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Innovation Performance Measurement in Entrepreneurial Business: A Comparative Study between Start-ups and More Established Enterprises Eri Mardiani; A.Ratna Sari Dewi; Feliks Anggia Binsar Kristian Panjaitan; Unika Oktaviani Damau
West Science Journal Economic and Entrepreneurship Vol. 1 No. 10 (2023): West Science Journal Economic and Entrepreneurship
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsjee.v1i10.302

Innovation performance measurement is an important aspect of understanding and improving entrepreneurial success, which has implications for economic development, organizational growth, and community welfare. This study uses comprehensive bibliometric analysis to systematically review and analyze the literature on innovation performance measurement in entrepreneurial business. The research covers startups and established companies, aiming to uncover key themes, influential works, and an ever-evolving research landscape in this dynamic field. His methodological approach integrates bibliometric analysis and visualization using VOSviewer, which provides a holistic view of the intellectual structure in the domain. Key findings include the identification of thematic groups, influential authors, and important works, which provide valuable insights for academics, practitioners, and policymakers involved in fostering innovation and entrepreneurship.

B2B Digital Marketing and ROI Measurement: Challenges and Opportunities in the Business-to-Business Industry for MSMEs in Indonesia Eri Mardiani; Eva Yuniarti Utami; Muhammad Umer Farooq Mujahid
West Science Interdisciplinary Studies Vol. 1 No. 09 (2023): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v1i09.249

In order to maintain growth and competitiveness in the modern business environment, digital marketing must be strategically integrated, especially for Micro, Small, and Medium-Sized Enterprises (MSMEs) that conduct business-to-business (B2B) transactions. This study looks into the potential and difficulties that come with B2B digital marketing as well as how to measure return on investment (ROI) for MSMEs in Indonesia. Surveys and in-depth interviews were used in a mixed-methods approach to collect both quantitative and qualitative data. The results show that MSMEs have widely adopted digital marketing tactics, with social media and content marketing being the most popular. There are still issues like tight budgets, hard ROI calculations, and fierce market competition. The report makes actionable suggestions, such as group marketing campaigns, the creation of uniform ROI measurements, and a focus on innovation via emerging technologies and niche targeting. The insights provide practitioners, policymakers, and industry stakeholders with practical advice for improving the knowledge of the dynamics in B2B digital marketing for MSMEs in Indonesia.

Improving Trust and Accountability in AI Systems through Technological Era Advancement for Decision Support in Indonesian Manufacturing Companies Eri Mardiani; Loso Judijanto; Arief Yanto Rukmana
West Science Interdisciplinary Studies Vol. 1 No. 10 (2023): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v1i10.301

This study explores how technological developments in Artificial Intelligence (AI) decision support systems within Indonesian manufacturing organizations interact with the intricate dynamics of trust, accountability, and technology. The study employed a cross-sectional quantitative research approach to gather responses from a representative sample of professionals spanning different organizational levels, age groups, and functions. The results show that there is a high degree of trust in AI systems, which is largely impacted by dependability and transparency. Strong perceived accountability frameworks encourage prudent decision-making. Technological developments have a big impact on trust and responsibility, especially in Explainable AI and bias prevention. A nuanced interpretation is ensured by the study's demographic analysis, which provides practitioners and policymakers with practical insights to support ethical AI integration in Indonesia's industrial sector.

Analisis Prediksi Pendapatan Penduduk dengan Metode K-Nearest Neighbor, Decision Tree, Naive Bayes, Ensemble Methods, dan Linear Regression Eri Mardiani; Nur Rahmansyah; Endah Tri Esti Handayani; Sari Ningsih; Deny Hidayatullah; Dhieka Avrilia Lantana; Yuni Latifah; Alica Dwi Fahira; Keysha Belynda Tyva Panggabean; Imelta Natalia Ginting
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.v3i4.4121

