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"Frequently Asked Questions (FAQs) adalah dokumen (seperti di situs web) yang memberikan jawaban atas daftar pertanyaan umum yang mungkin ditanyakan pengguna mengenai subjek tertentu. Tokopedia adalah salah satu website e-commerce terbesar di Indonesia. Penelitian ini menyajikan konstruksi Knowledge Graph (KG) dengan data dari halaman FAQ Tokopedia. Penelitian ini mendemokan use cases yang memanfaatkan FAQ KG tersebut. Pendekatan penelitian ini melibatkan metode top- down dalam konstruksi KG, yang meliputi web scraping, part-of-speech (POS) tagging untuk mendapatkan kata benda, kata sifat, dan kata kerja dari FAQ, pembuatan ontologi kata kerja, dan pembuatan KG berbasiskan Resource Description Framework (RDF). Temuan-temuan utama mengungkapkan kemampuan baru seperti kueri untuk mencari FAQ berdasarkan suatu kata kerja dan sinonimnya, serta wawasan yang diperoleh dengan exploratory data analysis dan menggunakan kueri SPARQL. Temuan ini bisa meningkatkan layanan FAQ untuk e-commerce melalui pembuatan KG.

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Frequently Asked Questions (FAQs) are documents (such as on a website) that give answers to a list of common questions that users may ask about a certain topic. Tokopedia is one of the largest e-commerce websites in Indonesia. This research presents the construction of a Knowledge Graph (KG) with data from Tokopedia's Frequently Asked Questions (FAQs) page. This research demonstrates use cases that utilize the FAQ KG. The research approach involves a top-down method in KG construction, which includes web scraping, part-of-speech (POS) tagging to obtain nouns, adjectives, and verbs from the FAQ, verb ontology generation, and Resource Description Framework (RDF)-based KG generation. The findings reveal new capabilities such as queries to search FAQs based on a verb and its synonyms, as well as insights gained by exploratory data analysis (EDA) and using SPARQL queries. These findings can improve FAQ services for e-commerce through KG generation."

"More and more eBay sellers are gradually turning their entrepreneurial efforts on the world's foremost online auction site into serious business enterprises. Whether they see their eBay business as a modest addition to their revenue or a potentially fulltime venture, they need expert advice on how to do it right. Filled with in-depth, easily-understood answers readers can flip to, as-needed, this is a one-of-a-kind resource for any eBay seller."

"Performa sistem tanya jawab berbasis Knowledge Graph (KGQA) sangat dipengaruhi oleh dua tugas, yaitu deteksi entitas dan penautan entitas dan relasi. Daftar entitas dan relasi yang dihasilkan oleh tugas ini akan digunakan oleh konstruktor kueri untuk memperoleh data yang benar dari Knowledge Graph (KG). Telah ada beberapa penelitian terkait kedua tugas ini. Namun, pada kedua tugas ini masih terdapat beberapa isu. Terdapat tiga isu utama pada tugas deteksi entitas. Pertama, tidak semua entitas yang ada di dalam pertanyaan digunakan di dalam kueri. Kedua, sebuah pertanyaan menggunakan entitas, tetapi tidak dikenali oleh Named Entity Recognizer (NER), dan ketiga adalah tidak diketahuinya posisi entitas di dalam Triple. Untuk mengatasi isu pada tugas deteksi entitas ini penulis mengusulkan sebuah pendekatan pola berbasis posisi. Pendekatan ini memanfaatkan pola dari sebuah pertanyaan untuk memprediksi di mana posisi entitas berada di dalam Triple. Sementara itu, pada tugas penautan entitas dan relasi, terdapat dua isu utama yaitu isu kesenjangan leksikal dan ambiguitas entitas. Untuk mengatasi isu-isu tersebut, penulis mengusulkan sebuah pendekatan penautan entitas dan relasi dengan menggunakan konsep pencarian bertahap. Dalam pendekatan ini, prediksi relasi dilakukan sebelum penautan entitas. Selanjutnya, penautan entitas dilakukan secara bertahap dimulai dengan pencarian berbasis teks sampai dengan pencarian berbasis vektor. Hasil evaluasi menunjukkan bahwa pendekatan pola berbasis posisi untuk deteksi entitas memperoleh nilai akurasi lebih baik dari Falcon 2.0, yaitu sebesar 98,91% dan 89,52% pada SimpleQuestions dan LC-QuAD 2.0. Pendekatan pencarian bertahap untuk penautan entitas dan relasi juga menunjukkan akurasi yang lebih baik dari Falcon 2.0. Masing-masing 89,87% dan 74,83% pada SimpleQuestions dan LC-QuAD 2.0 untuk penautan entitas dan 91,74% dan 61,96% pada SimpleQuestions dan LC-QuAD 2.0 untuk penautan relasi.

