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All Journal International Journal of Electrical and Computer Engineering Jurnal Informatika Jurnal Teknik Elektro Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmiah Informatika Komputer Jurnal Manajemen Teknologi Jurnal Momentum TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications International Journal of Advances in Intelligent Informatics Jurnal Teknobisnis Seminar Nasional Informatika (SEMNASIF) Journal of Information Systems Engineering and Business Intelligence The Asian Journal of Technology Management (AJTM) Indonesian Journal on Computing (Indo-JC) Proceeding of the Electrical Engineering Computer Science and Informatics JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Filsafat Indonesia Jurnal Teknik Informatika (JUTIF) International Journal of Social Service and Research Media Riset Akuntansi Auditing & Informasi Jurnal Komputer Bisnis JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Kridanto Surendro
Institut Teknologi Bandung
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Social Sciences

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Quantum Machine Learning Untuk Prediksi Emisi Gas Rumah Kaca dalam Perspektif Filsafat Sains : Quantum Machine Learning for Predicting Greenhouse Gas Emissions from a Philosophy of Science Perspective Hidayat, Wahyu; Surendro, Kridanto; Mahayana, Dimitri; Rosmansyah, Yusep
Jurnal Filsafat Indonesia Vol. 7 No. 2 (2024)
Publisher : Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jfi.v7i2.72236

Abstract

The climate change issues due to greenhouse gas emissions and the emergence of Quantum Machine Learning technology have sparked various studies in utilizing quantum machine learning (QML) to predict greenhouse gas emissions (GHG). This article aims to illustrate research related to the implementation of QML for GHG emission prediction from the perspective of the philosophy of science, particularly in terms of the scientific revolution from Thomas Kuhn's perspective, research program analysis from Imre Lakatos' perspective, pseudoscience pitfalls, potential biases of injustice, ethical and moral aspects, and their impact on society. The article is structured using a qualitative descriptive method. Reference sources include original articles and review articles from journals collected from the Scopus database with topics related to GHG emission prediction. Based on the review of the articles, it can be outlined that research on QML for GHG emission prediction is a progressive science currently in the phase of intensive exploration and development, where the research paradigm in this area is dominated by logical positivism and pragmatism. However, over time and with the development of the research context, new paradigms may emerge as additions or even replace existing research paradigms. The article also identifies the potential biases of injustice, ethical and moral aspects, and the impact of research in this field on society, recommending five strategies to avoid pseudoscience pitfalls related to research on QML for GHG emission prediction.
COMPARATIVE ANALYSIS OF MULTI-CRITERIA DECISION MAKING METHODS IN DETERMINING REDD+ PROJECT LOCATION Irawan, Aditya Putra; Surendro, Kridanto
International Journal of Social Service and Research Vol. 4 No. 8 (2024): International Journal of Social Service and Research
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/ijssr.v4i8.879

Abstract

The Reducing Emissions from Deforestation and Forest Degradation (REDD+) mechanism is aimed at reducing global greenhouse gas (GHG) emissions. This study aims to develop a multi-criteria decision-making (MCDM) model specifically designed to prioritize locations for REDD + projects. The proposed research design focuses on developing a MCDM framework for determining the priority locations for projects using criteria such as climate impact reduction, contributions to local communities, and biodiversity conservation. The study utilized the Analytic Hierarchy Process (AHP), Simple Additive Weighting (SAW), Weighted Product Method (WPM), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to determine the prioritization of alternatives based on compromise solutions. The success of this research demonstrates that a systematic approach to determining priority locations can be effectively carried out using MCIM. This research is expected to aid policymakers and stakeholders in making more informed and effective decisions for environmental conservation and climate change mitigation.
Perancangan Model Pengukuran Layanan Teknologi Informasi pada Perguruan Tinggi (Studi Kasus: Perguruan Tinggi X) Adelia Adelia; Kridanto Surendro
Jurnal Teknik Informatika dan Sistem Informasi Vol 1 No 2 (2015): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v1i2.581

Abstract

Information technology services within the organization need to be taken to ensure that the service providers can provide quality service and benefit for service user. The research model to measure information technology services provided to users of the service providers, especially in college. In the design of model, using the concepts included in the service intelligence and ISO 20000, Balanced Scorecard, Balanced Scorecard and IT Balanced Scorecard management of information technology services. Measurement services performed by using models generated from mapping the concepts used in the study. Colleges may use the measurement model is a college that has been using information technology in supporting the activities of the college. Measurements of IT service level emphasizes on IT services owned by the college and different type of IT services to users in the college
Enhancing the Comprehensiveness of Criteria-Level Explanation in Multi-Criteria Recommender System Rismala, Rita; Maulidevi, Nur Ulfa; Surendro, Kridanto
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.160-172

