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All Journal JURNAL INFORMATIKA Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Information Systems and Technology (JISTech)
Ery Muchyar Hasiri
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Other

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Peringatan Dini Banjir Menggunakan Multi Sensor Pada Prototype Aliran Sungai Berbasis Internet of Things Ery Muchyar Hasiri; Hikmah Nur Allia
JURNAL INFORMATIKA Vol 12, No 1 (2023): Jurnal Informatika
Publisher : Prodi Teknik Informatika Unidayan Baubau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55340/jiu.v12i1.1299

Abstract

Salah satu dampak nyata dari perubahan iklim adalah banjir yang telah terjadi lebih sering di banyak wilayah padat penduduk dan menyebabkan dampak pada kehidupan manusia dan mata pencaharian. Untuk mendapatkan ketinggian permukaan air kanal, dengan cara memanfaatkan rambatan gelombang suara ultrasonik yang dipantulkan pada obyek. Dengan diketahuinya jarak obyek, maka dapat dilakukan komputasi untuk mengetahui ketinggian permukaan air kanal. Nilai ketinggian permukaan air kanal dikirim melalui jaringan internet menuju Internet of Thing (IoT) cloud server yang dapat di monitor oleh pengguna. Penelitian ini bertujuan untuk merancang bangun alat mengukur ketinggian air sungai sehingga dapat mendeteksi apabila akan terjadi banjir, alat ini menggunakan multi level sensor sebagai sensor yang dapat mendeteksi ketinggian air dan memanfaatkan teknologi IoT untuk monitoring langsung. Hasil yang dicapai dalam penelitian ini alat prototype peringkatan dini banjir dapat yang dikontrol menggunakan aplikasi android untuk mengetahui ketinggian air melalui sensor yang dipasang pada aliran sungai, sehingga dapat dijadikan sebagai system peringatan dini banjir. 
Implementasi Augmented Reality untuk Pembelajaran Gerakan Pencak Silat Menggunakan Unity dan Vuforia Fahmi; Alders Paliling; Ery Muchyar Hasiri; LM. Fajar Israwan
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Pencak Silat is a traditional martial art that originated in Indonesia, now pencak silat is a sport that has many enthusiasts in various countries. At the State Junior High School 4 Wangi - Wangi, pencak silat still uses a learning method with direct practice in the field which is only done 1 time a week. This research aims to design and build a learning application for the Pencak Silat movement by applying Augmented Reality technology. In making this application, there are several stages, namely, character design and animation using avatars sdk and blender which then markers are stored in the Vuforia database and built using unity. This research produces the application of Augmented Reality in Learning Pencak Silat movements as a learning medium that can be used as a learning medium for students, where students can learn Pencak Silat movements by looking at the movements of characters in the application in 3 dimensions so that it will make students enthusiastic in learning Pencak Silat.
Pengembangan Sistem Informasi Seleksi Penerimaan Bantuan Langsung Tunai Menggunakan Metode K-Nearest Neighbor Hardianto; Kharis Syaban; Ery Muchyar Hasiri
JISTech : Journal of Information Systems and Technology Vol. 1 No. 2 (2024): Desember 2024
Publisher : Perhimpunan Ahli Teknologi Informasi dan Komunikasi Indonesia

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Abstract

The implementation of the Cash Transfer Assistance (BLT) program in Indonesia aims to assist economically disadvantaged communities, especially during crises such as the pandemic. However, the selection process for BLT recipients often faces challenges related to accuracy and efficiency, particularly in determining eligible recipients based on various economic and social criteria. This research develops an information system based on the K-Nearest Neighbor (K-NN) method to address these issues. The system is designed to classify BLT candidates by considering several variables, such as family income, number of dependents, employment status, housing conditions, and family health. The optimal K value was determined through trial and error to achieve the highest accuracy. The system was tested using both training and testing data, and the evaluation results showed an accuracy rate of 85%. This information system not only processes data quickly but also provides transparent and objective results, making it useful for village authorities to efficiently select BLT recipients. By implementing the K-NN algorithm, this system is expected to offer a practical solution for village governments in improving the accuracy of aid distribution to eligible communities.
Analisis Keputusan Multi-Kriteria Menggunakan SAW dengan Pendekatan Interpretabilitas Model Mohamad Arif Suryawan; Ery Muchyar Hasiri
JISTech : Journal of Information Systems and Technology Vol. 2 No. 2 (2025): Desember 2025
Publisher : Perhimpunan Ahli Teknologi Informasi dan Komunikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71234/jistech.v2i2.102