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The performance of knowledge graph question answering (KGQA) systems is significantly influenced by entity detection tasks and entity and relation linking tasks. The correct entities and relations output by the tasks is a must to retrieve the correct data from a KG. Some works have been proposed for the tasks. However, the tasks still have challenging issues. There are three main issues with the entity detection task. First, a question may contain an entity(s) that is/are not used in the query. Second, a question uses an unrecognizable entity(s) by Named Entity Recognizer (NER). The last one is where the position of an entity(s) is unknown in the Triple. To address the issues, we propose an approach called the position-based pattern. While the entity and relation linking task have two main issues, namely, lexical gap and entity ambiguity. To overcome the issues, we propose an approach to gradually link entities and relations. Our proposed approach predicts the relation(s) used by the question first and then gradually searches the proper entity(s) against the entity(s) of the KG by using text-based searching and vector-based searching approach. The position-based pattern outperforms the baselines on SimpleQuestions and LC-QuAD 2.0 datasets, namely 98.91% and 89.52% for SimpleQuestions and LC-QuAD 2.0, respectively. For the entity linking task, using a gradual searching approach reaches 89.87% and 74.83% for SimpleQuestions and LC-QuAD 2.0, respectively, on average. This approach outperforms the baseline for relation linking, namely, 91.74% and 61.96% for SimpleQuestions and Lc-QuAD 2.0, respectively."

""From knowledge of the Qur'an and Sharia'a law, to new and old Islamic financial concepts, Islamic terms and financial instruments and services, this book covers all the key areas that practitioners need to know in order to understand Islamic finance. The book also features overviews of the product and services, illustrative examples of how these work in practice, and a question and answer section for readers seeking to test and build their knowledge of the area." -- back cover.Contents1. The Islamic banking timeline (1890-2010)2. Frequently asked questions3. Why is interest (riba) forbidden to Muslims?4. Derivatives and Islamic finance5. How do you establish an Islamic bank?6. Islamic banking and finance qualifications7. How much Arabic do you need to know to work in the industry?8. Test your knowledge9. Further readingApp. Answers to Chapter 8 test your knowledge.Notes"

"ABSTRAKDi tengah persaingan e-commerce di Indonesia yang semakin ketat, membuat perusahaan e-commerce dituntut dapat bersaing dalam memberikan nilai tambah layanan bagi pelanggannya agar dapat meningkatkan jumlah pelanggan dan disertai dengan angka pemesanan yang meningkat juga. Hal ini juga berlaku bagi e-commerce dalam industri pariwisata, salah satunya Triptrus. Salah satu tantangan yang dihadapi Triptrus adalah untuk meningkatkan angka conversion rate. Salah satu cara peningkatan angka conversion rate adalah pemberian fitur rekomendasi produk. Penelitian ini bertujuan untuk mencari metode yang dapat memberikan rekomendasi terbaik yang pada akhirnya bertujuan agar dapat meningkatkan angka conversion rate dari Triptrus yang masih rendah. Pada penelitian ini dilakukan pencarian metode rekomendasi yang terbaik disesuaikan dengan data internal yang dimiliki Triptrus. Penelitian ini bermula dari pengumpulan data internal untuk kemudian dibangum model rekomendasi menggunakan beberapa metode. Metode yang digunakan dalam penelitian ini diantaranya collaborative filtering, content based filtering, Hybrid Filtering dan stochastic gradient descent. Berdasarkan hasil penelitian, metode collaborative filtering, content based, dan hybrid kurang mampu memberikan rekomendasi yang cukup baik terhadap data Triptrus. Hasil terbaik dari ketiga metode ini didapatkan metode hybrid dengan nilai error RMSE 0.71. Di sisi lain algoritma stochastic gradient descent dapat memberikan rekomendasi paling baik dan memberikan ratio error RMSE paling kecil yaitu 0.11. Hasil penelitian ini adalah model rekomendasi produk yang dapat memberikan rekomendasi terbaik berdasarkan data internal Triptrus yaitu model yang dihasilkan menggunakan metode stochastic gradient descent.

