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All Journal Syntax Idea Cakrawala Repositori Imwi Journal Of World Science Jurnal Indonesia Sosial Teknologi Journal of Business, Social and Technology Eduvest - Journal of Universal Studies Lentera: Multidisciplinary Studies Lentera: Multidisciplinary Studies Journal of Digital Marketing and Search Engine Optimization Journal of Applied Econometric Journal of Artificial Intelligence Research
Farizki, Rafi
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Neuroscience Public Health Social Sciences

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SISTEM APLIKASI PEMESANAN TIKET BUS BERBASIS WEBSITE PADA PO SINAR JAYA Ramdhani, Adhitya Ilham; Khasanah, Siti; Farizki, Rafi
Syntax Idea Vol 2 No 9 (2020): Syntax Idea
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-idea.v2i9.556

Abstract

Media komunikasi yang digunakan untuk mengakses internet seiring sejalan dengan banyaknya pengguna internet di dunia ini semakin pesat. Dengan demikian sangat mudah membuka peluang bagi perusahaan untuk melakukan pengembangan pelayanan bisnis, relasi, dan sebagai sarana untuk memperkenalkan perusahaan kepada masyarakat luas melalui media internet salah satunya yaitu perusahaan penyedia layanan transportasi. Sebelum adanya internet penumpang harus datang ke agen untuk memesan tiket, tidak jarang juga penumpang dibuat kecewa karena tiket yang dipesan telah habis. PO Sinar Jaya merupakan salah satu perusahaan penyedia layanan transportasi yang sangat berkembang dan belum memanfaatkan teknologi internet sebagai sarana pengembangan layanan kepada penumpang. Hal ini sering menjadi permasalahan karena penumpang tidak dapat melihat jadwal dan jumlah tiket yang tersisa secara langsung dan perusahaan tidak dapat menginformasikan secara langsung kepada pelanggan, proses pelayanan lambat terkadang membuat penumpang harus rela menunggu sampai ber jam – jam dan tidak jarang tiket yang sudah dipesan sudah habis, penumpang datang tergesa – gesa karena takut kehabisan tiket bus, maka dengan membangun sistem informasi berbasis website guna memudahkan dalam hal mengakses informasi yang berhubungan dengan PO Sinar Jaya baik profil maupun layanan melalui teknologi dan sistem yang diuji dengan menggunakan metode black box, semuanya mempunyai keterangan ok, yang berarti sistem berjalan dengan baik dan benar tanpa ditemukan kesalahan.
Dampak Disrupsi Teknologi AI terhadap Ketenagakerjaan dan Struktur Ekonomi di Negara Berkembang Santika, Rani; Farizki, Rafi
Lentera: Multidisciplinary Studies Vol. 3 No. 3 (2025): Lentera: Multidisciplinary Studies
Publisher : Publikasiku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57096/lentera.v3i3.164

Abstract

Munculnya teknologi Kecerdasan Buatan (AI) telah memicu transformasi signifikan di berbagai sektor, khususnya yang berdampak pada struktur ketenagakerjaan dan sistem ekonomi di negara-negara berkembang. Studi ini bertujuan untuk mengeksplorasi efek ganda dari disrupsi AI: peluang untuk pertumbuhan produktivitas dan modernisasi ekonomi versus risiko perpindahan pekerjaan dan ketimpangan pendapatan yang semakin parah. Dengan menggunakan pendekatan metode campuran yang menggabungkan analisis pasar tenaga kerja kuantitatif dengan wawancara kualitatif dari para pemangku kepentingan industri utama di seluruh Asia Tenggara, penelitian ini menyoroti pola-pola penting transisi tenaga kerja. Temuan tersebut mengungkapkan bahwa meskipun adopsi AI meningkatkan efisiensi operasional dan menciptakan permintaan untuk pekerjaan berketerampilan tinggi, namun secara bersamaan mengancam pekerjaan berketerampilan rendah, terutama di sektor manufaktur dan jasa. Selain itu, distribusi adopsi teknologi yang tidak merata memperparah kesenjangan ekonomi regional. Studi ini menawarkan kontribusi teoritis dan praktis yang penting dengan mengusulkan kerangka kebijakan adaptif untuk menyeimbangkan kemajuan teknologi dengan mekanisme perlindungan sosial. Implikasinya menggarisbawahi kebutuhan mendesak bagi pemerintah dan industri di negara-negara berkembang untuk memprioritaskan strategi digital yang inklusif, program pelatihan ulang keterampilan, dan tata kelola AI untuk memastikan pembangunan ekonomi yang berkelanjutan di tengah perubahan teknologi yang cepat.
Dampak Disrupsi Teknologi AI terhadap Ketenagakerjaan dan Struktur Ekonomi di Negara Berkembang Santika, Rani; Farizki, Rafi
Lentera: Multidisciplinary Studies Vol. 3 No. 3 (2025): Lentera: Multidisciplinary Studies
Publisher : Publikasiku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57096/lentera.v3i3.164