Abstract

Background: The explainability of recommender systems (RSs) is currently attracting significant attention. Recent research mainly focus on item-level explanations, neglecting the need to provide comprehensive explanations for each criterion. In contrast, this research introduces a criteria-level explanation generated in a content-based pardigm by matching aspects between the user and item. However, generation may fall short when user aspects do not match perfectly with the item, despite possessing similar semantics.  Objective: This research aims to extend the aspect-matching method by leveraging semantic similarity. The extension provides more detail and comprehensive explanations for recommendations at the criteria level.    Methods: An extended version of the aspect matching (AM) method was used. This method identified identical aspects between users and items and obtained semantically similar aspects with closely related meanings.   Results: Experiment results from two real-world datasets showed that AM+ was superior to the AM method in coverage and relevance. However, the improvement varied depending on the dataset and criteria sparsity.  Conclusion: The proposed method improves the comprehensiveness and quality of the criteria-level explanation. Therefore, the adopted method has the potential to improve the explainability of multi-criteria RSs. The implication extends beyond the enhancement of explanation to facilitate better user engagement and satisfaction.  Keywords: Comprehensiveness, Content-Based Paradigm, Criteria-Level Explanation, Explainability, Multi-Criteria Recommender System
Development of an AI Governance Model for Higher Education Using the Capability Maturity Model Integration (CMMI) Walhidayah, Irfan; Surendro, Kridanto
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4709

Abstract

The increasing adoption of Artificial Intelligence (AI) in higher education presents strategic opportunities for institutional transformation, while introducing complex challenges related to ethics, accountability, transparency, and regulatory compliance. Responding to the growing complexity of AI implementation in academic environments , this study proposes a governance model for AI named GOVAIHEI (Governance of Artificial Intelligence for Higher Education Institutions), conceptualized using the Capability Maturity Model Integration (CMMI) framework. The model was developed using the Design Research Methodology (DRM), which consists of four stages: Research Clarification, Descriptive Study I, Prescriptive Study, and Descriptive Study II. GOVAIHEI encompasses five primary domains: Data and Information, Technology and Infrastructure, Ethics and Social Responsibility, Regulation and Compliance, and Monitoring and Evaluation. Each domain is articulated into capability areas and measurable practices, assessed using the tiered NPLF scale (Not, Partial, Largely, Fully Achieved) to determine institutional capability and maturity levels. The model was validated through expert judgment by three domain specialists, confirming its relevance, methodological soundness, and alignment with CMMI principles. A web-based evaluation system was also developed using Laravel, PostgreSQL, Redis, and Nginx, enabling structured, efficient, and automated assessments. Implementation in a case study at Institute XYZ revealed an initial maturity level (Level 1) with development goals toward Level 3 (Defined). The findings demonstrate a practical foundation for navigating the multifaceted nature of AI adoption in higher education through a structured and adaptable governance approach, which aligns with the increasing demand for robust digital governance frameworks in technology-driven environments.  
Deteksi Cyberbullying dengan Mesin Pembelajaran Klasifikasi (Supervised Learning): Peluang dan Tantangan Setiawan, Yudi; Maulidevi, Nur Ulfa; Surendro, Kridanto
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 7: Spesial Issue Seminar Nasional Teknologi dan Rekayasa Informasi (SENTRIN) 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022976747