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ABSTRACTIndonesian e commerce markets are getting more tight. This condition forces e commerce companies to provide value added services for their customer in order to increase numbers of customer, which also followed by increasing number of purchases. This also happened in tourism e commerce company, Triptrus. The challenge that triptrus faces is how to increase their conversion rates. One way to increase the number of conversion rate is the provision of a product recommendation feature. The purpose of this research is to find the best recommendation method that can improve conversion rate in Triptrus. In this research we looked for the best recommendation method that adapted to internal data of Triptrus. This research started with gathering internal data that followed by build recommendation based on several methods. Methods that used in this research are collaborative filtering, content based filtering, hybrid filtering and stochastic gradient descent. Based on the research result, collaborative filtering, content based, and hybrid lack of capability to give good recommendation. The best result from these three methods is hybrid with an error 0.71. In the other side stochastic gradient descent could gave best recommendation with smallest error ratio RMSE at 0.11. The result of this research is recommendation model that can give best recommendation adapted to Triptrus internal data. Best recommendation model is model that generated by stochastic gradient descent."

"Perkembangan teknologi telah mempengaruhi berbagai sektor di kehidupan termasuk juga dengan sektor pembelanjaan, seperti e-commerce. E-commerce termasuk media belanja yang selalu berkembang, salah satunya live streaming. Layanan live streaming social media menjadi terkenal di kisaran tahun 2020-2021 dengan tingkat penjualan di siaran langsung meningkat tajam hingga 76 persen di seluruh dunia. Tiktok live shopping merupakan layanan dari aplikasi Tiktok yang menawarkan peluang bagi brand untuk memamerkan produk secara real-time melalu acara live streaming. Penelitian ini bertujuan untuk menganalisis faktor yang mempengaruhi prilaku transaksi impulsif melalui live streaming e-commerce Tiktok live menggunakan model Stimulus Organism Respons (SOR). Penelitian ini dilakukan dengan melakukan survei terhadap pengguna aktif TikTok live yang telah melakukan pembelian produk melalui live streaming e-commerce. Pengumpulan data dilakukan dengan teknik non-probability sampling dan analisis data menggunakan Partial Least Square (PLS). Penelitian ini bertujuan untuk menganalisis beberapa faktor seperti price promotion, promotion time limit, customer-streamer interaction, customer-customer interaction, best deal, visual appeal, perceived value, shopping convenience terhadap transaksi impulsif. Hasil analisis membuktikan bahwa price promotion, customer-streamer interaction, best deal, visual appeal, perceived value, shopping convenience berpengaruh terhadap transaksi impulsif, terdapat beberapa variabel penelitian seperti promotion time limit, customer-streamer interaction, customer-customer interaction, best deal, visual appeal, perceived value, shopping convenience berpengaruh negatif terhadap perceived risk. Dari hasil penelitian dapat dilihat bahwa perceived risk memediasi hubungan antara promotion time limit, customer-streamer interaction, customer-customer interaction, best deal, visual appeal, perceived value, shopping convenience dan transaksi impulsif.

