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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika Geo Media: Majalah Ilmiah dan Informasi Kegeografian JURNAL SISTEM INFORMASI BISNIS Jurnal Simetris Bulletin of Electrical Engineering and Informatics Jurnal EECCIS Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika International Journal of Advances in Intelligent Informatics Jurnal Manajemen Pendidikan Journal of Applied Geospatial Information Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Informatika Jurnal CoreIT Acta Pharmaciae Indonesia : Acta Pharm Indo JMM (Jurnal Masyarakat Mandiri) Edukasi Islami: Jurnal Pendidikan Islam ILKOM Jurnal Ilmiah AL-TANZIM : JURNAL MANAJEMEN PENDIDIKAN ISLAM KOMPUTIKA - Jurnal Sistem Komputer Spatial : Wahana Komunikasi dan Informasi Geografi DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Jurnal Isema : Islamic Educational Management Geodika: Jurnal Kajian Ilmu dan Pendidikan Geografi PREPOTIF : Jurnal Kesehatan Masyarakat JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal of Islamic Education Studies (IJIES) Jurnal Teknik Informatika (JUTIF) Journal of Soft Computing Exploration International Journal of Computer and Information System (IJCIS) Journal Computer Science and Informatic Systems : J-Cosys Journal Of World Science Teokristi: Jurnal Teologi Kontekstual dan Pelayanan Kristiani Jurnal Islam Nusantara SIENNA Mandala of Health : A Scientific Journal Kartika: Jurnal Studi Keislaman International Journal of Multidisciplinary Approach Research and Science 'Asabiyah: Jurnal Pengabdian Hukum Jurnal Komplikasi Anestesi Scientific Journal of Informatics Indonesian Journal of Islamic Education Studies (IJIES) Jurnal Kefarmasian Indonesia Proceeding Of International Conference On Education, Society And Humanity Intelektual: Jurnal Pendidikan dan Studi Keislaman International Journal of Instructional Technology Journal of Software Engineering And Technology Jurnal Info Kesehatan
Adi Wibowo
STAI An-Nawawi Purworejo
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Pendeteksi Suhu dan Kelembaban Ruangan Menggunakan Sensor DHT11 Berbasis Web Server Nugroho, Adam; Wibowo, Adi; Triraharjo, Bambang
Sienna Vol 5 No 2 (2024): Sienna Volume 5 Nomor 2 Desember 2024
Publisher : LPPM Universitas Muhammadiyah Kotabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47637/sienna.v5i2.1644

Abstract

This article discusses the development of an Internet of Things (IoT)-based system to detect room temperature and humidity using a DHT11 sensor whose data is monitored through a web server interface. The research aims to create a real-time monitoring system with effectively integrated data. The research method includes hardware and software design, sensor data collection, and web-based interface development. The results show that this system can detect changes in temperature and humidity with a high level of accuracy and provide easy access via the web. This system has the potential to be applied in the management of indoor environments such as offices, homes, and storage rooms.
Analysis of West Sumatra's Tourism Attraction on The Development of The Minangkabau International Airport Area Anggraini, Kurnia; Wibowo, Adi
Journal of Applied Geospatial Information Vol. 8 No. 2 (2024): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jagi.v8i2.7300

Abstract

The West Sumatra region is very rich in tourism potential, in the form of natural beauty and culture which makes many tourists come to the West Sumatra area. The aim of this research is to analyze the tourist attractions in West Sumatra regarding the development of the Minangkabau International Airport area. The method used in the research uses a qualitative descriptive approach to analyze the tourist attractions in West Sumatra regarding the development of the airport area. The data used to analyze tourist attractions uses secondary data from various related agencies. The development of the airport area uses a remote sensing approach, namely, the digitization method on Google Earth images carried out on Google Earth Pro Software in 2013 and 2023. The results of the research conclude that aircraft movements and passenger movements have increased. From the results of digitization via Google Earth in 2013 and 2023, over the last 10 years, the airport area has experienced development, especially the aircraft parking area, passenger terminal, car parking area, in 2023 there will be additional buildings, namely, the airport station.
Identification of Grouper Fish Types using Convolutional Neural Network Resnet-50 Algorithm Nuraini, Rini; Syafei, Wahyul Amien; Wibowo, Adi; Jaya, Indra
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp173-178

