Article Per Year (5 Year)
p-Index From 2021 - 2026
4.465
P-Index
This Author published in this journals
All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jupiter Prosiding Semnastek Annual Research Seminar JOIN (Jurnal Online Informatika) Jurnal Ilmiah Matrik Jurnal Sisfokom (Sistem Informasi dan Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JOISIE (Journal Of Information Systems And Informatics Engineering) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Journal of Information Systems and Informatics Jurnal Teknologi Dan Sistem Informasi Bisnis Zonasi: Jurnal Sistem Informasi Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Teknologi Informatika dan Komputer Journal of Computer and Information Systems Ampera Jurnal Pengembangan Sistem Informasi dan Informatika Jurnal Media Informatika Jurnal Nasional Pengabdian Masyarakat Jurnal Komputer, Informasi dan Teknologi International Journal Software Engineering and Computer Science (IJSECS) RESLAJ: Religion Education Social Laa Roiba Journal Ngabdimas Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
Ilman Zuhri Yadi
Universitas Bina Darma
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

Published : 40 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 40 Documents
Search

 1   2   3   4 
RANCANG BANGUN DESIGN UIUX PADA APLIKASI WORKFIT MENGGUNAKAN METODE DESIGN THINKING Alsindo, Yanzen; Ariandi, Muhamad; Yadi, Ilman Zuhri; Oktarina, Tri
JOISIE (Journal Of Information Systems And Informatics Engineering) Vol 7 No 2 (2023)
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/joisie.v7i2.3596

Abstract

Berangkat dari pemasalahan di tengah pandemic, Penelitian ini berfokus untuk mengatasi tantangan yang di mana masyarakat enggan keluar rumah dan mengalami penurunan pola hidup sehat. dengan memanfaatkan kemajuan teknologi informasi dan komunikasi, Penelitian ini akan mengembangkan platform inovatif bernama Workfit. Workfit bukan hanya sekadar platform booking kelas gym secara online, tetapi juga merupakan alat dukungan komprehensif bagi masyarakat untuk mengadopsi gaya hidup sehat. metode yang digunakan dalam perancangan platform ini adalah Design Thinking, yang melibatkan tahapan empathize, define, ideate, prototype, dan test. Dalam proses ini, penelitian tidak hanya fokus pada fungsi teknis platform, tetapi juga memahami secara mendalam kebutuhan dan keinginan pengguna. Hal ini bertujuan untuk menciptakan pengalaman pengguna yang optimal. Hasil penelitian ini mencakup pengembangan model UI/UX untuk aplikasi mobile Workfit. model ini tidak hanya menyelesaikan permasalahan praktis dalam pemesanan kelas gym, tetapi juga memberikan informasi, artikel, dan video yang relevan untuk memotivasi pengguna dalam menjalani gaya hidup sehat, Oleh karena itu, penelitian ini memiliki urgensi yang tinggi dalam mendukung kesehatan dan kesejahteraan masyarakat di era modern ini.
Image segmentation of Komering script using bounding box Hamanrora, Muhammad Dio; Kunang, Yesi Novaria; Yadi, Ilman Zuhri; Mahmud, Mahmud
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i3.pp1565-1578

Abstract

The development of deep learning technology is widely used for various purposes, including recognizing characters in a document. One of the scripts that can benefit from this deep learning technology is the Komering script, which is a local script in the South Sumatra region. However, there are challenges in reading documents written in this script, requiring a method to separate each character in a document. Therefore, there is a need for a technology that can automatically segment images of documents written in the Komering script. This research introduces an innovative technique for segmenting images of characters in documents that contain Komering script characters. The segmentation technique employs bounding box technology to separate each Komering script character, subsequently recognized by a pre-trained deep learning model. The bounding box approach imposes restrictions on the segmented object area. To recognize Komering characters, a deep learning model with a convolutional neural network (CNN) algorithm is employed.
Analisa QoS Pada Jaringan Voice Over Internet Protocol Server Portable Berbasis Raspberry Pi Menggunakan Metode Action Research Pada Daerah Tak Terjangkau Sinyal Dan Sumber Daya Listrik M. Dimas Goworzky; Alex Wijaya; Ilman Zuhri Yadi; Timur Dali Purwanto
Jurnal Komputer, Informasi dan Teknologi Vol. 4 No. 2 (2024): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v4i2.2115

