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Aplikasi Helpdesk Dengan Pendekatan Knowledge Management System Menggunakan Framework Codeigniter Dan Notifikasi Telegram Shidiq Arif Siwiantoko; Herman Herman; Huzain Azis
Buletin Sistem Informasi dan Teknologi Islam (BUSITI) Vol 3, No 2 (2022)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v3i2.1119

Abstract

Pengadilan Tinggi Makassar membawahi 27 satuan kerja Pengadilan Negeri sehingga bagian Teknologi Informasi Pengadilan Tinggi tidak hanya menanggani permasalahan di Pengadilan Tinggi saja tetapi juga permasalahan pada Pengadilan Negeri. Bagian Teknologi Informasi Pengadilan Tinggi Makassar belum memiliki suatu aplikasi yang dapat digunakan sebagai media untuk melaporkan masalah terkait aplikasi, server serta kendala teknis yang berhubungan dengan teknologi informasi serta belum ada basis knowledge yang berkaitan dengan teknologi informasi. Untuk saat ini jika terjadi permasalah yang tidak dapat diselesaikan pada satuan kerja Pengadilan Negeri maka bagian teknologi informasi Pengadilan Negeri akan menghubungi bagian teknologi informasi Pengadilan Tinggi Makassar melalui media whatsapp atau telephone untuk melaporkan permasalah dan meminta bantuan untuk diperbaiki. Hal itu membuat permasalah yang ada tidak terdokumentasikan dengan baik serta sulit untuk dilakukan monitoring dan pelaporan. Berangkat dari permasalahan yang ada maka penulis tertarik untuk membuat sebuah aplikasi helpdesk yang dapat menjadi solusi dari permasalah yang ada. Aplikasi ini akan dibangun dalam bentuk web dengan menggunakan Framework Codeigniter versi 3.1.10 yang akan diintegrasikan dengan aplikasi telegram. Metode yang digunakan dalam pembuatan aplikasi ini yaitu dengan menggunakan metode Extreme Programming yang termasuk kedalam Agile Methods.
ANALISIS PERFORMA METODE K-NEAREST NEIGHBOR UNTUK IDENTIFIKASI JENIS KACA Mus Mulyadi Baharuddin; Huzain Azis; Tasrif Hasanuddin
ILKOM Jurnal Ilmiah Vol 11, No 3 (2019)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i3.489.269-274

Abstract

Nowadays, the industry makes various types of goods that have glass-based materials, float car window panes, non-float building windows, lamps, jars, and tableware. These glasses have the same production material, the difference between one and the other is the composition of the production material. K-Nearest Neighbor (KNN) algorithm which is one of the classification methods in data mining and also a supervised learning algorithm in machine learning is a method for classifying objects based on learning data that is the closest distance to the object.. This study discusses the performance measurement (accuracy, precision, recall and f-measure) of the KNN method with a variety of values on 1000 glass type production data objects obtained from the central UCI Machine Learning Repository dataset. The conclusion of this research is the results of the value of K = 3 to K = 9, the best performance values obtained at K = 3, where the level of accuracy reaches 64%, 63% precision, 71% recall, and F-Measure of 67%.
The weighted product method and portfolio assessment in ranking student achievement Andi Tenri Sumpala; Muhammad Nurtanzis Sutoyo; Huzain Azis; Fadhila Tangguh Admojo
ILKOM Jurnal Ilmiah Vol 13, No 2 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i2.827.148-154