Abstract

Grouper is a type of fish that is popular with the public. It is necessary to identify the type of grouper fish based on color patterns with increase the epoch value to get the best accuracy. The purpose of the research is to predict the type of grouper. This research use CNN Resnet-50 algorithm. 30 data used. The accuracy of prediction is 75 % to predict the image groupers. In the grouper prediction process, the more we increase the epoch value, we will get the best accuracy value. Epoch is a factor that affects the time of training an AI model and affects the accuracy value of the AI model.
Analisis Sentimen Evaluasi Mahasiswa terhadap Layanan di UNISNU Jepara menggunakan Algoritma Support Vector Machine Azizah, Noor; Wibowo, Adi; Warsito, Budi; Maori, Nadia Annisa
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 16, No 1 (2025): JURNAL SIMETRIS VOLUME 16 NO 1 TAHUN 2025
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v16i1.14540

Abstract

Peningkatan kualitas layanan di perguruan tinggi menjadi salah satu fokus utama dalam dunia pendidikan. Evaluasi layanan oleh mahasiswa sering kali mencakup komentar dalam bentuk teks bebas, sehingga memerlukan pendekatan berbasis kecerdasan buatan untuk mengolah data secara efisien dan akurat. Penelitian ini bertujuan untuk menganalisis sentimen mahasiswa terhadap tiga layanan utama di UNISNU Jepara, yaitu layanan akademik, beasiswa, dan perpustakaan, menggunakan algoritma Support Vector Machine (SVM).Penelitian ini mengikuti tahapan metodologi CRISP-DM, meliputi pemahaman bisnis, pemahaman data, persiapan data, pemodelan, evaluasi, serta penarikan kesimpulan. Data yang digunakan berasal dari hasil evaluasi berbentuk komentar terbuka yang dikumpulkan melalui sistem SIAKAD. Data tersebut diproses melalui tahapan text preprocessing sebelum diterapkan algoritma SVM untuk klasifikasi sentimen.Hasil penelitian menunjukkan bahwa algoritma SVM mampu memberikan tingkat akurasi tinggi pada analisis sentimen terhadap ketiga jenis layanan, yaitu 95,8% untuk layanan akademik, 95,7% untuk layanan beasiswa, dan 98,4% untuk layanan perpustakaan. Temuan ini mengindikasikan bahwa algoritma SVM merupakan metode yang efektif untuk analisis sentimen dalam konteks data tidak terstruktur, serta memberikan wawasan strategis yang dapat membantu perguruan tinggi meningkatkan kualitas layanan mereka..
Boosting real-time vehicle detection in urban traffic using a novel multi-augmentation Ashari, Imam Ahmad; Syafei, Wahyul Amien; Wibowo, Adi
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp656-668

Abstract

Real-time vehicle object detection in urban traffic is crucial for modern traffic management systems. This study focuses on improving the accuracy of vehicle identification and classification in heavy traffic during peak hours, with particular emphasis on challenges such as small object sizes and interference from light reflections. The use of multi-label images enables the simultaneous detection of various vehicle types within a single frame, providing more detailed information about traffic conditions. You only look once (YOLO) was chosen for its capability to perform real-time object detection with high accuracy. Multi-augmentation techniques were applied to enrich the training data, making the model more robust to varying lighting conditions, viewpoints, object occlusions, and issues related to small objects. YOLOv8n and YOLOv9t were selected for their speed and efficiency. Models without augmentation, 10 single-augmentation techniques, and 5 multi-augmentation techniques were tested. The results show that YOLOv8n with multiaugmentation (scaling, zoom in, brightness adjustment, color jitter, and noise injection) achieved the highest mAP50-95 score of 0.536, surpassing YOLOv8n with single-augmentation Blur, which had an mAP50-95 of 0.465, as well as YOLOv8n without augmentation, which scored 0.390. Multiaugmentation proved to significantly enhance YOLO’s performance.
ANESTHESIA MANAGEMENT FOR PATIENTS WITH LOW EJECTION FRACTION UNDERGOING CORONARY ARTERY BYPASS GRAFTING (CABG) Wibowo, Adi; Pratomo, Bhirowo Yudho
Mandala Of Health Vol 17 No 2 (2024): Mandala of Health: a Scientific Journal
Publisher : Fakultas Kedokteran Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.mandala.2024.17.2.12982

