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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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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%.
SISTEM PENANDA KEPEMILIKAN FILE DOKUMEN MENGGUNAKAN METODE DIGITAL WATERMARK PADA FILE PENELITIAN DOSEN UNIVERSITAS MUSLIM INDONESIA Yulita Salim; Huzain Azis
ILKOM Jurnal Ilmiah Vol 9, No 2 (2017)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v9i2.125.161-166

Abstract

UMI sebagai perguruan tinggi terbesar dan terbaik di Indonesia bagian timur memiliki database yang cukup besar, terutama pada database penelitian dosen. Banyaknya data yang tersimpan memiliki resiko adanya pengambilan dan pengakuan kepemilikan data khususnya data penelitian dosen. Penelitian ini bertujuan untuk merancang sebuah sistem yang dapat memberi penanda kepemilikan pada sebuah dokumen teks penelitian yang dapat digunakan oleh dosen di UMI. Metode penelitian yang dilakukan meliputi identifikasi masalah, studi literature mengenai file dokumen yang akan digunakan sebagai data uji dan metode Digital Watermark sebagai algoritma untuk penanda kepemilikan file dokumen yang diuji, desain aplikasi desktop menggunakan bahasa pemrograman Java dan MySQL sebagai database server. Hasil penelitian ini adalah sistem yang dapat digunakan dosen maupun pihak Lembaga Penelitian dan Pengembangan Sumber Daya (LP2S) UMI untuk memberi tanda kepemilikan pada dokumen agar dapat memberikan layanan tambahan dalam pengecekan kemiripan judul yang telah ada sebelumnya di LP2S.
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.
Detection System of Strawberry Ripeness Using K-Means Dolly Indra; Ramdan Satra; Huzain Azis; Abdul Rachman Manga; Harlinda L
ILKOM Jurnal Ilmiah Vol 14, No 1 (2022)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v14i1.1054.33-39

Abstract

Strawberry is one type of fruit that is favored by the people of Indonesia. The detection process to identify strawberries can be done by utilizing advances in computer technology, One of them is in the field of digital image processing. In this study, we made a strawberry ripeness detection system using the values of Red, Green and Blue as the reference values, while for identification in determining the type of classification using the K-Means algorithm that uses the Euclidean distance difference as the reference. Based on the results of testing using the K-Means algorithm on 51 strawberry images consisting of ripe, semi ripe and raw fruit yielding an accuracy rate of 82.14%, we also conducted tests other than strawberry images as many as 8 images yielded an accuracy rate of 100%.
ANALISIS LAYANAN KEAMANAN SISTEM KARTU TRANSAKSI ELEKTRONIK MENGGUNAKAN METODE PENETRATION TESTING Huzain Azis; Farniawati Fattah
ILKOM Jurnal Ilmiah Vol 11, No 2 (2019)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i2.447.167-174

Abstract

Payment transactions developed along with technological developments, now days technology supports digital payment, each type of digital transaction has its own security services,  this study focus on the analysis of security services (confidentiality, integrity and availability) using the Penetration Testing method on magnetic stripe cards as a payment transaction playground facility, then comparing security services to the Radio Frequency Identification (RFID) electronic transaction tool. The results of this study are RFID electronic transaction cards that provide a more complete security service as an electronic payment transaction.
Performa Klasifikasi K-NN dan Cross Validation pada Data Pasien Pengidap Penyakit Jantung Huzain Azis; Purnawansyah Purnawansyah; Farniwati Fattah; Inggrianti Pratiwi Putri
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.507.81-86

Abstract

Globally, the number one cause of death each year is cardiovascular disease. Cardiovascular disease is a disease caused by impaired function of the heart and blood vessels, such as coronary heart disease, heart failure or heart failure, hypertension and stroke. The purpose of this study was to measure the performance of accuracy, precision, recall and f-measure of the K-NN and Crossvalidation methods on a dataset of cardiovascular patients. The dataset used was 1000 records consisting of 11 attributes (age, gender, height, etc.) cardiovascular and non cardiovascular patient data, the dataset was obtained from the UCI Machine Learning Repository managed by the Hungarian Institute of Cardiology Budapest: Andras Janosi, MD, University Hospital, Zurich, Switzerland. The steps taken are: dividing the simulation ratio of the dataset to 20:80, 50:50 and 80:20, applying crossvalidation (k-fold = 10) and classification using the K-NN method (k = 2 to K = 900). The research results from the simulation of the dataset ratio 50:50 obtained an accuracy value of 82%, 82% precision, 82% recall and 80% f-measure at a value of K = 13, then the research results from the simulation of the dataset ratio 20:80 obtained an accuracy value of 87%, 87% precision, 97% recall and 92% f-measure at the value of K = 3, and the results of research from the simulation of the dataset ratio 80:20 obtained an accuracy value of 91%, 92% precision, 60% recall and 72% f-measure at the value K = 5.
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
Analisis Performa Metode Support Vector Regression (SVR) dalam Memprediksi Harga Bahan Sembako Nasional Huzain Azis; Purnawansyah Purnawansyah; Nirwana Nirwana; Felix Andika Dwiyanto
ILKOM Jurnal Ilmiah Vol 15, No 2 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i2.1686.390-397

Abstract

Support Vector Regression (SVR) is a supervised learning algorithm to predict continuous variable values. The basic goal of the SVR algorithm is to find the most suitable decision line. SVR has been successfully applied to several issues in time series prediction. In this research, SVR is used to predict the price of staple commodity, which are constantly changing in price at any time due to several factors making it difficult for the public to get groceries that are easy to reach. National staple commodity data consisting of 17 commodities, including shallots, honan garlic, kating garlic, medium rice, premium rice, red cayenne peppers, curly red chilies, red chili peppers, meat of broiler chicken, beef hamstrings, granulated sugar, imported soybeans, bulk cooking oil, premium packaged cooking oil, simple packaged cooking oil, broiler chicken eggs, and wheat flour. With a data set for the last 3 years, including from January 1, 2020, to December 31, 2022. There are 3 variables in the data set, namely commodity, date, and price. This research divides the entire dataset into 80% training and 20% testing data. The results of this research show that SVR using the RBF kernel produces good forecasting accuracy for all datasets with an average Mean Square Error (MSE) training data of 6,005 while data testing is 6,062, Mean Absolute Deviation (MAD) of training data is 6,730 while data testing is 6.6831, Mean Absolute Percentage Error (MAPE) training data is 0.0148 while data testing is 0.0147, and Root Mean Squared Error (RMSE) training data is 7.772 while data testing is 7.746.
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