Data mining bermula dari peningkatan data yang cukup pesat dilihat dari segi volume serta variasi data yang dihasilkan oleh berbagai sumber, dan jumlahnya yang sangat besar, serta kompleksitasnya data hingga pembuatannya yang cepat. Dengan data bisa menghasilkan prediksi yang membantu pemerintah dalam mengambil keputusan dan kebijakan di masa mendatang. Selain itu prediksi dapat membantu pemerintah dalam perencanaan kegiatan yang akan dilakukan untuk mencapai tujuan, karena prediksi ini dapat memberikan output terbaik sehingga diharapkan resiko kesalahan yang disebabkan oleh kesalahan perencanaan dapat ditekan seminimal mungkin. Prediksi biasanya digunakan untuk menemukan informasi dari sejumlah data yang besar sehingga diperlukan data mining. Data mining dapat digunakan untuk menggali informasi dari data yang besar sehingga didapatkan informasi yang dapat digunakan dalam memprediksi sesuatu. Dalam data mining terdapat banyak teknik dalam pengerjaannya, untuk menemukan pola atau informasi yang tersembunyi diantaranya adalah Klasterisasi (clustering), Regresi (regression), Asosiasi (association), dan Klasifikasi (classification)

Sistem Informasi Penjualan Pada Jeeni Shop Eri Mardiani; Ferdan Akbar Ramadhan
Innovative: Journal Of Social Science Research Vol. 3 No. 5 (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.v3i5.4741

Jeeni Shop merupakan toko yang menyediakan berbagai macam kebutuhan elektronik dan fashion. Umumnya, JeEni Shop lebih mengutamakan kebutuhan untuk para remaja hingga dewasa. Saat ini sistem di JeEni Shop untuk melakukan promosi barang masih menggunakan facebook dan instagram tidak adanya penjualan jarak jauh yang bisa mempermudah perusahaan dalam memperluas wilayah pemasaran. JeEni Shop merupakan toko yang menerapkan model bisnis B2C (Business to Customer), dan konsumen harus datang sendiri ke lokasi dan pembayaran dilakukan secara tunai. Hal ini tentu menyulitkan para calon konsumen dari dalam dan luar kota, dikarenakan harus mengeluarkan biaya untuk mengunjungi JeEni Shop. Sehingga calon konsumen membutuhkan layanan pembelian dan pembayaran secara online dan transfer melalui rekening. Melalui pemanfaatan sistem informasi website ini, diharapkan mampu meningkatkan kebutuhan akan data dan informasi kepada calon konsumen JeEni Shop, dimana calon konsumen dapat melakukan pertukaran data dan informasi hingga transaksi tentang segala produk yang ada pada JeEni Shop

Analyzing the Global Visibility and Influence of Social Enterprise Research: A Bibliometric Review of Citation, International Collaboration, and Cross-Cultural Perspectives Eri Mardiani; Waqiah; Siska Jeanete Saununu; Benny Novico Zani
West Science Interdisciplinary Studies Vol. 1 No. 08 (2023): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v1i08.182

The literature review highlights the growing research on social enterprises, exploring key concepts such as double bottom line and social impact assessment. While there has been progress, there are still gaps in understanding the global visibility and influence of social enterprise research. This research method fills the gap by using bibliometric analysis as a quantitative research method. The methodology section presents a comprehensive approach to data collection, extraction, and analysis. Relevant databases and sources are identified, and inclusion/exclusion criteria for publication are established. Keywords and search strategies are used to collect data on authorship, year of publication, journal, and number of citations. Bibliometric analysis techniques, including citation analysis and network analysis, are used to analyze data and uncover patterns and trends. The results and discussion sections present the findings of the bibliometric analysis. Citation patterns, influential works, and authors are identified, thus providing insight into the intellectual structure of the field. International collaboration trends and cross-cultural perspectives are analysed, highlighting global research networks and the application of social enterprise concepts across multiple contexts.

Mapping the Landscape of Artificial Intelligence Research: A Bibliometric Approach Eri Mardiani; Muhammad Subhan Iswahyudi
West Science Interdisciplinary Studies Vol. 1 No. 08 (2023): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v1i08.183

This research study employs a comprehensive bibliometric approach, enhanced by the utilization of VOS viewer, to map the expansive landscape of artificial intelligence (AI) research. Through the meticulous collection, pre-processing, and analysis of a diverse dataset, this study uncovers the multifaceted dimensions that define AI research. The analysis encompasses publication trends, authorship dynamics, citation patterns, and emergent research themes. The integration of VOS viewer’s visualization capabilities enriches the exploration by offering intuitive representations of collaboration networks, citation maps, and thematic clusters. The results highlight the growth trajectory of AI research, the collaborative networks among researchers and institutions, the influence of seminal works, and the emergence of thematic trends. Moreover, the study contextualizes the findings, discussing their implications for interdisciplinary collaboration, ethical considerations, and the societal impact of AI research. Ultimately, this research contributes to a comprehensive understanding of AI research dynamics, guiding future exploration, collaboration, and innovation within this rapidly evolving domain.

