Article Per Year (5 Year)
p-Index From 2020 - 2025
3.648
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Komputer Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) SENTIA 2015 MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Informatika dan Rekayasa Elektronik Journal of Information Systems and Informatics TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Bumigora Information Technology (BITe) Jurnal Pengabdian kepada Masyarakat Nusantara ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat International Journal of Electronics and Communications Systems Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) SATIN - Sains dan Teknologi Informasi Journal Of Artificial Intelligence And Software Engineering Jurnal Pengabdian kepada Masyarakat IPTEKS Jurnal Pengabdian Pada Masyarakat IPTEKS
Triwijoyo, Bambang Krismono
Universitas Bumigora
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Nursing Social Sciences Other

Published : 27 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 27 Documents
Search

 1   2   3 
Smart Parking Space Detection Using Advanced Deep Learning Techniques Aguswandi, Lalu Heri; Triwijoyo, Bambang Krismono; Martono, Galih Hendro
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6473

Abstract

This study aims to develop an accurate and efficient empty parking slot detection model to assist users in finding parking spaces. The developed model utilizes YOLOv11 as a pretrained model and demonstrates excellent performance with a precision of 99%, recall of 99%, and a Mean Average Precision (mAP) of 99%. These results validate the model's ability to accurately detect empty parking slots with 100 training epochs. Additionally, the model operates in real-time with a frame rate of 25 frames per second (FPS)
Integrasi Basis Data Properti Menggunakan Metode Schema Matching Dengan Pendekatan Linguistic dan Constraint Hariri, Muhammad; Triwijoyo, Bambang Krismono; Martono, Gallih Hendro
Jurnal Bumigora Information Technology (BITe) Vol. 7 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v7i1.4872

Abstract

Background: The rapid development of technology has driven progress across various sectors, including the property industry in Indonesia. However, property data integration on Lombok Island still faces challenges due to the diversity of attribute naming, which hinders efficient information retrieval.Objective: This study aims to integrate four property databases (Saduthama, Salva, SJP, and Garden View) using a schema matching method based on linguistic and constraint approaches.Methods: The linguistic approach is used to identify similarities between attributes, even when their names differ, using the Bigram technique, which proved effective in identifying attribute similarities with a threshold of 0.7. Meanwhile, the constraint approach evaluates the compatibility of attributes based on additional criteria such as data type, attribute length, null values, and uniqueness, ensuring that the integrated attributes work compatibly. The integration process includes preprocessing, generalization, and attribute matching.Result: The evaluation results show precision (P), recall (R), and F-measure of 90%, with an average accuracy of 84%.Conclusion: This result outperforms previous studies that achieved 100% precision, 60% recall, and 75% F-measure.
Pendampingan Dan Pelatihan Desain Grafis SMK Islam Terpadu Darul Mujahidin Lombok Tengah Adil, Ahmat; Tajuddin, Muhammad; Pribadi, Agus; Triwijoyo, Bambang Krismono; Anas, Andi Sofyan; Santoso, Heroe
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 2 (2025): Jurnal Pengabdian kepada Masyarakat Nusantara Edisi April - Juni
Publisher : Lembaga Dongan Dosen

