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All Journal e-Dinamis ELT Worldwide: Journal of English Language Teaching KAREBA : Jurnal Ilmu Komunikasi Jurnal Penelitian Sains JURNAL MEDIA INFORMATIKA BUDIDARMA BERDIKARI : Jurnal Inovasi dan Penerapan Ipteks UICELL Conference Proceeding Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat IJISH (International Journal of Islamic Studies and Humanities) LISANAN ARABIYA: Jurnal Pendidikan Bahasa Arab Mobile and Forensics Signal and Image Processing Letters Jurnal Ilmiah Permas: Jurnal Ilmiah STIKES Kendal English Teaching and Linguistics Journal (ETLiJ) Al-Fathin: Jurnal Bahasa dan Sastra Arab Letters in Information Technology Education (LITE) Jurnal Kesehatan Tambusai Jurnal Jarlit JTechLP El 'Aailah Journal Medical Informatics Technology Bulletin of Social Informatics Theory and Application International Journal of Business English and Communication (IJoBEC) Jurnal Literasi dan Pembelajaran Indonesia Celebes Journal of Language Studies QOSIM: Jurnal Pendidikan, Sosial & Humaniora Journal of Sustainable Community Development GEMBIRA (Pengabdian Kepada Masyarakat) Multidisciplinary Indonesian Center Journal Journal on Mathematics Education Signal and Image Processing Letters Axiology
Ahmad Azhari
Unknown Affiliation
Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Performance Comparison of Three Classification Algorithms for Non-alcoholic Fatty Liver Disease Patients Using Data Mining Tool Octaviantara, Adi; Abbas, Moch Anwar; Azhari, Ahmad; Riana, Dwiza; Hewiz, Alya Shafira
Journal Medical Informatics Technology Volume 1 No. 1, March 2023
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v1i1.2

Abstract

This study aims to carry out a comparative analysis of the three classification algorithms used in research on Nonalcoholic Fatty Liver Disease (NAFLD) Patients. NAFLD is a liver condition associated with the accumulation of fat in the liver in individuals who do not consume excessive alcohol. The algorithms used in the analysis are Decision Tree, Naïve Bayes, and k-Nearest Neighbor (k-NN), with data processing using RapidMiner software. The data used is sourced from Kaggle which comes from the Rochester Epidemiology Project (REP) database with research conducted in Olmsted, Minnesota, United States. The measurement results show that the Decision Tree algorithm has an accuracy of 92.56%, a precision of 93.24%, and a recall of 99.08%. The Naïve Bayes algorithm has an accuracy of 89.93%, a precision of 95.40% and a recall of 93.56%. While the k-Nearest Neighbor algorithm has an accuracy of 91.33%, a precision of 91.94%, and a recall of 99.27%. ROC curve analysis, all algorithms show "Excellent" classification quality. However, only the k-NN algorithm reached 1.0, showing excellent classification results in solving the problem of classifying Nonalcoholic Fatty Liver Disease patients. This study concluded that the k-NN algorithm is a better choice in solving the problem of classifying Non-alcoholic Fatty Liver Disease patients compared to the Decision Tree and Naïve Bayes algorithms. This study provides valuable insights in the development of classification methods for the early diagnosis and management of NAFLD.
Reconstruction Old Students Image Using The Autoencoder Method Negara, Candra Putra; Zaman, Azmi Badhi’uz; Setiawan, Dimas Aji; Azhari, Ahmad
Letters in Information Technology Education (LITE) Vol 5, No 2 (2022)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um010v5i22022p51-54

Abstract

Image Processing is image processing with a digital computer to produce new images according to the user's wishes. One implementation is to reconstruct the image. Through the extraction stages are able to get the characteristics of an image. The algorithm used is Adam Optimization, which is an extension of the stochastic gradient reduction that has just seen wider adoption for deep learning applications in computer vision and natural language processing. In this study using the autoencoder technique, which is one variant of artificial neural networks that are generally used to "encode" data. Autoencoder is trained to be able to produce the same output as the input. This image reconstruction aims to process an image whose quality is not very clear to be clear. This if possible can be used to detect someone's face from a distance of photos. In reconstructing this image through the encode and decode process by defining Conv2D and Maxpool, it is processed into training with epoch 100 times while for the prediction process using Keras library. Then the last one gets an accuracy of 0,022. The final result is the output of the reconstructed image and calculation graph.
Reconstruction Old Students Image Using The Autoencoder Method Azhari, Ahmad; Negara, Candra Putra; Zaman, Azmi Badhi'uz; Setiawan, Dimas Aji
Letters in Information Technology Education (LITE) Vol 6, No 1 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um010v6i22023p1-5

