Henry Pandia

Social commerce platforms increasingly serve as ecosystem orchestrators, coordinating technological infrastructures, financial systems, governance mechanisms, and algorithmic resource allocation. While prior research has predominantly focused on consumer behavior, limited attention has been given to merchant vulnerabilities arising from platform dependency. This study investigates operational vulnerabilities within the TikTok Shop ecosystem using 8993 negative merchant reviews collected from the Google Play Store. BERTopic, a transformer-based contextual topic modeling approach, was employed to identify latent vulnerability themes embedded in merchant complaint narratives. The results revealed 28 interpretable topics, which were aggregated into six higher-order vulnerability dimensions: Infrastructural Instability, Ecosystem Integration Vulnerability, Financial Vulnerability, Algorithmic Dependency, Coordination Breakdown, and Governance Asymmetry. Among these dimensions, Infrastructural Instability (13.59%) and Ecosystem Integration Vulnerability (13.44%) emerged as the most prominent sources of merchant dissatisfaction. The findings indicate that merchant vulnerability extends beyond isolated operational issues and is embedded within interconnected technological, financial, governance, algorithmic, and coordination structures. This study contributes to platform ecosystem research by providing empirical evidence and a structured interpretation of how platform-controlled resource orchestration may be associated with merchant vulnerability alongside value creation, while highlighting ecosystem integration as a significant source of risk during platform transformation.

Purpose of the Study: This study examines the relationships among Digital Self-Learning (DSL), Institutional Support (IS), Professional Development (PD), and Technology Integration (TI) among Indonesian teachers. Specifically, the study investigates how teachers' autonomous digital learning behavior contributes to classroom-level ICT integration beyond formal institutional and training mechanisms.Methodology: A quantitative cross-sectional survey was conducted involving 221 Indonesian in-service teachers. The study applied Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the data, examine relations among the proposed constructs, and explore the mechanisms underlying technology integration.Main Findings: Digital Self-Learning is the strongest predictor of both Professional Development and Technology Integration. Institutional Support significantly influences Digital Self-Learning but does not directly affect Technology Integration, suggesting that institutional conditions primarily contribute through enabling teachers' self-directed learning behavior. Professional Development further strengthens Technology Integration, whereas demographic variables such as age, gender, and educational level exert little influence. Although the proposed model confirmed substantial explanatory power, its out-of-sample projecting performance was limited. Therefore, the findings should be interpreted primarily from an explanatory rather than a predictive perspective.Novelty/Originality of this Study: The novelty of this study lies in its reconceptualization of ICT integration as a behaviorally driven process in which Digital Self-Learning functions as the central mechanism linking institutional conditions, professional growth, and classroom technology integration. The findings contribute to the growing discourse on teacher digital capability and offer practical insights for developing more adaptive and sustainable ICT integration strategies in educational settings.

Purpose of the Study: This study examines the relationships among Digital Self-Learning (DSL), Institutional Support (IS), Professional Development (PD), and Technology Integration (TI) among Indonesian teachers. Specifically, the study investigates how teachers' autonomous digital learning behavior contributes to classroom-level ICT integration beyond formal institutional and training mechanisms.Methodology: A quantitative cross-sectional survey was conducted involving 221 Indonesian in-service teachers. The study applied Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the data, examine relations among the proposed constructs, and explore the mechanisms underlying technology integration.Main Findings: Digital Self-Learning is the strongest predictor of both Professional Development and Technology Integration. Institutional Support significantly influences Digital Self-Learning but does not directly affect Technology Integration, suggesting that institutional conditions primarily contribute through enabling teachers' self-directed learning behavior. Professional Development further strengthens Technology Integration, whereas demographic variables such as age, gender, and educational level exert little influence. Although the proposed model confirmed substantial explanatory power, its out-of-sample projecting performance was limited. Therefore, the findings should be interpreted primarily from an explanatory rather than a predictive perspective.Novelty/Originality of this Study: The novelty of this study lies in its reconceptualization of ICT integration as a behaviorally driven process in which Digital Self-Learning functions as the central mechanism linking institutional conditions, professional growth, and classroom technology integration. The findings contribute to the growing discourse on teacher digital capability and offer practical insights for developing more adaptive and sustainable ICT integration strategies in educational settings.