Abstract

Munculnya teknologi Kecerdasan Buatan (AI) telah memicu transformasi signifikan di berbagai sektor, khususnya yang berdampak pada struktur ketenagakerjaan dan sistem ekonomi di negara-negara berkembang. Studi ini bertujuan untuk mengeksplorasi efek ganda dari disrupsi AI: peluang untuk pertumbuhan produktivitas dan modernisasi ekonomi versus risiko perpindahan pekerjaan dan ketimpangan pendapatan yang semakin parah. Dengan menggunakan pendekatan metode campuran yang menggabungkan analisis pasar tenaga kerja kuantitatif dengan wawancara kualitatif dari para pemangku kepentingan industri utama di seluruh Asia Tenggara, penelitian ini menyoroti pola-pola penting transisi tenaga kerja. Temuan tersebut mengungkapkan bahwa meskipun adopsi AI meningkatkan efisiensi operasional dan menciptakan permintaan untuk pekerjaan berketerampilan tinggi, namun secara bersamaan mengancam pekerjaan berketerampilan rendah, terutama di sektor manufaktur dan jasa. Selain itu, distribusi adopsi teknologi yang tidak merata memperparah kesenjangan ekonomi regional. Studi ini menawarkan kontribusi teoritis dan praktis yang penting dengan mengusulkan kerangka kebijakan adaptif untuk menyeimbangkan kemajuan teknologi dengan mekanisme perlindungan sosial. Implikasinya menggarisbawahi kebutuhan mendesak bagi pemerintah dan industri di negara-negara berkembang untuk memprioritaskan strategi digital yang inklusif, program pelatihan ulang keterampilan, dan tata kelola AI untuk memastikan pembangunan ekonomi yang berkelanjutan di tengah perubahan teknologi yang cepat.
Utilizing Data Analytics to Improve Search Engine Marketing (SEM) Strategy in the Retail Industry Farizki, Rafi
Journal of Digital Marketing and Search Engine Optimization Vol. 2 No. 1 (2025): Journal of Digital Marketing and Search Engine Optimization
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jseo.v2i1.9

Abstract

In the competitive digital era, retail companies face the challenge of optimizing digital marketing strategies to increase visibility and conversions. One increasingly important approach is the integration of data analytics in Search Engine Marketing (SEM) strategies. This research aims to analyze how the implementation of multi-level data analytics can increase the effectiveness of SEM campaigns in retail companies. The method used is descriptive qualitative research with data collection techniques through in-depth interviews, observation, and documentation of retail companies that have implemented data-based SEM strategies. The results show that the comprehensive use of descriptive, predictive, and prescriptive analytics improves SEM performance, which is characterized by an increase in Click-Through Rate (CTR) of 128%, an increase in Conversion Rate of more than 100%, and a decrease in Cost Per Acquisition (CPA) by 42%. The integration of data analytics also encourages faster, more accurate, and responsive decision-making to changes in consumer behavior. In conclusion, the application of data analytics in SEM has a significant impact on improving the effectiveness of digital campaigns and the efficiency of using marketing budgets. The implications of this research emphasize the importance of developing analytics capacity and strengthening data infrastructure in companies to deal with the dynamics of the evolving digital market. This research also contributes to enriching the literature on data-driven marketing strategies in the digital era.
Classification of Drug Usage Patterns and Identification of Diseases in the Provision of Drug Types Using the K-Nearest Neighbors Method Farizki, Rafi; Supriatna, Nano; Juliana, Christine
Journal of World Science Vol. 3 No. 11 (2024): Journal of World Science
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jws.v3i11.600

