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All Journal Jurnal Penelitian Inovatif Jurnal Bisnis Mahasiswa Social Sciences Insights Journal
Arohman, Rifki
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Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Public Health Social Sciences Other

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Dinamika transformasi digital, pengalaman kerja, dan kesenjangan generasi terhadap efikasi digital di PT Besmindo Materi Sewatama, Riau Syamsuri, Abd Rasyid; Asrilsyak, Sharnuke; Abdurrahman, Rezi; Islami, Fiqri Hadi; Arohman, Rifki
Jurnal Bisnis Mahasiswa Vol 5 No 6 (2025): Jurnal Bisnis Mahasiswa
Publisher : PT Aksara Indo Rajawali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/jbm.903

Abstract

Transformasi digital telah menjadi tuntutan penting bagi perusahaan dalam menghadapi perubahan lingkungan bisnis yang dinamis. Penelitian ini bertujuan untuk memahami dinamika transformasi digital, pengalaman kerja, dan kesenjangan generasi dalam membentuk efikasi digital karyawan di PT Besmindo Materi Sewatama, Riau. Menggunakan pendekatan kualitatif, data diperoleh melalui wawancara mendalam, observasi, dan telaah dokumen terkait. Hasil penelitian menunjukkan bahwa transformasi digital mendorong perubahan budaya kerja, namun penerapannya dipengaruhi oleh variasi pengalaman kerja dan adanya kesenjangan generasi di lingkungan karyawan. Generasi muda cenderung lebih adaptif terhadap teknologi, sementara generasi senior mengandalkan pengalaman kerja dalam menghadapi perubahan, yang terkadang menimbulkan resistensi. Peran kesenjangan generasi terbukti menjadi faktor penting dalam memediasi hubungan antara pengalaman kerja dan efikasi digital. Penelitian ini menegaskan bahwa pemahaman terhadap dinamika antar generasi dan pengalaman kerja menjadi kunci dalam meningkatkan efikasi digital karyawan di era transformasi digital. Temuan ini diharapkan dapat memberikan kontribusi bagi pengembangan strategi manajemen sumber daya manusia dan kebijakan transformasi digital di perusahaan.
Integration of machine learning in e-commerce: A systematic literature review on consumer behavior prediction and product recommendation Syamsuri, Abd. Rasyid; Arohman, Rifki; Saputra, Muhammad Renaldy; Ikhlash, Muhammad; Damanik, Sri Karyani
Social Sciences Insights Journal Vol. 3 No. 3 (2025): Social Sciences Insights Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/sg7wnx04

Abstract

This systematic literature review examines the integration of machine learning (ML) in e-commerce, focusing on consumer behavior prediction and product recommendation systems. Following PRISMA guidelines, we searched Scopus, Web of Science, IEEE Xplore, and ACM Digital Library, identifying 1,247 records. After screening, 48 peer-reviewed articles (2019-2024) were included. This review makes three novel contributions: (1) a taxonomy of ML algorithms categorizing approaches by function (prediction vs. recommendation) and technique (supervised, unsupervised, deep learning); (2) a comparative analysis of algorithm performance across different e-commerce contexts; and (3) identification of specific research gaps requiring investigation. Findings reveal that hybrid recommendation systems combining collaborative filtering with deep learning achieve superior accuracy (mean improvement of 15-23% over single-method approaches), while gradient boosting methods (XGBoost, LightGBM) demonstrate the highest predictive performance for purchase behavior. Critical challenges include cold-start problems, data sparsity, algorithmic bias, and privacy concerns. We propose an integrative framework mapping ML technique to specific e-commerce applications and identify five priority areas for future research. Limitations include English-language restrictions and potential publication bias toward positive results.
The impact of online shopping features on consumer buying behavior: A systematic literature review Syamsuri, Abd. Rasyid; Arohman, Rifki; Saputra, Muhammad Renaldy; Halim, Abd.; Surbakti, Afridayanti
Social Sciences Insights Journal Vol. 3 No. 3 (2025): Social Sciences Insights Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/x4zvq336

Abstract

This study examines the impact of online shopping features on consumer buying behavior by synthesizing findings from recent scholarly works through a systematic literature review. The research aims to identify how various digital features, including personalization, security mechanisms, interactive technologies, and social commerce elements, influence consumer trust, decision-making, and purchase intentions. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a structured selection process was applied to peer-reviewed journal articles, academic reports, and books published within the last five years, resulting in 25 studies included in the final review. A descriptive synthesis approach was used to categorize themes and compare patterns across different contexts. The findings indicate that functional aspects such as website design and usability strongly affect satisfaction and trust, while interactive and experiential features, including augmented reality, chatbots, and live streaming commerce, enhance engagement and drive purchasing outcomes. Additionally, the review highlights challenges related to privacy concerns, consumer fatigue, and ethical issues, suggesting that sustainable e-commerce strategies require balancing technological innovation with consumer-centric design. The study implies that platforms integrating trust, convenience, and personalization are more likely to achieve long-term consumer loyalty and competitive advantage in digital markets.
The role of AI in enhancing employee experience and HR effectiveness in hybrid work models: A systematic literature review Syamsuri, Abd. Rasyid; Arohman, Rifki; Saputra, Muhamad Renaldy; Esmeralda, Angel II P.
Social Sciences Insights Journal Vol. 3 No. 3 (2025): Social Sciences Insights Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/v4p4q169

