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All Journal INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Wahana Internet of Things and Artificial Intelligence Journal
Prayogi, Andi
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Identification of Tajweed Recognition using Wavelet Packet Adaptive Network based on Fuzzy Inference Systems (WPANFIS) Siregar, Ratu Mutiara; Satria, Budy; Prayogi, Andi; Pane, Muhammad Akbar Syahbana; Awal, Elsa Elvira; Sari, Yessi Ratna
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 1 (2024): Volume 4 Issue 1, 2024 [February]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i1.703

Abstract

This research aims to develop a system capable of processing voice input to recognize Al-Quran reading by recitation of Tajwid, using wavelet signal extraction and classification of Tajwid rules using ANFIS. The process stages include data acquisition, audio data pre-processing, extraction using wavelet packets, division of training data and test data, and classification. The data obtained were 20 observations from 10 observations carried out in data pre-processing. The wavelet decomposition process produces six main features as ANFIS input variables and 64 rules. Then the data was separated into 17 observations for training data and three for testing data. The test results obtained from the training that had been carried out produced plots that were too fit; in this experiment, the WPANFIS classification model got 100% appropriate classification and SSE values that were the same as the training result, 0.00081225.
Sosialisasi Digital Marketing pada UMKM Keripik Selasih di Kelurahan Sentang, Kecamatan Kisaran Timur, Asahan Simbolon, Hasanal Fachri Satia; Pane, Muhammad Akbar Syahbana; Saleh, Khairul; Siregar, Ratu Mutiara; Prayogi, Andi; Sugianto, Raden Aris; Wahyuni, Ritna
Wahana Jurnal Pengabdian kepada Masyarakat Vol. 4 No. 1 (2025): Edisi Juni
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/wahana.v4i1.906

Abstract

UMKM memiliki peran strategis dalam mendorong pertumbuhan ekonomi masyarakat, termasuk di Kabupaten Asahan, Sumatera Utara. Salah satu UMKM yang berpotensi untuk dikembangkan adalah Keripik Selasih, yang memiliki produk unggulan namun masih mengalami kesulitan dalam pemasaran digital. Kurangnya pengetahuan dan keterampilan dalam memanfaatkan teknologi digital menjadi hambatan utama dalam memperluas jangkauan pasar. Kegiatan Pengabdian Kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan kapasitas pelaku UMKM Keripik Selasih dalam bidang digital marketing, melalui pelatihan yang mencakup penggunaan media sosial, pembuatan konten kreatif, dan pemanfaatan platform promosi daring. Metode pelaksanaan meliputi tahap persiapan, pelatihan tatap muka, praktik langsung, serta evaluasi hasil. Diharapkan melalui kegiatan ini, pelaku UMKM mampu memasarkan produk secara lebih efektif, memperluas jaringan konsumen, dan meningkatkan pendapatan usaha. Kegiatan ini juga menjadi bentuk kontribusi nyata mahasiswa dalam mendukung pemberdayaan ekonomi lokal melalui pendekatan teknologi informasi.
Palm Oil Quality Based on Free Fatty Acid Using SVM Prayogi, Andi; Aly, Moustafa H.; Ikhwan, Ali; Pane, Muhammad Akbar Syahbana; Siregar, Ratu Mutiara
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 9 No 2 (2025): August 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v9i2.24797

Abstract

Background: Palm oil is one of the key commodities in both the food and non-food industries, with its quality largely influenced by the level of Free Fatty Acid (FFA). Obejctive: High FFA content can reduce the stability and market value of the oil. Classify palm oil quality based on FFA levels using the Support Vector Machine (SVM) algorithm. Methods: FFA levels were measured across multiple samples with varying usage frequencies (0, 5, 7, and 9 cycles) using the alkalimetric titration method. The measured data was categorized as "Suitable" if FFA ≤ 0.3% and "Unsuitable" if it exceeded this threshold. The developed SVM model was trained using 70% of the data and tested with the remaining 30%. Results: Evaluation results indicate that the model achieved an accuracy of 95%, a precision of 92%, and a recall of 94%, demonstrating SVM's effectiveness in classifying data. Additionally, hyperplane visualization using PCA provided a clearer distinction between oil categories based on FFA levels. Conclusion: This study highlights that SVM can serve as an effective alternative for FFA-based palm oil quality classification. The implementation of this model is expected to enhance efficiency in the palm oil industry, particularly.
Co-Authors Ali Ikhwan Aly, Moustafa H. Awal, Elsa Elvira Khairul Saleh Muhammad Akbar Syahbana Pane Ratu Mutiara Siregar Ritna Wahyuni Sari, Yessi Ratna Simbolon, Hasanal Fachri Satia Sugianto, Raden Aris