Abstract

Teknologi telekomunikasi sudah menjadi kebutuhan penting bagi manusia untuk bersosialisasi. Contohnya telepon, namun telepon memerlukan alat pendukung agar beroperasi sesuai fungsinya seperti sumber daya listrik dan pemancar provider. Pada penelitian ini metode yang digunakan adalah Action Reseach dalam pembuatan VoIP Server berbasis Raspberry Pi tanpa koneksi internet menggunakan baterai aki mobil sebagai sumber energi dan menggunakan sistem operasi RasPBX sebagai pondasi utama dengan aplikasi Asterisk dan FreePBX. Selanjutnya uji coba performansi QoS saat melakukan panggilan yaitu dengan komunikasi antar client dan komunikasi terhadap jarak router access point menggunakan parameter Delay, Jitter, Throughput, Packet Loss dan parameter Mean Opinion Score untuk pengukuran kualitas suara. Hasil penelitian ini merupakan sebuah implementasi metode Action Research pada VoIP Server berbasis Raspberry Pi tanpa koneksi internet menggunakan baterai aki mobil sebagai sumber energi dan memperoleh nilai QoS komunikasi antar client yaitu dengan rata–rata Delay (6 ms), rata-rata Jitter (5.6 ms), rata-rata Packet Loss (0.73%), rata-rata Througput (341 bps), rata–rata MOS (5 atau sempurna) sedangkan komunikasi terhadap jarak router access point memperoleh nilai QoS yaitu dengan rata–rata Delay (10 ms), rata-rata Jitter (9 ms), rata-rata Packet Loss (3.15%), rata–rata Througput (168 bps), rata–rata MOS (4 atau baik).
Clustering Model for OKU Timur Script Images Toriko, Liu; Purnamasari, Susan Dian; Kunang, Yesi Novaria; Yadi, Ilman Zuhri; Andri, Andri
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 1 (2025): JANUARY
Publisher : ISB Atma Luhur

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

Abstract

Abstract— The OKU Timur is a regency located in South Sumatra Province. In the OKU Timur region there are many historical heritage sites, one of which is the script. In general, script is a system of symbols for writing language. The OKU Timur script is a writing system that is usually used by the local community. This writing system is characterized by its unique characters and has high historical and aesthetic value for the local community. The OKU Timur script is used in daily communication, traditional ceremonies, historical documents, and various other cultural contexts. This research aims to develop a clustering model that is used to efficiently and accurately group Of OKU Timur script images based on certain characteristics. By using techniques in the field of clustering such as the K-Means algorithm this model is developed so that the clustering of OKU Timur script images is made automatically in order to save time and effort. The study employs the K-Means algorithm to divide the data into several clusters, grouping data with similar characteristics into one cluster and data with different characteristics into another. This research is also expected to contribute to preserving digital culture so that the development of OKU Timur characters can be passed on to future generations.Keywords— OKU Timur Script, Clustering, K-Means
Pendampingan Pengembangan Aplikasi Statistik Komoditi Berbasis Web pada Dinas Perkebunan Sumatera Selatan Dzakwan, Fadhlur Rahman; Kunang, Yesi Novaria; Yadi, Ilman Zuhri; Afiyudi, Afiyudi
Jurnal Nasional Pengabdian Masyarakat Vol. 6 No. 1 (2025): Jurnal Nasional Pengandian Masyarakat
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jnpm.v6i1.2586