Abstract

Background: Coronary Artery Disease (CAD) is a condition caused by the formation of blockages in the coronary blood vessels. The primary non-invasive procedure for CAD patients is Percutaneous Coronary Intervention (PCI). However, complications during PCI, such as unstable hemodynamic arrhythmias, can occur, possibly due to Abrupt Vessel Closure (AVC). This remains a major issue for PCI failure and necessitating Coronary Artery Bypass Grafting (CABG). Case: We report a 68-year-old male patient with CAD and total occlusion of the Right Coronary Artery (RCA) and total occlusion of the Left Circumflex (LCx) who was unable to undergo PCI at a previous hospital. Subsequently, re-catheterization at RSUP Dr. Sardjito, CAD3VD was diagnosed, leading to a planned CABG surgery. The patient’s clinical condition was relatively stable, though he had a low ejection fraction (41%). Induction, invasive monitoring placement, and intubation proceeded smoothly. CABG was performed with three grafts (LIMA-LAD, SVG-OM, SVG-PDA), and successful weaning was achieved with dobutamine support. The patient was in the ICU for 2 days for clinical and hemodynamic optimization before being transferred to the ICCU for further intensive care. Discussion: The main principle of anesthetic management in this case is to maintain a balance between myocardial oxygen supply and demand. Strict monitoring of hemodynamic changes during surgery is essential to guide necessary supportive therapy. Patients with low ejection fractions are at high risk for post-operative mortality and complications. Post-operative management in the ICU focuses on optimizing clinical condition and addressing any emerging potential issues. Conclusion: Surgery for patients with CABG requires complicated and complex anesthetic techniques. This operation requires collaboration and good communication between the surgeon and the anesthesiologist.
Traffic flow prediction using long short-term memory-Komodo Mlipir algorithm: metaheuristic optimization to multi-target vehicle detection Ashari, Imam Ahmad; Syafei, Wahyul Amien; Wibowo, Adi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i4.pp3343-3353

Abstract

Multi-target vehicle detection in urban traffic faces challenges such as poor lighting, small object sizes, and diverse vehicle types, impacting traffic flow prediction accuracy. This study introduces an optimized long short-term memory (LSTM) model using the Komodo Mlipir algorithm (KMA) to enhance prediction accuracy. Traffic video data are processed with YOLO for vehicle classification and object counting. The LSTM model, trained to capture traffic patterns, employs parameters optimized by KMA, including learning rate, neuron count, and epochs. KMA integrates mutation and crossover strategies to enable adaptive selection in global and local searches. The model's performance was evaluated on an urban traffic dataset with uniform configurations for population size and key LSTM parameters, ensuring consistent evaluation. Results showed LSTM-KMA achieved a root mean square error (RMSE) of 14.5319, outperforming LSTM (16.6827), LSTM-improved dung beetle optimization (IDBO) (15.0946), and LSTM-particle swarm optimization (PSO) (15.0368). Its mean absolute error (MAE), at 8.7041, also surpassed LSTM (9.9903), LSTM-IDBO (9.0328), and LSTM-PSO (9.0015). LSTM-KMA effectively tackles multi-target detection challenges, improving prediction accuracy and transportation system efficiency. This reliable solution supports real-time urban traffic management, addressing the demands of dynamic urban environments.
Implementation of Support Vector Machine - Recursive Feature Elimination for MicroRNA Selection in Breast Cancer Classification Permatasari, Ratih; Wibowo, Adi
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.602

Abstract

Breast cancer is the most frequent cancer caused death among women. An attempt to reduce death cases caused by breast cancer, was to detect cancer cells when it still in early stage. MicroRNA is one of the biomarker for cancer that can be used to detect cancer cell even in its early stage. However, MicroRNA data tends to have thousand types of expression which required a lot of costs if it examined one by one thoroughly. Feature selection method can be used to extract important MicroRNAs that support clasification process between normal people and people with breast cancer. Support Vector Recursive Feature Elimination (SVM-RFE) is one of the feature selection method that can be used to select MicroRNA data. This research aims to produce the best smallest subset that contains selected MicroRNA expressions using the SVM-RFE as feature selection method. This experiment result showed that the best selected subset was able to provide 99% classification accuracy with only 3 MicroRNA expressions, where 2 from 3 selected MicroRNA hold potential as a biomarker of breast cancer.
Evaluation of Machine Learning Algorithms for Classifying User Perceptions of a Child Health Monitoring Application Rahmawati, Eka; Wibowo, Adi; Warsito, Budi
Jurnal Informatika Vol 12, No 2 (2025): October
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/inf.v12i2.24639

Abstract

Child growth and development are crucial aspects that every parent should monitor carefully. Proper growth and development foster the creation of a high-quality generation for the nation’s future. Recognizing the importance of monitoring children's growth, the Indonesian Pediatric developed PrimaKu, an application designed to assist parents in tracking the children's growth and development. The application includes health guidelines, growth monitoring tools, and immunization schedules. To maximize the application’s effectiveness, it is essential to evaluate its acceptance by the community, which can be assessed through user perceptions. This study evaluates the performance of machine learning algorithms, including Random Forest, Support Vector Machine, Naive Bayes, and Decision Tree, in classifying user perceptions of the PrimaKu application. The results revealed that the Support Vector Machine model achieved the highest accuracy of 81%, followed by Random Forest at 77%, Decision Tree at 74%, and Naive Bayes at 73%. Precision, recall, and F1-score used to validate the models' performance as the evaluation metrics. The findings underscore the potential of machine learning techniques in effectively classifying user feedback, providing valuable insights for improving application development and enhancing user satisfaction. This study contributes to understanding user acceptance of digital tools for child health monitoring, paving the way for better application usability and community impact
Design of a Web-Mobile Based Information System for Monitoring Maintenance and Repair Reports of Electrical Substations Leni, Leni; Wibowo, Adi
International Journal of Computer and Information System (IJCIS) Vol 6, No 3 (2025): IJCIS : Vol 6 - Issue 3 - 2025
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v6i3.256

