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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu Komputer dan Informasi IPTEK The Journal for Technology and Science CommIT (Communication & Information Technology) Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Systems Engineering and Business Intelligence Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Komtika (Komputasi dan Informatika) Masyarakat Telematika Dan Informasi : Jurnal Penelitian Teknologi Informasi dan Komunikasi Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informatika Ekonomi Bisnis Computer Science and Information Technologies Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknimedia: Teknologi Informasi dan Multimedia Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Pendidikan Indonesia (Japendi) International Journal of Engineering Continuity J-Icon : Jurnal Komputer dan Informatika Jurnal Informatika Ekonomi Bisnis Jurnal Sistem Informasi The Indonesian Journal of Computer Science Jurnal Komtika (Komputasi dan Informatika)
Yova Ruldeviyani
Faculty Of Computer Science, Universitas Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences

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Peningkatan Kualitas Data Talent Karyawan pada Human Capital Management PT XYZ Sulaeman, Achmad Firmansyah; Ruldeviyani, Yova
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4628

Abstract

The importance of high quality data is a top priority for PT XYZ’s Human Capital Management (HCM) in handling Talent Management, Career Management, and Employee Performance Management. information security audit revealed several issues, such as delayed data updates and inconsistencies across functions. To address these issue, an assessment of the Data Quality Management (DQM) maturity level is needed to evaluate the implementation of consistency, accuracy, and integrity. This study uses David Loshin’s framework, with the results explained referring to DQM guidelines in DMBOK. Results show DQM maturity level is at level 2 (Repeatable), with an average score of 2.3. Three dimensions with the lowest scores are the main focus for improvement, which Data Quality Expectations (1.6), Data Quality Protocols (1.8) and Data Quality Technology (1.2). Recommendations from this study focus on enhancing these dimensions to improve data quality and address the issues highlighted in information security audit.
Evaluating Mdm Maturity In Human Capital Data: Case Study of Jasa Marga Juliansyah, Mohamad Denis; Ruldeviyani, Yova; Rahman, Henry Aulia; Astagina, Shania Eriadhani
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 1 (2025): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i1.871

Abstract

Effective Master Data Management (MDM) is essential for organizations to ensure data consistency, accuracy, and accessibility, particularly within intricate operational settings. This study assesses the maturity level of MDM for human capital data at PT Jasa Marga (Persero) Tbk, Indonesia’s leading state-owned toll road developer and operator. Human capital data is currently managed through two primary applications: SAP for the main company and the JM-Click Human Capital Information System (HCIS) for its subsidiaries. This separation has led to data silos and inconsistencies, diminishing the reliability and accessibility of critical human capital data. Utilizing the Master Data Management Maturity Model (MD3M) by Spruit and Pietzka, this research investigates five main topics and 13 focus areas within the organization. Data collection involved questionnaires and interviews with key experts. Results indicate that PT Jasa Marga has implemented 76.92% of necessary MDM capabilities, with Data Protection and Usage & Ownership scoring the highest maturity level of 5. However, Data Quality is at level 2, indicating a need for major enhancements in data maintenance and consistency across subsidiary data models. This study provides actionable recommendations for improving data quality, aligning data models, and integrating advanced technologies, stressing the importance of continuous MDM improvements to better support the organization’s strategic objectives and operational demands.
Analisis Faktor Berbagi Informasi Pribadi di Media Sosial: Studi Skala Kecil Belia Rida Syifa Fauzia; Lukman Yudokusumo; Yova Ruldeviyani
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 13 No 3: Agustus 2024
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v13i3.9908

