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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) JPPI (Jurnal Pendidikan Islam Pendekatan Interdisipliner) Astonjadro Lexeme : Journal of Linguistics and Applied Linguistics Indonesian Journal of Multidisciplinary on Social and Technology Riwayat: Educational Journal of History and Humanities OPHIOLITE : Jurnal Geologi Terapan Jurnal Kecerdasan Buatan dan Teknologi Informasi Research in Accounting Journal Jurnal Wicara Desa
Irfan Saputra
Institut Teknologi Sepuluh Nopember
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Kinerja Angkutan Umum Dinamis Bus Trans Metro Dewata Pada Masa dan Pasca Pandemi Gunayasa, I Gusti Putu Adi; Susanto, Gede Sri Edi; Pratama, I Gede Putu Riyan Adhi; Saputra, Irfan; Wijaya, Luh Ade Gihan Ayu; Pramesti, Made Indira
Indonesian Journal of Multidisciplinary on Social and Technology Vol. 2 No. 1 (2024)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/ijmst.v2i1.253

Abstract

Transportation is an inseparable part of human life as it plays a crucial role in the distribution of goods, the movement of people, and commodities as micro components of the economy. Transportation is a key element in the economy as it is related to the distribution of goods, services, and labor, and it forms the core of economic activities in urban areas. Various forms of public transportation with different characteristics and levels of service offered, influence the development of urban public transportation systems. This research aims to evaluate the operational performance of public transportation in providing standard services to its passengers. It is expected that the results of this survey will be beneficial for the Government, especially those who manage public transportation in the districts of Tabanan, Badung, and Denpasar. Thus, it can be concluded that Public Transportation in these areas still meets the established operational performance standards.
Web-based geothermal drilling stuck pipe prediction using decision tree algorithm Muhtadlor, Rosyihan; Rosyid, Nur Rohman; Fauziyyah, Anni Karimatul; Setiawan, Lalu Hendra Permana; Saputra, Irfan; Stasa, Pavel; Benes, Filip; Syafrudin, Muhammad; Alfian, Ganjar
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp604-614

Abstract

In geothermal drilling operations, data from rig-mounted sensors play a crucial role in maintaining operational efficiency and preventing drilling failures. However, sensor uncertainties and complex subsurface conditions can lead to stuck pipe incidents, causing significant non-productive time and financial losses. This study proposes web-based drilling monitoring system integrated with machine learning (ML) to predict stuck pipe occurrences in geothermal drilling. Several ML algorithms—decision tree (DT), random forest (RF), naïve Bayes (NB), multilayer perceptron (MLP), and support vector machine (SVM)—were evaluated using geothermal drilling data from an Indonesian geothermal project conducted in 2023. To address class imbalance, the synthetic minority oversampling technique (SMOTE) was applied to the training dataset. Feature selection was performed using the correlation coefficient method, and predictions were generated using a 5 minute sliding window. Among the evaluated models, the DT consistently demonstrated superior performance across multiple prediction horizons (PH), achieving an accuracy of 97.4%, precision of 98.6%, recall of 72.9%, and a ROC-AUC of 0.729 using the top five selected features. The trained model was integrated into web-based monitoring platform that provides visualization and predictive alerts. This system enables early detection and better decision-making, helping improve drilling efficiency, reduce stuck pipe risks, and enhance operational safety.
Co-Authors Aini, Kuratun Akhmad, Ikhbal Alfian, Ganjar Ambarsari, Ika Sartika Anggraeni, Erika Ayu Anisa Putri, Baiq Anshari, Erwin Astari, Novia Umi Asyari, Adam Avini, Terttia Azmi, Zul B, Jalil Benes, Filip Betiya, Vegi Mahlul Chandra Hermanto, Willi Fauziyyah, Anni Karimatul Fikrina, Garin Firdaus Firdaus Gunayasa, I Gusti Putu Adi Handayani, Ridhatul Imam Rozy Zarkasih, Muhammad Imamfajri, Sultan Irwan Muthahanas Ita Juita, Ita Maslan, Maslan Matyani, Matyani Muhammad Syafrudin Muhtadlor, Rosyihan Nuryadin, Nuryadin Pramesti, Made Indira pratama, febri Pratama, I Gede Putu Riyan Adhi Putri, Melinda Kurnia Rahayu, Anita Suciati Ramadan, Galih Resmayanti, Resmayanti Roni, Imran Rosyid, Nur Rohman Septiandani, Risna Septiandani Septiyana, Linda Setiawan, Lalu Hendra Permana Sofyaun, Ashari Stasa, Pavel Sucipto, Muhammad Adi Susanto, Gede Sri Edi thahir, Thahir thahir, Thahir thahir Wahab Wahab Wijaya, Luh Ade Gihan Ayu