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All Journal Jurnal Informatika dan Rekayasa Elektronik Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Publikasi Teknik Informatika (JUPTI) Harmoni: Jurnal Ilmu Komunikasi Dan Sosial Jurnal Sistem Informasi dan Ilmu Komputer Jurnal Penelitian Teknologi Informasi dan Sains Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi RESLAJ: Religion Education Social Laa Roiba Journal Router : Jurnal Teknik Informatika dan Terapan Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi Modem : Jurnal Informatika dan Sains Teknologi Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Router : Jurnal Teknik Informatika dan Terapan Jurnal Sistem Informasi dan Ilmu Komputer
Andreas Nugroho Sihananto
Unknown Affiliation
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Social Sciences

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MONITORING DAN KONTROL RUANGAN OBAT DENGAN SISTEM IOT DAN FUZZY Moch Firman hidayat; Basuki Rahmat; Andreas Nugroho Sihananto
Jurnal Informatika dan Rekayasa Elektronik Vol. 7 No. 2 (2024): JIRE NOPEMBER 2024
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v7i2.1286

Abstract

Penyimpanan obat yang tepat sangat penting untuk menjaga kualitas dan efektivitasnya. Perubahan suhu dan kelembaban yang tidak terkendali dapat menyebabkan kerusakan obat, yang berpotensi membahayakan pasien. Penelitian ini bertujuan merancang sistem pemantauan dan pengendalian suhu serta kelembaban pada ruang penyimpanan obat menggunakan metode Fuzzy Mamdani. Sistem ini memanfaatkan sensor suhu dan kelembaban AHT25 yang terhubung dengan mikrokontroler ESP32 untuk pemantauan waktu nyata. Data suhu dan kelembaban ditampilkan pada layar LCD 16x4 serta Node-red, dan sistem dilengkapi dengan IR Transmitter untuk mengontrol AC agar suhu ruangan tetap terjaga sesuai standar Farmakope. Pengembangan sistem ini menggunakan metode Rapid Application Development (RAD). Hasil pengujian menunjukkan bahwa sistem yang dikembangkan mampu memantau kondisi ruang penyimpanan obat dengan akurasi tinggi, dengan rata-rata error sebesar 0,15% untuk suhu dan 0,29% untuk kelembaban dibandingkan alat ukur komersial. Pengujian fuzzy dengan MATLAB menunjukkan rata-rata error 0,3%. Selain itu, sensor IR Transmitter dapat mengontrol AC secara optimal pada sudut 90° dan jarak 2 meter, dengan delay antara tampilan LCD dan respon solenoid door lock sebesar 4,2%. Sistem ini menawarkan solusi efektif untuk menjaga kualitas obat dalam ruang penyimpanan, memiliki solutivitas yang tinggi karena menawarkan solusi konkret yang bertujuan untuk menyelesaikan masalah tertentu, yaitu menjaga kualitas obat.
Pengembangan Game Edukasi Doa Islam: Desain Arsitektur dan Implementasi Alfian Dorif Murtadlo; Pratama Wirya Atmaja; Andreas Nugroho Sihananto
Reslaj: Religion Education Social Laa Roiba Journal Vol. 6 No. 9 (2024): RESLAJ: Religion Education Social Laa Roiba Journal 
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/reslaj.v6i9.2516

Abstract

The development of educational games has become increasingly important in this modern era, particularly in addressing the challenges of engaging the younger generation in religious education. This paper presents the architectural design and implementation of an educational game focused on Islamic prayers. By leveraging technologies such as Unity for game development, Next.js for frontend web development, and Express.js for backend server functions, coupled with Supabase for efficient database management, this game offers a deep and interactive learning experience. The game's storyline encompasses various stages where players navigate scenarios related to Islamic prayers, earning rewards and knowledge along the way. Through comprehensive user analysis and iterative testing, the game aims to bridge the gap between traditional religious education and modern digital engagement. Integration of real-time performance parameters, such as call speed averaging below 30ms, ensures continuous improvement in game functionality and user experience, thereby enhancing the game's effectiveness as a learning tool. Overall, this research contributes to the advancement of educational gaming in the context of Islamic education, providing insights into effective strategies for engaging and educating young audiences in religious practices..
Implementasi Arsitektur Inception V3 Dengan Optimasi Adam, SGD dan RMSP Pada Klasifikasi Penyakit Malaria Eren Dio Sefrila; Basuki Rahmat; Andreas Nugroho Sihananto
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 2 (2024): Mei: Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i2.62