Abstract

Image Processing is image processing with a digital computer to produce new images according to the user's wishes. One implementation is to reconstruct the image. Through the extraction stages can get the characteristics of an image. The algorithm used is Adam Optimization, an extension of the stochastic gradient reduction that has seen wider adoption for deep learning applications in computer vision and natural language processing. In this study, we use the autoencoder technique, one variant of artificial neural networks generally used to "encode" data. The autoencoder is trained to produce the same output as the input. This image reconstruction aims to process an image whose quality is not very clear, to be precise. This, if possible, can be used to detect someone's face from photos. In reconstructing this image through the encode and decode process by defining Conv2D and Maxpool, it is processed into training with epoch 100 times while for the prediction process using Keras library. Then, the last one gets an accuracy of 0,022. The result is the output of the reconstructed image and calculation graph
Training Abroad on Developing E-portfolio for Thai Teachers: Lessons Learned Ali, Raden Muhammad; Hastuti, Dwi; Azhari, Ahmad; Biddinika, Muhammad Kunta
UICELL No 7 (2023): UICELL Conference Proceedings 2023 (in progress)
Publisher : Universitas Muhammadiyah Prof. DR. HAMKA

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

Abstract

International programs by university lecturers in Indonesia, both research and community service, are currently highly encouraged. This kind of international program is believed to provide many benefits such as: increasing cooperation networks both academically and non-academically. In its implementation, not all international programs run smoothly as planned. There are various problems faced by the organizers caused by differences in language, culture, rules, etc. This article will reveal the author's experience in organizing an international training program on developing electronic portfolio ( e-portfolio) especially for English and Arabic teachers in Thailand, covering challenges and lessons learned that come with it. This study uses a qualitative narrative approach with data collection through observation, interviews, and documentation. The data analysis technique is based on the theory of Miles and Huberman which includes: data reduction, data display, and conclusion drawing/verification. The findings of this study are the constraints and lessons that can be drawn from this training. Some of the obstacles faced are preparation that requires sufficient time, language barriers, and differences in culture and rules in the two countries. Some lessons that can be taken from this experience are: international programs require sufficient time and careful preparation, it needs language mastery for facilitators according to the language of the trainees, and the rules and culture of the partner country or school need to be understood so that there is no misunderstanding between the organizer and the partner. Keywords : international program, electronic portfolio, training for teachers, challenges, lessons learned
K-Means for Majoring Informatics Students' Interests Based on Brainwave Signals Robin, Qori Aulia; Azhari, Ahmad
Mobile and Forensics Vol. 5 No. 1 (2023)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v5i1.6629

Abstract

This study investigates the potential of utilizing EEG (electroencephalogram) as a determinant for the specialization choices of Informatics students. EEG, measuring brain activity patterns, is employed to discern majors of interest among students. A questionnaire revealed that some students opt for specializations due to class availability and peer influence, leading to potential mismatches between their abilities and interests, consequently affecting their final project or thesis. EEG data from 30 respondents, recorded using NeuroSky Mindwave and MyndPlayer Pro software, were subjected to K-Means Clustering after feature extraction through PCA. However, the evaluation using Silhouette indicated a low score of 0.453, possibly due to significant distance between cluster data and centroids, minimal dataset size, and random respondent selection without considering their specific areas of interest. This suggests limitations in using EEG alone for determining specialization choices, necessitating further refinement and integration with additional factors for more accurate predictions.
Improved Breadth First Search For Public Transit Line Search Optimization Kartoirono, Suprihatin; Riadi, Imam; Furizal, Furizal; Azhari, Ahmad
Mobile and Forensics Vol. 5 No. 1 (2023)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v5i1.7906

Abstract

People in general find it difficult to determine the transportation route, because to get to one destination there are many alternative paths that must be passed. This study aims to model the search for alternative bus route routes that are faster to produce routes that must be passed. The method used in this study is Improved Breadth first search by modifying BFS so that its performance is improved in producing route search completion. The improved BFS method is basically the same as BFS doing a level-by-level search stop if a false finish point is found. As the experiment above with a starting point of 175 and an end point of 54 the BFS algorithm takes 27 seconds 564 milliseconds, while the Improve BFS algorithm takes 171 milliseconds. The results showed that improved BFS can improve the performance of the BFS method. Research can be a model to be applied to other optimal route finding cases.
Development of Mandarin Education Quiz Game Using Android-Based Multimedia Development Life Cycle Topani, Muhammad Alfikri Maida; Azhari, Ahmad
Mobile and Forensics Vol. 5 No. 2 (2023)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v5i2.7947

