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Sembiring, Arnes
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Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Transportation

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Journal : Journal of Mathematics and Technology (MATECH)

 1 
IDENTIFICATION OF BANANA FRUIT USING BACKPROPAGATION METHOD Widodo, Dian; Fauzi, Achmad; Sembiring, Arnes
Journal of Mathematics and Technology (MATECH) Vol. 2 No. 2 (2023): Journal MATECH (November 2023)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v2i2.155

Abstract

Identifikasi jenis buah pisang dan penilaian tingkat kematangannya merupakan proses yang penting dalam industri pertanian dan distribusi. Dalam upaya untuk mengotomatisasi proses ini, penulis menyarankan pendekatan pemaparan buah pisang dan tingkat kematangannya menggunakan jaringan saraf tiruan Backpropagation . Melalui proses pengolahan citra digital, citra atau gambar dari buah pisang akan dilakukan ekstraksi ciri-ciri seperti RGB ( red green blue ), metrik dan eksentrisitas(ciri bentuk). Hasil proses training data citra sebanyak 55 data citra yang diinputkan, diperoleh proses training data jenis pisang dengan 11 iterasi dari inputan maksimum epoch 10000, target error atau performance 0.00642 dengan nilai rata-rata sebesar 80%. Selanjutnya diperoleh proses data pelatihan tingkat kematangan pisang dengan 4 iterasi dari input maksimum epoch 10000, target error atau performance 0.00606 dengan nilai akurasi sebesar 90%. Dari proses uji citra yang telah dilakukan bahwa sistem dapat mengidentifikasi jenis buah pisang beserta tingkat kematangannya berdasarkan inputan ekstraksi fitur dari citra buah pisang. Penelitian ini juga bertujuan untuk menguji dan mengetahui tingkat akurasi penerapan metode Backpropagationdalam mengidentifikasi jenis buah pisang dan tingkat kematangannya.
PREDICTION OF STUDENT PASSING SCORE USING BACKPROPAGATION METHOD (CASE STUDY: SMP NEGERI 1 SEI BINGAI LANGKAT) Sembiring, Jams David Pindona; Gultom, Imeldawaty; Sembiring, Arnes
Journal of Mathematics and Technology (MATECH) Vol. 3 No. 1 (2024): Journal MATECH (May 2024)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v3i1.165

Abstract

Education is one of the most important aspects in life in order to form quality human resources and be able to follow the flow of the increasingly advanced era. Students ' passing scores can be used as useful data to see the development of children who will continue their education at the next level, with the results of high passing scores, can create confidence in these students to continue the level of education they want. But not all students get the passing score in accordance with what they want, due to several factors, for example lack of discipline and not too focused on pursuing grades and some are busy working so that school is forgotten. From these conditions, the SMP Negeri 1 Sei Bingai Langkat need to create a system that can predict the passing score of students who will come. The results of these predictions can be used to recommend a decent and good school for students to enter with a high enough passing score. The process in predicting the passing score of students can be done with a computerized system, one of the processes that can be done is the application of Artificial Neural Networks (Ann) with the use of the method Backpropagation process. With the construction of the system is expected to facilitate and assist SMP Negeri 1 Sei Bingai Langkat in knowing the passing score of their students, so that it can be used as a basis in recommending a school that they deserve to enter as the next level of Education. From the research conducted, the results of the number of output layer errors is still large and has not met the target error of 0.001, namely the value of Mathematics for school exams (US) Ade Christy in Junior High School (SMP) Negeri 1 Sei Bingai Langkat are as follows: maximum value (a) : 99 minimum value (b) : 70.
Co-Authors Achmad Fauzi Ady Pratama, Ramadhan Ahmad Zakir, Ahmad Algama, Bella Asmah Indrawati Dadan Ramdan Erianto Ongko Gultom, Imeldawaty Harahap, Jaffar Siddik Hartono Hartono Hartono Hartono Hasibuan, Ade Hasibuan, Ade Zulkarnain Ilham, Fauzi Irawan, Amri Kristina Annatasia Br Sitepu Martini, Dewi Muhammad Khahfi Zuhanda Naufal, Tengku Akhdan Pane, Ilham Maratua Rachmat Aulia, Rachmat Rahmad Syah, Rahmad Rahman, Sayuti Ray, Raja Pahlefi Retna Astuti Kuswardani Rifai, Abas Rizky, Bagaskara Dwi Saifuddin Muhammad Jalil Sembiring, Hermansyah Sembiring, Jams David Pindona Shidqi, Sultan Simanjuntak, Magdalena Sinaga, Nicolas Novelico Siregar, Budi Arisa Utomo Siregar, Rosyidah suswati suswati Widodo, Dian Yunika , Vica