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All Journal POSITRON Jupiter Coding: Jurnal Komputer dan Aplikasi Techno.Com: Jurnal Teknologi Informasi Jurnal Edukasi dan Penelitian Informatika (JEPIN) Infotech Journal CESS (Journal of Computer Engineering, System and Science) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JET (Journal of Electrical Technology) SMARTICS Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) CYBERNETICS JURIKOM (Jurnal Riset Komputer) Indonesian Journal of Applied Informatics Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Teknologi Informasi dan Komunikasi KLIK: Kajian Ilmiah Informatika dan Komputer JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga) Arus Jurnal Psikologi dan Pendidikan CONSEN: Indonesian Journal of Community Services and Engagement The Indonesian Journal of Computer Science Mekongga: Jurnal Pengabdian Masyarakat Journal of Renewable Energy and Smart Device
Irma Nirmala
Universitas Tanjungpura
Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Journal : journal of computer system and informatics josyc

 1 
Klasifikasi Buah Pinang Berdasarkan Data Sensor Menggunakan Metode K-Nearest Neighbor Berbasis Web Dea Rizki Febrinamas; Rahmi Hidayati; Irma Nirmala
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3805

Abstract

Buah Pinang merupakan salah satu jenis buah yang banyak diekspor dan memiliki manfaat dalam bidang kecantikan, pewarna makanan serta sebagai bahan baku untuk industri tekstil. Proses klasifikasi buah pinang secara manual membutuhkan waktu dan tenaga yang banyak. Sehingga untuk membantu mempercepat dan mempermudah proses klasifikasi buah pinang dibutuhkan sistem klasifikasi yang dapat mengenali buah pinang berdasarkan warna dalam berbagai tingkat kematangan buah yaitu mentah, matang dan tua. Penelitian ini menggunakan metode K-Nearest Neighbor (K-NN) untuk proses klasifikasi buah pinang. Data yang digunakan sebanyak 600 data yang diperoleh dari sensor, terdiri dari 200 buah pinang mentah, 200 buah pinang matang, dan 200 buah pinang tua. Parameter yang digunakan yaitu mentah, matang dan tua dengan rentang nilai Red, Green, Blue (RGB) yang berbeda setiap kondisinya. Pengujian menggunakan nilai ketetanggaan (K) yaitu 5, 7, 9 dan 11 dan diperoleh nilai ketetanggaan (K) terbaik adalah K = 7. Hasil pengujian dilakukan menggunakan confusion matrix didapatkan nilai accuracy sebesar 98,33%, recall sebesar 97,24%, dan precision sebesar 100%.
Sistem Pemilah Menggunakan Conveyor dan Pemantauan Ketinggian Sampah Logam, Anorganik, dan Organik Berbasis Internet of Things Youla Gessel; Syamsul Bahri; Irma Nirmala
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3841

Abstract

Pemilahan jenis sampah logam, anorganik dan organik dilakukan agar sampah terkumpul sesuai jenisnya dan mempermudah pengolahan. Selain itu, pemantauan diperlukan untuk memberi informasi pada saat tempat sampah dalam keadaan penuh. Oleh sebab itu, diperlukan sistem yang dapat memilah dan memantau ketinggian sampah pada tempatnya. NodeMCU ESP32 sebagai pengendali keseluruhan sistem. Sensor proximity induktif, kapasitif, dan optik untuk deteksi jenis sampah, motor servo untuk pemilahan, dan sensor ultrasonik HC-SR04 untuk pemantauan ketinggian sampah. Antarmuka website digunakan untuk pemantauan tempat sampah dari jarak jauh. Pengujian keseluruhan oleh ketiga sensor pendeteksi jenis sampah mendapatkan akurasi keberhasilan yaitu 96,67%. Pengujian pembacaan sensor ultrasonik HC-SR04 mendapatkan nilai error sebesar 2,517% untuk ultrasonik HC-SR04 1, nilai error sebesar 1,9315% untuk ultrasonik HC-SR04 2, dan nilai error sebesar 2,176% untuk ultrasonik HC-SR04 3. Hasil pengujian sistem menunjukkan sampah yang terkumpul sudah sesuai dengan jenisnya dan mempermudah pengguna dalam memantau tempat sampah penuh atau tidak.
Sistem Pemilah Otomatis Tingkat Kematangan Buah Kelapa Sawit Menggunakan Metode Logika Fuzzy Mamdani Dan Sensor TCS3200 Salma Salsabilla; Irma Nirmala; Tedy Rismawan
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4449

