Rancang Bangun Alat Sortir Buah Apel Berdasarkan Perbedaan Ukuran dan Warna Menggunakan Mikrokontroller Arduino

M. Noor Khafit(1), Nur Khamdi(2), Jajang Jaenudin(3), Edilla Edilla(4),
(1) Teknologi Rekayasa Mekatronika, Politeknik Caltex Riau  Indonesia
(2) Teknologi Rekayasa Mekatronika, Politeknik Caltex Riau  Indonesia
(3) Teknologi Rekayasa Mekatronika, Politeknik Caltex Riau  Indonesia
(4) Teknologi Rekayasa Mekatronika, Politeknik Caltex Riau  Indonesia

Corresponding Author


DOI : https://doi.org/10.24036/jtev.v9i1.122935

Full Text:    Language : ind

Abstract


Indonesia is a country rich in natural resources, especially in agriculture. Plantation products, both in the form of raw materials and processed products, are one of the major contributors to the country's foreign exchange. Local apples from Batu City are one of the products exported. However, the process of sorting apples still uses human labor and is an obstacle for Indonesia to increasing the economic value of local apples in the export market. Therefore, an automatic sorting system was created to separate apples based on size and color. The system uses experimental methods and collects empirical data from each process for more accurate automated sorting. The size sorting mechanic consists of a conveyor that is designed to be tilted at 30 degrees to facilitate the process of sorting apples and then measuring rollers, hoopers, and shelters. The data processing controller used is Arduino Mega 2560. The main data input comes from the TCS3200 color sensor and proximity sensor. Meanwhile, the sorting executor uses 1 MG996 servo motor and 2 MG90s servo motors. Although there are constraints on the TCS3200 sensor which are sensitive to distance and light which affect the RGB value results, this automatic sorting system can successfully sort apples with a success rate of 96% for size sorting and 80% for color sorting.


Keywords


sistem sortir otomatis, metode eksperimental, data empiris, sensor warna TCS3200, sensor proximity

References


S. Y. Limpo, “Mentan Sebut Petani Indonesia Bertambah 8 Juta Selama Pandemi,” 2021. https://news.detik.com/berita-jawa-barat/d-5552969/mentan-sebut-petani-indonesia-bertambah-8-juta-selama-pandemi

U. Isbah and R. Y. Iyan, “Analisis Peran Sektor Pertanian dalam Perekonomian dan Kesempatan Kerja di Provinsi Riau,” J. Sos. Ekon. Pembang., vol. Tahun VII, no. 19, pp. 45–54, 2016.

A. J. Sahwal, “Komoditas Buah Apel Indonesia di Pasar Internasional,” 2013, [Online]. Available: https://blog.ub.ac.id/aliphjuan/2013/07/17/komoditas-buah-apel-indonesia-di-pasar-internasional/

J. Rusman and N. Pasae, “Prototype Sistem Penyortir Buah Kopi Arabika Berdasarkan Tingkat Kematangan Menggunakan Metode Support Vector Machine,” Teknika, vol. 12, no. 1, pp. 65–72, 2023, doi: 10.34148/teknika.v12i1.602.

K. Setyadjit, B. Hariadi, and J. T. Elektro, “Menentukan kualitas buah apel malang berdasarkan kulitnya memanfaatkan pengolahan citra digital,” vol. 25, no. 2, pp. 1–12, 2022.

N. Asiah, L. Cempaka, K. Ramadhan, and S. H. Matatula, Prinsip Dasar Penyimpanan Pangan Pada Suhu Rendah, vol. 1. 2020.

M. Rahmasinta, “Laporan Praktik Kerja Lapangan (Pkl) Penerapan Mesin Pascapanen Dan Pengemasan Produk Hortikultura Di Lembang Agri,” pp. 1–61, 2022.

dkk Febyan Dimas Pramanta, “Sistem Cerdas Penyortir Apel Berdasarkan Warna Dan Ukuran Berbasis Mikrokontroler Arduino,” 2017, [Online]. Available: http://www.proceeding.sentrinov.org/index.php/sentrinov/article/download/261/239

L. N. Fitiriani, F. Utaminingrum, and W. Kurniawan, “Tampilan Klasifikasi Jenis Buah Apel Lokal Berdasarkan Penciri Warna, Aspectratio dan GLCM Menggunakan Belt Konveyor Berbasis Raspberry Pi,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 3, no. 2, pp. 1167–1173, 2019, [Online]. Available: https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/4322/2018

N. Network and F. Extraction, “JITE ( Journal of Informatics and Telecommunication Engineering ) A Good Accuracy in Apple Fruits Quality Based on Back Propagation,” vol. 6, no. July, pp. 38–48, 2022.

W. Angela, “Berdasarkan Tingkat Kematangan Menggunakan Sensor Warna Tcs3200 Laporan Skripsi Universitas Islam Riau,” 2022.

D. Rahman Sya’ban, A. Hamzah, and E. Susanti, “Klasifikasi Buah Segar Dan Busuk Menggunakan Algoritma Convolutional Neural Network Dengan Tflite Sebagai Media Penerapan Model Machine Learning,” Pros. Snast, no. November, pp. F7-16, 2022, doi: 10.34151/prosidingsnast.v8i1.4180.

M. F. Amin, S. R. Akbar, and E. R. Widasari, “Rancang Bangun Sistem Sortir Buah Apel Menggunakan Sensor Warna Dan Sensor Suhu,” J. Pengemb. Teknol. Inf. dan Ilmu Komput. Univ. Brawijaya, vol. 1, no. 3, pp. 236–240, 2017.

A. Azizah, “Rancang Bangun Sistem Panen Buah Kelapa Muda Berbasis Mikrokontroler,” 2018, [Online]. Available: http://repositori.uin-alauddin.ac.id/13867/%0Ahttp://repositori.uin-alauddin.ac.id/13867/1/Ayu Azizah.pdf

R. D. Nareswara and A. imam Agung, “Rancang Bangun Sistem Pengendalian Beban Listrik Berbasis Internet Of Things (IOT),” vol. 08, 2019.

N. M. Ratminingsih, “Penelitian Eksperimental Dalam Pembelajaran Bahasa Kedua,” Prasi, vol. 6, no. 11, pp. 31–40, 2010.

I. Alwi, “Kriteria Empirik dalam Menentukan Ukuran Sampel Pada Pengujian Hipotesis Statistika dan Analisis Butir,” Form. J. Ilm. Pendidik. MIPA, vol. 2, no. 2, pp. 140–148, 2015, doi: 10.30998/formatif.v2i2.95.

S. A. Adegbite, S. K. Adeyemi, A. O. Komolafe, M. O. Salami, C. F. Nwaeche, and A. A. Ogunbiyi, “Design and Development of Fruit Washer,” J. Sci. Res. Reports, vol. 21, no. 6, pp. 1–11, 2019, doi: 10.9734/jsrr/2018/46041.

N. S. M. Elkaoud and R. K. Mahmoud, “Revista Brasileira de Engenharia Agrícola e Ambiental Design and implementation of sequential fruit size sorting machine 1 Projeto e implementação de uma máquina sequencial de classificação por tamanho de frutas,” pp. 722–728, 2022.

N. Satriawan, “Pengertian Metode Penelitian Eksperimen dan Cara Menggunakannya,” 2018. https://ranahresearch.com/pengertian-metode-penelitian-eksperimen/

A. Jayadi and D. Meilinda, “Klasifikasi Tingkat Kematangan Buah Pepaya Berdasarkan Warna Kulit Menggunakan Sensor Warna TCS3200,” vol. 3, no. 2, pp. 1–13.


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