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Technological advancements have influenced various sectors of life, including the retail sector, such as e-commerce. E-commerce, including live streaming, is a constantly evolving shopping medium. One of the popular trends in recent years is live streaming on social media platforms. Live streaming services on social media gained popularity around 2020-2021, with live broadcast sales increasing by up to 76 percent worldwide. TikTok live shopping is a service offered by the TikTok app that provides opportunities for brands to showcase their products in real-time through live streaming events. The purpose of this research is to analyze the factors that influence impulsive transaction behavior through TikTok live e-commerce using the Stimulus Organism Response (SOR) model. This study conducted a survey among active TikTok live users who have made product purchases through live streaming e-commerce. Data collection was done using non-probability sampling techniques, and data analysis was performed using Partial Least Square (PLS). The research aims to analyze several factors such as price promotion, promotion time limit, customer-streamer interaction, customer-customer interaction, best deal, visual appeal, perceived value, and shopping convenience in relation to impulsive transactions. The analysis results demonstrate that price promotion, customer-streamer interaction, best deal, visual appeal, perceived value, and shopping convenience have an influence on impulsive transactions. Additionally, several research variables such as promotion time limit, customer-streamer interaction, customer-customer interaction, best deal, visual appeal, perceived value, and shopping convenience negatively affect perceived risk. From the research findings, it can be observed that perceived risk mediates the relationship between promotion time limit, customer-streamer interaction, customer-customer interaction, best deal, visual appeal, perceived value, shopping convenience, and impulsive transactions."

"Penelitian ini bertujuan untuk mengetahui perbandingan intensi pembelian konsumen produk Islamic fashion pada situs e-commerce dan e-commerce Islam dilihat dari sisi transaction-related services dan pre-purchase services seperti billing and paying mechanism, delivery arrangement, security and privacy, product pricing, support of product search and evaluation, dan web appearance. Data diperoleh dari penyebaran kuesioner kepada 318 responden wanita muslim konsumen produk Islamic fashion berusia minimal 17 tahun yang pernah melakukan pengalaman online pada situs Zalora dan Hijup. Analisis data dilakukan melalui analisis deskriptif dan partial least squares menggunakan Smart PLS 2.0. Hasil penelitian menunjukkan bahwa situs e-commerce dan e-commerce Islam signifikan berbeda dan konsumen masih cenderung memilih e-commerce dalam pembelian produk Islamic fashion.

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This study aims to determine the comparison of consumer purchase intention of Islamic fashion products on conventional e commerce and Islamic e commerce in terms of transaction related services and pre purchase services such as billing and paying mechanism, delivery arrangement, security and privacy, product pricing, support of product search and evaluation, and website appearance. Data obtained from 318 respondents aged at least 17 year old Muslim women who have done online experience on Zalora and Hijup web sites. Data was performed by descriptive analysis and partial least squares using Smart PLS 2.0. The results indicates that conventional e commerce and Islamic e commerce are significantly different and consumer still tend to choose conventional e commerce in purchasing Islamic fashion products."

"Penelitian ini bermula dari fenomena UMKM yang menggunakan E-commerce serta sedang berkembang saat ini. Penelitian ini menguji pengaruh antara aspek pemasaran dan aspek operasi terhadap kinerja usaha pada UMKM di Indonesia. Penelitian ini juga menyelidiki peran E-commerce experience dan firm size dalam memoderasi hubungan antara dampak penggunaan E-commerce pada aspek operasi dan pemasaran terhadap kinerja UMKM di Indonesia. Penelitian ini menggunakan data survei sebanyak 120 responden yaitu UMKM yang menggunakan E-commerce di Indonesia. Teknik analisis data yang digunakan adalah regresi linear berganda untuk mengetahui pengaruh aspek operasi dan aspek pemasaran terhadap kinerja. Serta, untuk mengetahui peran moderat firm size dan E-commerce experience dengan menggunakan analisis regresi moderat. Hasil penelitian menunjukkan bahwa aspek operasi dan aspek pemasaran memberi pengaruh yang signifikan pada kinerja UMKM yang menggunakan Ecommerce. Sedangkan, firm size dan E-commerce experience dalam memoderasi aspek operasi dan aspek pemasaran terhadap kinerja, masing-masing menunjukkan hasil yang tidak berpengaruh secara signifikan.

