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All Journal TEKNIK Jurnal Teknologi dan Manajemen Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL LENTERA : Kajian Keagamaan, Keilmuan dan Teknologi JOURNAL OF APPLIED INFORMATICS AND COMPUTING Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Sisfokom (Sistem Informasi dan Komputer) Technomedia Journal Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Capture : Jurnal Seni Media Rekam Jambura Journal of Informatics Building of Informatics, Technology and Science Jurnal ABDINUS : Jurnal Pengabdian Nusantara Jurnal Teknik Informatika (JUTIF) Business Economic, Communication, and Social Sciences Journal (BECOSS) Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Jurnal Pendidikan dan Teknologi Indonesia Jurnal Locus Penelitian dan Pengabdian Formosa Journal of Computer and Information Science Eduvest - Journal of Universal Studies Jurnal Indonesia : Manajemen Informatika dan Komunikasi The Indonesian Journal of Computer Science
Santoso, Handri
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Strategi Peningkatan Tata Kelola TI di PT Kereta Commuter Indonesia untuk Memenuhi Standar COBIT 2019 Purwadi; Santoso, Handri
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 6 (2025): JPTI - Juni 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.775

Abstract

Tata kelola Teknologi Informasi (TI) yang efektif merupakan faktor krusial dalam menunjang efisiensi operasional dan keberlanjutan layanan pada sektor transportasi publik. PT Kereta Commuter Indonesia (KCI), sebagai penyedia layanan transportasi berbasis rel, menghadapi tantangan dalam meningkatkan tata kelola TI agar selaras dengan standar industri dan regulasi yang berlaku. Penelitian ini bertujuan mengevaluasi tingkat kematangan tata kelola TI di KCI menggunakan framework COBIT 2019 serta merumuskan strategi peningkatan yang relevan. Metode penelitian yang digunakan adalah pendekatan deskriptif kualitatif melalui wawancara, observasi, dan studi dokumentasi. Analisis dilakukan dengan menggunakan teknik konten dan gap analysis untuk mengidentifikasi kesenjangan antara kondisi eksisting dengan target kematangan. Evaluasi mencakup 22 domain COBIT 2019 yang terbagi dalam lima area utama: EDM, APO, BAI, DSS, dan MEA. Hasil asesmen menunjukkan bahwa sebagian besar domain berada pada tingkat Defined (Level 3) dengan rata-rata maturity level sebesar 3,27, menandakan proses telah terdokumentasi namun belum optimal. Beberapa kesenjangan yang diidentifikasi meliputi rendahnya tingkat automasi, keterbatasan kompetensi SDM, serta pengelolaan risiko TI yang belum sistematis. Strategi peningkatan yang diusulkan meliputi penerapan IT Service Management (ITSM), adopsi teknologi cloud, pelatihan dan sertifikasi COBIT 2019, serta penerapan manajemen risiko berbasis ISO 31000. Penelitian ini memberikan kontribusi praktis dalam membantu KCI mencapai tata kelola TI yang lebih matang dan menjadi referensi pengembangan tata kelola TI di sektor transportasi lainnya.
Evaluasi Kematangan Tata Kelola TI dalam Manajemen Risiko dan Keamanan Informasi di PT Kereta Commuter Indonesia Menggunakan COBIT 2019 Purwadi; Santoso, Handri
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 6 (2025): JPTI - Juni 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.776