Abstract

Mandarin is a language that is widely spoken and studied by people all over the world. Parents who start enrolling their children in Mandarin language courses from an early age with the hope that their children will become accustomed and proficient in using Mandarin. However, for elementary school children, the difficulty of constructing sentences in Mandarin is a major obstacle for children in the process of learning Mandarin. The purpose of this research is to create a unity-based mandarin quiz educational game application that is useful as an alternative media in the learning process to make it easier to learn. which is useful for a. Help make it easier for tutors in learning activities teaching by utilizing media technology in the form of Android-based educational games. Help students learn Chinese HSK material with a happy feeling and don't feel bored, because the content in the educational game "Mandarin Quiz" is displayed in an attractive way with audio, animation, and games on an Android smartphone. Helping children's enthusiasm for learning to know Mandarin. System development for users will be developed using the Multimedia Development Life Cycle (MDLC) methodology. Each step or stage of this method is suitable for system development in multimedia applications and these stages can swap positions according to research needs. It is hoped that the results of testing and designing the Mandarin Quiz educational game application using Unity 2D can be further developed so that this application can help increase interest in learning. The test results and feasibility of this educational game used the Usability Scale System (SUS) which consisted of 46 functions with 10 questions, the final test result was obtained with a score of 88, so that the mandarin quiz educational game was declared acceptable.
EEG Classification for Brain Response Analysis through University Website Interface in Yogyakarta Using Naive Bayes and KNN Suhail, Faiq; Azhari, Ahmad
Mobile and Forensics Vol. 6 No. 1 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v6i1.9056

Abstract

One of the challenges high school students face is the abundant availability of information about various campuses through different media, making it difficult to accurately predict their interest in a particular campus. Electroencephalogram (EEG) technology can read human brain activity, such as when students access information on a campus website. The Naive Bayes and K-Nearest Neighbor (KNN) methods can be employed to predict student interest in a campus based on EEG signals recorded while they browse the official campus website. Naive Bayes is known for achieving high accuracy with small datasets, whereas KNN excels at classifying noisy data. These two methods offer variables that can be directly compared. Classification using Naive Bayes and KNN achieved the highest accuracy score of 92%. The most appropriate algorithm is determined by evaluating performance using a confusion matrix. In this case study, Naive Bayes slightly outperformed KNN, as evidenced by precision, recall, and f1-score matrices. The Naive Bayes method resulted in an F1-score of 94%, compared to KNN’s 92%.
Rediscover Story Of Muhammadiyah Through 3D Game By Applying Game Development Life Cycle Hafizh, Achmad Nur; Azhari, Ahmad
Mobile and Forensics Vol. 6 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v6i2.11388

Abstract

Though specifically in Indonesia, Muhammadiyah is already well known but there are still some who do not know their history. This makes people that do not know about Muhammadiyah and the history behind it to make unfounded assumptions about the Islamic refined organization. The purpose is to make an educational game based on Muhammadiyah Museum to further increase the wisdom of players about Muhammadiyah’s history and also to remember and know the history behind each artifact is visualized in form of a game to increase the player’s knowledge. The game development for players will be developed using the Game Development Life Cycle (GDLC) methodology and mostly the modelling technique that will be used is mesh modelling technique in Blender. Each step of this methodology is fitting for the game development and the step might be skipped or swapped according to the needs of research. There are 2 black box tests conducted, the first black box test that has 15 functions result is 47% in accordance with several bugs found which was fixed in the second black box test that resulted 87% in accordance, 13% not in accordance because of the feature was not yet implemented but listed in the main menu. The second test conducted which results and practicality of this educational game using the System Usability Scale (SUS) which consists of 10 instrument statements were scored 85.3 which means that this educational game was declared excellent and acceptable.
Penyuluhan dan Penyebaran Media Video sebagai Upaya Pencegahan Penyakit Tuberkulosis (TBC) pada Masyarakat di Kelurahan Pondok Betung Kota Tangerang Selatan Lubis, Dhian Wahyudi; Azhari, Cindy; Kamal, Sofia; Syahriyah, Shilfia Fadhilatul; Putri, Zelza Alifvia Samudera; Azhari, Ahmad; Nabila, Ai; Safitri, Bunga; Faizah, Faizah; Darmawansyah Alnur, Rony
Journal of Sustainable Community Development Vol. 2 No. 3 (2024): Journal of Sustainable Community Development
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13889995