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This study is initially from Indonesian SMEs which using E-commerce phenomenon. This study is to distinguish the impacts of E-commerce on marketing and operations aspects and investigate how these impacts have affected performance. This study also investigates moderating roles of firm size and Ecommerce experience between operations and marketing effect on business performance.

This study using survey data from 120 responses of Indonesian SMEs in adopting E-commerce. The analysis used a multiple linear regression to determine the effect of operations and marketing effect on performance. And verified the roles of size and E-commerce experience using moderated regression analysis.

The results show that operations and marketing aspects of E-commerce have strong impacts significantly on performance of SMEs while firm size and Ecommerce experience have no impact significantly between operations and marketing effect on business performances."

"Dalam layanan E-commerce menimbulkan dampak negatif yaitu terjadi pencurian dan penjualan Data Pribadi konsumen pengguna layanan oleh pihak tidak bertanggungjawab. E-commerce dan Perlindungan Konsumen saling berkaitan, penting dalam praktik kegiatan e-commerce untuk menjaga kepercayaan konsumen selaku pengguna layanan, maka pelindungan data pribadi mendapat perhatian negara-negara di lingkup Kawasan Asia Tenggara. Penelitian ini membahas terkait pengaturan Pelindungan Hak atas Data Pribadi sebagai bagian dari hak konsumen dalam penyelenggaraan E-commerce di Indonesia, pengaturan hak untuk memperbaiki data, hak atas penghapusan Data Pribadi, hak portabilitas data dalam konsep Pelindungan Data Pribadi di negara Indonesia, Malaysia, dan Singapura, dan implementasi hak konsumen atas Pelindungan Data Pribadi di negara Indonesia, Malaysia, dan Singapura dalam konteks E-commerce. Metode penelitian ini adalah hukum normatif dengan pendekatan Peraturan Perundang-undangan dan komparatif. Adapun kesimpulannya yaitu  pengguna selaku konsumen berhak untuk mengetahui informasi yang jelas akan akuntabilitas, transparansi, proses pencegahan, dan penegakan hukum dalam kasus kebocoran Data Pribadi yang dialami dalam penyelenggara e-commerce. Masalah Pelindungan Data Pribadi menjadi isu di Negara Singapura dan Malaysia, dan pengaturan mengenai Tiga Hak diatas berbeda-beda. Dalam implementasi penegakan Pelindungan Data Pribadi, Singapura dan Malaysia memiliki organisasi khusus yang berwenang dalam penegakan hukumnya, sedangkan Indonesia berupaya membentuk Lembaga khusus untuk memastikan implementasi Pelindungan Data Pribadi

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E-commerce services have a negative impact, namely the theft and sale of Personal Data of service users by irresponsible parties. E-commerce and Consumer Protection are interrelated, important in the practice of e-commerce activities to maintain consumer confidence as service users, then the protection of personal data gets the attention of countries in the scope of Southeast Asia Region. This research discusses the regulation of the Protection of the Right to Personal Data as part of consumer rights in the implementation of E-commerce in Indonesia, the regulation of the right to correct data, the right to erasure of Personal Data, the right to data portability in the concept of Personal Data Protection in Indonesia, Malaysia, and Singapore, and the implementation of consumer rights to Personal Data Protection in Indonesia, Malaysia, and Singapore in the context of E-commerce. This research method is normative law with Legislation and comparative approach. The conclusion is that users as consumers have the right to know clear information on accountability, transparency, prevention process, and law enforcement in the case of Personal Data leakage experienced in e-commerce providers. The issue of Personal Data Protection is an issue in Singapore and Malaysia, and the regulation of the Three Rights above is different. In the implementation of Personal Data Protection enforcement, Singapore and Malaysia have special organizations authorized to enforce the law, while Indonesia seeks to establish a special institution to ensure the implementation of Personal Data Protection."