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All Journal ELKHA : Jurnal Teknik Elektro Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Journal of Economics, Business, & Accountancy Ventura Prosiding SNATIF Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Jurnal Terapan Abdimas PROtek : Jurnal Ilmiah Teknik Elektro ITEj (Information Technology Engineering Journals) Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika INVOTEK: Jurnal Inovasi Vokasional dan Teknologi AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JURNAL MEDIA INFORMATIKA BUDIDARMA IT JOURNAL RESEARCH AND DEVELOPMENT Indonesian Journal of Artificial Intelligence and Data Mining INOVTEK Polbeng - Seri Informatika Jurnal Sisfokom (Sistem Informasi dan Komputer) Prosiding Seminar Nasional Sains dan Teknologi Terapan Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal RESISTOR (Rekayasa Sistem Komputer) Patria Artha Technological Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) EDUMATIC: Jurnal Pendidikan Informatika Jurnal Teknologi Informasi dan Pendidikan Building of Informatics, Technology and Science bit-Tech Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Jurnal Pengabdian Masyarakat Bumi Raflesia Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Technology and Informatics (JoTI) J-SAKTI (Jurnal Sains Komputer dan Informatika)
Irma Salamah
Politeknik Negeri Sriwijaya
Aerospace Engineering Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Social Sciences Transportation Other

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RANCANG BANGUN SISTEM PEMISAH TELUR FERTIL DAN IN-FERTIL OTOMATIS DENGAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN) Noviani, Fadiah; Salamah, Irma; Lindawati, Lindawati
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 3 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i3.6101

Abstract

Tujuan dari penelitian ini adalah untuk merancang dan membangun sistem yang secara otomatis memisahkan telur subur dan tidak dibuahi dengan menggunakan metode convolutional neural network (CNN). Metode ini digunakan untuk mengklasifikasikan kondisi telur berdasarkan gambar lilin.Pengujian dilakukan pada kumpulan data yang terdiri dari telur subur dan tidak dibuahi. Berdasarkan hasil penelitian, rata-rata akurasi sistem yang dikembangkan adalah 85%, dengan akurasi 90% untuk telur fertil dan akurasi 80% untuk telur tidak dibuahi. Hasil ini menunjukkan bahwa sistem ini dapat diandalkan untuk aplikasi praktis, meskipun terdapat beberapa kasus pendeteksian kondisi telur yang tidak konsisten. Namun, validasi dan penyempurnaan lebih lanjut diperlukan untuk meningkatkan akurasi sistem sehingga hasilnya akurat secara konsisten dalam berbagai kondisi. Pengenalan sistem ini diharapkan dapat mendukung proses pemisahan telur secara efisien dan efektif, membantu meningkatkan produktivitas dan kualitas produk dalam peternakan.
Perancangan Helm Pintar dengan Fitur Keselamatan Deteksi Kantuk Berbasis NodeMCU dan Accelerometer Julianti, Amelia; Salamah, Irma; Hesti, Emilia
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5534

Abstract

Driving safety is a major focus given the high number of accidents caused by drowsy drivers. This article discusses the design of a smart helmet that detects drowsiness to improve rider safety. The smart helmet integrates technology with drowsiness detection to reduce the risk of accidents and provide a safer driving experience. The system uses NodeMCU and MPU6050 Accelerometer to monitor head movement, activating an alarm if the head moves more than 5 degrees, which indicates drowsiness or loss of focus. It is expected that the risk of accidents due to drowsiness can be significantly reduced with this approach. The test results show that the system is able to effectively detect unusual head movements and provide a quick alarm response, thus improving driving safety as expected. In the context of this measurement, the lower error values of 0.70% and 1.18% indicate that the MPU6050 sensor provides more accurate results in measuring the angle against a given reference angle. The angle measurement results between the reference and the MPU6050 sensor show that the value obtained from the sensor is not much different from the reference angle. Although there is a slight difference, the accuracy of the MPU6050 is still reliable for practical purposes, showing consistent performance and close to the actual value. This indicates that the MPU6050 sensor is capable of providing quite precise results, so it can be used as an effective angle measuring device in various applications. The integration of this sensor into smart helmets enables early detection of signs of drowsiness, which can then activate automatic alerts to improve driver safety. Test results also demonstrated the helmet's ability to monitor and send real-time data to ThingSpeak, providing easy-to-understand visualizations, historical data storage, and automatic notifications when signs of drowsiness are detected.
Implementasi Convolutional Neural Network Pada Alat Klasifikasi Kematangan dan Ukuran Buah Nanas Berbasis Android Salamah, Irma; Humairoh, Sherina; Soim, Sopian
Jurnal Inovtek Polbeng Seri Informatika Vol 8, No 2 (2023)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v8i2.3413