Abstract

The learning process has a correlation with learning achievement which can be shown through the marks given by a teacher to students from several fields of study. The ranking of student learning achievements performed by the school refers to the grades of the subject is important for the SNMPTN (National Selection for State Higher Education). To determine student achievements, the method used in the current study is the weighted product. If the results of student ranking using the WP method have the same value, then a portfolio assessment is used. Of the 127 student achievement ratings, there were seven people who had the same Vector value. Then, the seven people who have the same vector value were graded using portfolio assessment. The results showed that the implementation of the WP method and portfolio assessment could determine the ranking of student achievement.
PERANCANGAN SISTEM INFORMASI WISATA HALAL GUNUNG KANDORA TANA TORAJA Herdianti Darwis; Abdul RAchman Manga; Huzain Azis
JURNAL PENGABDIAN MANDIRI Vol. 2 No. 1: Januari 2023
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Sistem informasi berbasis web telah menjadi salah satu trend pemanfaatan teknologi yang saat ini ditemui di dunia pariwisata dan ekonomi kreatif sebagai salah satu alternatif penyampaian informasi (pengetahuan dan berita) berbasis Internet yang dikeluarkan oleh dinas pariwisata atau pengelola tempat wisata dengan tujuan untuk kemudahan dalam pendistribusian informasi pada publik, baik masyarakat sekitar, wisatawan domestik, maupun wisatawan mancanegara. Sehubungan dengan hal tersebut, Fakultas Ilmu komputer sebagai lembaga yang berperan aktif dalam pengembangan dan penerapan teknologi informasi di Kawasan Indonesia Timur dengan visi fakultas yaitu “Smart Village” yang bersinergi dengan visi Universitas Muslim Indonesia terkait “Halal Issues” melakukan peningkatan kualitas dan pengembangan desa di Lembang Marinding Kecamatan Mengkendek Tana Toraja khusus di bidang pariwisata halal dan ekonomi kreatif melalui sebuah kegiatan pengabdian kepada masyarakat (PkM) yang dilaksanakan dalam bentuk pengembangan website bagi pengelola Gunung Kandora Kabupaten Tana Toraja demi peningkatan pendapatan ekonomi daerah dan secara khusus untuk kesejahteraan masyarakat sekitar.
Investigasi Aplikasi Facebook Messenger Pada Smartphone Berbasis iOS Menggunakan Metode DFRWS Muhammad Syahrizal Darwis; Erick Irawadi Alwi; Huzain Azis
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 9 No 2 (2023): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v9i2.2696

Abstract

The increase in the number of Facebook Messenger application users certainly has positive and negative impacts. Common crimes such as drug trafficking, terrorism, murder planning and other crimes that use facebook messenger as a medium of communication. The crime will certainly leave a trail that can be used as digital evidence. This study aims to conduct an analysis on an iOS-based smartphone and examine digital evidence on the Facebook Messenger application. The method used is a digital forensics research workshop in investigating smartphone devices by looking for evidence in the form of digital conversations via text messages. The results of the investigation carried out in the form of information to prove that the perpetrator is a criminal, the information is then presented in the form of a forensic report that will be used during the trial. Keywords— Facebook-Messenger, iOS, Digital Evidence, DFRWS Meningkatnya jumlah pengguna aplikasi Facebook Messenger tentunya membawa dampak positif dan negatif. Kejahatan umum seperti perdagangan narkoba, terorisme, perencanaan pembunuhan dan kejahatan lainnya yang menggunakan facebook messenger sebagai media komunikasi. Kejahatan tersebut tentunya akan meninggalkan jejak yang dapat dijadikan sebagai barang bukti digital. Penelitian ini bertujuan untuk melakukan analisis terhadap smartphone berbasis iOS dan mengkaji bukti digital pada aplikasi Facebook Messenger. Metode yang digunakan adalah workshop penelitian forensik digital dalam menginvestigasi perangkat smartphone dengan mencari bukti berupa percakapan digital melalui pesan teks. Hasil penyidikan yang dilakukan berupa informasi untuk membuktikan bahwa pelaku merupakan pelaku tindak pidana, informasi tersebut kemudian disajikan dalam bentuk laporan forensik yang akan digunakan selama persidangan. Kata Kunci—Facebook-Messenger, iOS, Bukti Digital, DFRWS
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 study aimed 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 by using Canny Segmentation to create the edges of objects and clarify image details. The Hu Moments method, which describes the pixel distribution and shape of objects, was used to extract special features from images. Furthermore, classification modeling was carried out with Decision Tree and Random Forest to classify banknotes based on extracted characteristics. Model evaluation was carried out by measuring accuracy, precision, recall and f1-score performance and using cross-validation with k-fold = 5. The results showed that the Random Forest method was able to classify Rupiah banknotes well. In performance evaluation, the Random Forest method achieved an accuracy of 0.93 and good precision, recall, and f1-score scores for several banknote classes. The Decision Tree method also achieved good results, with an accuracy of 0.86. The results of the classification evaluation showed that the Random Forest method was better than the Decision Tree in classifying the 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.