Abstract

Perkembangan teknologi media sosial tidak hanya memberikan kemudahan dalam berkomunikasi antar individu, akan tetapi juga dapat mengancam kehidupan sosial individu seperti tidakan cyberbullying. Bervariasinya pola dan karakteritik cyberbullying mengakibatkan sulitnya proses deteksi cyberbullying, yang dilakukan oleh pelaku cyberbullying. Penelitian deteksi pola dan karakteristik cyberbullying banyak dilakukan dengan berbagai metode, seperti dengan mengimplementasikan Machine Learning, Natural Language Processing (NLP), dan Sentiment Analysis yang memiliki variasi akurasi yang berbeda, dengan keunggulan dan kelemahan dari masing-masing metode. Implementasi Machine Learning untuk deteksi cyberbullying dapat dilakukan dengan berbagai algoritma, seperti algoritma probabilistik (Naïve Bayes) maupun supervised learning (Support Vector Machine, k-Nearest Neighbour, Decission Tree), dan metode lainnya yang hingga saat ini terus dikembangkan dengan berbagai pendekatan untuk meningkatkan akurasi deteksi cyberbullying atau non-cyberbullying. Adapun peluang dan tantangan penelitian deteksi cyberbullying seperti penerapan pada variasi domain bahasa, dan bentuk ekspresi yang dilakukan pada suatu lingkungan atau budaya, yang masih terdapat ruang untuk dikembangkan dan dijelajah secara luas. Pada artikel ini menjabarkan penelitian berikutnya berupa mengimplementasikan metode pembelajaran klasifikasi (Supervised Learning) dengan modifikasi tahapan untuk meningkatkan akurasi klasifikasi.
A System Dynamics Model of 5G Low-Band Spectrum Management Shalahuddin, Muhammad; Sunindyo, Wikan Danar; Effendi, Mohammad Ridwan; Surendro, Kridanto
Journal of ICT Research and Applications Vol. 19 No. 1 (2025)
Publisher : DRPM - ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2025.19.1.3

Abstract

The fifth-generation (5G) mobile communication system represents a major advancement in wireless technology, relying on effective radio spectrum management to ensure optimal performance. Among the available frequency ranges, the 5G low-band spectrum provides extensive coverage but limited capacity, making its efficient management a critical challenge. This study presents a predictive model based on the system dynamics approach to analyze the management of the 5G low-band spectrum. The model captures the interrelationships between technical and economic variables that influence spectrum allocation and service adoption over time. Three simulation scenarios—low, medium, and high allocation rates—were developed to examine allocation patterns and their effects on 5G service diffusion. The results revealed that spectrum management in 5G exhibits goal-seeking behavior constrained by spectrum scarcity, with service adoption showing a growth-to-saturation pattern. The findings demonstrate that appropriate low-band spectrum management can significantly enhance 5G deployment efficiency. The proposed model serves as a decision-support tool for policymakers and regulators, enabling evaluation of alternative management strategies prior to policy implementation and promoting evidence-based decision-making in future 5G spectrum policies.
Data Governance Design for Optimization of Hospital Management Information System (SIM-RS) at ABC Regional Hospital Muhammad Furqan Nazuli; Irfan Walhidayah; Neng Ayu Herawati; Lenny Putri Yulianti; Kridanto Surendro
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 16 No. 01 (2025): Vol.16, No. 01 April 2025
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2025.v16.i01.p03

Abstract

The increasing complexity of hospital data management requires a robust Data Governance (DG) framework to ensure data quality, security, and compliance. This study focuses on developing a DG framework tailored to the Hospital Management Information System (SIM-RS) at RSUD ABC to enhance data integration, accessibility, and regulatory adherence. A qualitative approach with a case study method was employed, involving interviews and document analysis to identify key challenges in data management. The proposed DG framework aligns with ICD-10 and regulatory requirements, ensuring interoperability and efficient data processing. Implementing the Master Patient Index (MPI) reduces duplicate records, while Two-Factor Authentication (2FA) and AES-256 encryption strengthen data security. FHIR standards facilitate seamless data exchange across healthcare systems, optimizingoperational efficiency. AI-driven data analytics further enhances clinical decision-making and administrative workflows. Evaluation of the framework demonstrates significant improvements in data quality, regulatory compliance, and risk management, leading to improved patient care and reduced medical errors. The High-Level Roadmap outlines a phased implementation strategy for sustainable DG adoption. Future research may explore performance metrics, Blockchain integration, and organizational change management to refine DG practices in healthcare institutions further.
MODEL PENGEMBANGAN DASHBOARD UNTUK MONITORING DAN EVALUASI KINERJA PERGURUAN TINGGI Eva Hariyanti; Indah Werdiningsih; Kridanto Surendro
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 9, No 1, Januari 2011
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (580.545 KB) | DOI: 10.12962/j24068535.v9i1.a63

