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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Knowledge Engineering and Data Science ILKOM Jurnal Ilmiah CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Computer Science and Information Technologies Indonesian Journal of Data and Science Innovation in Research of Informatics (INNOVATICS) Buletin Sistem Informasi dan Teknologi Islam Ilmu Komputer untuk Masyarakat Jurnal Pengabdian Mandiri Open Community Service Journal Bulletin of Social Informatics Theory and Application NERO (Networking Engineering Research Operation) International Journal of Artificial Intelligence in Medical Issues
Huzain Azis
Unviersitas Muslim Indonesia
Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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The use of augmented reality to educate preschoolers on preventing dental malocclusion Salim, Yulita; Puspitasari, Yustisia; Azis, Huzain; Anas, Risnayanti
Bulletin of Social Informatics Theory and Application Vol. 3 No. 2 (2019)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v3i2.184

Abstract

According to the World Health Organization (WHO), malocclusion is a deviation in dentofacial growth or an abnormal relationship between the teeth of both arches, which results in impaired physical function for sufferers. Causes of malocclusion include genetic factors, inappropriate growth and development processes, bad habits of children, and malnutrition. Also, malocclusion can be caused by a lack of knowledge of children, parents, and guardians of students in the school environment in maintaining oral health. Nurul Falah Kindergarten, located in Mamajang District in the middle of Makassar City. However, students in kindergarten are from the middle to lower economies with a lack of dental and oral health awareness. According to the principal, some students come with the condition of not brushing teeth and with cavities. This service activity aims to help solve the problems faced by teachers in pre-school age students by providing dental education based on Augmented Reality and Topical Application Fluor (TAF) as an effort to prevent malocclusion. It is hoped that through this activity malocclusion prevention can be done through promotive efforts on dental health. This dental extension will be complemented by the utilization of information technology advances in the form of android-based Augmented Reality (AR) technology that is able to visualize an object in 3 dimensions so that the counseling process becomes more interactive and real.
One-gateway system in managing campus information system using microservices architecture Salim, Yulita; Muis, Ismunandar; Syafie, Lukman; Azis , Huzain; Rachman Manga, Abdul
Bulletin of Social Informatics Theory and Application Vol. 7 No. 2 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i2.635

Abstract

Universitas Muslim Indonesia (UMI) has developed several applications for managing the campus's digital information and management systems, both internally and externally. However, several applications were previously created in the development of information system applications at UMI. However, these applications were not well-suited for long-term use due to their complexity and lack of integration. Therefore, UMI aims to create a fully integrated and well-managed campus information system by implementing the concept of microservices. The microservices approach involves dividing large applications into smaller interconnected components. This approach facilitates the management of application systems and enables better integration. Moreover, the microservices approach simplifies system maintenance for application developers, as each application is separated into smaller components
Multiclass Classification of Rupiah Banknotes Based on Image Processing Azis, Huzain; Purnawansyah, Purnawansyah; Alfiyyah, Nurul
ILKOM Jurnal Ilmiah Vol 16, No 1 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i1.1784.87-99

Abstract

This research aims to classify the nominal value of Rupiah banknotes using image processing and classification methods. The research design was conducted by collecting a dataset of Rupiah banknotes consisting of 30 classes, each with 100 images. This research uses image preprocessing using Canny Segmentation to create object edges and clarify image details. The Hu Moments method, which describes pixel distribution and object shape, is used to extract special features from the image. Classification modeling is then performed using Decision Tree and Random Forest to classify banknotes based on the extracted characteristics. Model evaluation is performed by measuring accuracy, precision, recall, and f1socre performance and using cross-validation with k-fold=5. The results show that the Decision Tree method is able to classify Rupiah banknotes well. In the performance evaluation, the Decision Tree method achieved the highest accuracy of 86.83% and good precision, recall, and f1-score for several banknote classes. The Random Forest method also achieved good results, with the highest accuracy of 78.67%. The classification evaluation results show that the Decision Tree method is better than the Random forest in classifying Rupiah banknotes.
An Analysis of Classification Method Performance on Handwritten Lontara Numerals Bustam, Faida Daeng; Purnawansyah, Purnawansyah; Azis, Huzain
Innovation in Research of Informatics (Innovatics) Vol 6, No 2 (2024): September 2024
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v6i2.11999

Abstract

The research investigates the performance of various classification methods on handwritten Lontara digits, a script used by the Bugis and Makassar communities in South Sulawesi, Indonesia. The dataset comprises 10,890 samples from 99 individuals, categorized into 10 classes (digits 0-9). The study employs the K-Nearest Neighbors (KNN), Gaussian Naive Bayes (GNB), and Nu-Support Vector Classifier (NuSVC) algorithms, implementing cross-validation to assess accuracy, precision, recall, and F1 score. The results indicate varying performance across classifiers, with GNB showing the highest recall, while KNN and NuSVC display moderate effectiveness. The study concludes with recommendations for further improving classification accuracy through enhanced feature extraction and algorithm optimization.
Comparative Performance Evaluation of Classification Methods for Arabic Numeral Handwritten Recognition Saly, Intan Novita; Purnawansyah, Purnawansyah; Azis, Huzain
Innovation in Research of Informatics (Innovatics) Vol 6, No 2 (2024): September 2024
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v6i2.11998