Abstract

This article discusses a community service program involving assistance in developing a web-based commodity statistical application at the South Sumatra Plantation Office. This activity aims to enhance data processing efficiency and disseminate information related to plantation commodities. This program involves training staff in the use of information technology and developing applications that meet user needs. The methodologies applied include needs analysis, system design, implementation, and application evaluation. The assistance results indicate a significant improvement in data accuracy and ease of information access, positively impacting policy decision-making in the plantation sector. This activity is expected to contribute to developing similar applications in other government agencies and encourage the use of technology in commodity data management.
Rule-Based Transliteration of Ulu Kaganga Script using Character Mapping Yadi, Ilman Zuhri; Kunang, Yesi Novaria; Sari, Tia Permata; Mahmud, Mahmud; Ramadhona, Nuzulur
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.1000

Abstract

Ulu Kaganga script is a historical writing tradition that developed in the southern region of Sumatra. With the widespread use of Latin script, the Ulu Kaganga script has become rare, and very few people can read and write in this script. To preserve the Ulu script, a tool is needed to assist in transliterating Latin text into the Ulu script. This research aims to preserve the Ulu script with the help of technology. In this study, a mobile and web-based application has been developed to transliterate the Ulu Kaganga script from Latin text. The technique used for this script conversion is rule-based, which is employed to break words into syllables and map those syllables into Ulu script characters. Through the rule-based technique and character mapping, adding Indonesian syllables and writing Ulu Kaganga script characters, consisting of 1139 primary characters, becomes easy. This application has been repeatedly tested to improve the mapping of Ulu script characters. The results of testing the application to transliterate 1746 words from Latin script were successful in transliterating. The tests conducted show that the approach used is very effective, with a transliteration accuracy from Latin to Ulu script of 99.98% The testing results show that the application can transcribe text accurately and conveniently, allowing non-expert users to write in Ulu script characters.
Prapemrosesan untuk Klasifikasi Gambar Aksara OKU Timur Prasetya, M. Iqbal; Yadi, Ilman Zuhri; Kunang, Yesi Novaria; Permatasari, Susan Dian
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 1 (2025): Januari 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i1.1629

Abstract

This study investigates methods to enhance the quality of OKU Timur script images through preprocessing techniques utilizing Adaptive Thresholding. The OKU Timur script, significant for daily communication and traditional ceremonies, encounters challenges such as skew, rotation, and low resolution in image processing. The proposed preprocessing approach includes contrast normalization to improve image clarity, noise reduction to eliminate unwanted artifacts, and feature extraction to emphasize critical image characteristics. These steps are designed to enhance the accuracy of character recognition. The findings indicate that proper preprocessing is crucial for effective recognition of OKU Timur script and holds substantial potential for preserving this cultural heritage through modern technological applications.
Clustering Data Penyakit Pasien Pada Puskesmas Mulyaguna Menggunakan Algoritma K-Means Ziqrullah, Muhammad Hafiz; Andri, Andri; Purnamasari, Susan Dian; Yadi, Ilman Zuhri
Jurnal Media Informatika Vol. 6 No. 1 (2024): Jurnal Media Informatika Edisi September - Desember
Publisher : Lembaga Dongan Dosen

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

Abstract

asdsad
Besemah Language Translation Machine Model Based on Machine Learning with Recurrent Neural Network (RNN) Model Algorithm Andika, Muhamad; Kunang, Yesi Novaria; Yadi, Ilman Zuhri; Purnamasari, Susan Dian
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 1 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i1.2614