Abstract

Sumatera Selatan merupakan wilayah produksi buah nanas paling tinggi di tahun 2021. Dalam proses penjualan buah nanas bergantung pada ukuran dan kematangan. Para petani mengklasifikasikan buah nanas secara subjektif dengan kedua mata, sehingga menyebabkan proses klasifikasi tidak efektif. Teknologi machine learning berkembang sangat pesat, salah satunya deep learning yang menggunakan syaraf tiruan (neural network) yang sangat dalam (deep) untuk mempelajari representasi fitur dari data secara otomatis. Penelitian ini bertujuan untuk mengimplementasikan algoritma Convolutional Neural Network (CNN) untuk mengklasifikasi kematangan dan ukuran buah nanas agar proses pemilahan hasil produksi buah nanas menjadi efektif dan akurat. Terdapat 6 label klasifikasi yaitu, nanas besar matang, besar setengah matang, sedang matang, sedang setengah matang, kecil matang dan kecil setengah matang. Digunakan Raspberry pi 3B+ dan kamera pi sebagai alat pengambilan citra buah. Didapatkan hasil akurasi proses training sebesar 99,4 % dan akurasi proses validasi sebesar 92,4% dengan dataset sebanyak 275 data untuk setiap label. Dataset digunakan 80% sebagai data training dan 20% data validasi. Sedangkan untuk pengujian testing pada alat digunakan 90 data uji dengan hasil akurasi sebesar 90,83%. Dan hasil klasifikasi akan tampil pada aplikasi android termasuk jumlah stok nanas yang telah dideteksi, sehingga dapat mempermudah pekerjaan petani dalam menyortir buah nanas.
Rancang Bangun Sistem Monitoring Keamanan Laboratorium Menggunakan Komunikasi Long Range (LORA) Berbasis Android Aliffiyah, Muhammad Bayu; Salamah, Irma; Fadhli, Mohammad
Patria Artha Technological Journal Vol 5, No 2 (2021): Patria Artha Technological Journal
Publisher : Department of Electrical Engineering, University of Patria Artha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33857/patj.v5i2.442

Abstract

It is undeniable that wireless communication technology is developing very rapidly, especially in an emergency. For example in the laboratory. The laboratory is a place to carry out practical or research activities that are supported by complete laboratory equipment and infrastructure. Therefore, it is not impossible that the complete laboratory equipment becomes an excuse for people with the aim of committing crimes. The most frequent crime in the laboratory is theft, the thieves usually take advantage of the moment when the laboratory personnel are not in the room and they can take valuables in the room without being noticed by the officers freely. Therefore our goal in this research is to improve security for laboratories with wireless communication technology methods. This technology uses a communication system named Lora equipped with ALOHA protocol based on Android to be able to monitor remotely. The test was carried out at a height of 80 cm and this study resulted in the largest RSSI value of -130 dB at a maximum distance of 600 m with a delay of 29 seconds. Packet loss is affected by distance, so packet loss or data loss will be higher at longer distances.
Android-based Automatic Steak Grilling Tool Salamah, Irma; Syaniah, Yunita; Hadi, Irawan
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12880