Abstract

The palm oil sector has a strategic impact on the growth of Indonesia's economy, because the fruit of palm oil produces oil which can be used as alternative fuel, food oil and basic materials for various industries. Currently, oil palm fruit is sorted manually based on color, which takes much longer. As a result, a system was created to categorize oil palm fruit according to their state of maturity. This system uses the TCS3200 sensor as the main sensor to detect the color of oil palm fruit and implements the Mamdani fuzzy logic method to classify it. Arduino Uno can control the hardware components used in the system. Data obtained from RGB color values ​​(red, green, blue) obtained by the TCS3200 sensor is used as input in the system. Meanwhile, the outcomes this system produced are in the form of maturity levels of oil palm fruit which are classified into 3 categories, namely unripe, ripe and past ripe. Based on tests carried out with the confusion matrix, the accuracy value obtained was 95.6%.
Sistem Pemantauan Kesehatan Kambing Berdasarkan Suhu Tubuh dan Detak Jantung Berbasis Internet of Thing Sibarani, Yohana Oktavia; Rismawan, Tedy; Nirmala, Irma
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.5012

Abstract

The goat is one of the species of livestock that has many benefits. Goat benefits become one of the important aspects of keeping goats healthy. Predicting diseases in goats is quite difficult because of the lack of medical experts in the field to check the health condition of the goats. The research has created a system that can determine the health of goats based on their body temperature and heart rate. The system is designed to make it easier for farmers to monitor their health and perform early treatment when there are sick goats. The data used in this study is the normal body temperature and heart rate of the goat. This research uses NodeMCU as a microcontroller and also a sensor. The sensors used are the DS18B20 temperature sensor and the MAX30102 heart rate sensor. The system can measure both temperature and heart rate at the same time. The test results showed an average data error on the measurement of the DS18B20 sensor and the MAX30102 sensor. In these measurements, the average error of the sensor was 0.77% and the sensor MAX30102 was 2.23%. The data from the monitoring of this sensor will be displayed on the website so that it can be viewed by the user.
Co-Authors Abdul Muid Abdul Muid Akbar, Rico Andre, Hendrikus Andreni, Gracella Angger Gindaong, Carlos Aprillio Ardiansyah, Romi Arif Rahmawan Arif Setiawan Asep Hermawan Aulia Amin, Muhammad Azmi Azhar, Sahari Bayti Widya Rezky Cani, Cani Christian, Calvin Cucu Suhery Damiyanto, Edwan Dea Rizki Febrinamas Dedi Triyanto Dedi Triyanto DONI, OKTAVIANUS Dwi Marisa Midyanti Dwi Pura, Destra Elegant, Gustavo Dipo Endah Sayekti Erniajan, Yunita Faizal Cahyo Handoko Firdaus, Akmal Hafiz Muhardi Hansen Alexander Rustan Hasanuddin Herawati, Yunita Herlian, Wildan Hirzen Hasfani Ikhsan, Afif Muhammad Ikhwan Ruslianto Imam Samudra Imroah, Nurfitri Karmila, Mira Kartika Sari Kartika Sari Kasliono Kasliono Kevin William Kurniasari Safitri Mahardika, Nanda Rizky Marettania, Felisitas Marisa Midyanti, Dwi Minsas, Sukal Muhammad Fahrizal, Muhammad Muhammad Luthfi Muhardi Nia Handayani Nur Fitriana Putri Nurazura Alfahira P.W., Elvi Rusmiyanto PERMADANI, CHANDRA MONICA Prastika, Ranny Puji Ardiningsih Putri, Nabila Adinda Dwi Rahmi Hidayati Rahmi Rahmi Rizka Amalia Ananda Rizky, Sri Salma Salsabilla Sampe Hotlan Sitorus Sampe Hotlan Sitorus, Sampe Hotlan Sari, Reny Puspita Sibarani, Yohana Oktavia Suhardi Suhardi Suhardi Suhardi Suhardi Suhardi Sy Kamal Baraqbah Syamsul Bahri Syamsul Bahri Syamsul Bahri Tedy Rismawan Uray Ristian Wahiddatun Nisa Yasa Khalqiah Yoastha, Qano Triez Youla Gessel Yudhi Zettia, Zhara