Abstract

Indonesia consists of various tribes with their respective regional languages, one of which is the Besemah tribe in South Sumatra Province with its language culture, namely the Besemah Language. Until now, the Besemah Language is still used by the Besemah tribe, but over time the number of Besemah Language speakers has decreased, plus most of the wider community does not know what the Besemah Language is. Machine Learning is a part of artificial intelligence that is often used to solve various problems. Machine Learning involves the use of computers and mathematical algorithms that use data to make predictions in the future. Machine translation is a tool that can convert one language to another. This study aims to collect datasets in the form of sentences and words from the Besemah Language, then create a Besemah Language translation machine to Indonesian and vice versa. In the research conducted, the approach used is Experimental Research in Machine Learning. Experimental research in machine learning for language translation is a research approach that involves designing and implementing a series of experiments to test and validate the performance of the language translation model. In this study, Neural Machine Translation (NMT) technology was applied with the Recurrent Neural Network (RNN) approach. The results of the study showed that the val_accuracy value for the Besemah-Indonesian translation was 0.8469 and for Indonesia-Besemah was 0.8492, in the translation trial conducted using the RNN model, 100 epochs, batch size 64, and validation split of 0.2.
Clustering OKU Timur Script Images using VGG Feature extraction and K-Means Toriko, Liu; Purnamasari, Susan Dian; Kunang, Yesi Novaria; Yadi, Ilman Zuhri; Andri, Andri
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 1 (2025): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i1.2292

Abstract

This study focuses on the utilization of clustering models to group manuscript images from the OKU Timur region based on specific characteristics. OKU Timur is rich in cultural heritage, including a unique writing system known as the OKU Timur script. The development of intelligent systems technology can be employed to recognize the OKU Timur script. For this purpose, a dataset of OKU Timur script is needed, which will later be used for classifying script images. One of the challenges in preparing the dataset is grouping a large number of script image samples according to the number of characters. A proposed solution in this research is to automatically group script images by applying the K-Means algorithm. The dataset comprises 2,280 images, representing 19 characters and 228 variations with different diacritics. Features are extracted using the VGG16 model, which are then clustered with the K-Means algorithm. Clustering performance is evaluated based on the percentage of correctly grouped characters. For 19 groups (character count), the model achieves an accuracy of 82.6%. For 228 groups (variations and diacritics), it correctly groups 48.16% of characters. Despite the challenges, the results demonstrate the model’s potential for further refinement. This study’s contribution lies in introducing an efficient clustering approach for cultural manuscripts, supporting digital preservation, and advancing automatic recognition of the OKU Timur script. These efforts aim to preserve the script for future generations.
Co-Authors Afiyudi, Afiyudi Afriyudi Aldi Hermawan Alex Wijaya Alhimni Alhimni Alsindo, Yanzen Amalia, Rahayu Andika, Muhamad Andri Andri Andri, Andri Anisa Kardiana Anjelina Anjelina Ariandi, Muhamad Ayu Gahardina Bagas Hijra Primantara dedi irawan Dedi Irawan Deni Erlansyah Deska Novita Sari Dzakwan, Fadhlur Rahman Faishol, Ahmad Dzulfaqqor Fikri, M Gllen yusuf abbel Hamanrora, Muhammad Dio Hermawan, Aldi Kurniasih, Rani Tri Kurniati, Rafiqah Kusuma, Doni Lang Dimas Perkasa Leon Andretti Abdillah M Noufal Ikhsani M. Dimas Goworzky Mahmud Mahmud Maria Ulfa Miranda Khairunnisa Muhamad Ariandi Muhammad Deni Alfani Noperman Noperman Oktarina, Tri Oktaviani, Nia Oktaviani, Nia Permatasari, Susan Dian Prasetya, M. Iqbal Putra, M. Soekarno Rahmadini, Aulia Nurul Ramadhona, Nuzulur Reza Juanda Rio Ananda Fitriansyah Sapitri, Wulan Sari, Tia Permata Sisca Monita Suryayusra, Suryayusra Susan Dian Purnamasari Susan Dian Purnamasari, Susan Dian Suyanto Suyanto Suzi Oktavia Kunang Timur Dali Purwanto Toriko, Liu Yesi Novaria Kunang Yulianingsih, Evi Ziqrullah, Muhammad Hafiz