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Comparison of Information Technology Governance Maturity Levels Based on COBIT 2019 at PT Kereta Commuter Indonesia in 2023 and 2024 Purwadi, Purwadi; Santoso, Handri
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.2025.6.5.5200

Abstract

This study aims to analyze and compare the maturity level of Information Technology (IT) governance at PT Kereta Commuter Indonesia (KCI) between 2023 and 2024 using the COBIT 2019 framework. The background of this study is based on the operational complexity of KCI which serves a high daily passenger volume, so that the information system becomes the backbone of the smooth transportation service. The method used is a descriptive-comparative case study with a mixed approach, through interviews, Likert scale questionnaires, and internal document reviews such as IT audit reports and government regulations. The results of the analysis show a significant and consistent increase, where the level of IT governance maturity which was previously at level 2 (Managed) and 3 (Defined) in 2023, increased to level 3 and 4 (Quantitatively Managed) in 2024. The most prominent improvements were seen in the strategic domain EDM01 (Ensure Governance Framework Setting) and the operational domain DSS01 (Manage Operations), which successfully reached level 4. This success reflects top management's commitment and ongoing internal evaluation in strengthening IT governance strategically and operationally. The research findings confirm that annual evaluations serve as an objective benchmark for identifying governance gaps, developing digital strategies, and determining future IT investment priorities. Overall, this study confirms that regular assessments can improve the effectiveness of data-driven IT transformation and ensure alignment of IT implementation with the company's business objectives.
BIG ENTERTAINMENT’S FILM AND MUSIC CREATION DESIGN: PLATFORM-BASED BUSINESS MODEL CANVAS AND ENTERPRISE ARCHITECTURE Ruddin, Isra; Santoso, Handri; Indrajit, Richardus Eko; Dazki, Erick
Capture : Jurnal Seni Media Rekam Vol. 13 No. 1 (2021)
Publisher : Seni Media Rekam ISI Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33153/capture.v13i1.3946

Abstract

BIG Entertainment is an application that offers unparalleled music and film entertainment. Previously, applications like Spotify were all about music, while Netflix, Joox, and Disney were all about movies. This entertainment combines movies and music into a single application. This research seeks to examine the Big Entertainment application's business model canvas. This study employs the literature review method, which gathers various scientific and relevant sources. The findings suggest that BIG Entertainment service providers work hard to expand their offerings in response to changing market trends and technology advancements. The business model offers both tangible and intangible assets for customers who require not only the final product (music service) but also a one-stop service. BIG Entertainment can generate profit while developing a distinctive and efficient business model if it successfully integrates tangible and intangible assets.
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.  
Framework for Generating Synthetic Customer Data to Enhance Model Training in Banking Agustiana, Puspa Riri; Santoso, Handri
TEPIAN Vol. 6 No. 4 (2025): December 2025
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v6i4.3385

Abstract

Data-driven decision-making has taken on a more central role in the banking sector. However, privacy regulations and data security concerns limit the accessibility of real customer data for model training. To address this challenge, synthetic data generation offers a promising solution. This paper presents a framework tool for generating synthetic customer data that closely mimics the statistical properties of real-world data using advanced machine learning techniques, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), to enhance model training in banking applications. By leveraging advanced machine learning techniques, our framework can replicate the real Production Data to Synthetic Data customer. This synthetic data can be used to augment existing datasets, enhance model training, and improve the accuracy and robustness of predictive models. We demonstrate the effectiveness of our framework through a case study in a banking context, showcasing its potential to address challenges related to data privacy, data scarcity, and model performance.