya, Indah Wardati Malik Arman Morshidi Mashoedah Mashoedah Mauridhy Hery Purnomo Mir Suhail Alam Mira Kartiwi Mira Kartiwi Moh Ali Aljauhari Mohamed Hadi Habaebi Mohamed Hadi Habaebi Muhammad Faozan Mulad Khalik Muhammad Rofiq Banu Alfath Muslikhin Ningrum Astriawati Nur Hasanah Pahtoni, Tri Yuli Prabowo, Hernawan Prasetyo Prasetyo Raharjo, Muhammad Mukti Rahmahwati, Febri Suci Rajif, R. Amirur Ramadhan, Rayhan Dwi Rashidah Funke Olanrewaju Richard Sambera Sagala Rizal, Randi Rosminazuin Ab. Rahim Rozainanee Mohd Zain sapina, Sapina Sri Andayani Suprapto Suprapto Swadyaya, Putu Yana Syaiful Rijal, Bait Teddy Surya Gunawan Teddy Surya Gunawan Teddy Surya Gunawan Teddy Surya Gunawan Tri Arief Sardjono Yaacob, Mashkuri Zainal Arifin Zainihariyati Mohd Zain

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