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RANCANG BANGUN ARSITEKTUR ENTERPRISE MENGGUNAKAN TOGAF PADA SISTEM ADMINISTRASI SURAT MENYURAT DI POLDA XYZ Saputra, Joneten; Shandy; Prawinnetou, Wassy; Rahman, Abdul; Wahyu Sudrajat, Antonius
Jurnal Ilmiah Informatika Global Vol. 16 No. 2: August 2025
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v16i2.5641

Abstract

In today's era, advancements in information technology (IT) are driving digital transformation across various sectors, including government institutions such as Polda Xyz. A key element of this transformation is the administrative correspondence system, which must be managed efficiently, structurally, and securely. This study aims to design an enterprise architecture that serves as the foundation for the comprehensive and integrated development of information systems, using the TOGAF (The Open Group Architecture Framework) methodology. This approach addresses challenges such as process inefficiencies, lack of integration between work units, and weak information security. By applying TOGAF through the Architecture Development Method (ADM), the proposed architecture encompasses four core domains: Business Architecture, Application Architecture, Data Architecture, and Technology Architecture. This research adopts a qualitative approach through literature studies, observations, interviews, and data analysis. The results produce an enterprise architecture blueprint and an implementation roadmap for the E-Office system, which are expected to enhance operational efficiency, communication effectiveness, and data security within Polda Xyz.
FRAUD TRIANGLE THEORY DAN KECURANGAN LAPORAN KEUANGAN DENGAN JARAK KEKUASAAN SEBAGAI VARIABLE MODERASI Khairani, Siti; Malik, Shahib Hibatullah; Hermawati, Lisa; Sudrajat, Wahyu
JEMBATAN (Jurnal Ekonomi, Manajemen, Bisnis, Auditing, dan Akuntansi) Vol 10 No 1 (2025): Jurnal JEMBATAN (Jurnal Ekonomi, Manajemen, Bisnis, Auditing dan Akuntansi)
Publisher : P3M STIE Mulia Darma Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54077/jembatan.v10i1.212

Abstract

Tujuan penelitian ini adalah untuk menguji pengaruh tekanan keuangan, kesempatan, dan rasionalisasi terhadap kecurangan laporan keuangan dengan jarak kekuasaan sebagai varibel moderasi. Sampel yang digunakan dalam penelitian ini adalah Badan Usaha Milik Negara (BUMN) di Negara Indonesia, Australia, Amerika Serikat, Jerman dan Afrika Selatan pada periode 2021-2023. Metode purposive sampling digunakan dalam pengumpulan sample dan terdapat tujuhpuluh BUMN yang memenuhi kriteria. Metode analisis regresi logistik digunakan dalam penelitin ini yang mencakup uji log likelihood value, uji Hosmer dan Lameshow Test dan uji goodness of fit. Hasil penelitian secara empiris membuktikan bahwa tekanan keuangan dan rasionalisasi tidak berpengaruh positif signifikan terhadap kecurangan laporan keuangan sedangkan kesempatan berpengaruh positif signifikan terhadap kecurangan laporan keuangan. Jarak kekuasaan mampu memoderasi hubungan antara tekanan keuangan dan kesempatan terhadap kecurangan laporan keuangan, sedangankan rasionalisasi terhadap kecurangan laporan keuangan tidak mampu dimoderasi oleh jarak kekuasaan. Penelitian ini menyimpulkan bahwa jarak kekuasaan yang tinggi tetap menjadi motivasi terjadinya kecurangan laporan keuangan.
PERANCANGAN DAN IMPLEMENTASI SISTEM INFORMASI KEPEGAWAIAN PADA PT ANUGERAH SUKSES KHARISMA Suwandi Suwandi; Antonius Wahyu
Jurnal Indonesia Sosial Teknologi Vol. 4 No. 3 (2023): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v4i3.591