Abstract

In the current era of technological advancement, deep learning has become a widely discussed and utilized topic, particularly in image classification, object detection, and natural language processing. A significant development in deep learning is the Convolutional Neural Network (CNN), which is enhanced with various optimizations such as Adam, RMSProp, and SGD. This thesis implements the Inception v3 architecture for the deep learning model, utilizing these three optimization methods to classify malaria disease. The study aims to evaluate performance and determine the best optimization based on classification accuracy. The results indicate that the SGD optimization with a learning rate of 0.001 achieved an accuracy of 94%, RMSProp with learning rates of 0.001 and 0.0001 achieved an accuracy of 96%, and Adam with learning rates of 0.001 and 0.0001 achieved an accuracy of 95%.
Pengembangan Aplikasi Pembelajaran Grammar Bahasa Inggris Menggunakan Gamifikasi dan ChatGPT Lintang Pramudya Anpurnan; Andreas Nugroho Sihananto; Pratama Wirya Atmaja
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 2 (2024): Juni : Router: Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Profesi Telekomunikasi dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i2.60

Abstract

Education serves as the main pillar in the effort to develop human resources, continually evolving in line with the progress of time. Within the realm of education, English language learning plays a crucial role. However, the process of English language learning often faces challenges, including low levels of student motivation. This research explores the use of gamification with integrated chatGPT as an innovative solution capable of boosting student motivation and making learning more engaging and effective. Adapting previously proposed methodologies, this application is web-based, developed using Laravel, and tested using Likert scale. The testing yielded a satisfactory average result of 83%, with a 15.64% increase in user scores. The findings of this research provide a positive contribution to enhancing the quality of English language education in Indonesia, particularly at the Junior High School level.
Klasifikasi Penyakit Kronis Melalui Mata Menggunakan Algoritma Convolutional Neural Network Dengan Model MobileNet-V3 Mohammad Haydir Awaludin Waskito; Andreas Nugroho Sihananto; Achmad Junaidi
Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Vol. 2 No. 2 (2024): Juni: Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/uranus.v2i2.120

Abstract

Chronic diseases in humans are very difficult to detect visually, for example glaucoma, hypertension, diabetes, and others. So it takes a lot of time for further medical examination by visiting a health center or hospital. Therefore, this research aims to find a solution combining medical and computer science to classify quickly and precisely. Classifying eye images requires good features and characteristics so that disease images can be classified. This research uses the Deep Learning method, namely Convolutional Neural Network with MobileNet-V3 architecture which can extract features from large resolution images very well. This research resulted in accurate classification of images of chronic diseases Normal, Diabetes, Glucoma, Cataract, Age related macular degeneration, Hypertension, Pathalogical Myopia. uses the MobileNet-V3 architecture, with transfer learning reaching 81%, and loss only 0.4913.
Perbandingan Algoritma Random Forest dan Logistic Regression Untuk Analisis Sentimen Ulasan Aplikasi Tumbuh Kembang Anak Di Play Store Muhammad Alfyando; Fetty Tri Anggraeny; Andreas Nugroho Sihananto
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 1 (2024): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i1.2262

Abstract

Early childhood plays an important role in forming the basis of development, which involves stimulation of various aspects such as moral religious values, social emotional, language, cognitive, and physical motor skills. The concept of early childhood learning is focused on play, where every activity is designed to be play, so that learning becomes more effective. Parents also need to understand today's children's education to interact with children positively. This research focuses on sentiment analysis of children's education-based app reviews on the Google Play Store, using Random Forest and Logistic Regression methods. The review data is taken from three apps with the theme of child development, namely "About Kids", "PrimaKu", and "Teman Bumil", with a range of review years between 2018 and 2023. The test results show that Logistic Regression has higher accuracy compared to Random Forest, especially in the "About Kids" and "PrimaKu" applications with accuracy above 90%. The conclusion of this research highlights the importance of sentiment analysis in improving understanding of user responses to children's education applications, with suggestions for future research to increase the number of datasets and variations in testing schemes by tuning hyperparameters to improve prediction accuracy and more optimal results.
Co-Authors Aan Evian Nanda Achmad Junaidi Achmad Zahrul Ali Zadan Agung Mustika Rizki Alfian Dorif Murtadlo Anggraini Puspita Sari Arif Widiasan Subagio Basuki Rahmat Eren Dio Sefrila Eva Yulia Puspaningrum Fetty Tri Anggraeny Firza Prima Aditiawan Joni Bastian Lintang Pramudya Anpurnan Made Hanindia Prami Swari Moch Firman hidayat Mochammad Yanuar Fitroni Mohammad Haydir Awaludin Waskito Muhammad Alfyando Muhammad Eko Prasetyo Muhammad Fernanda Naufal Fathoni Pratama Wirya Atmaja Rifki Riza Alfiansyah