The growing reliance on mobile banking has brought convenience to users but also heightened security risks, making the analysis of users' knowledge, attitudes, and behaviors toward information security incident reporting critical. This study investigates these dimensions within the context of mobile banking in Indonesia, aiming to bridge gaps between awareness and action. A survey involving 430 respondents was conducted, utilizing an instrument adapted from the Human Aspect of Information Security Questionnaire (HAIS-Q). Statistical analyses, including Cronbach's alpha, composite reliability, and Average Variance Extracted (AVE), were employed to validate the constructs. The results reveal that while respondents exhibit high levels of knowledge (mean = 4.21) and positive attitudes (mean = 4.20), their proactive reporting behaviors are relatively low (mean = 3.26). Path coefficient analysis indicates that knowledge strongly influences attitudes (0.722) but has a weaker direct impact on behaviors (0.162). Gender differences also play a significant role, affecting knowledge and behavior. These findings underscore the need for targeted interventions, including enhanced training, supportive reporting cultures, and robust monitoring mechanisms, to mitigate risks and improve incident reporting practices. Future research should explore psychological and technological factors to further enhance mobile banking security.

Indonesia memiliki produksi komoditas yang beragam dan melimpah dengan nilai ekspor yang luar biasa, khususnya pada bidang agrikultur. Banyaknya komoditas yang tersedia, membuat para eksportir maupun calon ekportir mengalami kesulitan menentukan komoditas yang mempunyai potensi untuk diekspor. Karena itu dibutuhkan sebuah sistem pendukung keputusan yang dapat merekomendasikan komoditas ekspor dengan cepat, tepat dan akurat. Penelitian ini bertujuan untuk menerapkan algoritme machine learning untuk menentukan komoditas yang disarankan untuk diekspor ke negara tertentu. Data pada penelitian ini diambil dari website Trademap International Trade Center (ITC) menggunakan HS Code (Harmonized System). Data yang digunakan merupakan data eksport tahun 2017-2021 yang terdiri dari data transaksi, negara pengimpor, komoditas, nilai impor, jumlah impor, dan pertumbuhan nilai. Data yang dipilih berasal dari beberapa jenis komuditas seperti: sayuran, buah-buahan, rempah-rempah, umbi-umbian, tanaman aromatik, serta jenis daun dan dahan. Menggunakan sebuah model dengan algoritme K-Nearest Neighbors (KNN), penelitian ini mengelompokkan sebuah komoditas ke dalam kelompok rekomendasi rendah, sedang dan tinggi. Hasil pengujian menunjukkan KNN memiliki nilai accuracy tertinggi yaitu pada parameter K=1 dengan nilai accuracy 85.71%. Nilai accuracy terendah terdapat pada parameter K=7 dan K=9 dengan nilai 78.57%. Peneliti berhasil menerapkan metode K-Nearest Neighbor untuk rekomendasi komoditas ekspor berdasarkan nilai yang diimpor, pertumbuhan nilai tahunan, dan jumlah yang diimpor. Penelitian dapat memberikan rekomendasi komoditas agrikultur yang bisa mempermudah para eksportir, maupun calon eksportir untuk memilih komoditas yang tepat untuk diekspor. Kata Kunci: Euclidean Distance, K-Nearest Neighbor, Komoditas Ekspor, Rekomendasi

In the digital economy era, small service business struggle to compete in a rapidly changing and dynamic market. Therefore, through digital transformation (DT), small service business seek to increase their competitive advantage, improve business performance, and achieve business growth. Having limited resources and capabilities, small service business must deal with several barriers and challenges. This study aims to discover the barriers, and the roles of government, for digital transformation in small service business. This study applied a qualitative approach involving semi-structured in-depth interviews with top management of small service business. Then, we employed the content analysis method to examine interview data and construct a model. This research reveals four main barriers to digital transformation in small service business: lack of funding, lack of digital capability, lack of human resources, and technical barriers. We found there are four government roles for supporting digital transformation in small service business: build a digital platform for small service business, promote mobile/digital payment, provide digital training, and build a digital collaboration ecosystem. Additionally, based on this study’s findings, a model for barriers and government support of digital transformation in small service business is presented. This study contributes to the conceptual framework and management implications in the digital transformation field. The study’s findings provide insights to practitioners and suggest that the government could alter the current policies and programs to support digital transformation in small service business.

Micro-enterprises are critical to the national economy in many countries, although they have many limitations. Therefore, governments have proposed many policies and programs to generate and enhance micro-enterprises’ growth to assure national economies’ growth and sustainability. This study evolves an index to evaluate growth in science and technological innovation among micro-enterprises that participated in collaborative innovation through a counselling program. The results not only define growth indicators through a literature review but also examine evidence of growth among 10 micro-enterprises through interviewing subjects located in various regions in Taiwan and related to different industries. This study uses multiple case study methods and data statistics to verify growth indicators; this reveals that micro-enterprises focusing on collaborative technological innovation demonstrated an increasing trend toward this study’s chosen growth indicators in a majority of cases. According to the survey results, nine indicators lead to positive growth. Finally, after establishing growth assessment indicators, the data collected from an empirical investigation proves the indicators’ credibility. The study then discusses the chosen cases’ experiences with growth and presents managerial implications.