Abstract

Pengambilan keputusan dalam berbagai bidang sering kali melibatkan banyak kriteria dengan tingkat kepentingan yang berbeda, sehingga diperlukan metode yang mampu menghasilkan keputusan secara objektif dan transparan. Penelitian ini bertujuan untuk menganalisis pengambilan keputusan multi-kriteria menggunakan metode Simple Additive Weighting (SAW) dengan pendekatan interpretabilitas model. Metode SAW dipilih karena kesederhanaan proses perhitungan serta kemampuannya dalam memberikan hasil keputusan yang mudah dipahami oleh pengguna. Penelitian ini menggunakan data dummy yang terdiri atas lima alternatif dan empat kriteria, yang mencakup kriteria benefit dan cost. Tahapan penelitian meliputi penyusunan matriks keputusan, normalisasi nilai kriteria, pembobotan, perhitungan nilai preferensi, dan perangkingan alternatif. Hasil penelitian menunjukkan bahwa metode SAW mampu menghasilkan peringkat alternatif secara konsisten dan transparan, di mana setiap nilai preferensi dapat ditelusuri kontribusinya berdasarkan bobot dan nilai masing-masing kriteria. Pendekatan interpretabilitas yang diterapkan memberikan pemahaman yang lebih jelas mengenai alasan di balik peringkat alternatif yang dihasilkan, sehingga meningkatkan kepercayaan pengambil keputusan terhadap sistem pendukung keputusan. Dengan demikian, metode SAW dengan pendekatan interpretabilitas model dapat dijadikan sebagai solusi yang efektif dan akuntabel dalam pengambilan keputusan multi-kriteria.
Implementasi Algoritma Deep Learning YOLO dan OpenCV untuk Mendeteksi Perbedaan Buah Ery Muchyar Hasiri; Fahmi; Mohamad Arif Suryawan; Nurfida Ain
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The development of computer vision technology and artificial intelligence has driven innovation in automation in various fields, including the agricultural sector and fruit trading. The process of identifying fruit quality, which is generally done manually, is still vulnerable to human error and inconsistencies. Based on these problems, this study aims to develop an automated system to detect the difference between fresh and rotten fruit using a deep learning-based You Only Look Once (YOLO) algorithm integrated with the OpenCV library. The system is designed in the form of a web application that is easy for fruit sellers to use. The dataset used consists of images of apples, mangoes, and bananas labeled through Roboflow into two categories, namely fresh and rotten. The model was trained using YOLOv11, then tested with new data that had never been used before. The test results showed high performance with an accuracy of 99.01%, mAP@50 of 0.925, precision of 0.93, recall of 0.90, and F1-score of 0.91. Based on these results, the system is able to detect the condition of the fruit automatically and in real-time with an excellent level of accuracy. This implementation proves that the integration between YOLO and OpenCV is effective in improving the efficiency, accuracy, and consistency of the fruit quality identification process.
Pengembangan Sistem IoT Berbasis Sensor untuk Analisis Kesuburan Tanah pada Lahan Pertanian Ery Muchyar Hasiri; Fahmi; Mohamad Arif Suryawan; Marselfa Nasir
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The development of Internet of Things (IoT) technology has had a significant impact in various fields, including the agricultural sector. One of the main challenges in modern agriculture is the efficient and accurate measurement of soil fertility, including temperature, humidity, and nutrient content parameters such as nitrogen (N), phosphorus (P), and potassium (K). Manual measurements take considerable time, effort, and cost, and often result in less accurate data because they are subjective and not real-time. This research aims to design and build an IoT-based soil fertility measuring device that integrates NPK sensors, Soil Moisture sensors, and DHT22 sensors with ESP32 microcontrollers as the system control center. The methods used include hardware and software design, ESP32 programming using Arduino IDE, and integration with the Firebase platform for online data storage. It reads the soil conditions in real-time and displays the measurement results on the LCD, as well as transmitting data to a smartphone application over the internet. The test results show that the tool can distinguish fertile and infertile soil conditions well. In fertile soils, a temperature of 29°C, humidity of 89%, and NPK content of Nitrogen 20–23 ppm, Phosphorus 32 ppm, and Potassium 190–195 ppm, respectively. Meanwhile, in infertile soils, a temperature of 23–32°C, humidity below 75%, and a Nitrogen content of 12 ppm, Phosphorus 22 ppm, and Potassium 118–120 ppm. This system provides benefits in remote monitoring, resource efficiency, and increased agricultural productivity.
Co-Authors alders paliling Fahmi Hardianto Hikmah Nur Allia LM. Fajar Israwan Marselfa Nasir Mohamad Arif Suryawan Nurfida Ain Syaban, Kharis