Article Per Year (5 Year)
p-Index From 2021 - 2026
2.771
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Teknosains: Media Informasi Sains dan Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer REKAYASA JOIV : International Journal on Informatics Visualization Jurnal Teknologi Pendidikan Madrasah Indonesian Journal of Electrical Engineering and Computer Science Jurnal Pengabdian kepada Masyarakat Nusantara Journal of Applied Data Sciences Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Jurnal Edukasi dan Pengabdian kepada Masyarakat (JEPKM) International Journal of Health and Information System (IJHIS) Jurnal Imu Pendidikan dan Keagamaan Ruang Komunitas : Jurnal Pengabdian Masyarakat
Tajuddin, Muhammad
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Library & Information Science Medicine & Pharmacology Physics Public Health Social Sciences Other

Published : 18 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 18 Documents
Search

 1   2 
Development of character extraction techniques to detect chicken gender based on egg shape Setiawan, Adil; Yuhandri, Yuhandri; Tajuddin, Muhammad
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp1851-1861

Abstract

This research investigates the differentiation of chicken sex based on egg shape images by developing an innovative eccentricity shape feature extraction method. The goal is to determine the sex of chickens before hatching, by identifying the sex of the egg prior to incubation. Images of eggs are captured using a smartphone camera, creating a dataset of 150 images each of male and female eggs, with expert assistance. The research aims to accurately identify male and female eggs, aiding breeders in sorting them. The research introduces a unique method to expand the eccentricity value range, enhancing the precision of egg shape analysis. Characteristic extraction results include: area = 1290194, eccentricity = 6.56, contrast = 0.03, correlation = 0.99, energy = 0.44, and homogeneity = 0.98, with a previous value of 0.72. For Feature Selection, the values obtained are: eccentricity = 0.901188049, Area = 0.73, Energy = 0.03, Contrast = 0.01, Homogeneity = 0.01, and Correlation = 0.01. These findings demonstrate significant improvements in differentiating chicken sex from egg images, showcasing the effectiveness of the newly developed eccentricity shape feature extraction method.
Pendampingan Dan Pelatihan Digital Marketing UMKM Desa Batu Asak - Lombok Tengah adil, ahmat; Tajuddin, Muhammad; Anas, Andi Sofyan; Muhid, Abdul; Pribadi, Agus; Dharma, I Made Yadi
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 1 (2025): Jurnal Pengabdian kepada Masyarakat Nusantara Edisi Januari - Maret
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v6i1.4765

Abstract

Usaha Mikro Kecil dan Menengah (UMKM) merupakan suatu bentuk usaha kecil masyarakat yang sangat berperan dalam mengurangi tingkat pengangguran yang ada di Indonesia karena dapat menyerap banyak tenaga kerja. UMKM di Desa Batu Asak terdiri dari beragam usaha, seperti makanan tradisional, kerajinan tangan dan lain-lain, yang pelakunya adalah sekumpulan ibu rumah tangga. Terdapat banyak permasalahan dalam mengembangkan usaha mereka, terutama menyangkut pemasaran produk yang hanya dijual dilingkungan sekitar atau menerima pesanan saat ada kegiatan pernikahan dan keagamaan. Hal ini disebabkan kurangnya pengetahuan pelaku usaha terhadap pemasaran produk termasuk kurang memahami pemanfaatan teknologi dalam memasarkan produk. Oleh karena itu, dibutuhkan pendampingan dan pelatihan untuk meningkatkan pengetahuan dan wawasan mitra dibidang digital marketing. Hasil akhir yang diharapkan dari kegiatan ini adalah, peserta memperoleh pemahaman yang lebih baik tentang strategi digital marketing seperti SEO, SEM, pemasaran media sosial, dan email marketing, dan menggunakan alat-alat digital marketing seperti Google Analytics, Google Ads, dan platform media sosial.
Membangun Kesadaran Mengaji Sebagai Pembentukan Karakter Islami Pada Generasi Muda Ganrang Batu Selatan, Kabupaten Jeneponto Fathin, Alfidhah; Aksa, Aksa; Yani, Ahmad; Tajuddin, Muhammad
Jurnal Edukasi dan Pengabdian kepada Masyarakat Vol. 3 No. 2 (2024): Desember 2024
Publisher : Yayasan Insan Literasi Cendekia (INLIC) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35914/jepkm.v3i2.241