Abstract

Tuberkulosis adalah penyakit menular yang berpotensi mematikan. Jika tidak dicegah, infeksi dapat menyebar luas. Tujuan pengabdian masyarakat di Kelurahan Pondok Betung ini adalah meningkatkan kesadaran masyarakat tentang pencegahan tuberkulosis. Kegiatan diawali dengan brainstorming bersama Puskesmas dan Kelurahan, dilanjutkan koordinasi dengan kader, program intervensi, dan evaluasi. Sasaran program adalah masyarakat Pondok Betung. Intervensi dilakukan melalui penyuluhan dan penyebaran video edukasi di WhatsApp. Penyuluhan dievaluasi dengan pre-test dan post-test untuk menghitung nilai mean, median, serta z-score, dan hasil dianalisis menggunakan uji Wilcoxon. Terdapat peningkatan signifikan pada pengetahuan masyarakat dengan p-value <0,001. Sementara itu, video edukasi disebarkan ke 16 grup WhatsApp dan 679 orang telah menontonnya, menunjukkan keberhasilan distribusi informasi melalui media video.
Co-Authors Abbas, Moch Anwar Adys, Himala Praptami Affan, Dhava Chairul Agus Aktawan, Agus Ahmad Barizi Ali, Raden Muhammad Ammattulloh, Fathia Irbati Ammatulloh, Fathia Irbati Ammatulloh, Fathia Irbati Anantatama, Surya Andi Hajar Andi Kamariah Arief, Husniah Arwinsyah Arwinsyah, Arwinsyah Asfah, Indrawaty Asriati Ayu .H, Sendi Sandra Azhari, Cindy Azwar Abbas Bakri Muhammad Bakhiet Budiarti, Gita Indah Danial Hilmi Darmawansyah Alnur, Rony Darmiany Destiyanti, Intan Dharma Ariawan, Ade Dwi Hastuti Dwi Normawati, Dwi Dwiza Riana Dzaki , Arif Rahman Eirene, Jessica Endo, Hiroyuki Endri Junaidi, Endri Enok Sureskiarti Fadlansyah, Holy Faizah Faizah Fariza, Riska Fika Novatiana Furizal, Furizal Gesbi Rizqan Rahman Arief Hadi Saputra Hadi, Muhammad Saepul Hafizh, Achmad Nur Hafizh, Muhammad Naufal Hewiz, Alya Shafira Himala Praptami Adys Husniati Husniati, Husniati Imam Riadi Insan Kamil Sinaga Ismail Ismail Jamilah Jamilah Jaya, Erlangga Jefree Fahana Kamal, Mustapa Kamal, Sofia Kamariah, Andi Kartoirono, Suprihatin Khosyi'ah, Siah Kusaka, Satoshi Kyswantoro, Yunita Firdha Lubis, Dhian Wahyudi Mahmuddin Adriansyah Milkhatun, Milkhatun Muhammad Fahri Jaya Sudding Muhammad Kunta Biddinika Murein Miksa Mardhia Musdalifah Musdalifah Musdalifah Nabila, Ai Negara, Candra Putra nisa, Anisa Shahratul Jannah Nugroho, Prasetiyanto Nur Fatimah Nur Robiah Nofikusumawati Peni Nurfitrah Nuril Anwar, Nuril Octaviantara, Adi Pangistu, Lalu Arfi Maulana Purnaramadhan, Riza Putri, Zelza Alifvia Samudera RAMADAN, RIZKY Robin, Qori Aulia Rosyid A.A, Achmad Rully Charitas Indra Prahmana Safitri, Bunga Sahadi, Syah Reza Pahlevi Sembiring, Surya Anantatama Seny Luhriyani Sunusi Seny Luhriyani Sunusi Setiawan, Dimas Aji Son Ali Akbar Soviyah Sudding, Muhammad Fahri Jaya Suhail, Faiq Surya Anantatama Sembiring Suryanto, Imam Suryanto, Indra Swara, Ajie Kurnia Saputra Syafatullah, Muhammad Rafli Syafrina Lamin, Syafrina Syahriyah, Shilfia Fadhilatul Syuhadak Syuhadak Tanikawa, Kanako Topani, Muhammad Alfikri Maida Tuti Purwaningsih, Tuti Wardoyo, Girindra Sulistiyo Zaman, Azmi Badhi'uz Zaman, Azmi Badhi’uz