Abstract

This study aims to evaluate the performance of various classification methods in recognizing handwritten Arabic numerals, particularly the K-Nearest Neighbors (KNN), Gaussian Naive Bayes (GNB), and NU Support Vector Classifier (NU SVC) algorithms. In this study, a dataset of handwritten Arabic numerals consisting of 9,350 samples with 10 different classes was used. The research process involved data collection, data labeling, dividing the dataset into training and testing data, implementing classification algorithms, and performance testing using cross-validation methods. The results showed that NU SVC had more stable performance with accuracy close to KNN, while GNB showed the lowest performance. The conclusion of this study emphasizes that the selection of algorithms and parameter optimization is crucial to improve the accuracy and efficiency of handwriting recognition systems. Support Vector Machine (SVM) based algorithms proved to be superior in handling complex classification tasks compared to GNB. This study provides significant contributions to the field of handwriting recognition, particularly in the context of Arabic numeral handwriting, and can serve as a reference for developers of optical character recognition (OCR) systems in the future. Future research is recommended to increase the variety of datasets and further explore parameter optimization and data preprocessing techniques to improve system accuracy.
Analisis Quality of Service Layanan Video Surveillance Area Traffic Control System (ATSC) Pada Jaringan Internet Dinas Perhubungan Kota Kendari Nur bahri, Nur Bahri; Salim, Yulita; Azis, Huzain
Indonesian Journal of Data and Science Vol. 3 No. 3 (2022): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v3i3.52

Abstract

Dinas Perhubungan Kota Kendari menjadi salah satu kota yang telah menerapkan teknologi ATCS. Proses pemantau dilakukan menggunakan CCTV melalui jaringan internet yang dipantau secara real time melalui ruang kontrol Dinas Perhubungan Kota Kendari. Penerapan layanan video surveilance ATCS pada dinas perhubungan kota Kendari masih sering terjadi kendala seperti akses video surveillance yang dilakukan secara real-time mengalami buffering sehingga kualitas video yang ditampilkan tidak optimal. Permasalahan yang terjadi tersebut perlu dilakukan tindak lanjut penanganan dengan melakukan analisa layanan atau yang dikenal dengan Quality of Service. untuk menentukan apakah kualitas jaringan pada Layanan Video surveillance ATCS yang digunakan telah sesuai atau perlu dilakukan peningkatan kualitas sesuai standarisasi Tiphon dengan menggunakan metode Action Research (AR). Hasil penelitian menunjukkan hasil dari penguuran jaringan dinas Perhubungan Kota Kendari mendapatkan nilai QoS “3,55” dengan indeks “memuaskan” dan Pada Provider data (Tri) dengan nilai QoS “3,31” dengan kategori “memuaskan” yang telah di kategorikan pada standarisasi Tiphon.
Analisis Performa Metode Gaussian Naïve Bayes untuk Klasifikasi Citra Tulisan Tangan Karakter Arab Nurul A'ayunnisa; Salim, Yulita; Azis, Huzain
Indonesian Journal of Data and Science Vol. 3 No. 3 (2022): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v3i3.54

Abstract

Berdasarkan penelitian yang dilakukan oleh Herman dkk., peneliti mencoba mengangkat kembali metode yang diterapkan dengan menggunakan dataset yang berbeda dan dengan jumlah yang lebih banyak. Penelitian ini bertujuan untuk menghitung performa metode (akurasi, presisi, recall, dan f-measure) Gaussian Naïve Bayes. Dataset yang digunakan adalah citra tulisan tangan karakter arab. Berdasarkan hasil perhitungan performa menunjukkan tingkat akurasi tertinggi sebesar 12%, presisi 10%, recall 12%, dan f-measure 8%.
Prediksi Potensi Donatur Menggunakan Model Logistic Regression jabir, sitti rahmah; Azis, Huzain; Widyawati, Dewi; Tenripada, Andi Ulfa
Indonesian Journal of Data and Science Vol. 4 No. 1 (2023): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v4i1.64