Abstract

Pembentukan karakter Islami pada generasi muda merupakan aspek penting dalam menjaga nilai-nilai agama dan moralitas di tengah arus modernisasi. Penelitian ini bertujuan untuk mengkaji peran kesadaran mengaji dalam pembentukan karakter Islami pada generasi muda di Dusun Ujung Bori. Melalui pendekatan kualitatif, penelitian ini dilakukan dengan metode observasi, wawancara, dan studi literatur untuk mengeksplorasi tingkat kesadaran mengaji dan dampaknya terhadap pembentukan karakter Islami. Hasil PKM menunjukkan bahwa kesadaran mengaji yang tinggi di kalangan generasi muda di Dusun Ganrang Batu Selatan memiliki korelasi positif dengan perilaku yang mencerminkan nilai-nilai Islami, seperti kedisiplinan, kejujuran, dan rasa tanggung jawab. Keterlibatan keluarga dan dukungan komunitas lokal juga terbukti sebagai faktor penting dalam mendorong kesadaran mengaji. Penelitian ini menyimpulkan bahwa penguatan program mengaji secara berkelanjutan dan berbasis komunitas dapat menjadi strategi efektif dalam membentuk karakter Islami yang kuat pada generasi muda.
Hybrid CNN Approach for Post-Disaster Building Damage Classification Using Satellite Imagery Sonang, Sahat; Yuhandri, Y; Tajuddin, Muhammad
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.931

Abstract

Accurate post-disaster building damage assessment is critical for timely response and effective reconstruction planning. This study proposes a hybrid deep learning architecture that integrates Inception-ResNet-v2 and EfficientNetV2B0, designed to enhance post-disaster damage classification from high-resolution satellite imagery. The model leverages dual-stream feature extraction, followed by concatenated fully connected layers optimized with dropout and batch normalization to improve generalization and reduce overfitting. The objective is to outperform standard Convolutional Neural Network (CNN) models in terms of classification and segmentation performance across multiple damage categories: no damage, minor damage, major damage, destroyed, and unclassified. The model was trained and validated on the publicly available xView dataset, covering over 12,000 annotated images from various natural disasters. Comparative evaluation against ResNet, GoogleNet, DenseNet, and EfficientNet demonstrates that the proposed model achieves the highest accuracy (86%), precision (85%), recall (86%), and F1-score (84%). Furthermore, it outperforms all baseline models in segmentation metrics, achieving an Intersection over Union (IoU) score of 0.7749 and a Dice Similarity Coefficient (DSC) of 0.8726. The model also significantly reduces misclassification rates in critical categories such as “major damage” and “destroyed.” A Wilcoxon signed-rank test confirmed that these improvements are statistically significant (p 0.05) across all major performance indicators. The novelty of this study lies in the fusion of two state-of-the-art CNN backbones with tailored architectural modifications, yielding a robust and generalizable model suitable for automated disaster damage assessment. This research contributes a scalable deep learning approach that can be integrated into real-time or semi-automated disaster response systems, offering improved decision-making support in emergency contexts. The results affirm the model’s potential as a reliable tool in post-disaster scenarios and set a foundation for future work in multi-modal and real-time AI-based disaster management.
INVENTARISASI ASSET KETAHANAN SOSIAL DI DESA RATTE KABUPATEN POLEWALI MANDAR DENGAN PENDEKATAN ASSET BASED COMMUNITY DEVELOPMENT Hildayanti, Andi; Machrizzandi, M Sya’rani; Tajuddin, Muhammad
Teknosains Vol 17 No 1 (2023): Januari-April
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/teknosains.v17i1.32215

Abstract

Ratte Village, which is located in Tutar or Tubbi Taramanu District, is one of the underdeveloped villages in Polewali Mandar Regency, West Sulawesi Province. The Village Building Index Index shows the lowest index. This is what underlies the implementation of this research activity to be carried out in Ratte Village seeing the status of the underdeveloped village. Through this Asset-Based Community Development approach in a sustainable manner, it can establish community independence by increasing income to increase welfare. This study aims to inventory Social Security Assets in Ratte Village, Polewali Mandar Regency with the Asset Based Community Development (ABCD) Approach. This research uses action research or Participatory Action Research which is carried out through stages (1) Discovery (Assessment); (2) Dream (Dream); (3) Design (procedure); and (4) Define and Destiny. The results of the study indicate that the potential or ability of cooperation, social networks, and social harmony, as well as the activeness of several correctional institutions that are intertwined among the people of Ratte Village are quite strong. Among the 4 (four) social indicators in the IDM, it is known that the education indicator is the indicator with the highest index of achievement. This is reflected in the very high motivation to learn and public awareness in the field of education. The availability of educational facilities and mountain water resources as a mode of driving the village electricity network is also sufficient to help the community carry out daily activities.
Sistem Pengenalan Pembicara dengan Metode Wavelet-MCFF dan Pengklasifikasi Hidden Markov Models (HMM) Hidayat, Syahroni; Anas, Andi Sofyan; Yusuf, Siti Agrippina Alodia; Tajuddin, Muhammad
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 1: Februari 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.0813284