Abstract

In the contemporary social landscape, the widespread use of social media, such as platforms like TikTok, Instagram, and YouTube, has become a prominent trend in various circles of society, especially in Indonesia. As the number of users on these platforms increases, concerns regarding user security and privacy also increase. Data breaches in 2021 affecting 235 million users on Instagram, TikTok, and YouTube underscored the importance of researching the multifaceted dynamics around privacy concerns, levels of trust, risk awareness, and user behavior patterns related to sharing personal information on social media platforms. This research aimed to address this critical issue by introducing a research model developed based on relevant hypotheses from previous research. The sample used in this research consisted of social media users in Indonesia. Methodologically, this research used sophisticated structural equation modeling (SEM) tools for hypothesis testing and confirmatory factor analysis (CFA) to validate the efficacy of existing research models. These findings indicated that users’ trust, awareness, privacy concerns, and behavioral intentions significantly and positively influence the tendency to share personal data on social media platforms. This research provides valuable insights into the complex interactions between factors influencing user behavior in social media privacy, thereby offering implications for academia and practical applications.
Making AI Work for Government: Critical Success Factor Analysis Using R-SWARA Brillianto, Bramanti; Ruldeviyani, Yova; Sidiq, Darmawan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 3 (2024): June 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i3.5813

Abstract

This study quantifies what makes Artificial Intelligence (AI) work for government, the critical success factors (CSFs) for successful AI implementation within the Directorate General of Taxes (DGT). Analyzing factors such as technology, organization, process, and environment, the research highlights the importance of organizational readiness, strategic vision, and leadership support to drive successful AI integration within DGT. The dimension of the organization became the most critical factor, followed by technology, process, and environment. The findings offer actionable insights for DGT's decision-making processes, aiding in strategic resource allocation and tailored AI strategy refinement. Furthermore, this research is a valuable reference for other public sector organizations that aim to enhance operational efficiency through the adoption of AI. This study empowers decision makers within the DGT and the wider public sector by providing nuanced information on the critical factors that influence the successful implementation of AI, fostering improved operational efficiency and governance practices.
Evaluasi Kualitas Data Pada Daftar Produk Tayang Di Katalog Elektronik Versi 6.0 Pratiwi, Aprilia; Mahsa Elvina Rahmawyanet; Amanda Ghaisani; Tri Broto Siswoyo; Yova Ruldeviyani; Yudho Giri Sucahyo
The Indonesian Journal of Computer Science Vol. 14 No. 3 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i3.4858

Abstract

Data quality is important aspect in supporting transparency, accountability, and efficiency of the government procurement process. Electronic Catalog data acts as a source of information on products, services, and providers of goods/services. The transition from Electronic Catalog v5 to v6 is form of digital transformation in the government procurement of goods/services as form of improving public services. Measuring the quality of Electronic Catalog v6 data has significant role in providing effective, efficient and accountable information. This study aims to evaluate the quality of data on Electronic Catalog v6 product data using the Total Data Quality Management (TDQM) framework. There are 6 dimensions used in evaluating data quality, completeness, accuracy, data integrity, fairness, consistency, and precision. The results of the study show that the dimensions of consistency, accuracy, completeness, fairness and precision reach above 90% while data integrity reaches below 50% and requires improvement on product data quality.
Peningkatan Manajemen Data Master Rekam Medis Elektronik Rumah Sakit: Studi Kasus di Rumah Sakit XYZ Setyo Nugroho, Aloysius Prastowo; Ruldeviyani, Yova
Jurnal Pendidikan Indonesia Vol. 6 No. 7 (2025): Jurnal Pendidikan Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/japendi.v6i7.8375

