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Tuanku Burhanuddin Reviews West Sumatra Armansyah Armansyah; Abd Mukti; Sapri Sapri
Edumaspul: Jurnal Pendidikan Vol 8 No 1 (2024): Edumaspul: Jurnal Pendidikan
Publisher : Universitas Muhammadiyah Enrekang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33487/edumaspul.v8i1.8185

Abstract

One of the famous reform scholars in West Sumatra is Sheikh Burhanuddin. The purpose of this article is to find out about the life history, scientific spirit and educational system of Tuanku Burhanuddin Ulakan, West Sumatra. The method used in the research is through literature study by carrying out an inventory of all the literature sources used and then carefully verifying them to ensure the level of relevance of the material collected to the object that is the focus of the study in the research. This method is to provide a guarantee of the level of objectivity of the data used. The conclusions from this article are: (1) Sheikh Burhanuddin is thought to have been born in 1056 Hijiriah/1646 AD to a family that adhered to Buddhism. He comes from the Guguk Sikaladi Pariangan area, Padang Panjang, then his parents moved to Sintuak Lubuk Alung. (2) Sheikh Burhanuddin's way of imparting Islamic teachings to the children of Tanjung Medan was in a gradual, soft way. He didn't want to do it hard. The way to do this is to apply one of the verses of the Koran which reads: "Lā Iqraha Fiddīn" (there is no compulsion in religion). (3) It is important to understand that through the Syattariyah congregation which is Sheikh Burhanuddin's means of preaching Islam, Islamic teachings seem to be more easily accepted by the Minangkabau people. Because he presented the Islam of the tarekat which prioritizes the importance of spiritual qualities and inner purification compared to the practices and rituals of the tarekat in general
Klasifikasi Biner Bipolar Pada Data Kusioner Pelamar Asisten Laboratorium Menggunakan Model Hebbian Dan Perceptron Muhammad Fathir Aulia; Armansyah Armansyah
Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Vol 8, No 2 (2025): Juli
Publisher : Akademi Ilmu Komputer Ternate

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47324/ilkominfo.v8i2.324

Abstract

Abstrak: Penelitian ini bertujuan untuk mengimplementasikan model Hebbian dan Perceptron untuk klasifikasi data kuesioner pelamar Asisten Laboratorium yang dikonversi ke format biner dan bipolar. Data kuesioner mengukur ketertarikan dan pengetahuan pelamar terkait bidang ilmu komputer guna menganalisis efektivitas, kecepatan, dan akurasi masing-masing model. Hasil implementasi menunjukkan bahwa model Hebbian dengan input biner tidak mengenali pola hingga epoch ke-10, sedangkan dengan input bipolar berhasil pada epoch ke-2. Model Perceptron dengan input biner mengenali pola pada epoch ke-2, sementara dengan input bipolar pada epoch ke-3. Kedua model dilatih dengan bobot dan bias awal = 0, serta parameter Perceptron berupa threshold (θ) = 0.5 dan learning rate (η) = 0.1. Dari empat pelamar, dua berminat mendaftar. Data dianalisis menggunakan model Hebbian dan Perceptron untuk mengevaluasi ketepatan, kecepatan, akurasi, serta efektivitas. Hasilnya, model Perceptron lebih direkomendasikan karena fleksibel dan mampu bekerja dengan format biner serta bipolar. Temuan ini memberikan wawasan dalam memilih model klasifikasi yang tepat untuk seleksi pelamar Asisten Laboratorium.Kata kunci: Klasifikasi, Hebbian, Perceptron, Biner - BipolarAbstract: This research aims to implement the Hebbian and Perceptron models for the classification of Laboratory Assistant applicant questionnaire data converted to binary and bipolar formats. The questionnaire data measures the applicant's interest and knowledge related to the field of computer science to analyze the effectiveness, speed, and accuracy of each model. The implementation results show that the Hebbian model with binary input does not recognize patterns until the 10th epoch, while with bipolar input it succeeds at the 2nd epoch. The Perceptron model with binary input recognized the pattern at the 2nd epoch, while with bipolar input at the 3rd epoch. Both models were trained with initial weight and bias = 0, and Perceptron parameters of threshold (θ) = 0.5 and learning rate (η) = 0.1. Of the four applicants, two were interested in applying. The data was analyzed using Hebbian and Perceptron models to evaluate precision, speed, accuracy, and effectiveness. As a result, the Perceptron model is more recommended as it is flexible and able to work with binary as well as bipolar formats. The findings provide insights in choosing the right classification model for Laboratory Assistant applicant selection.Keywords: Classification, Hebbian, Perceptron, Binary - Bipolar