Abstract

Teknologi Informasi (TI) menjadi tulang punggung operasional perusahaan transportasi modern, termasuk PT Kereta Commuter Indonesia (KCI). Tantangan digitalisasi dan tuntutan regulasi mengharuskan tata kelola TI yang matang. Penelitian ini bertujuan mengevaluasi tingkat kematangan tata kelola TI KCI berdasarkan framework COBIT 2019 untuk mengidentifikasi kekuatan dan area perbaikan. Metode penelitian menggabungkan kuesioner (57 responden), wawancara mendalam dengan stakeholder TI, dan analisis dokumen kebijakan. Hasil menunjukkan tingkat kematangan Defined (3,27) dengan capaian tertinggi pada manajemen risiko (EDM03/nilai 80) dan keamanan informasi (DSS05/nilai 90), sementara arsitektur enterprise (APO03/nilai 65) dan manajemen data (APO14/nilai 55) perlu peningkatan. Analisis mengungkap keselarasan dengan standar BUMN meski terdapat empat rekomendasi strategis: (1) penyelarasan arsitektur TI-bisnis, (2) penguatan kerangka manajemen risiko, (3) implementasi kebijakan keamanan siber terpadu, dan (4) pengembangan program pelatihan SDM berbasis kompetensi. Temuan ini menjadi panduan bagi KCI dan operator transportasi sejenis dalam memperkuat tata kelola TI menghadapi era digital.
TRANSFER LEARNING IMPLEMENTATION ON IMAGE RECOGNITION OF INDONESIAN TRADITIONAL HOUSES Firmansah, R Arif; Santoso, Handri; Anwar, Agus
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 6 (2023): JUTIF Volume 4, Number 6, Desember 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.6.767

Abstract

Indonesia is the largest archipelago in the world that has cultural diversity, one of Indonesia's cultural wealth is the architectural uniqueness of the types of traditional houses that come from different tribes and regions. in this era of digitalization, the younger generation of this nation must continue to preserve cultural wealth, one of which is by building a system that can document and provide learning about image recognition of the archipelago's traditional houses. Thanks to Artificial Intelligence Technology, it is possible to create a smart model that functions as an image recognition with system learning by working with a neural network called deep learning, which is supported by a transfer learning algorithm that can utilize previous models that have been trained, one of which is the MobileNetV2, Resnet50, VGG16 and Xception models as an effort to get a model with high accuracy with limited dataset conditions. So, the purpose as well as the update of this research is to build an image recognition model of Indonesian traditional houses with the transfer learning method. The methods and stages used are CRISP-DM (Cross Industry Standard Process for Data Mining), a standard used to build applications that aim to gain insight from a dataset, the image dataset used in this study was created with the image scraper technique from the internet. The conclusion of this research is that an image recognition model of Indonesian traditional houses is produced by training experiments from 5 transfer learning models that have been determined and the greatest accuracy is obtained, namely 0.96% of the MobileNetV2 transfer training method, the potential for further development for future research is to add more classes and amount of data and design a more detailed and detailed deployment model.
From Logs to Insights in the Pulp & Paper Industry: Generating Structured Alarm Reports Using LLMs and RAG Santoso, Handri; Wijaya, Oktavianus Hendry; Andriani, Febri; Prijantono, Sonny
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5225

Abstract

Effective alarm management is essential in industrial environments to ensure operational safety and minimize costly downtime. Traditional rule-based reporting systems often struggle to handle heterogeneous alarm log formats and the complexity of natural language queries, limiting their adaptability in real-world applications. To address these limitations, this study proposes a generative alarm reporting system that integrates Large Language Models (LLMs) with a Retrieval-Augmented Generation (RAG) framework. The system converts natural language queries into structured JSON filters, enabling efficient retrieval of contextual information from historical alarm logs. Three open-source LLMs—CodeLlama-7B, LLaMA 3.1-8B, and Mistral-7B—were locally deployed and evaluated using both quantitative and qualitative methods. Experimental results show that CodeLlama-7B achieved the best overall performance, with an Exact Match Accuracy of 0.80, a Field Match score of 93.8%, and a 0% Parse Failure Rate, outperforming the other models in reliability and structural consistency. Compared to conventional rule-based approaches, the proposed LLM-RAG integration demonstrates improved relevance, interpretability, and responsiveness in alarm reporting. This work represents the first systematic benchmarking of locally deployed open-source LLMs for industrial alarm management, providing a replicable framework and highlighting their potential to advance intelligent, real-time, and domain-specific reporting in the pulp and paper industry and beyond.
Design and Implementation of A Hot Sealing System on A Bag Machine Based on PLC Tauhid, Tauhid; Sutarna, Nana; Santoso, Handri
Eduvest - Journal of Universal Studies Vol. 5 No. 10 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i10.50005