Abstract

Tujuan utama dari penelitian ini adalah merancang model pengembangan dashboard untuk kebutuhan perguruan tinggi. Dashboard adalah aplikasi sistem informasi yang menyajikan informasi mengenai indikator utama dari aktifitas organisasi secara sekilas dalam layar tunggal. Pembuatan model memperhatikan 3(tiga) aspek utama dashboard yaitu penyajian data/informasi, personalisasi, dan kolaborasi antar pengguna. Model yang dihasilkan digunakan untuk pengembangan dashboard bagi kebutuhan monitoring dan evaluasi kinerja perguruan tinggi. Monitoring dan evaluasi kinerja mutlak dilakukan secara terus menerus oleh perguruan tinggi untuk memastikan bahwa proses bisnis yang dijalankannya dapat mencapai tujuan yang telah ditetapkan, melalui strategi pengelolaan yang tepat. Metode penelitian yang digunakan adalah studi literatur dan survei kuesioner. Studi literatur dilakukan untuk membuat rancangan awal model. Sedangkan survei kuesioner dilakukan untuk mengidentifikasi kebutuhan calon pengguna dashboard dan mengetahui faktor-faktor yang yang mempengaruhi kesuksesan pengembangan sistem informasi di perguruan tinggi. Jumlah responden sebanyak 95 orang di lingkungan Universitas Airlangga (UA) dan Institut Teknologi Bandung (ITB). Hasil penelitian menunjukkan bahwa terdapat perbedaan prioritas kebutuhan dashboard untuk pengguna di UA dan ITB. Namun secara umum dapat dinyatakan bahwa kebutuhan yang terkait aspek penyajian data/informasi, personalisai, dan performansi merupakan hal yang dianggap penting untuk sebuah dashboard. Sedangkan aspek kolaborasi hanya dianggap sebagai daya tarik dashboard. Model pengembangan dashboard yang dihasilkan menggambarkan bahwa kepuasan pengguna dipengaruhi oleh kualitas sistem, kualitas layanan, dan manfaat positif yang diberikan oleh sistem.
PENGEMBANGAN MODEL ARSITEKTUR ENTERPRISE UNTUK PERGURUAN TINGGI Roni Yunis; Kridanto Surendro; Erwin S. Panjaitan
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 8, No 1, Januari 2010
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1392.266 KB) | DOI: 10.12962/j24068535.v8i1.a70

Abstract

Salah satu tujuan dari penerapan arsitektur enterprise adalah menciptakan keselarasan antara bisnis dan teknologi informasi bagi kebutuhan organisasi. Penerapan arsitektur enterprise tidak terlepas dari bagaimana sebuah organisasi merencanakan dan merancang arsitektur enterprise tersebut. Tahapan dalam pengembangan model arsitektur enterprise sangatlah penting dan akan berlanjut pada tahapan berikutnya yaitu rencana implementasi. Penelitian ini membangun sebuah arsitektur enterprise yang nantinya bisa dijadikan oleh organisasi untuk mencapai tujuan strategisnya. Model arsitektur ini dapat dijadikan sebagai model dasar bagi institusi perguruan tinggi didalam pengembangan arsitektur enterprise.
Co-Authors , Ronaldi Adelia Adelia Adelia Adelia, Adelia Adiska Fardani Aradea Ari Fajar Santoso Ayu Purwarianti Basuki Sugiharto Basuki Sugiharto Cicely Martini Asihwardji Dicky Prima Satya Dimitri Mahayana Dwi H Widyantoro Dwi H. Widyantoro Effendi, Mohammad Ridwan Erwin B. Setiawan Erwin B. Setiawan Erwin S. Panjaitan Erwin S. Panjaitan Eva Hariyanti Farrell Yodihartomo Febriantoro, Wicaksono Hanung Nindito Prasetyo Heru Nugroho Heru Nugroho Hibban, Daffa Maulana Indah Werdiningsih Indra Lukmana Sardi Iping S Suwardi Iping Supriana Iping Supriana Iping Supriana Iping Supriana Suwandi Irawan, Aditya Putra Irfan Walhidayah Kristian Telaumbanua Lenny Putri Yulianti Ma'mun, Nurhayati Maniah Maniah Maria Irmina Prasetiyowati Megawati . Muhammad Furqan Nazuli Muhammad Shalahuddin Neng Ayu Herawati Nur Ulfa Maulidevi Nurhajati Ma'mun Olivia Olivia Ririn Dwi Agustin Rita Rismala Ronaldi Ronaldi Roni Yunis Roni Yunis Roni Yunis Sakam, R. Djunaedy Sarifah Putri Raflesia Setiawan, Erwin B. Soni Fajar Surya G Sri Agustina Rumapea Sri Handayaningsih Stevanus Wisnu Wijaya Sugondo Hadiyoso Sukma Nirad, Dwi Welly Sunindyo, Wikan Danar Tati Latifah Erawati Rajab Wahyu Hidayat Wawan Dhewanto Widyantoro, Dwi H Yudi Setiawan Yusep Rosmansyah