Abstract

In an era of rapid technological development, technology is increasingly accessible and easily applied by humans. One of the significant developments is the Internet of Things (IoT), where physical devices such as sensors, equipment, and vehicles are equipped to communicate and interact via the Internet network. The application of IoT has expanded to various sectors, including culinary. In this regard, preparing and presenting food, especially steaks, becomes an exciting focus. There are multiple types of steaks, such as sirloin and tenderloin, and cooking involves various techniques, such as searing and grilling. However, suitability for maturity and risk during cooking is challenging for steak makers and connoisseurs. To overcome this, the application of IoT is needed in an automatic steak roaster to be a promising solution. This research is also equipped with real-time monitoring via an Android application. This aims to ensure proper doneness and consistent results in the steak cooking process. This research makes an automatic steak grill with a success rate of 83%, which shows that the tool's performance and functionality align with expectations. This tool also has an Android application to monitor and control the device remotely efficiently. This research gives confidence that this can be a solution that has been developed and provides significant benefits in roasting steaks with automatic monitoring and operation.
Rancang Bangun Extractor Susu Kedelai Menggunakan Metode Komunikasi Serial Asinkron Berbasis IoT Nurmalasari, Aprilliya; Salamah, Irma; Rakhman, Abdul
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 6 No. 1 (2023): Jurnal RESISTOR Edisi April 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v6i1.1408

Abstract

Kacang kedelai banyak diminati, terutama dalam bidang olahan bahan dasar makanan. Harga kacang kedelai yang relatif murah sangat mudah dipasarkan di semua kalangan. Memproses kacang kedelai dengan cara manual sudah sangat lazim dilakukan dan diproses menggunakan mesin juga sudah dilakukan oleh industri-industri menengah ke bawah apalagi industri menengah ke atas dengan perbedaan jumlah produksi dalam waktu yang berbeda-beda. Pada penelitian ini dilakukan pengembangan dengan menambahkan IoT pada mesin extractor yang menggunakan sistem software dari Thingspeak, di desain pada web MIT Inventor dan juga trasnfer data dengan metode komunikasi data serial Asinkron. Dengan muatan sekali produksi susu kedelai yang tidak begitu besar karena untuk alat bantu rumah tangga.
Innovation in Smart Fencing with Internet of Things (IoT) Technology for Ease of Use Salamah, Irma; Rahmika, Rahmika; Nurdin, Ali
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 6 No. 3 (2023): Jurnal RESISTOR Edisi Desember 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v6i3.1438

Abstract

The fence is a structure that is deliberately designed to limit or protect the house. The fence serves to provide protection or block views so that the house becomes safer. It is usually pushed manually by hand to open and close the fence. This is considered very inconvenient and time-consuming. This problem underlies the idea of creating an automatic fence opening and closing system using a smartphone by utilizing Internet of Things (IoT) technology in order to facilitate human work to open and close the fence. A smartphone is used as a NodeMCU controller contained in the ESP8266 WiFi module via an internet connection to connect to the Android Studio application. To move the fence using an electric motor as the driving force which is connected directly to NodeMCU. When the fence opens and closes, the relay will regulate and activate to give orders to the electric motor to move the fence. The fence will stop when the switch opens and the switch close responds, the motor will stop moving. Realtime data results are stored in Firebase and the results of this design are expected that all components are connected properly so that automatic fences can be used.
Image Identification System for Beef and Pork Using a Convolutional Neural Network Fauzi, Nadiyah Salsabila; Salamah, Irma; Hadi, Irawan
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

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

Abstract

In the modern era, assurance of the halalness of meat products has become a fundamental need for Indonesian Muslims, as awareness and sensitivity towards the consumption of halal products increases. This has led to the development of innovative solutions to ensure the authenticity of beef and distinguish it from pork. This research presents an Android-based meat image identification tool that relies on the Convolutional Neural Network (CNN) algorithm to process and analyze images. The research includes hardware design, deep learning model with CNN algorithm, and Android application for real-time integration of detection results. This tool is equipped with an LCD screen and speaker to display identification results. The results show the accuracy of the CNN model reaches 99% in distinguishing beef and pork on the test dataset. In real-time testing of the tool using fresh beef and pork samples, the system achieved 92% accuracy, demonstrating good performance under practical conditions. The system provides a reliable and practical solution for consumers to verify the type of meat, while contributing to efforts to ensure the halalness of food products in society.
Design of An Internet of Things-Based Intelligent Cutlery Cleaning Tool Lindawati, Lindawati; Salamah, Irma; Astari, Devina
Jurnal Teknologi Informasi dan Pendidikan Vol. 17 No. 1 (2024): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v17i1.792