Abstract

The adhesive or sealing system using the type of bag sealing machine used in the packaging industry is generally using a full-automatic continuous hot sealing machine which is the result of the development of a manual hot sealing type that uses a type of tape sealing bag (duct tape) such as the one in PT.X. Sealing bag problems that often occur are unstable heating processes, clamping settings and also cooling systems that are too fast. Planning the appropriate machine system and program control system can eliminate the problems caused by the sealing in several ways, including; Conducting system simulations and program design based on observation data, assembling and testing the built system. Conducting trials and tests of machine performance as well as testing the results of the bag sealing process. Furthermore, an evaluation of system performance and sealing bag quality results was carried out as well as improvements in system performance results in accordance with ASMEF88 standards. The design and implementation of the manufacture of automation machines and monitoring systems will involve PLC components and IoT technology. So that during the process, the system can be monitored in real time. The final result of this study is expected to reduce the problem of broken sealing in packaging bags by 1%.
Pelatihan Dasar IoT Menggunakan Tinkercad Bagi Siswa SMK Kristen Immanuel Pontianak Rochadiani, Theresia Herlina; Santoso, Handri
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 6 (2023): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v7i6.16031

Abstract

Internet of Things (IoT) technology as one of the technologies in the Industrial Revolution 4.0 era allows communication between electronic devices and sensors via the internet. This is very helpful for human life. Various applications of IoT have expanded in the fields of medicine, agriculture, logistics, energy, and many more. With the rapid growth of IoT even in the industrial world, professionals who have capabilities in this field are needed. Responding to the need for manpower in the Industrial Revolution 4.0 era, this community service activity was carried out to equip students at Vocational High Schools (SMK). The implementation of this activity succeeded in providing understanding and knowledge to the students of Christian Vocational High School Immanuel, Pontianak. This is indicated by 63% of the student participants experiencing an increase in their pre-test and post-test scores.
Sound-Based Smart Toddler Monitoring System: AIoT Development with YAMNet on Raspberry Pi Rochadiani, Theresia Herlina; Santoso, Handri; Wasito, Ito; Sucipto, Nadya Rudie; Anggraini, Astria Febrian; Panna, Ariya
TEKNIK Vol 46, No 3 (2025): Juli 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/teknik.v46i3.76484

Abstract

The safety of toddlers at home is paramount for parents, but constant monitoring is difficult due to busy schedules. The limitations of camera-based monitoring solutions, namely privacy concerns and heavy processing, drive the need to develop monitoring systems that utilize sound recognition. This research aims to develop Smart Guardian, an Artificial Intelligence of Things (AIoT) system that can detect risky or emergency sound patterns from children and send real-time notifications to parents' mobile phones. The applied method includes the development of a YAMNet-based speech recognition AI model, installed on a Raspberry Pi as an edge computing device, with a microphone functioning to record environmental sounds. This system is designed to identify crucial environmental sounds such as breaking glass, explosions, screaming, water, fire alarms, smoke detectors, in addition to infant crying. The results of prototype trials under laboratory conditions indicate that the fire alarm and smoke detector classes have extremely high confidence levels (around 0.95 and 0.83). However, the glass class showed varying confidence levels (around 0.5), while cough, explosion, water, and screaming had lower confidence levels (median 0.15, 0.13, 0.25, and 0.4, respectively). The conclusion from these findings is that Smart Guardian has great potential as a privacy-focused toddler monitoring solution, although further optimization is needed to improve the speech recognition performance of events with low and varying confidence levels.  
Pengembangan Computational Thinking Melalui IoT Apps Programming Dengan Tinkercad Rochadiani, Theresia Herlina; Santoso, Handri; Mayatopani, Hendra
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 6 No 1 (2022): Volume 6 Nomor 1 Tahun 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v6i1.16007

Abstract

Computational thinking is one of competencies are needed recently. Most countries had already included computational thinking into their curriculum. Based on PISA 2018, Indonesia placed 72nd ranking of 77 countries for reading, 72nd ranking of 78 countries for mathematics, and 70th ranking of 78 countries for sciences. It is of concern to government and us to elevate this computational thinking ability, especially for students. Through this community service, the training of IoT programming using Tinkercad is given to PAHOA Senior High School students. Theory and hands-on practical in this training was followed by 40 students for 4 months. Based on questionnaire in the end of this training, 62% participations agreed that their computational thinking increase through this training and 96% participations could make IoT apps.
Pelatihan Machine Learning Menggunakan Bahasa Pemrograman Python Bagi Karyawan PT. Yokogawa Indonesia Santoso, Handri; Rochadiani, Theresia Herlina
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 6 No 2 (2022): Volume 6 Nomor 2 Tahun 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v6i2.16018

