Many challenges confront the efforts to build procurement fraud risk management in Industry 4.0. This study aims to assess the risk of procurement fraud in industry 4.0 and disclose strategies to optimize the role of internal auditors in mitigating these risks. The mixed-method has been conducted with data on procurement fraud risks generally accepted by government agencies. A survey involving 140 respondents and interviews with five experts have been completed. The risk assessment in the research findings involved seven procurement fraud risks, with "collusion between providers in e-tendering" ranking the highest. Procurement management must detect and prevent fraud by creating anti-hacker applications, conducting data analytics on business ownership, and ongoing monitoring. Internal auditors must undertake fraud prevention by improving their ability in data analytics, encouraging probity plans, and procurement assistance. Fraud detection is carried out through performance audits using computer-assisted audit techniques, probity audits, information technology governance audits, continuous audits, data analytics, and internal auditor integrity assessments through surveys to the auditee.

The era of digital transformation requires management and auditors to apply data analytics. This era also increases the risk of procurement fraud. This study aims to determine the application of data analytics in handling the risk of procurement fraud in the 4.0 era. Quantitative methods are applied with data analytics techniques to 2018 provincial tender data. The results show that descriptive statistical techniques can reveal the profile of collusion risk attributes. The average provincial construction tender in 2018 indicates a risk of collusion above 50% for the high price attribute. The visualization technique produces a tender collusion risk dashboard. There are 3 provincial LPSEs detected to meet the combined risk indications of collusion. The level of likelihood of collusion risk in the 3 provinces also shows “almost certain to occur” or with a value of 5. The results of this study have implications for data analytics which are very important to be immediately applied in government procurement to manage the risk of procurement fraud.

Setiap instansi pemerintah harus bertransformasi digital. Kompetensi penggunaan data analytics menjadi keniscayaan. Riset data analytics belum mengungkap penggunaan data analytics dalam Lembaga pelatihan. Sementara, Pusdiklatwas BPKP belum optimal menggunakan data analytics, potret kesenjangan digital belum ada dan ada sinyalemen 41,22% peserta belum yakin dengan penerapan data analytics. Penelitian ini mempunyai tujuan untuk mengungkap gambaran penerapan teknik data analytics dan mengungkap kesenjangan digital yang mempengaruhi keyakinan peserta pelatihan tentang penerapan data analytics. Pendekatan penelitian kuantitatif digunakan dengan studi literatur, studi eksplorasi dan penerapan teknik data analytics, berupa; teknik statistik dan teknik visualisasi. Objek penelitian berupa 169 peserta pelatihan data analytics for audit. Hasil penelitian menunjukkan empat tipe data analytics dapat diterapkan di lembaga pelatihan. Analisa deskriptif digunakan untuk mengungkap insight ketidakselarasan profil peserta dengan keyakinan peserta pelatihan. Analisa diagnostik dapat mengungkap variabel kesenjangan digital berkorelasi kuat dan sangat kuat dengan kelas keyakinan peserta. Analisa prediksi dengan decision tree mengungkap akurasi 55,71%. Kombinasi kesenjangan digital pada kelas keyakinan peserta. Akar pohon keputusan yang utama berupa jenis kelamin, pemahaman statistik&/TIK, dukungan laptop yang dimiliki. Analisa preskriptif dengan text analytics mengungkap 10 peringkat kata perlu menjadi perhatian untuk pengembangan pelatihan berikutnya. Hasil penelitian ini berimplikasi menjadi sumbangsih akademik dan akselerasi tranformasi digital di penyelenggara pelatihan.