Abstract

The increasing complexity of healthcare systems highlights the need for data-driven approaches to optimize drug usage patterns and improve disease management. This study employs the K-Nearest Neighbors (KNN) algorithm to analyze correlations between prescribed medications and associated diseases, utilizing a dataset comprising attributes such as patient demographics, drug types, dosages, and treatment frequencies. The results reveal significant trends, including the predominance of "Drug_D" due to its versatility across multiple conditions such as hypertension, diabetes, and cardiovascular diseases. The study also highlights the prevalence of chronic conditions like hypertension and respiratory disorders, underscoring the importance of preventive healthcare and resource allocation. Simplified dosage regimens, predominantly "Once_Daily," were found to enhance patient adherence, aligning with global best practices in chronic disease management. The analysis further emphasizes targeted prescribing practices, with specific drugs strongly correlated to particular diseases, such as "Drug_A" for hypertension and "Drug_B" for respiratory disorders. However, the broad usage of certain medications raises concerns about potential over-reliance, necessitating regular monitoring. These findings demonstrate the value of machine learning in improving healthcare decision-making, enhancing operational efficiency, and supporting evidence-based practices. Future research should expand the dataset to include genetic and lifestyle factors to further refine predictive accuracy and contribute to the advancement of personalized medicine. This study underscores the transformative potential of integrating data mining techniques into healthcare systems to achieve better patient outcomes and more effective resource management.
The Advantages and Challenges of Digital Resources as Supporting Learning Media in Teaching Narrative Writing Text Santika, Rani; Farizki, Rafi; Jamal, Ahmad; Azis, Irfan
Eduvest - Journal of Universal Studies Vol. 4 No. 2 (2024): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v4i2.1036

Abstract

This research aims to investigate the advantages and challenges of digital resources as supporting learning media in teaching narrative writing text. This research used qualitative methods by using descriptive qualitative design. The data was obtained through document analysis, observation and interview. The subject of this research were two English teachers in Vocational High School Ibnu Khaldun at 10th Grade the academic years of 2022/2023 who implemented digital resources in teaching narrative writing text. The findings of this research show there are four advantages of digital resources. First, digital resources help English teachers in delivering material. Second, access a wider range of material and resources. Third, it can create fun and enjoyable classes. Fourth, improve the quality of learning by new activities. Furthermore, there are three challenges, First, limited internet connectivity. Second, choosing digital resources appropriately. Third, the lack of digital resources implemented by English teachers.
Development of A Risk Management System To Reduce The Impact of Cyber Threats Farizki, Rafi; Antonius Alijoyo, Frasciskus
Jurnal Indonesia Sosial Teknologi Vol. 5 No. 3 (2024): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v5i3.967

Abstract

Cyber threats are one of the main issues in the digital era. Cyberattacks can result in financial, reputational and even operational disruption for organizations. In an effort to overcome this, organizations need to have an effective risk management system to identify, assess and manage cyber risks. The aim of this research is to determine the effectiveness of a risk management system that can help organizations reduce the impact of cyber threats. This study used qualitative research methods. The data collection technique in this research is literature study. The data that has been collected is then analyzed in three stages, namely data reduction, data presentation and drawing conclusions. The research results show that developing an effective risk management system is an important step for organizations in reducing the impact of cyber threats. A good risk management system can help organizations protect information assets, increase cyber resilience, and build customer trust.
ETHICAL ANALYSIS OF THE USE OF AI IN MEDICAL DATA MANAGEMENT: PRIVACY CHALLENGES IN THE DIGITAL AGE Farizki, Rafi
Journal of Artificial Intelligence Research Vol. 1 No. 1 (2025): Journal of Artificial Intelligence Research
Publisher : Asosiasi Persatuan Pengusaha Muda Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64910/jouair.v1i1.10