Abstract

Penelitian pengolahan sinyal digital yang berfokus pada pengenalan pembicara telah dimulai sejak beberapa dekade yang lalu, dan telah menghasilkan banyak metode-metode pengenalan pembicara. Di antara algoritma pembentukan koefisien ciri yang telah dikembangkan tersebut, ada dua algoritma yang dapat memberikan akurasi yang tinggi jika diterapkan pada sistem, yaitu Mel Frequency Cepstral Coefficient (MFCC) dan Wavelet. Penelitian ini bertujuan untuk menguji dan memilih kanal terbaik dari proses wavelet-MFCC yang dapat dijadikan sebagai koefisien ciri baru untuk diterapkan pada sistem pengenal pembicara. Koefisien ciri baru tersebut kemudian disebut dengan koefisien ciri Wavelet-MFCC. Kofisien ini dibentuk dari merubah kanal hasil dekomposisi wavelet, yaitu kanal aproksimasi (cA), kanal detail (cD), dan penggabungannya (cAcD), menjadi koefisien MFCC. Metode dekomposisi wavelet yang digunakan adalah metode dyadic dengan menerapkan level dekomposisi level 1 dan level 2. Setiap koefisien ciri kemudian menjadi inputan pada sistem pengklasifikasi Hidden Markov Models (HMM). Keluaran dari HMM kemudian dihitung akurasinya dan dianalisis. Dari pengujian yang dilakukan, diperoleh bahwa kanal detail (cD) sebagai ciri dapat memberikan akurasi yang sama dengan menggunakan kanal gabungan (cAcD) dan lebih tinggi dari kanal aproksimasi (cA), dengan akurasi sebesar 95%. Hal ini menunjukkan bahwa, kanal detail pada dekomposisi level 1 menyimpan ciri suara dari setiap pembicara sehingga sudah cukup untuk dijadikan sebagai koefisien ciri. Maka, penggunaan dekomposisi level 1 dan kanal detail cD sebagai ciri Wavelet-MFCC pada sistem pengenalan pembicara dapat meringankan dan mempercepat proses komputasi. AbstractResearch in digital signal that focused on speaker recognition has begun since decades ago, and has resulted many speaker recognition methods. there are two algorithms that can provide high accuracy in recognition system, which are Mel Frequency Cepstral Coefficient (MFCC) and Wavelet. the aims of this study is to examine and chose the best channel from wavelet-MFCC process that can be used as new feature coefficient, then called as Wavelet-MFCC features coefficient. The coefficient is built by converting the wavelet decomposition channels, which are approximation (cA), detail (cD), and its combination (cAcD), into the MFCC coefficient. Wavelet dyadic decomposition with level 1 and level 2 of decomposition is applied. Each feature coefficient acts as an input to the HMM classifier. The accuracy of the HMM output is calculated, then analyzed. The obtained results show that the detail chanel (cD) achieve equal accuracy as the combination chanel (cAcD), and higher accuracy compared to aproximation channel (cA), with accuracy 95%. Thus, it can be conclude that the detail channel on level 1 decomposition contains features of each speaker's. Then, cD is enough to be used as a Wavelet-MFCC feature. Thus, its implementation in the SRS can ease and speed up the computing process.
Convolutional Autoencoder for Reconstruction of Historical Document Images: Ancient Manuscript Babad Lombok Syuhada, Fahmi; Firdaus, Asno Azzawagama; Ni'mah, Ana Tsalitsatun; Sa’adatai, Yuan; Tajuddin, Muhammad
Rekayasa Vol 17, No 1: April, 2024
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v17i1.26101