Abstract

Rumah Sakit XYZ memiliki sistem elektronik berupa Electronic Medical Record (ERM). Permasalahan yang dihadapi pada ERM rumah sakit adalah kurangnya standar data master ditunjukkan dengan pengecekan manual dependensi dan relasi database tiap perubahan aplikasi. Untuk menanganinya perlu diketahui tingkat maturitas saat ini guna mengetahui potensi masalah, dan proses internal yang dapat dioptimalkan. Frame work md3m Penelitian ini dipilih Master Data Management Maturity Model (MD3M) oleh Spruit-Pietzka karena metode ini berfokus pada lima bidang penting dan tiga belas area yang sesuai dengan kebutuhan penilaian Data Master ERM dan secara praktis dirancang untuk mengukur kematangan manajemen data master. Tujuan dari penelitian ini adalah untuk meningkatkan pengelolaan master data rekam medis yang sesuai bagi rumah sakit XYZ. Hasil pengukuran menunjukkan tingkat maturitas keseluruhan adalah 3, dengan rincian 87% kapabilitas sudah terpenuhi atau terpenuhi 55 kapabilitas dari total 63 kapabilitas yang diukur. Hal ini menunjukkan bahwa organisasi sudah memiliki kolaborasi pertama terjadi pada tingkat taktis memiliki kesadaran untuk adanya inisiatif lain dalam pengelolaan master data ERM rumah sakit. Pentingnya melakukan peninjauan kembali model master data untuk konsisten dan mengurangi redundansi data dan menerapkan Stewardship guna melakukan proses teknis serta memelihara dan mengupdate repositori data.
Pengukuran Tingkat Kapabilitas Sistem Pengolahan Data Survei Pada Manajamen Kinerja Dan Manajemen Data Operasi Menggunakan Dmbok Dan Cobit2019 Di BPS RI Wintang, Siti Mawar Rini; Ruldeviyani, Yova; Parmiyanto, Joko; Putra Hulu, Freddy Richard; Putri, Azanisa; Sulistiyo, Rifta Dimas
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 3: Juni 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023106533

Abstract

BPS telah membangun salah satu sistem pengolahan data survei yang disebut Integrated Collection System (ICS) dalam upaya melakukan transformasi digital. ICS merupakan sistem untuk mengumpulkan data multimetode yang terdiri dari Pen and Paper Interviewing (PAPI), Computer Assisted Personal Interviewing (CAPI), Computer Assisted Web Interviewing (CAWI), dan Acquisition of Administrative Data. Sistem ini mereformasi cara BPS mengumpulkan data menggunakan berbagai teknologi dan mengintegrasikan data. Sejak diinisiasi tahun 2019, penggunaan ICS semakin bertambah sejalan dengan meningkatnya kebutuhan data yang cepat dan akurat. Untuk menyukseskan transformasi digital, ICS diharapkan memiliki kemampuan manajemen kinerja dan operasi data yang baik maka penelitian ini mengakomodir untuk mengukur tingkat kapabilitas pada ICS dengan proses yang spesifik tersebut. Penelitian ini menggunakan acuan framework dari COBIT 2019, DMBoK dan CMMI. Dari hasil penelitian menunjukkan tingkat manajemen kinerja dari 5 sub domain area, yaitu MEA.01.01-MEA.01.05 masih berada pada tingkat 1, sedangkan hasil penelitian tingkat manajemen operasi data didapatkan bahwa 2 PA (practice areas) berada di level 1, 8 PA berada di level 2, dan 5 PA berada pada level 3. Rekomendasi disusun untuk mengoptimalkan tingkat kapabilitas pada manajemen kinerja dan manajemen operasi data pada ICS sehingga ICS dapat dijalankan dengan baik sesuai dengan target transformasi digital BPS. AbstractAs an effort to carry out digital transformation, BPS has built one of the survey data processing systems known as Integrated Collection System (ICS). ICS is a system for multimode data collection through Pen and Paper Interviewing (PAPI), Computer Assisted Personal Interviewing (CAPI), Computer Assisted Web Interviewing (CAWI), and Acquisition of Administrative Data. ICS reforms the way BPS collects and integrates data using various technologies. Since its initiation in 2019, the use of ICS has increased. With the increasing demand for data, a system that can produce fast and accurate data is extremely necessary. To achieve the goals of digital transformation through the implementation of ICS, it is crucial to have good performance and data operations managements. Therefore, this study accommodates to measure the Capability Level of ICS with these specific processes by applying the frameworks from COBIT 2019, DMBoK, and CMMI as references. From the Performance Management measurement, it was found that the 5 sub-domain areas (MEA.01.01-MEA.01.05) were still at Level 1. Furthermore, the Data Operations Management measurement showed that 2 PA (Practice Areas) were at Level 1, 8 PA were at Level 2, and 5 PA were at Level 3. Based on the results of this study, recommendations have been made to optimize the Capability Level in both Performance Management and Data Operations Management of ICS so that it can be run properly in accordance with the goals of digital transformation of BPS.
A Practical Approach to Enhance Data Quality Management in Government: Case Study of Indonesian Customs and Excise Office Nugraha, Tito Febrian; Wibowo, Wahyu Setiawan; Genia, Venera; Fadhil, Ahmad; Ruldeviyani, Yova
Journal of Information Systems Engineering and Business Intelligence Vol. 10 No. 1 (2024): February
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.10.1.51-69

