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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Pendidikan Teknologi dan Kejuruan Techno.Com: Jurnal Teknologi Informasi Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Penelitian Ekonomi dan Bisnis Journal of Educational Science and Technology Scientific Journal of Informatics ANDHARUPA CESS (Journal of Computer Engineering, System and Science) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan SISFOTENIKA Jurnal Administrasi Publik : Public Administration Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Teknoinfo Technomedia Journal Journal of Education Technology Aptisi Transactions on Management JTP - Jurnal Teknologi Pendidikan Aptisi Transactions on Technopreneurship (ATT) CCIT (Creative Communication and Innovative Technology) Journal Journal of Maternity Care and Reproductive Health ADI Journal on Recent Innovation (AJRI) International Journal of Marine Engineering Innovation and Research ADI Bisnis Digital Interdisiplin (ABDI Jurnal) Journal of Applied Data Sciences IAIC Transactions on Sustainable Digital Innovation (ITSDI) International Journal of Engineering, Science and Information Technology ADI Pengabdian kepada Masyarakat Jurnal (ADIMAS Jurnal) MAVIB Journal : Jurnal Multimedia Audio Visual and Broadcasting Indonesian Journal Accounting (IJAcc) International journal of education and learning International Journal of Cyber and IT Service Management (IJCITSM) Universal Raharja Community (URNITY Journal) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi International Transactions on Education Technology (ITEE) Blockchain Frontier Technology (BFRONT) International Transactions on Artificial Intelligence (ITALIC) Jurnal ilmiah teknologi informasi Asia Journal of Computer Science and Technology Application
Ninda Lutfiani
Universitas Raharja
Religion Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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Digital Green Strategies Driving Sustainable Competitive Advantage in Agripreneurial SMEs Andriyansah Andriyansah; Fatia Fatimah; Venty Fitriany Nurunisa; Ninda Lutfiani; Carlos Perez
Aptisi Transactions On Technopreneurship (ATT) Vol 8 No 3 (2026): November
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v8i3.858

Abstract

Achieving Sustainable Competitive Advantage (SCA) for green agricultural products in demanding international markets, particularly Europe, requires strategic integration beyond conventional marketing approaches. Although green branding and digital marketing have been widely recognized, the synergistic mechanism through which digital strategies, green value propositions, and market penetration collectively strengthen SCA remains underexplored. This study aims to develop and validate an integrated model that explains how Digital Traffic Management, Green Product Value, and Market Penetration contribute to SCA while supporting sustainability-oriented business growth. This study employs Structural Equation Modeling (SEM) because it provides stronger analytical robustness than conventional regression through latent variable estimation, construct validation, and comprehensive goodness-of-fit evaluation. The \textbf{findings} show that Market Penetration is the strongest predictor of SCA (β = 0.44), indicating that market expansion through digital channels significantly enhances long-term competitiveness. The results also reveal a positive reinforcement cycle between Green Product Value and SCA, demonstrating a virtuous loop of continuous improvement, digital adaptability, and green competitiveness. Furthermore, Market Penetration and Digital Traffic Management support SDG 8, SDG 9, and SDG 17 by encouraging sustainable economic growth, technology-based innovation, collaborative business ecosystems, and stronger digital partnerships for SMEs. This study provides a robust empirical foundation and strategic blueprint for SMEs, policymakers, and digital marketers to enter and grow in international markets while strengthening sustainable competitiveness and contributing meaningfully to a greener future.
Improving Recommender Systems using Hybrid Techniques of Collaborative Filtering and Content-Based Filtering Riya Widayanti; Mochamad Heru Riza Chakim; Chandra Lukita; Untung Rahardja; Ninda Lutfiani
Journal of Applied Data Sciences Vol 4, No 3: SEPTEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i3.115

Abstract

This innovative study introduces a novel enhancement to recommendation systems through a synergistic integration of Collaborative Filtering (CF) and Content-Based Filtering (CBF) techniques, termed the hybrid CF-CBF approach. By seamlessly amalgamating the strengths of CF's user interaction insights and CBF's content analysis prowess, this approach pioneers a more refined and personalized recommendation paradigm. The research encompassed meticulous phases, including comprehensive data acquisition, efficient storage management, meticulous data refinement, and the skillful application of CF and CBF methodologies. The findings markedly highlight the prowess of the hybrid approach in generating recommendations that exhibit enhanced diversity and precision, surpassing the outcomes obtained from either technique in isolation. Remarkably, the hybrid CF-CBF approach effectively addresses the inherent shortcomings of individual methods, such as CF's vulnerability to the "cold start" problem and CBF's limitation in fostering recommendation diversity. By fostering a harmonious synergy, this novel approach transcends these limitations and provides a holistic solution. Furthermore, the interplay of CF and CBF augments the recommender system's cognitive grasp of user preferences, subsequently enriching the quality of recommendations provided. In conclusion, this research stands as a pioneering contribution to the evolution of recommendation systems by championing the hybrid CF-CBF approach. By ingeniously fusing two distinct techniques, the study engenders a breakthrough in personalized recommendations, thereby propelling the advancement of more sophisticated and effective recommendation systems.
Pengabdian Masyarakat dalam Pemberdayaan UMKM dengan Melakukan Implementasi Website Menggunakan Plugin Elementor Sebagai Media Promosi Danny Manongga; Untung Rahardja; Irwan Sembiring; Ninda Lutfiani; Ahmad Bayu Yadila
ADI Pengabdian Kepada Masyarakat Vol 3 No 1 (2022): ADI Pengabdian Kepada Masyarakat
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/adimas.v3i1.810