Abstract

The Babad Lombok is an ancient literary or manuscripts document that generally contains stories about the origins of the people of Lombok. This document is written on a lontar leaf, which in the past was used to write manuscripts, letters, and documents. At present, the Babad Lombok document can be seen in the form of photos or scans, so it can be viewed without having to go to a museum or cultural heritage site where the document is usually exhibited. However, because this document is an ancient artifact that has been around for hundreds of years, it has naturally experienced fading in the original document or its scanned versions. This makes the text inside less clear. This paper proposes to automatically reconstruct/repair the Babad Lombok document using a neural network. The type of neural network used is an Autoencoder or Convolutional Autoencoder (CAE). The CAE model is built sequentially and trained using original images of Babad Lombok as its training data and manually corrected images of Babad Lombok as the target or ground truth data. In the process, the two types of data are iteratively cropped to a size of 64x64 along the original size of the Babad Lombok image. This process results in input and target data for the CAE training process in this research, each consisting of 48,288 images. Testing the trained autoencoder model shows that the Babad images have been successfully repaired, making the text quality clearer before reconstruction. Ultimately, the proposed CAE has achieved training and validation accuracies of 89.09% and 94.57%, with corresponding loss values of 0.0418 and 0.0226.
Integrasi Kearifan Lokal Massenrempulu dalam Perancangan Sistem Drainase Berkelanjutan di Kabupaten Enrekang Syam, Febrianto; Rivai, Aspin Nur Arifin; Amra, Muhammad Fikri; Irfan, Ahmad Asrul Azwar; Bakar, Abu; Tajuddin, Muhammad; Umar, Kusnadi
RUANG KOMUNITAS: Jurnal Pengabdian Masyarakat Vol 3 No 2 (2025): Ruang Komunitas: Jurnal Pengabdian Masyarakat
Publisher : Program Studi Ilmu Politik bekerjasama Program Studi Hubungan Internasional, Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/rkjpm.v3i2.62516

Abstract

Kabupaten Enrekang menghadapi permasalahan drainase yang kompleks akibat topografi bergunung, curah hujan tinggi, serta lemahnya integrasi antara sistem modern dan kearifan lokal masyarakat. Artikel ini merupakan hasil kegiatan pengabdian kepada masyarakat yang bertujuan mendukung penyusunan naskah akademik Rancangan Peraturan Daerah (Ranperda) tentang Sistem Drainase Perkotaan dan Pedesaan Kabupaten Enrekang. Kegiatan ini mengadopsi pendekatan partisipatif dengan mengintegrasikan pengetahuan teknis modern dan sistem tradisional Massenrempulu. Metode yang digunakan meliputi pendekatan yuridis-normatif dan empiris, kajian literatur, analisis spasial, serta diskusi multipihak. Hasil kegiatan menunjukkan bahwa integrasi kearifan lokal dalam desain sistem eco-drainage mampu meningkatkan efektivitas pengelolaan air, memperkuat partisipasi masyarakat, dan menurunkan risiko banjir hingga 40%. Rekomendasi utama dari kegiatan ini adalah pembentukan Unit Pengelola Drainase Terpadu berbasis kolaborasi pemerintah, masyarakat, dan lembaga adat. Upaya ini diharapkan menjadi model replikasi bagi daerah lain dalam mewujudkan tata kelola air yang berkelanjutan dan berkeadilan ekologis.
Co-Authors Abdul Aziz Abdul Muhid, Abdul Abu Bakar Agus Pribadi ahmad yani Ahmat Adil Akbar Juliansyah Aksa Aksa, Aksa Aldi, Febri Amra, Muhammad Fikri Ana Tsalitsatun Ni'mah Andi Hildayanti Andi Sofyan Anas Ardi, R Fanny Printi Asno Azzawagama Firdaus Fathin, Alfidhah Hammad, Rifqi I Made Yadi Dharma Irfan, Ahmad Asrul Azwar Machrizzandi, M Sya'Rani Masrifah, Rofiah Mildawati, Titi Muchtar, Azmy Ali Nadiroh, Nurlaila Nursalimah, Putri Putra, Ondra Eka Rivai, Aspin Nur Arifin Santoso, Heroe Sa’adatai, Yuan Septiana, Vina Tri Setiawan, Adil Sonang, Sahat Sumijan Sumijan Syahroni Hidayat Syam, Febrianto Syuhada, Fahmi Triwijoyo, Bambang Krismono Umar, Kusnadi Yanto, Musli Yuhandri Yuhandri, Yuhandri Yuhandri, Y Yusuf, Siti Agrippina Alodia Zainal Abidin