With the advancement of Building Information Modeling (BIM) technology, BIM gains more importance and becomes a prerequisite in building projects. BIM is useful throughout a building lifecycle; from building bid, design, construction, completion, operation, and maintenance to building demolition. However, current information exchange surrounding BIM is still limited and bound to a single participant or organization and is also limited to a particular phase in the building lifecycle. This paper aims to explore BIM information exchange among many parties involved in a secure manner using a blockchain platform throughout the whole building lifecycle. In this research, many parties involved in the building project will be able to recognize one another through deployment of a permissioned blockchain. This information exchange uses Hyperledger Composer, a permissioned blockchain running on a blockchain platform called Hyperledger Fabric. Our experiment shows that BIM information exchange could be further improved. In this study, BIM information exchange can be implemented not only in one building phase but throughout the whole building lifecycle. It also facilitates BIM information exchange among multiple participants in a secure manner via a permissioned blockchain.

With the increasing need to store large amounts of unstructured and semi-structured data, the database that used to be mostly using SQL technology, began using the NoSQL database. The purpose of this paper is to conduct a literature study of the characteristics, advantages and disadvantages of SQL and NoSQL databases. This literature study shows that there are differences in SQL databases and based on characteristics (ACID for SQL vs. BASE and CAP for NoSQL); data model (relational for SQL and key-value for NoSQL); data structure (structured for SQL and non- or semi-structured for NoSQL); process (subquery, join and grouping / aggregation and complex queries faster only for SQL); and the number of servers used (single large server for SQL and multiple multiple levels for NoSQL). A literature review for further SQL and NoSQL applications is needed in the future.

PT PLN (Persero) mengembangkan aplikasi PLN Mobile untuk menyediakan layanan kelistrikan melalui aplikasi mobile. Ulasan di Google Play Store diberi peringkat dari 1 hingga 5, tetapi pengguna sering memberikan peringkat yang tidak sesuai dengan ulasan mereka, jadi ini tidak cukup menggambarkan kualitas aplikasi. Aplikasi PLN Mobile berisi begitu banyak ulasan atau data ulasan yang membaca semuanya akan sulit dan memakan waktu. Sistem klasifikasi digunakan untuk mengukur sentimen publik. Analisis sentimen dilakukan terhadap 1000 sampel review yang dikumpulkan melalui PLN Mobile App antara Januari hingga Juni 2022. Langkah-langkah dalam penelitian ini dilakukan dengan meninjau teknik pengumpulan data seperti web scraping, machine translation, data labeling, text preprocessing, TF-IDF , klasifikasi teks, dan evaluasi model. Hasil untuk pendekatan klasifikasi teks berbasis Lexicon, yang akan menggunakan pendekatan berbasis kamus Vader Lexicon, adalah 489 sentimen positif, 145 sentimen negatif, dan 366 netral. Berdasarkan hasil perbandingan kelas positif, netral, dan negatif terhadap 1000 sampel data dari Vader Lexicon, kelas positif mendapat rating 67%, kelas netral mendapat rating 6%, dan kelas negatif mendapat rating. dari 27%. Metode Naive Bayes juga digunakan dalam proses klasifikasi. Untuk distribusi data uji dan data latih, penulis menggunakan rasio data split 90:10. Proses evaluasi matriks konfusi memiliki tingkat akurasi 70%.

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A Practical Byzantine Fault Tolerance (PBFT) is a consensus algorithm deployed in a consortium blockchain that connects a group of related participants. This type of blockchain suits the implementation of the Building Information Modeling (BIM) information exchange with few participants. However, when much more participants are involved in the BIM information exchange, the PBFT algorithm, which inherently requires intensive communications among participating nodes, has limitations in terms of scalability and performance. The proposed solution for a multi-layer BFT hypothesizes that multi-layer BFT reduces communication complexity. However, having more layers will introduce more latency. Therefore, in this paper, Double-Layer Byzantine Fault Tolerance (DLBFT) is proposed to improve the blockchain scalability and performance of BIM information exchange. This study shows a double-layer network structure of nodes that can be built with each node on the first layer, which connects and forms a group with several nodes on the second layer. This network runs the Byzantine Fault Tolerance algorithm to reach a consensus. Instead of having one node send messages to all the nodes in the peer-to-peer network, one node only sends messages to a limited number of nodes on Layer 1 and up to three nodes in each corresponding group in Layer 2 in a hierarchical network. The DLBFT algorithm has been shown to reduce the required number of messages exchanged among nodes by 84% and the time to reach a consensus by 70%, thus improving blockchain scalability. Further research is required if more than one party is involved in multi-BIM projects.