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All Journal Sibatik Journal : Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, Dan Pendidikan Jurnal Minfo Polgan (JMP) Innovative: Journal Of Social Science Research
Bryan Habib Gautama
Politeknik Keuangan Negara STAN
Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

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Fraud Early Warning System : Identifikasi Potensi Fraud dalam Pelaporan Harta Kekayaan Penyelenggara Negara Berbasis Big Data Bryan Habib Gautama; Rijal Hanif; Sessa Tiara Maretaniandini
Innovative: Journal Of Social Science Research Vol. 3 No. 4 (2023): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v3i4.3779

Abstract

Indonesia has faced challenges regarding the lack of compliance to the requirement of disclosing the financial assets of state administrators. This issue has contributed to the development of unfavorable public sentiment towards the compliance of state administrators, particularly in relation to corruption. Indonesia has implemented a corruption prevention mechanism known as the State Officials Wealth Report (LHKPN). The LHKPN is a compulsory declaration pertaining to the assets possessed by individuals from the time they assume a position in the government until their retirement. Despite the level of compliance achieved in LHKPN reporting, the report content is susceptible to some shortcomings in terms of its validity. The issue of validity is further compounded by the constraint of a limited resource of human resources. This phenomenon gives rise to the possibility of fraud occurring through the misrepresentation or concealment of assets. In light of the aforementioned, it is imperative to establish a comprehensive big data system integrated with risk management protocols to facilitate the LHKPN inspection procedure. This study aims to provide new ideas in the identification of potential fraud using early warning. In this study, the preparation of the system uses Software Development Life Cycle (SDLC). The Fraud Early Warning System integrates LHKPN data and comparative technical data using specific indicators and variables to assess the amount of risk within the identification framework. This system is able to provide red flag for assets that have not been disclosed or are deemed inappropriate, hence enabling the initiation of further follow-up actions. The application of this system can be a solution for strengthening fraud early detection related to the assets of state administrators as well as the potential to increase compliance in LHKPN reporting.
RE-ACTUALIZATION SIRI’ NA PACCE’ CULTURE THROUGH SECTOR COLLABORATION WITH PENTA HELIX MODEL Bryan Habib Gautama; Muhammad Ripurio; Ghea Rahmayanti
SIBATIK JOURNAL: Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, dan Pendidikan Vol. 2 No. 9 (2023): August
Publisher : Lafadz Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/sibatik.v2i9.969

Abstract

Siri' na pacce' has lived, developed, and is believed to be a cultural value of the people of South Sulawesi. Siri' na pacce' culture has an important role in maintaining civil society. In society, there is a growing perception that this culture is starting to be abandoned and forgotten due to deviations that occur and external influences that eliminate its existence. This research aims to identify efforts to preserve siri' na pacce' culture through re-actualization, based on considerations such as supporting and inhibiting factors, culture dynamics, development trends, and the sense of urgency. This research uses a qualitative methodology and library research. Re-actualization is carried out with a collaborative approach between various parties using the penta helix model. Based on the analysis, siri' na pacce' has an important role in building community knowledge so it needs to be preserved. Preservation efforts are carried out by re-actualization by involving the government as a regulator, academics acting as drafters, business actors as presenters of economic markets with community participation, the community as intermediaries, providing input, and maintaining cultural values, and the media as a means of promotion to carry out preservation efforts.
Penggunaan Chatbot Artificial Intelligence dan Pembangunan Karakter Mahasiswa: Sebuah Studi Empiris Anggi Prastyono; Bryan Habib Gautama; Ihza Zhafranianto
Jurnal Minfo Polgan Vol. 12 No. 2 (2023): Artikel Penelitian 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v12i2.13316

Abstract

Perkembangan teknologi yang mendorong penggunaan Chatbot Artificial Intelligence (Chatbot AI) dalam dunia pendidikan. Penggunaan teknologi ini dapat memberikan dampak positif dan negatif khususnya pada karakter mahasiswa. Politeknik Keuangan Negara (PKN) STAN memiliki kurikulum yang terintegrasi dengan pembangunan karakter mahasiswa. Penelitian ini bertujuan untuk mengukur pengaruh karakter yang dihasilkan dari penggunaan chatbot AI terhadap tujuan pembangunan karakter. Metode penelitian yang digunakan adalah metode kuantitatif dengan menerapkan model Structural Equation Modeling-Partial Least Squares (SEM-PLS). Hasil penelitian menunjukkan bahwa dari 12 jalur yang dianalisis, sebanyak 11 jalur memiliki pengaruh signifikan positif terhadap tujuan pembangunan karakter. Sedangkan jalur profesionalisme terhadap tujuan pembangunan karakter tidak signifikan. Namun, penelitian ini juga mengungkap bahwa jika dilakukan mediasi melalui variabel intervening, profesionalisme dapat berpengaruh positif terhadap tujuan pembangunan karakter melalui variabel integritas dan kesempurnaan. Hal ini menunjukkan bahwa penggunaan chatbot AI dapat secara positif mempengaruhi pembangunan karakter mahasiswa.
Co-Authors Anggi Prastyono Ghea Rahmayanti Ihza Zhafranianto Muhammad Ripurio Rijal Hanif Sessa Tiara Maretaniandini