Abstract

The use of artificial intelligence (AI) in medical data management has improved efficiency and accuracy in healthcare, but it presents significant ethical challenges, especially when it comes to patient privacy. Along with the rapid development of technology, concerns over the security and privacy violations of medical data are increasing, which can impact public trust in AI-based healthcare systems. The study aims to analyze the ethical challenges in the use of AI in medical data and identify strategies to strengthen patient safety and privacy. Using a qualitative method with a case study approach, this study involves in-depth interviews and analysis of policy documents from several health institutions. The results of the study reveal three main themes: (1) ethical challenges related to transparency and patient consent, (2) the risk of medical data leakage due to the lack of AI security standards, and (3) barriers to ethical AI implementation in the health environment, especially in developing countries. The recommendations of this study include the implementation of the latest encryption protocols, increased ethical awareness among medical personnel, and policy transparency to patients. These findings contribute to the development of medical data privacy policies in the digital era, as well as increasing public trust in AI technology in the health sector.
The Role of Digital Transformation in Labor Market Changes: An Econometric Analysis of the Impact of Automation on the Manufacturing Sector Santika, Rani; Farizki, Rafi
Journal of Applied Econometric Vol. 1 No. 1 (2025): Journal of Applied Econometric
Publisher : Sekolah Tinggi Agama Islam Kuningan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59784/journaljoae.v1i1.3

Abstract

Digital transformation is fundamentally changing the landscape of the global labor market, especially in the manufacturing sector that is increasingly adopting automation technology. Developing countries, including Indonesia, face significant challenges in responding to shifting skills needs due to these technological developments. This study aims to analyze in depth the impact of automation on labor market dynamics in the manufacturing sector, focusing on changing patterns of skills demand and their implications for labor productivity and resilience. Using a sophisticated econometric approach, this study utilizes panel data from the manufacturing industry in Indonesia over the past ten years. The analysis was conducted using fixed-effects and multivariate regression methods to assess the relationship between the adoption rate of automation technology and key variables of the labor market, such as changes in skill composition, wage levels, and demand for skilled versus unskilled labor. The results of the analysis show that there is a significant impact of automation in reducing the demand for non-skilled labor, while specialized skills, especially in the field of technology and maintenance, are experiencing an increase in demand. This research provides important insights for the formulation of policies that support the upskilling of the workforce in the face of the digital era, and shows that the sustainability of the manufacturing sector is highly dependent on the adaptation and development of technology-based skills.
Performance-Based Management and Its Role in Enhancing Organizational Efficiency Farizki, Rafi; Santika, Rani
Cakrawala Repositori IMWI 1706-1712
Publisher : Institut Manajemen Wiyata Indonesia & Asosiasi Peneliti Manajemen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52851/cakrawala.v8i5.835

Abstract

Performance-based management has been widely adopted as a managerial approach to enhance organizational efficiency and accountability in increasingly competitive and complex environments. However, many organizations continue to experience inefficiencies despite the formal implementation of performance-based management systems, indicating a gap between managerial intent and actual operational outcomes. This study aims to examine the role of performance-based management in improving organizational efficiency by analyzing its overall effect and the relative contribution of its key dimensions, including performance planning, performance monitoring, performance evaluation, and performance feedback. This study employed a quantitative explanatory research design. Data were collected through a structured survey administered to managerial-level employees involved in the implementation and evaluation of performance-based management practices within their organizations. The data were analyzed using descriptive and inferential statistical techniques to assess the relationship between performance-based management and organizational efficiency. The results indicate that performance-based management has a positive and statistically significant effect on organizational efficiency. Further analysis shows that performance planning and performance monitoring are the strongest contributors to efficiency, emphasizing the importance of proactive managerial practices. In contrast, performance evaluation and feedback demonstrate weaker effects, suggesting that their impact depends on how effectively performance information is used in managerial decision-making. This study contributes to the performance management literature by offering an integrative organizational-level perspective and provides practical insights for managers seeking to enhance efficiency through effective performance-based management implementation.
Co-Authors Ahmad Jamal Antonius Alijoyo, Frasciskus Azis, Irfan Juliana, Christine Ramdhani, Adhitya Ilham Santika, Rani Siti Khasanah Supriatna, Nano