Abstract

Background: The exponential data growth emphasises the importance of efficient information flow in organisations, especially in the financial sector. Data quality significantly influences decision-making, necessitating reliable Data Quality Management (DQM) frameworks. Previous studies propose DQM to maintain data quality through regulation, technology, measurement, evaluation, and improvement. Researchers highlight high-quality data benefits in private organisations but note the lack of improvement in data utilisation in public organisations. In Indonesia, data accuracy and quality are crucial for financial policies, with frequent reports of data inaccuracies in the Directorate General of Customs and Excise (DJBC), demanding standardised DQM practices. However, However, prior studies have yet to provide comprehensive and practical solutions to improve DQM practices. This study therefore aims to measure the DQM maturity, provide recommendations based on best practices, and formulate a practical strategy for improvements along with indicators tailored to the organisation, a topic that previous research has not explored. Methods: This study falls under a mixed method approach (a quantitative study followed by a qualitative study) and employs a three-stage methodology. The authors conduct maturity assessment using Loshin model through an assisted enumeration from 5 key stakeholders followed by recommendations based on the Data Management Body of Knowledge (DMBOK) and strategy formulation from internal documents and interview. Results: The data analysis yielded a DQM maturity score of 3.10, indicating a "defined to managed" level of maturity. Among eight components, only one receives a Managed level, two components are in the Defined level and the rest belongs to a Repeatable level. This study also proposes three strategies to bolster DQM by targeting 49 weak points, which will be progressively and sequentially implemented over a three-year period, using twelve possible solutions. Conclusion: The study highlights the importance of efficient data flow, particularly in the financial sector, and suggests DQM for maintaining data quality. DJBC's import DQM level is assessed using Loshin's measurements, revealing areas for improvement through key DMBOK activities. Recommendations include data governance, strategic planning, and sequential DQM implementation. The study concludes by formulating a practical approach to be applied in a three-year span with ten indicators to measure success.   Keywords: Data Quality Management, Data Quality Maturity Model, Data Quality Strategy, Loshin, DMBOK
The Maturity Model of Data Quality Management in Banking Industry: PT XYZ Core System Customer Data Mulyadi, Rahmad; Ruldeviyani, Yova; Alfiany, Noverina; Hidayanto, Achmad Nizar
Jurnal Komtika (Komputasi dan Informatika) Vol 7 No 1 (2023)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v7i1.8750

Abstract

PT XYZ, engaged in the financial industry, has a target to become a leading company in Southeast Asia and has been supported by more than 200 million customer data in its core system. This huge amount of data is expected to create business opportunities, build a risk-aware culture, and increase supremacy in the business strategy of PT XYZ. These things can be achieved if the data used is of good quality data. In fact, found anomalies in a large number of customer data. To get recommendations for improving the quality of customer data, it is necessary to assess the quality of customer data. The customer data quality assessment in this study uses the method introduced by Loshin (2011). Loshin’s Data Quality Management Model (DQMM) adopts a capability maturity level model in building its characteristic matrix. Maturity levels obtained are 3.6 (expectations), 3.6 (dimensions), 4.4 (policy), 3.8 (procedures), 4.2 (governance), 3.8 (standardization), 4, 2 (technology), and 3.8 (performance management). Regarding the expectation that senior management can achieve the highest level of data quality, 9 strategic recommendations were produced 9 strategy recommendations were submitted to PT XYZ is the result of mapping between criteria that have not been met with data quality management activity in Data Management Body of Knowledge (DMBOK) version 2.0. Measurement and monitoring of good data quality is the most influential recommendation for PT XYZ.
Pengukuran Tingkat Kesadaran Keamanan Informasi Pegawai Pada Instansi Pemerintah Krisna Maria Rosita Dewi; Yudistira, Ricko Dwiki; Ruldeviyani, Yova
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3950