Abstract

This systematic literature review examines the role of artificial intelligence (AI) in enhancing employee experience (EX) and human resource (HR) effectiveness within hybrid work models. Following PRISMA guidelines, we systematically searched Scopus, Web of Science, and Google Scholar databases, identifying 847 initial records. After applying inclusion criteria (peer-reviewed articles, published 2019-2024, English language, focusing on AI-HR integration in flexible/hybrid work contexts), 42 studies were included in the final synthesis. The review identifies three primary AI application domains in HR: (1) operational automation (recruitment screening, scheduling, administrative tasks), (2) analytics and decision support (predictive retention modeling, performance analytics), and (3) personalized employee support (adaptive learning, well-being monitoring, conversational agents). Our synthesis reveals that AI positively influences EX outcomes—including engagement, satisfaction, and perceived HR responsiveness—when implemented with transparency, human oversight, and adequate digital infrastructure. However, significant challenges persist, including algorithmic bias in high-stakes decisions, data privacy concerns, skill gaps among HR professionals, and organizational resistance. The review proposes a conceptual framework integrating technological, organizational, and individual factors that moderate AI's effectiveness in hybrid contexts. Key moderating conditions include leadership support, data quality, employee digital literacy, and governance mechanisms. Limitations include potential publication bias, English-language restriction, and the nascent state of longitudinal research in this domain. We conclude with a specific research agenda identifying methodological approaches, contextual variables, and outcome measures warranting future investigation.
Tinjauan Literatur Potensi Pengembangan Palm Kernel Cake sebagai Sumber Daya Serbaguna dalam Industri Sawit Berkelanjutan Arohman, Rifki; Afrilia, Dhika; Septiyaningsih, Dwi; Ramadhan, Risky; Natasya, Natasya
Jurnal Penelitian Inovatif Vol 6 No 1 (2026): JUPIN Februari 2026
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jupin.2087

Abstract

Industri kelapa sawit Indonesia menghasilkan volume limbah padat yang besar, salah satunya Palm Kernel Cake (PKC), residu dari ekstraksi minyak inti sawit yang kaya protein, lemak, serat kasar, mineral, dan karbohidrat kompleks. Studi ini menganalisis potensi PKC sebagai biomassa multifungsi yang mendukung bioindustri sawit berkelanjutan dan terintegrasi sesuai prinsip ekonomi hijau. Metode penelitian menggunakan pendekatan deskriptif-analitis melalui pengumpulan data primer di PTPN IV Sei Pagar serta telaah komparatif terhadap dua belas studi (2016–2025) yang berfokus pada komposisi biokimia, efisiensi konversi, dan kelayakan industri. Hasil penelitian menunjukkan bahwa pengolahan PKC melalui fermentasi mikroba dan perlakuan enzimatis dapat meningkatkan kadar protein hingga 25% dan kecernaan bahan kering 20%, sehingga layak sebagai bahan pakan alternatif berkualitas tinggi dan ramah lingkungan. Pemanfaatan PKC untuk bioenergi dan karbon aktif juga menunjukkan efisiensi konversi tinggi, dengan biogas mengandung lebih dari 50% metana dan karbon aktif berpori mencapai luas permukaan 980 m²/g, menandakan potensi kuat di sektor energi terbarukan dan remediasi lingkungan. Studi ini juga menemukan bahwa integrasi pengolahan PKC dalam model bioenergi bertingkat dapat memperkuat ekonomi sirkular sektor sawit melalui diversifikasi produk bernilai tambah seperti biofuel, biopolimer, perantara biokimia, dan material penyimpanan energi. Secara keseluruhan, temuan ini menegaskan bahwa PKC memiliki potensi strategis sebagai sumber daya industri hijau yang mendukung dekarbonisasi, pemberdayaan ekonomi pedesaan, dan pengelolaan limbah berkelanjutan sekaligus meningkatkan ketahanan ekonomi dan keberlanjutan lingkungan jangka panjang industri sawit Indonesia.
Co-Authors A Halim Abd. Rasyid Syamsuri Abdurrahman, Rezi Afrilia, Dhika Damanik, Sri Karyani Esmeralda, Angel II P. Islami, Fiqri Hadi Muhammad Ikhlash Natasya Natasya Ramadhan, Risky Saputra, Muhamad Renaldy Saputra, Muhammad Renaldy Septiyaningsih, Dwi Sharnuke Asrilsyak Surbakti, Afridayanti