Abstract

GRDS menghadapi kelangkaan dana, ketika diperlukan untuk merawat para korban Gaja. Gaja adalah topan bernama kelima dari musim siklon Samudra Hindia Utara 2018 yang mempengaruhi sebagian besar tempat di Tamil Nadu, India selama bulan November 2018. Tujuan dari penelitian ini adalah untuk menggunakan riwayat donasi untuk menganalisis apakah donator akan menyumbang atau tidak menggunakan regresi logistik. Data Tamil Nadu diberikan untuk menerapkan model yang dibangun untuk memprediksi donator yang paling mungkin menjadi korban topan Gaja. Pada tahap pengumpulkan data seringkali terjadi hambatan, salah satu hambatannya yaitu fenomena missing data atau data hilang. Akibat dari adanya missing data adalah pendugaan parameter menjadi tidak efisien. Ukuran data yang berkurang dapat mengakibatkan kesulitan dalam menganalisis, sehingga hasil yang didapatkan menjadi tidak valid dan tujuan dari penelitian tidak tercapai. Data yang hilang akan diisi menggunakan metode single imputation. Data yang telah diimputasi menggunakan beberapa metode akan membantu dalam melakukan prediksi. Dimana algoritma yang digunakan untuk melakukan prediksi ialah logistic regression. Beberapa data dihilangkan setelah melihat multikolinearitas. Dalam tahap pemodelan, data dibagi menjadi 2 yaitu 70% untuk data pelatihan dan 30% untuk data tes. Dimana hasil perhitungan akurasi dari model ialah 0,6129 yang menunjukkan bahwa model tidak melakukan prediksi dengan baik menggunakan metode tersebut.
Comparative Analysis of Machine Learning Algorithm Variations in Classifying Body Shaming Topics on Social Media X Nurul Fitri H, Sarah FIla; Fattah , Farniwati; Azis, Huzain
Indonesian Journal of Data and Science Vol. 5 No. 2 (2024): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v5i2.82

Abstract

Machine learning is an approach in computer science where systems or models can learn from data and experience to improve performance or perform specific tasks. There are several popular machine learning algorithms, such as naïve bayes, decision tree, K-NN, and SVM. This study aims to compare the performance of accuracy, precision, recall, and F-1 score in sentiment analysis of body shaming topics on Social Media X (formerly known as Twitter) by applying decision tree, K-NN, and SVM methods and identifying the most effective algorithm in classifying the data. Based on the classification performance testing results, it can be concluded that the classification method using the trigram feature model provides the best performance compared to other methods. The trigram model is able to achieve high recall, particularly in recognizing positive classes, without significantly compromising accuracy
Perancangan Aplikasi E-Ticketing dengan Model Arsitektur Microservice Menggunakan Kafka Pradinata, Awal; Belluano, Poetri Lestari Lokapitasari; Azis, Huzain
Buletin Sistem Informasi dan Teknologi Islam (BUSITI) Vol 4, No 3 (2023)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v4i3.1806

Abstract

Arsitektur microservice memecah sistem yang kompleks dan besar menjadi serangkaian layanan kecil dan mandiri. Salah satu pola arsitektur yang umum digunakan adalah pendekatan event driven, yang memungkinkan komunikasi berbasis event antar layanan. Namun, pendekatan ini juga membawa risiko kehilangan data, yang dapat diatasi dengan pola orkestrasi menggunakan Apache Kafka sebagai message broker. Kafka menyediakan platform yang cocok untuk komunikasi event driven dengan kemampuannya dalam menyimpan, menerima, dan mengirim pesan secara asinkron. Penelitian ini bertujuan membangun aplikasi e-ticketing berbasis web dengan menggunakan arsitektur microservice dan Kafka. Hasilnya adalah sebuah aplikasi e-ticketing yang menggunakan Kafka untuk komunikasi antar layanan, dengan implementasi lima topik untuk proses transaksi antar gate-ticketing-service dan gate-acl-service secara asinkron menggunakan Kafka sebagai media pengiriman event.
Co-Authors Abdul RAchman Manga Admojo, Fadhila Tangguh Alfa Faridh Suni Alfiyyah, Nurul Alisma, Alisma Alwi Alwi Anas, Risnayanti Andi Tenri Sumpala, Andi Tenri As'ad, Ihwana Baharuddin, Mus Mulyadi Bustam, Faida Daeng Dolly Indra Erick Irawadi Alwi Erma Susanti Fadhila Tangguh Admojo Faradibah, Amaliah Farniawati Fattah Farniwati Fattah Fattah , Farniwati Fattah, Farniawati Fattah, Farniwati Felix Andika Dwiyanto Fika Hastarita Rachman, Fika Hastarita Firdaus Solihin Harlinda Lahuddin Hasanuddin, Tasrif Haviluddin Haviluddin Herdianti Darwis Herdianti Darwis Herman Herman Ika Oktavia Suzanti Inggrianti Pratiwi Putri jabir, sitti rahmah Kamil, Fajrul Ihsan Lokapitasari Belluano, Poetri Lestari M. Imam Maulana Manga, Abdul Rachman Muh Nurtanzis Sutoyo Muhammad Syahrizal Darwis Muis, Ismunandar Mus Mulyadi Baharuddin Nirmala Nirmala, Nirmala Nirwana Nirwana Nur bahri, Nur Bahri Nurul A'ayunnisa Nurul Fitri H, Sarah FIla Pradinata, Awal Purnawansayah Purnawansayah Purnawansyah Purnawansyah Puspitasari, Yustisia Putri Utami, Aulia Putri, Aulia Maharani Putri, Inggrianti Pratiwi Rachman Manga, Abdul Ramadan, Syahril Ramdan Satra Rasman Rasman Rismayanti, Nurul Rochman, Eka Mala Sari Sainlia, Ahmad Fauzan Salim, Yulita Saly, Intan Novita Selvi Marcellia Shidiq Arif Siwiantoko Syafie, Lukman Tasrif Hasanuddin Tenripada, Andi Ulfa Widyawati, Dewi Yulita Salim