Abstract

Sistem informasi kepegawaian adalah sistem yang mampu memberikan informasi data-data pegawai pada perusahaan agar informasi tersampaikan dengan baik. Masalah yang ada pada PT Anugerah Sukses Kharisma adalah proses perekrutan calon karyawan yang lama, tidak adanya pendataan presensi, kehilangan surat penugasan, pemberhentian, mutasi dan demosi. Tujuan dari pembuatan sistem adalah mengatur proses recruitment secara online, absensi karyawan, dan fitur dokumentasi seperti data pemberhentian, mutasi, penugasan, dan demosi. Manfaat dari pembuatan sistem adalah mempermudah admin dalam mengatur lamaran, data karyawan, presensi, pemberhentian, mutasi, penugasan, dan demosi. Sistem ini dikembangkan menggunakan Metode Iterasi (iterative model), dan untuk menganalisis masalah menggunakan use case diagram, class diagram, activity diagram,bahasa pemrograman PHP dengan Framework Laravel dan database menggunakan MySql. Hasil dari pembuatan Sistem Informasi Kepegawaian ini adalah fitur fitur data seperti proses perekrutan calon karyawan secara online, pengajuan cuti sudah dilakukan pendataan sehingga terekap, Perekapan absensi sudah dilakukan secara online, surat penugasan, surat pemberhentian. surat mutasi karyawan dan surat demosi karyawan yang terdata sehingga memudahkan pencarian data. Membantu admin untuk mengolah data yang dibuat sudah memenuhi keperluan perusahaan dalam mengurus data karyawan.
Adopsi Artificial Intelligence pada UMKM: Tinjauan Sistematis Rizky Arya Pratama; Antonius Wahyu Sudrajat
MDP Student Conference Vol 5 No 2 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i2.15392

Abstract

This study examines research trends, adoption determinants, and the impact of Artificial Intelligence (AI) on Micro, Small, and Medium Enterprises (MSMEs) through a Systematic Literature Review (SLR). The review was conducted using the Kitchenham and Charters methodology and the PRISMA 2020 protocol to ensure methodological rigor and transparency. A total of 30 peer-reviewed journal articles published between 2020 and 2025 were selected from reputable international and national databases. The results indicate that the Technology–Organization–Environment (TOE) framework is the most dominant theoretical model used to explain AI adoption in MSMEs. Technological characteristics, organizational readiness, and environmental pressure are consistently identified as key determinants influencing adoption decisions. Furthermore, empirical evidence shows that AI adoption positively affects marketing performance, operational efficiency, innovation capability, and financial performance of MSMEs. Despite these benefits, empirical studies focusing on Indonesian MSMEs at the local level remain limited. Therefore, this study proposes a conceptual TOE–AI Adoption–MSME Performance model as a foundation for future empirical research.
The IT GOVERNANCE IN REGIONAL WATER COMPANY RISK MANAGEMENT USING THE COBIT 2019 METHOD Firmansyah Firmansyah; Antonius Wahyu Sudrajat
Journal of Computer Networks, Architecture and High Performance Computing Vol. 8 No. 1 (2026): Articles Research Januari 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v8i1.7723

Abstract

Digital transformation in the public utility sector, particularly in regional water-owned enterprises (BUMD), presents complex risk challenges ranging from cybersecurity threats to operational distribution disruptions. PT Tirta Sriwijaya Maju (Perseroda), as the research object, faces constraints in IT risk management processes that are currently manual, reactive, and disintegrated, potentially threatening the sustainability of public services. This study aims to evaluate the current IT governance capability and design risk management improvements using the COBIT 2019 framework. The research methodology employs a mixed-method approach utilizing the Design Toolkit to determine domain priorities based on the company's risk profile and strategy. The evaluation focuses on six critical domains: EDM03, APO12, APO13, BAI03, DSS01, and MEA01. The Design Factors analysis established a target capability at Level 3 (Defined Process) to ensure regulatory compliance. However, the current state (As-Is) measurement indicates that the company is at an average of Level 1 (Performed). A gap of 2 levels was identified, primarily caused by a disconnected evaluation cycle (MEA01), the absence of a formal Risk Appetite document, and reliance on spreadsheet-based risk monitoring. As a solution, this study provides strategic recommendations including the formalization of risk policies, the design of an integrated digital Monitoring Dashboard, and an Implementation Roadmap for 2025-2027. The implementation of this roadmap is expected to enhance risk governance maturity, ensure customer data integrity, and guarantee operational stability in accordance with Good Corporate Governance standards. Keywords: IT Governance, Risk Management, COBIT 2019, Design Factors, Regional Water Utility, Capability Level.
SARCASM DETECTION IN PALEMBANG LANGUAGE USING HYBRID CLASSICAL AND DEEP LEARNING APPROACHES Johannes Petrus; Antonius Wahyu Sudrajat; Muhammad Rachmadi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 12 No. 1 (2026): JITK Issue August 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v12i1.8222

