Abstract:Monitoring water conditions in real-time is a critical mission to preserve the water ecosystem in maritime and archipelagic countries, such as Indonesia that is relying on the wealth of water resources. To integrate the water monitoring system into the big data technology for realtime analysis, we have engaged in the ongoing project named SEMAR (Smart Environment Monitoring and Analytic in Real-time system), which provides the IoT-Big Data platform for water monitoring. However, SEMAR does not have an analytical system yet. This paper proposes the analytical system for water quality classification using Pollution Index method, which is an extension of SEMAR. Besides, the communication protocol is updated from REST to MQTT. Furthermore, the real-time user interface is implemented for visualisation. The evaluations confirmed that the data analytic function adopting the linear SVM and Decision Tree algorithms achieves more than 90% for the estimation accuracy with 0.019075 for the MSE.

The rapid development of technology greatly affects people's lives today, one of which in Fakfak City has all been entered by the development of information technology. Fakfak is one of the regencies on the Papua island, the people of Fakfak Regency highly uphold religious values ​​and it is proven by the motto "Satu Tungku Tiga Batu". In Fakfak Regency, one of the the problems faced by some people is the search of worship places that must be done manually, by asking people around, or by looking at a map. In addition, some places of worship have historical values ​​that need to be known by many people. For example, the oldest mosque in Papua and West Papua is in Fakfak Regency. Regarding to this problem, an information system was created that can display information about places of worship in Fakfak. The method used in this research is a waterfall process model. This application is tested using black box methods and questionnaires. The result reveals that an Android-based application of the Geographic Information System for Places of Worship in Fakfak Regency can help to make it easier for tourists and the Fakfak community to find and obtain information related to places of worship in Fakfak. The results of the black box test state that the functions of the application are running well. The questionnaire test gave results from questions filled out by 20 respondents who stated that the application of the Geographic Information System for Places of Worship was suitable to use by the Fakfak community in obtaining information about places of worship and information on religious history and making it easier for users to find the location of the worship places they wanted to visit.

Monitoring water conditions in real-time is a critical mission to preserve the water ecosystem in maritime and archipelagic countries, such as Indonesia that is relying on the wealth of water resources. To integrate the water monitoring system into the big data technology for realtime analysis, we have engaged in the ongoing project named SEMAR (Smart Environment Monitoring and Analytic in Real-time system), which provides the IoT-Big Data platform for water monitoring. However, SEMAR does not have an analytical system yet. This paper proposes the analytical system for water quality classification using Pollution Index method, which is an extension of SEMAR. Besides, the communication protocol is updated from REST to MQTT. Furthermore, the real-time user interface is implemented for visualisation. The evaluations confirmed that the data analytic function adopting the linear SVM and Decision Tree algorithms achieves more than 90% for the estimation accuracy with 0.019075 for the MSE.

Melayani penduduk yang berjumlah 3.243 jiwa (data BPS 2018), para pegawai Distrik Kokas dituntut untuk mampu bekerja dengan optimal agar segala kebutuhan administrasi masyarakat dapat terpenuhi, namun sayangnya sampai saat ini hanya beberapa dari pegawai Kantor Distrik Kokas yang mampu mengoperasikan komputer untuk membantu melaksanakan tugas pelayanannya dengan baik dan efisien. Hal ini mengakibatkan tugas pelayanan berjalan tidak prima, serta terjadi penumpukan pekerjaan dan berkas di beberapa pegawai yang memiliki kemampuan untuk mengoperasikan komputer dari rekan kerjanya yang tidak familiar dengan penggunaan komputer. Untuk melaksanakan tugas pelayanan, para pegawai Distrik Kokas harus dapat bekerja dengan optimal, dan salah satu hal yang tidak dapat dihindari adalah pemanfaatan komputer untuk membantu meningkatkan kinerja dan output kerja yang berkualitas. Oleh karena itu kegiatan pelatihan untuk meningkatkan kemampuan pegawai Distrik Kokas untuk melakukan tugas-tugas administrasi dengan menggunakan program Microsoft Word digagas dan akan dilaksanakan. Diharapkan setelah mengikuti kegiatan pelatihan, seluruh pegawai dapat mengoperasikan komputer, khususnya menjalankan program Microsoft Word untuk menunjang pekerjaan masing-masing secara lebih efisien dan tidak membebani hanya beberapa pegawai yang biasa bekerja dengan komputer seperti yang selama ini terjadi.

Monitoring water conditions in real-time is a critical mission to preserve the water ecosystem in maritime and archipelagic countries, such as Indonesia that is relying on the wealth of water resources. To integrate the water monitoring system into the big data technology for real-time analysis, we have engaged in the ongoing project named SEMAR (Smart Environment Monitoring and Analytic in Real-time system), which provides the IoT-Big Data platform for water monitoring. However, SEMAR does not have an analytical system yet. This paper proposes the analytical system for water quality classification using Pollution Index method, which is an extension of SEMAR. Besides, the communication protocol is updated from REST to MQTT. Furthermore, the real-time user interface is implemented for visualisation. The evaluations confirmed that the data analytic function adopting the linear SVM and Decision Tree algorithms achieves more than 90% for the estimation accuracy with 0.019075 for the MSE. The processing time of the SEMAR system only takes an average 0.5 seconds to process the data to be visualized.