Abstract

Technology that continues to develop has given rise to many new technologies that help humans work; one example is washing dishes. Because this work is quite time-consuming, it created an automatic dishwasher based on the Internet of Things (IoT). This tool aims to build a tool that can help homemakers complete one of their homework, namely washing tableware. This research was conducted by making a prototype design using Arduino Mega 2560 and NodeMCU and supported by Android applications using the XML programming language. In the application, there are control and monitoring features. The control feature in the application will control the number of rounds of water used, while the monitoring feature is used to monitor the water discharge used during washing. In addition, this tool also uses Firebase as a database used to store data. By incorporating sensors and technology into this appliance, a more efficient, programmable, and customized washing experience is possible. The appliance underwent 27 tests, with an overall success rate of 88,89%.
Implementasi Algoritma Naive Bayes Terhadap Klasifikasi Jenis Pertanyaan Pada Perancangan Chatbot Untuk Aplikasi Penjualan Songket Rosa, Adelia; Salamah, Irma; Suroso, Suroso
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7908

Abstract

Rapid developments in science and technology have had a significant impact on all aspects of people's lives, especially in business. E-commerce has become a popular choice among internet users in Indonesia, including MSMEs. However, conventional sales of songket products still limit product reach and competitiveness. In addition, the sales process generally provides customer service in charge of interacting and serving customer inquiries that can be contacted via telephone number. However, it is considered less effective because the seller has difficulty when responding to various questions from customers, so customers have to wait to get answers regarding the information needed. Therefore, the purpose of this research is to design a chatbot for songket sales applications using the naive bayes algorithm in classifying the types of customer questions, to improve the efficiency and effectiveness of interactions between sellers and customers, and expand the market reach of songket products. This chatbot is designed to simulate interactive conversations and provide sales information to customers quickly and efficiently. The naive bayes algorithm was chosen due to its ease of implementation and high accuracy in text classification. In this study, the chatbot was tested with various types of user questions with 5% of the total 50 questions as testing data. The test results show that the chatbot can classify the type of question with an accuracy of 90% and a precision value of 94%, recall 92%, and F1-Score 92%. In addition, testing of the application system as a whole shows that the application and chatbot are able to provide appropriate and efficient responses to various user questions. With this system, it is hoped that a technology-based solution can be realized that can improve the sales process and customer interaction with sellers, and increase the business potential of traditional songket craftsmen. 
Co-Authors AA Sudharmawan, AA Abdul Rakhman Agnes Manik, Agnes Ahmad Jazuli Ahmad Taqwa Aliffiyah, Muhammad Bayu Alisya, City Ardhela Almirah, Narita Tria Anggielita, Renata Anggraini, Nur Septi Aryanti Aryanti Asriyadi Asriyadi Astari, Devina Bambang Pratama, Bambang Cendrakasih, Aminah Chairunnisa, Dita Ayu Ciksadan, Ciksadan Damayanti, Shinta Eka Susanti Elmerillia, Elmerillia Emilia Hesti Endri, Jon Fadhli, Mohammad Fauzi, Nadiyah Salsabila Gustina, Meli Handini, Wulan Tri Hj. Lindawati Humairoh, Sherina Irawan Hadi Irma Suryani Julianti, Amelia Kurniasih, Wahyuni Kusmanto, RD. Kusumanto, R.D Lindawati Lindawati M. Aris Ganiardi, M. Aris Malinda, Threa Martinus Mujur Rose Mujur Rose, Martinus Mursalin, Zaldy Gumilang Nasron Nasron Ningrum, Shinta Sulistiya Noviani, Fadiah Nurhajar Anugraha Nurmalasari, Aprilliya Oktavia, Nadia Primulia, Muhammad Filly Putri Nur Azizah, Putri Nur Putri, Jullia Fatriana R.A., Halimatussa’diyah Rafiif, Muhammad Rahmadaniar, Desi Rahman, Wahyudi Rahmaniar, Fadhila Desti Rahmika, Rahmika Rakhman, Abdul Halim RD Kusumanto Reza Umami, Reza Rosa, Adelia Rose, Mujur Saskia, Kevi Agis Shendy Pratama Sholihin Sholihin Soleh, M. Zikri Sopian Soim, Sopian Suroso Suroso suzan zefi syafitri, kurnia Syaniah, Yunita Tata, Amanda Tsabita Putri Thayyib, Ahmad Reza Ulhaq, Nida Dhia Valerie, Michelle Wardana, Handava Wibowo, Muhamad Arya Al Ghifari Wulandari, Alysiah