Abstract

The manual workflow for reporting maintenance and repair of electrical substations at PT Haleyora Power, which relies on WhatsApp and Microsoft Excel, creates various obstacles, such as delays, risk of data errors, and a minimal capacity for real-time monitoring. This research aims to design and implement a web-based monitoring information system to overcome these inefficiencies. The development method used is Prototyping, which emphasizes active user involvement through an iterative evaluation cycle. The system was built using PHP-MySQL and comprehensively tested based on five quality aspects from the ISO/IEC 25010 standard: functional suitability, reliability, usability, performance efficiency, and security. The research results show the system was successfully built and passed all tests, achieving 100% in functional suitability, high reliability with no data loss, and a usability score of 86%, which is categorized as 'very feasible' by users. The implemented system successfully transformed the manual reporting process into a centralized digital workflow, significantly improving efficiency, data accuracy, and providing real-time monitoring capabilities for management.
Co-Authors Adi Wibowo Airawata, Chintya Puteri Akhmad Yun Jufan Amalia, Iza Nur Amir Amir Andre Leander Anggraini, Kurnia Anindya Wirasatriya Aprillia, Teya Aris Puji Widodo Ariyanti, Atika Astuty, Yulia Indri Aulia Kumala, Shofa Aulia, Hozana Baharun, Hasan Baskoro Baskoro, Baskoro Bayu Surarso Budi Warsito Budiman, Naufal Chin, Wei Hong Daimah Daimah Daimah, Daimah Djayanti Sari Drihananto, Angga Dyna Marisa Khairina eka rahmawati Evi Frimawaty Fajrul Falah, M Rizqi Faridah, Ida Febriatul Khasanah, Qoidah Firdonsyah, Arizona Gafuraningtyas, Dewi Gunanto, Sigit Hadi, Marhensa Aditya HENDRI WASITO Hening Pratiwi, Hening I Ketut Agung Enriko Imam Ahmad Ashari, Imam Ahmad Indra Jaya Indrajaya Indrajaya Ita Nurmalasari Khawaiji, Imron khusnul khotimah Khusnul Khotimah Kiswanto Kiswanto Kosasih, Eva Dania Kubota, Naoyuki Kumala, Shofa Aulia Kuncoro Adi Pradono Kurnianingsih Kurnianingsih, Kurnianingsih Kusworo Adi Lailiyah, Rosyidah Nur Leni Leni Lily Puspa Dewi Lutfan Lazuardi Made Suadnyani Pasek Maori, Nadia Annisa Mardalena, Ayu Moh. Roqib mohamad jamil Mohamad Madum Muhajir Muhajir, Muhajir Mulyani, Heny Muslihatin Nurhasanah Nahri, Aisyah Chorijatun Nia Kurnia Sholihat, Nia Kurnia Nisa’, Khoirun Noor Azizah Nugroho, Adam Nur Cholid, Nur Nur Hadian Nurmalasari, Ita Paramitha Putri, Nadya Pratomo, Bhirowo Yudho Purwanto Purwanto Putri, Niken Anissa Qolbi, Muhammad Syifaa’ul Rahmadi Rani Rubiyanti, Rani Ratih Permatasari Ribah, Muhammad Ato Ibnu Rini Nuraini, Rini Rizal, Himmatur Rofikatul Maula Roisu Eny Mudawaroch Roziana Roziana, Roziana Saepurohman, Aep Shintiani, Selly Shofy, Yuny Fikriyah Sholihah, Daimah Siti Nur Hasanah, Siti Nur Slamet Riyanto Solihat, Nia Kurnia Sri, Tovani subur subur Suhartini Ismail, Suhartini Supriyatin, Tabah Suseno, Aji suswati suswati Sutrisno, Sutrisno Tri, Indra Gaya Triraharjo, Bambang Ulumuddin, Imam Khoirul Vianita, Etna Wahyudi, Edi Wahyul Amien Syafei WARDAH, ZAHROTUL Whisnumurti Adhiwibowo Wiranjaya, I Wayan Satryadi Yulia, Nunung