B2B Digital Marketing and ROI Measurement: Challenges and Opportunities in the Business-to-Business Industry for MSMEs in Indonesia Eri Mardiani; Eva Yuniarti Utami; Muhammad Umer Farooq Mujahid
West Science Interdisciplinary Studies Vol. 1 No. 09 (2023): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v1i09.249

In order to maintain growth and competitiveness in the modern business environment, digital marketing must be strategically integrated, especially for Micro, Small, and Medium-Sized Enterprises (MSMEs) that conduct business-to-business (B2B) transactions. This study looks into the potential and difficulties that come with B2B digital marketing as well as how to measure return on investment (ROI) for MSMEs in Indonesia. Surveys and in-depth interviews were used in a mixed-methods approach to collect both quantitative and qualitative data. The results show that MSMEs have widely adopted digital marketing tactics, with social media and content marketing being the most popular. There are still issues like tight budgets, hard ROI calculations, and fierce market competition. The report makes actionable suggestions, such as group marketing campaigns, the creation of uniform ROI measurements, and a focus on innovation via emerging technologies and niche targeting. The insights provide practitioners, policymakers, and industry stakeholders with practical advice for improving the knowledge of the dynamics in B2B digital marketing for MSMEs in Indonesia.

Improving Trust and Accountability in AI Systems through Technological Era Advancement for Decision Support in Indonesian Manufacturing Companies Eri Mardiani; Loso Judijanto; Arief Yanto Rukmana
West Science Interdisciplinary Studies Vol. 1 No. 10 (2023): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v1i10.301

This study explores how technological developments in Artificial Intelligence (AI) decision support systems within Indonesian manufacturing organizations interact with the intricate dynamics of trust, accountability, and technology. The study employed a cross-sectional quantitative research approach to gather responses from a representative sample of professionals spanning different organizational levels, age groups, and functions. The results show that there is a high degree of trust in AI systems, which is largely impacted by dependability and transparency. Strong perceived accountability frameworks encourage prudent decision-making. Technological developments have a big impact on trust and responsibility, especially in Explainable AI and bias prevention. A nuanced interpretation is ensured by the study's demographic analysis, which provides practitioners and policymakers with practical insights to support ethical AI integration in Indonesia's industrial sector.

Penerapan Algoritma Supervised Learning untuk Klasifikasi Data Music Listening: Application of Supervised Learning Algorithm for Music Listening Data Classification Eri Mardiani; Nur Rahmansyah; Ira Kurniati; Andy Setiawan; Diah Widiastuti; Muhammad Ridwan; Muhammad Zidan Rosyid; Ari Febriansyah
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.879

Perkembangan teknologi informasi semakin pesat hingga saat ini terus dikembangkan teknologi-teknologi terbaru, penggunaan data sebagai pengolahan kini semakin banyak diterapkan pada berbagai bidang, dengan penggunaan data dapat dilakukan perkembangan teknologi yang dapat meningkatkankan kualitas dan efisiensi, pengolahan data dapat diterapkan di semua bidang dan salah satunya adalah di bidang musik. Musik sudah menjadi bagian dari kehidupan manusia sehari-hari. Sudah banyak media-media yang menyajikan berbagai macam lagu dengan genre yang beragam pula mulai dari Pop, Jazz, Rock, R&B, dan genre-genre lainnya. Dengan menggunakan data mining untuk mengolah data maupun menganalisis data-data musik kita dapat memprediksi keanekaragaman preferensi mendengarkan musik dan dengan menggunakan tools aplikasi Orange Data Mining dapat membantu masyarakat untuk mengetahui musik apa saja yang diminat dengan memprediksi melalui beberapa metode dalam tools orange, dengan Algoritma Naive Bayes memiliki tingkat akurasi yang lebih baik.

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