Abstract

Human Resources (HR) have become a factor that affects the success of e-government implementation in the era of rapid technological development. However, HR also play a role in creating information security risks for the organization. In order to deal with information security risks, BMKG implemented an information security management system by implementing ISO/IEC 27001:2013 in 2020. It also plans to implement it at three locations of the BMKG Regional Office. Therefore, this study aims to measure employees' level of information security awareness at the three locations using the Knowledge, Attitude, Behavior (KAB) concept and the HAIS-Q method combined with the information asset management sub-area of the KAMI’s Index. The results showed that employees' level of information security awareness is classified in the good category with a value of 81.67%. Some areas that need to be improved are password management (79.81%), mobile computing (75.59%), and incident reporting (79.81%). Regional Center A has the lowest employee information security awareness level, with an average score of 79.75%.
Co-Authors Achmad Nizar Hidayanto Adenia Adiresta Adi Gunawan, Adi Afif Gunung , Muhammad Agnes Sondita Payani Ahmad Fadhil, Ahmad Ahmad Hendra Maulana Ahmad Hizqil Ahmad Syaifulloh Imron Al Adawiyah, Rabiah Al Haq, Muhammad Hezby Al Qahar, Muhammad Yazid Aldiansah Prayogi Alfiandi, Rama Alfiany, Noverina Alia Mutia Mayanda Aloysius Prastowo Setyo Nugroho Aloysius Prastowo Setyo Nugroho Amanda Ghaisani Andro Harjanto Arif Hidayat Aris Budi Santoso Astagina, Shania Eriadhani Azis Amirulbahar Belia Rida Syifa Fauzia Bima Tri Ariyanto Brillianto, Bramanti Desiana Nurul Maftuhah Devina, Fakhira Faris Salbari Fathurahman Ma'ruf Hudoarma Fidyawan, Miftahul Agtamas Fitriya, Ghina GS Budhi Dharmawan Hafiz , Muhammad Halida Ernita Handayani, Putu Wuri Hendry, Darell I Made Kurniawan Putra Ibnu Pujiono Ines Dwi Andini Irfan Murtadho Agtyaputra Irvan Ramadhan Zarkasie Jefree W.L.H Manurung Jeri Apriansyah Pagua, Jeri Apriansyah Juliansyah, Mohamad Denis Khairunnas, Rezki Khairunnaziri, Muhammad Krisna Maria Rosita Dewi Kurniawati, Monica Vivi Layungsari Layungsari Layungsari Layungsari Layungsari Layungsari Lelianto Eko Pradana Lia Ellyanti Lukman Yudokusumo Maharani IF Bahar Mahsa Elvina Rahmawyanet Melani Puspasari, Hasna Muhammad Farhan Mukharomah, Ulfah Nur Nabasya, Oristania Wahyu Noverina Alfiany Noviana Pramitasari Nugraha, Tito Febrian Nugraheni, Sani Parmiyanto, Joko Prastowo, Rahardito Dio Pratiwi, Aprilia Priastomo, Ristyo Yogi Prisillia, Galuh Puja Putri Abdullah Purwandaru, Dhanang Putra Hulu, Freddy Richard Putra, Ramadhoni Putri, Azanisa Rahmad Mulyadi Rahman, Henry Aulia Rahmi Julianasari Raksaka Indra Alhaqq Ramayuda, Muhammad Davin Ratna Yulika Go Rina Rahmawati Sidiq, Darmawan Sudarwono, Dianto Adwoko Sulaeman, Achmad Firmansyah Sulistiyo, Rifta Dimas Syalevi, Rahmad Tri Broto Siswoyo Tri Utami, Avita Utami, Aisyah Nurlita Venera Genia Wibowo, Wahyu Setiawan Widoyono, Bambang Wintang, Siti Mawar Rini Yoga Pamungkas Yohan Adhi Styoutomo Yudho Giri Sucahyo Yudho Giri Sucahyo Yudistira, Ricko Dwiki Yuli Astuti Zharif Mustaqim, Ilham Zulmy, Mohamad Faisal