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

Abstract

Kegiatan pendampingan dan pelatihan desain grafis ini bertujuan untuk meningkatkan keterampilan siswa SMK Islam Terpadu Darul Mujahidin Lombok Tengah dalam bidang desain grafis, khususnya pada pembuatan produk percetakan seperti brosur, kartu nama, pamflet, dan kemasan produk. Pelatihan dilaksanakan sebagai bentuk penguatan kompetensi keahlian dan kesiapan siswa menghadapi dunia industri kreatif yang semakin berkembang pesat. Peserta mendapatkan manfaat dari pelatihan ini yaitu memperoleh pengetahuan dan keterampilan praktis di bidang desain grafis, khususnya dalam pembuatan produk percetakan seperti brosur, pamflet, kartu nama, dan siswa dapat menyalurkan ide dan kreativitasnya secara visual, serta belajar menyusun desain yang komunikatif dan menarik. Metode pelatihan meliputi pemberian materi dasar desain grafis, pengenalan software desain seperti Canva dan CorelDRAW, serta praktik langsung pembuatan desain cetak. Kegiatan dilakukan secara bertahap, mulai dari teori dasar desain (elemen & prinsip), tipografi, warna, hingga proses produksi desain siap cetak. Selain itu, diberikan pula sesi konsultasi dan evaluasi karya untuk mengasah kreativitas dan kerapian teknis. Hasil pelatihan menunjukkan bahwa peserta mengalami peningkatan pemahaman dan keterampilan teknis dalam membuat desain grafis yang sesuai standar industri percetakan. Pelatihan ini diharapkan mampu menjadi bekal awal bagi siswa dalam mengembangkan kemampuan desainnya secara mandiri dan profesional, serta membuka peluang usaha mandiri di bidang percetakan.
Implementasi Perangkat Lunak Deteksi Penyakit Retinopati Hipertensi Di Polimata Rumah Sakit Umum Provinsi Nusa Tenggara Barat Triwijoyo, Bambang Krismono; Adil, Ahmat; Zulfikri, Muhammad; Widyawati, Lilik; Miswaty, Titik Ceriyani; Patty, Elyakim Nova Supriyedi
Jurnal Pengabdian Pada Masyarakat IPTEKS Vol. 2 No. 1: Jurnal Pengabdian Pada Masyarakat IPTEKS, Desember 2024
Publisher : CV. Global Cendekia Inti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71094/jppmi.v2i1.71

Abstract

Hypertensive retinopathy is a type of eye disease where microvascular changes occur in the retina experienced by high blood pressure sufferers. The arterial and venous ratio (AVR) in the retina of the eye is an indicator used to determine the presence of high blood pressure, which is measured by the ratio of the width of the retinal arteries and veins. Traditionally, ophthalmologists use fundus images or retinal images of the eye to diagnose hypertensive retinopathy's physical symptoms and determine the phase of evolution. Still, traditional methods have limitations because, in the case of borderline stages, the early symptoms of hypertensive retinopathy will be difficult to identify manually, so they are often ignored. Referring to these problems, early diagnosis is needed for accurate prevention and treatment of hypertensive retinopathy. Based on the abovementioned issues, this service activity aims to implement a hypertensive retinopathy disease detection model using a local dataset from a regional general hospital in West Nusa Tenggara (NTB). It will compare the model detection results with those of three eye disease experts. Classification model testing results using the Messidor training and NTB Regional Hospital datasets. In models using the Messidor training dataset, the highest accuracy is a comparison with the results of the most senior expert's observations. The results of the classification model are only a tool to assist ophthalmologists in diagnosing hypertensive retinopathy, while the final decision remains with the expert or ophthalmologist.
Optic Disk Segmentation Using Histogram Analysis Triwijoyo, Bambang Krismono
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 1 No. 1 (2022): March 2022
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v1i1.1799

Abstract

In the field of disease diagnosis with ophthalmic aids, automatic segmentation of the retinal optic disc is required. The main challenge in OD segmentation is to determine the exact location of the OD and remove noise in the retinal image. This paper proposes a method for automatic optical disc segmentation on color retinal fundus images using histogram analysis. Based on the properties of the optical disk, where the optical disk tends to occupy a high intensity. This method has been applied to the Digital Retinal Database for Vessel Extraction (DRIVE)and MESSIDOR database. The experimental results show that the proposed automatic optical segmentation method has an accuracy of 55% for DRIVE dataset and 89% for MESSIDOR database
Visualization of Gastric Acid Reflux Using Mobile-Based Augmented Reality Adil, Ahmat; Triwijoyo, Bambang Krismono; Madani, Miftahul; Damar, Lalu Riyandi
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 1 No. 2 (2022): September 2022
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v1i2.2370