Abstract

Saat ini, teknologi informasi banyak digunakan di hampir semua bidang, termasuk yang berkaitan dengan pendidikan, perbankan, pemerintahan, dan pariwisata. e-Commerce adalah penggunaan teknologi informasi untuk mendukung aktivitas pembelian, penjualan, dan promosi produk. Website dapat dibangun dan diimplementasikan oleh UMKM dengan modal yang sesuai. Kemampuan situs web untuk memberikan deskripsi rinci tentang UMKM dan produk adalah salah satu keunggulannya. Di tengah pandemi Covid-19, kegiatan pengabdian masyarakat ini berupaya membantu usaha mikro, kecil, dan menengah (UMKM) Ola Alika Shop dengan membuat website sebagai sarana teknik pengembangan pemasaran produk. Tangerang menjadi lokasi proyek pengabdian masyarakat ini. Karyawan dan pemilik bisnis termasuk di antara mereka yang ambil bagian dari UMKM Ola Alika Shop. Strategi penulis diawali dengan wawancara dan survey bisnis untuk mengetahui keunikan UMKM yang akan dijadikan tagline, mencari konten yang sesuai, seperti foto dan video, untuk meningkatkan branding, mengerjakan dan mempresentasikan situs web, serta mengusulkan saran lain untuk menyempurnakan situs web, yang akan mereka tangani secara mandiri. Hasil akhirnya adalah terciptanya platform berupa website untuk media promosi, yang diproyeksikan dapat membantu UMKM meningkatkan penjualan dan tetap menjalankan usahanya dalam menghadapi pandemi Covid-19.
Advancing Startup Ecosystems Through AI-Driven Matchmaking: A Comprehensive Bibliometric Analysis Ninda Lutfiani; Sutarto Wijono; Untung Rahardja; Hindriyanto Dwi Purnomo
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1095

Abstract

This study investigates the integration of AI in streamlining the alignment process between startups and potential collaborators and partners, particularly in the Indonesian startup ecosystem. The motivation behind this research lies in the gaps and challenges startups face in efficiently connecting with suitable partners or investors. We employed a bibliometric analysis approach. This study sourced data from Scopus, analysing 515 articles and 59,412 citations published from 2018 to 2023. Key findings provide insights into the predominant role of AI technologies, notably machine learning methods like deep learning and data mining, and the significance of recommendation systems that incorporate collaborative filtering. Furthermore, the results underscore the increasing importance of AI as an indispensable tool in the startup landscape, enhancing the efficiency and productivity of collaborations. We assessed publications from several countries, authors, and citations through the bibliometric measures to comprehensively understand the current trends and trajectories. The study concludes by recognising the transformative potential of AI in fostering tighter and more efficient alliances within the startup ecosystem, laying the groundwork for future research into refining AI-driven collaborative processes.
A Machine Learning Framework for Startup Investor Matchmaking to Enhance Sustainable Innovation Ninda Lutfiani; Mochamad Heru Riza Chakim; Sutarto Wijono; Untung Rahardja; Hindriyanto Dwi Purnomo; Agung Rizky
Aptisi Transactions On Technopreneurship (ATT) Vol 8 No 3 (2026): November
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v8i3.842