Abstract

Research on sarcasm detection in sentences generally focuses on English and the national languages of certain countries, so that regional languages such as Palembang are still underrepresented in NLP research. This study aims to classify sarcasm in Palembang sentences by applying 12 models and evaluating their performance using a dataset containing 1,952 manually annotated samples. The experiment was also conducted using a 5-fold cross-validation scheme, and the statistical significance of the test results was analyzed using the Friedman t-test ( =41.96, FF=12.90). Contrary to common expectations, the Ensemble classifier achieved the best overall performance, attaining a mean F1-score of 0.877 and outperforming larger pre-trained and dialect-specific models. Even though it is still in the same language family, MelayuBERT's performance is very far behind (F1:0.691). Furthermore, the relatively lower performance of IndoBERT-1.5G (0.731) suggests that model scale alone does not guarantee effectiveness in low-resource language settings. These findings highlight the robustness of feature-engineered classical models compared to large-scale or dialect-specific pre-trained models for sarcasm detection in low-resource regional languages. Our research results with datasets sourced from varied domains have exceeded several national benchmarks. This study can be a baseline for further research.
Pengembangan Model Hybrid  Sistem Pendukung Keputusan Untuk Rekomendasi Calon Kepala Daerah Alessandro; Antonius Wahyu Sudrajat
Jurnal Ilmiah Matrik Vol. 28 No. 2 (2026): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/x4btmm34

Abstract

The selection process for regional head candidates by political parties often faces challenges of subjective assessment and conflicting criteria. Conventional selection methods have proven to be biased. This study aims to develop a Hybrid Multi-Criteria Decision Making (MCDM) model integrating Entropy as an objective weighter, with WASPAS and VIKOR as ranking engines, within a Web-based Decision Support System (DSS). A quantitative approach was used through the simulation of heterogeneous candidate data. The Entropy algorithm automatically determines weights based on data dispersion, which are then injected into WASPAS and VIKOR for ranking. Test results show Financial Capability (36.49%) and Bureaucratic Experience (27.27%) as the main determinants. A divergence was found: WASPAS recommended a stable candidate (Candidate J), while VIKOR recommended a candidate with maximum resources (Candidate G). Through Mean Rank consensus, Candidate G was determined as the best recommendation. Comparative tests show the Hybrid model correlates strongly (rs=0.81) with SAW, yet its final decision is more strategic. In conclusion, this model effectively reduces subjectivity and provides a robust compromise solution in political selection.
Comparative Study of IndoBERT and IndoBERT-BiLSTM Models Across Three Text Preprocessing Frameworks for Aspect-Based Sentiment Analysis on MyTelkomsel App Reviews Antonius Wahyu Sudrajat; Iis Pradesan Pradesan; Yulistia Yulistia Yulistia
International Journal of Artificial Intelligence Research Vol 10, No 2 (2026): December
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v10i2.1751

Abstract

This study examines how text preprocessing depth and model architecture jointly affect aspect-based sentiment analysis (ABSA) of MyTelkomsel application reviews. A total of 850 cleaned Google Play reviews were weakly labeled into 1,036 aspect-sentiment instances covering package price, network signal, and customer service using a keyword lexicon and a rating-derived heuristic. Three preprocessing frameworks of increasing complexity (transformer-oriented, hybrid, and augmented hybrid with class-imbalance handling) were each evaluated on three IndoBERT-based architectures (a frozen baseline, full fine-tuning, and an IndoBERT+BiLSTM hybrid) under an identical evaluation protocol. The augmented hybrid framework combined with full fine-tuning achieved the best performance (accuracy 92.16%, macro F1-score 0.7406), ahead of the transformer-oriented (macro F1 = 0.6219) and hybrid (macro F1 = 0.6404) frameworks, and its advantage for the fine-tuned model was consistent across three random seeds, although these differences do not survive correction for multiple comparisons at three seeds. Fine-tuning consistently outperformed both the frozen baseline and the BiLSTM extension, while the customer service aspect remained the hardest to classify because of class imbalance and weak-label noise. A post-hoc audit found that 61.5% of test instances share near-identical text with training instances, an artifact of splitting multi-aspect reviews at the row level; absolute scores are therefore upper bounds, and although all conditions share one split, the interaction between this overlap and the augmented framework's oversampling remains untested. Unlike prior Indonesian IndoBERT-based ABSA studies that fix a single preprocessing pipeline, this study isolates the separate contributions of preprocessing depth and model architecture.