Abstract

Interactive information media has many benefits in the process of conveying information, one of which is by visualizing objects in real time. Socialization activities at the Rensing Health Center in conveying information on gastric diseases still do not use visual aids as a medium for delivering counseling. Therefore, this study aims to develop information media in the form of an android application by utilizing Augmented reality (AR) technology to show the stomach acid process in real time which is visualized in the form of 3D animation. The method used in application development is Multimedia Development Life Cycle (MDLC). Where this method consists of 6 (six) stages of development, namely concept, design, Material Collecting, Assembly, testing and distribution. The results of this study are a visualization application of gastric acid reflux using mobile-based augmented reality built using Unity 2017.3.1f1 and the Vuforia Software Development Kit (SDK), with several stages of the process, namely entering the database and all assets into unity, lighting, creating a user interface, scripting and finally build the application to the android platform Based on the results of application trials that have been carried out at the Rensing Health Center, it shows that mobile-based augmented reality has succeeded in assisting officers in visualizing gastric acid reflux. The satisfaction of health officers in using the application can be seen from the results of the questionnaire to the respondents, where the results of the questionnaire 32% stated strongly agree, 59% agreed, 6% disagreed and 2% disagreed.
Image Classification of Medicinal Plants Using Inception V3 and CNN: A Novel Implementation Kartarina, Kartarina; Islamiah, Nuratun; Supatmiwati, Diah; Zulfiqri, Muhammad; Triwijoyo, Bambang Krismono; Amrullah, Rahayun
International Journal of Electronics and Communications Systems Vol. 5 No. 2 (2025): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042//ijecs.v5i2.27930

Abstract

Indonesia is recognized as one of the world's biodiversity hotspots, with around 30,000 of the 40,000 global medicinal plant species found in its territory. This biological wealth is a strategic asset for health innovation and digital preservation. In areas with limited access to healthcare services, medicinal plants are the primary source of treatment, but their use is still hampered by the lack of a technology-based identification and documentation system. This study aims to develop and test a classification model for medicinal plants using a Convolutional Neural Network with Inception V3 architecture. The study uses the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework, which ensures systematic stages of business understanding, data preparation, modeling, and evaluation. The dataset used consists of 2,750 leaf images in 25 classes, compiled from previous research and independent collections. The data was divided into 1,921 images for training and 823 images for testing using a 70:30 ratio. The model was evaluated using accuracy, precision, recall, and F1 score. The results showed that the Inception V3-based CNN achieved a training accuracy of 96%, which increased to 97% with optimized weights, while maintaining strong precision, recall, and F1 scores. This proves that the Inception V3-based approach is capable of providing high and stable classification performance for the identification of Indonesian medicinal plants. These findings highlight the effectiveness of the model in identifying Indonesian medicinal plants from leaf images, providing a promising foundation for the development of knowledge and potential real-world applications
Co-Authors Agus Pribadi, Agus Aguswandi, Lalu Heri Ahmat Adil Amrullah, Rahayun Andi Sofyan Anas Anthony Anggrawan Ayu Dasriani, Ni Gusti Azhar, Raisul Christopher Michael Lauw Dadang Priyanto Damar, Lalu Riyandi Deny Jollyta Diah Supatmiwati Dian Syafitri Chani Saputri Elyakim Nova Supriyedi Patty, Elyakim Nova Supriyedi Ervina Farijki Fahly, Moh. Rizky Galih Hendro Martono Hairani Hairani Hariri, Muhammad Husain Husain Islamiah, Nuratun Kartarina, Kartarina Lalu Riyandi Damar Lalu Yuda Rahmani Karnaen Lilik Widyawati Martono, Gallih Hendro Mayadi Mayadi Miftahul Madani Miswaty, Titik Ceriyani Muhammad Haris Nasri Ni Wayan Yuli Ariyanti Risca Anggraeni Dwiputri Santoso, Heroe Sirojul Hadi Tajuddin, Muhammad Tomi Tri Sujaka Zulfikri, Muhammad Zulfiqri, Muhammad