Abstract

Accelerating sustainable innovation is a critical mandate for emerging economies. However, the high failure rate of startups, primarily driven by inefficient founder-investor alignment and information asymmetry, remains a systemic obstacle. In Indonesia, this challenge is further exacerbated by traditional matchmaking processes that rely on social networks, often excluding high-potential Micro, Small, and Medium Enterprises (MSMEs). This study introduces and validates Artificial Intelligence Machine Learning Excellence Economy (AIMEE), a novel hybrid matchmaking framework designed to democratize access to capital and accelerate the twin transition of digitalization and sustainability. Utilizing a pilot dataset of 94 startup-investor pairs from five provinces in Java, we developed a policy-aware algorithm that integrates financial metrics with five entrepreneurial dimensions, including Sovereignty Scores based on alignment with the Sustainable Development Goals (SDGs). The framework employs a lightweight neural network optimized with SMOTE (Synthetic Minority Over-sampling Technique) to address data scarcity and class imbalance. Empirical validation shows that AIMEE achieves an F1-Score of 0.83, Recall of 0.82, and ROC-AUC of 0.89, significantly outperforming traditional Random Forest baselines by 12%. The model effectively identifies patterns of potential collaboration, overcoming the limitations of rigid networking. These findings confirm that AI-driven matchmaking can serve as a robust digital infrastructure to operationalize the Asta Cita vision and SDG 9, contributing to a more inclusive, resilient, and competitive innovation ecosystem in Indonesia.
Co-Authors AA Sudharmawan, AA Achani Rahmania Az Zahra Achmad Nizar Hidayanto Adam Faturahman Ade Iriani Adi Setiawan Agung Rizky Agung Rizky Ahmad Bayu Yadila Ajeng Toyibah, Restu Alfian Dimas Ahsanul Rizki Ahmad Ali Djamhuri Amelia, Sindy Aminuyati Amsyar, Izwan Anderson, Evelyn Andriyansah Andriyansah . Anggy Giri Prawiyogi Ankur Singh Anwar, Aang Solahudin Ariesya Aprillia Arif Andika Arini Dwi Lestari Arini Dwi Lestari Astriyani, Erna Atika Sari, Apriani Aulia Anjani, Sheila Bintoro, B. P. Kusumo Carlos Perez Chandra Lukita Choiriyah Citra Yulian Kristanti Cristhopher, Ethan Daelami Ahmad Danang, Danang Danny Manongga Desy Apriani Dhea Ayunanda Astrieta Djatmiko, Budi Edward Boris P Manurung Edward Boris P Manurung Efa Ayu Nabila Efa Ayu Nabila Eka Dian Astuti Eka Purnama Harahap Endah Nirmala Dewi Erick Febriyanto Ersa Aura Natasya Fadhilah, Andi Farida Agustin, Farida Fatia Fatimah Faturahman, Adam Fauziah, Zaleha Fauziyah, Nida Febiani, Dyah Ayu Febrianto, Kurnia Rizky Fernando Fhia Amelia Firman Hanafi Fitra Putri Oganda Fitria Marwati Suryaman Ginting Munthe, Rusli Harahap, Eka Purnama HARYANTO Hasta Sulistyaningrum Hendra Kusumah Hindriyanto Dwi Purnomo Ida Farida Indri Handayani Indri Handayani Indri Handayani, Indri Irwan Sembiring Isabella Yaumil Annisa Ita Sari Perbina Manik Iwan Setyawan Julianingsih, Dwi Juniar, Hega Lutfilah Juniar, Hega Lutfilah Juniar Kanon Mommsen Wongkar Khasanah, Kartika Trissanti Khoirunisa, Alfiah Kristanti, Citra Yulian Latifah, Haznah Leli Lestari Santoso, Nuke Puji Lidya Wijayanti Manik, Ita Sari Perbina Mardiana Mardiana Mardiansyah, Aditya Maria Saraswati Marviola Hardini Maulahikmah Galinium Meria, Lista Millah, Shofiyul Moch Sandi Alpansuri Mochamad Heru Riza Chakim Mochamad Heru Riza Chakim Mochamad Sandi Alpansuri Mohammed Iftequar Ali Moyo, Kgomotso Muhamad Yusup Muhammad Fachri Sholahuddin Muhammad Rehan Anwar Muhammad Suzaki Zahran Muhammad Suzaki Zahran Mumen, Md. Abdul Muttaqin Choiri Nabila, Efa Ayu Natalia, Ester Ananda Natalie Bibils Noah Rangi Noah Rangi Novriyanti, Bunga Nuke Puji Lestari Santoso Nur Aeni Trisna Lestari Nuryani Nuryani Padeli Po Abas Sunarya Pratikto, Hendro pratiwi, Dinda suci Pratomo Cahyo Kurniawan Priandito Primasatria Edastama, Primasatria Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Rakhmansyah, Mohamad Ramadan, Ahmad Resti Rahmawati Retno Setyaningrum Richard Evans Ridan Ahsani Te Awhina Ridhuan Ahsanitaqwim Rifqa Nabila Muti Riskhandini, Dinda Putri Riya Widayanti Rizky, Agung Rochmawati Rochmawati Saga, Rivialdo Sultan Santoso, Nuke Puji Lestari Sausan Raihana Putri Junaedi Septian, Rafly Ananda Dwi Septiani, Nanda Shepard, Anjani Shofiyul Millah Sigit Anggoro Siti Nurindah Sari Sri Mariyati, Wayan Sri Watini Sriyatin S Sudaryono Sudaryono Sulistiawati Sulistiawati Sulistio Sulistio Sunarjo, Richard Andre Suryaman, Fitria Marwati Suryari Purnama Sutarto Wijono Sutisna, Felix Syaidina, Musidiansyah Otto Tarisya Ramadhan Tatik Mariyanti, Tatik Tessa Handra Tessa Handra Tsara Ayuninggati Tuti Nurhaeni Tuti Nurhaeni Untung Rahardja Untung Raharja Untung Raharja Van Persie, Iky Venty Fitriany Nurunisa Viedya Wildan Wahyu Ningsih Wahyu Setya Wardana Widhy Setyowati Widya Febriani Wijayanti, Lidya Winanti Yolandari, Aulia Yusuf, Natasya Aprila Zahran, Muhammad Suzaki Zakaria, Noor Azura