Pengukuran kinerja pegawai merupakan sebuah pekerjaan yang sulit tetapi harus dilakukan jika organisasi ingin dapat mengelola dan mengembangkan kinerja para pegawainya. Karena itu, sebuah sistem informasi perlu dikembangkan untuk mendukung organisasi untuk merekam data kinerja pegawai secara efektif. Gereja Masehi Advent Hari Ketujuh (MAHK) Uni Indonesia Kawasan Barat (UIKB) merupakan sebuah organisasi yang mempunyai ratusan pegawai yang tersebar di delapan Konfrens/Daerah yang terpisah secara regional, membutuhkan sebuah sistem berbasis teknologi informasi yang dapat digunakan untuk mengumpulkan, merekam seluruh data aktivitas dan pelayanan dari Pendeta Jemaat sebagai pegawai dan Jemaat dimana pegawai tersebut ditempatkan. Sistem tersebut akan membantu manajemen puncak untuk mendapatkan informasi yang sesuai dan lengkap dalam proses pengambilan kebijakan dan kebutuhan serta promosi karir pegawai. Penelitian ini bertujuan untuk mengembangkan sebuah sistem yang memenuhi kebutuhan organisasi gereja MAHK di Uni Indonesia Bagian Barat menggunakan metode System Development Life Cycle (SDLC), metode yang umum digunakan dalam pengembangan sistem informasi menggunakan model Waterfall dengan tahapan-tahapan berikut: (1) Requirement Analysis, (2) Design (3) Implementation (4) Testing (5) Maintenance. Hasil dari penelitian ini adalah sebuah sistem informasi berbasis web yang dapat digunakan oleh Organisasi MAHK Uni Indonesia Kawasan Barat untuk merekam, menyimpan dan menyebarkan data dan informasi dari aktivitas, layanan dan kinerja dari Pendeta jemaat dan Jemaat yang tersebar di seluruh Indonesia Kawasan Barat.

Pada saat ini ojek merupakan salah satu transportasi alternatif yang banyak dipilih oleh kalangan masyarakat, hal ini dikarenakan ojek dapat menjadi solusi transportasi untuk menghindari kemacetan yang ada di tengah kota. Dalam perkembangan teknologi munculnya layanan baru berupa ojek online yang memberikan kemudahan kepada masyarakat dengan menggunakan aplikasi yang terintegrasi dengan perusahan, sehingga kemudahan yang ditawarkan oleh ojek online terkesan menenggelamkan keberadaaan ojek konvensional yang menimbulkan kerugian terhadap pendapatan mereka. Penelitian ini mencari hambatan yang di alami ojek konvensional untuk bergabung dengan ojek online. Tujuan dalam penelitian ini adalah untuk mengetahui apa saja barrier to adoption teknologi ojek online dikalangan para pengemudi ojek konvensional, dan mencari solusi mengurangi barrier to adoption teknologi ojek online dikalangan ojek konvensional. Adapun hambatan yang ditemukan dari 6 komponen yaitu, perilaku dan perilaku kepada penumpang, teknologi, finansial, kelengkapan berkendara, informasi dan paguyuban. Keenam komponen tersebut diukur terhadap 36 responden di wilayah Bandung dan sekitarnya, dimana responden adalah pengemudi ojek konvensional. Data dikumpulkan melalui wawancara dan penyebaran kuesioner, untuk data yang diolah. Penelitian ini adalah penelitian deskriptif yang menggambarkan objek atau peristiwa yang bertujuan untuk mengetahui keadaan yang terjadi pada saat sekarang untuk memperoleh gambaran serta solusi untuk barrier business yang terjadi pada ojek konvensional. Penulis mengambil kesimpulan bahwa dari semua komponen kuesioner, payuguban adalah hambatan yang paling besar untuk pengemudi ojek konvensional untuk mengadopsi teknologi ojek online, dimana mereka masih nyaman menunggu penumpang di pangkalan karena kebersamaan terhadap sesama pengemudi dianggap memperkecil persaingan dalam mencari penumpang, berdasarkan kesimpulan yang diperoleh dari hasil data, maka penulis memberi saran untuk mengurangi hambatan mengadopsi aplikasi online bahwa pendidikan adalah faktor yang cukup penting untuk meningkatkan kemajuan berfikir dari masyarakat dan salah satu modal untuk mempunyai suatu pekerjaan yang produktif dan efisien.