Abstract

Industry 4.0 insists companies to apply intelligent application technology to their industries. Machine learning as one of field of Artificial Intelligence has used widely in Smart Factory, such as to detect product defects, to predict potential problems and for its solutions. PT. Yokogawa Indonesia, one of global company, wanted to prepare its employees to implement Smart Factory, as its response for Industry 4.0 and competition with other companies. As a solution to this problem, the community service held machine learning training using Python for PT. Yokogawa Indonesia’s employees. The training was held once a week for five weeks. Interaction and discussion online between trainer and participants used Teams Microsoft application. It also used google classroom for managing materials and assignments during this training. More than 50% of participants never learn machine learning before this training. In the last session of the training, questionnaire was given to the participants. As the result, a half of total of participants agreed that their knowledge about machine learning has increased significantly through this training.
Enhancing the Efficiency of Jakarta's Mass Rapid Transit System with XGBoost Algorithm for Passenger Prediction Harriz, Muhammad Alfathan; Akbariani, Nurhaliza Vania; Setiyowati, Harlis; Santoso, Handri
Jambura Journal of Informatics VOL 5, NO 1: APRIL 2023
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v5i1.18814

Abstract

This study is based on a machine learning algorithm known as XGBoost. We used the XGBoost algorithm to forecast the capacity of Jakarta's mass transit system. Using preprocessed raw data obtained from the Jakarta Open Data website for the period 2020-2021 as a training medium, we achieved a mean absolute percentage error of 69. However, after the model was fine-tuned, the MAPE was significantly reduced by 28.99% to 49.97. The XGBoost algorithm was found to be effective in detecting patterns and trends in the data, which can be used to improve routes and plan future studies by providing valuable insights. It is possible that additional data points, such as holidays and weather conditions, will further enhance the accuracy of the model in future research. As a result of implementing XGBoost, Jakarta's transportation system can optimize resource utilization and improve customer service in order to improve passenger satisfaction. Future studies may benefit from additional data points, such as holidays and weather conditions, in order to improve XGBoost's efficiency.
Co-Authors Agus Anwar Akbar, Achmad Fathurrazi Akbariani, Nurhaliza Vania Amanda, Djaja Andrew Andrew, Andrew Andriani, Febri Anggraini, Astria Febrian Aprilia, Novia Pramesti Dazki, Erick Devanda, Faustin Eko Hadianto, Eko Firmansah, R Arif Fransisca, Viviana Harlis Setiyowati HARYONO Heni Jusuf Hindarto, Djarot Ho, Patricia ISWAHYUDI ISWAHYUDI Ito Wasito Karjadi, Daniel Avian Laurenso, Justin Lijaya, Hendra Lucia Sri Istiyowati Lupitha, Mariska Mareta, Arvin Maria Magdalena Mayatopani, Hendra Mohammad, Saiful Azhari Muhammad Alfathan Harriz Nana Sutarna Panna, Ariya Perdana, Nanda Praharto, Suwandhy Prawira, Khairul Thamrin Prijantono, Sonny Priswanto, Budi Purwadi Purwadi Purwadi Putri, Gladys Rahman, Ben Ramadhoni, Moehammad Richardus Eko Indrajit Rochadiani, Theresia Herlina Ruddin, Isra Sakti, Irwin Sandjaya, Julio Santoso, Billy Cahyo Saputra, Adi Dwifana Sari, Muh Masri Sembiring, Agustinus Sentosa, Steve Silalahi, Sondius Matogu Budiman Sucipto, Nadya Rudie Suhandi, Vartin Suherman, Endang Sumargo, Ruly Sze, Edward Tauhid, Tauhid Wedha, Alessandro Enriqco Putra Bayu Wedha, bayu Yasa Widjaja, Herman Wijaya, Oktavianus Hendry