Judul: Development of a Real-Time Machine Condition Monitoring System Using Internet of Things on Hot Press Machine at PT. XYZ
Abstrak: The increasingly high competition makes companies have to continue improving the productivity of existing production. One of the efforts can be made by improving the performance of the production facilities, such as machines and other supporting equipment. Human limitations in monitoring machine performance are factors in handling slow production processes. This factor causes no measurement of machine performance at any time and the risk of sudden machine damage. This project aims to design a real-time machine condition monitoring system using Internet of Things (IoT) technology and Overall Equipment Effectiveness (OEE) performance methods. The project is carried out using the method of engineering design stages. Based on the test results, the prototype designed can receive and send machine condition data to cloud services which are then integrated into mobile applications with the results of machine data visualization, namely availability, performance, quality, OEE, temperature, and vibration.
Keyword: internet of things, machine condition, overall equipment effectiveness

Judul: Pengembangan Sistem Predictive Maintenance Dengan Algoritma Prophet dan Decision Tree Pada Mesin Hot Press di PT Corinthian Industries Indonesia
Abstrak: A machine maintenance system is important in maintaining machine productivity and production productivity. PT Corinthian Industries Indonesia uses preventive maintenance as its machine maintenance system. The system still causes sudden damage because sometimes machine maintenance is not carried out at the right time according to its condition. An example is a Hot-press machine which has several breakdowns within a month. This project aims to develop a better maintenance system, namely a predictive maintenance system with the Prophet algorithm and a C4.5 decision tree based on a mobile application. The system initiates maintenance in response to certain machine conditions or performance degradation. Temperature and vibration are some parameters that can be measured as a marker of machine condition. This project develops a predictive maintenance system featuring real-time OEE calculations, machine condition detection from temperature and vibration sensors, and decision recommendations. Detection of machine conditions using the Prophet algorithm has a 5% MAPE. The decision recommendation using the C4.5 decision tree algorithm has an accuracy of 83%. Both algorithms have a fairly good percentage of accuracy, so they can be applied to the development of this system. The development of this system is used to determine the condition of the machine in real-time so that the response from the maintenance party can be carried out immediately., Sistem maintenance mesin merupakan aspek penting dalam menjaga produktivitas mesin dan produktivitas produksi. Saat ini, PT Corinthian Industries Indonesia menggunakan preventive maintenance sebagai sistem maintenance mesinnya. Sistem tersebut masih menyebabkan kerusakan mendadak karena terkadang maintenance mesin tidak dilakukan pada waktu yang tepat sesuai dengan kondisinya. Contohnya pada mesin Hot-press yang beberapa kali mengalami breakdown dalam waktu satu bulan. Tujuan dari projek ini adalah untuk mengembangkan sistem perawatan yang lebih baik yaitu sistem predictive maintenance dengan algoritma Prophet dan decision tree C4.5 berbasis aplikasi mobile. Sistem tersebut memulai perawatan sebagai respon terhadap kondisi mesin tertentu atau penurunan kinerja mesin. Suhu dan getaran adalah beberapa parameter yang bisa diukur sebagai penanda kondisi mesin. Projek ini mengembangkan sistem perawatan prediktif dengan fitur perhitungan OEE real-time, deteksi kondisi mesin dari sensor suhu dan getaran, dan saran keputusan. Deteksi kondisi mesin menggunakan algoritma Prophet memiliki MAPE 5%. Rekomendasi keputusan menggunakan algoritma decision tree C4.5 memiliki akurasi 83%. Kedua algoritma tersebut memiliki persentase akurasi yang cukup baik sehingga bisa diterapkan pada pengembangan sistem ini. Pengembangan sistem ini digunakan untuk mengetahui kondisi mesin secara real-time sehingga respon dari pihak maintenance dapat segera dilakukan.
Keyword: predictive maintenance, prophet algorithm, decision tree algorithm

Judul: Posisi Filogenetik Kura-Kura Carettochelys Insculpta  (Reptillia: Testudinata)
Abstrak: Carettochelys insculpta is an endemic freshwater turtle of southern Papua and northern Australia. Phylogenetic position of this turtle is remain unresolved until now. Most of the research conducted show close relationships of C. insculpta and members of Trionychidae family. However, some of the research show distance between C. insculpta and members of Trionychidae family. This research is conducted to analyze phylogenetic relationship between C. insculpta and other members of Testudinata using 12S rRNA, 16S rRNA, and both gene as markers. DNA samples were obtained from three different organisms of C. insculpta. Two species used as outgroups were Alligator mississippiensis and Iguana iguana. Phylogenetic analysis was carried out using Neighbor-Joining method with Felsenstein 1981 (F81) modeltest. A polytomy tree of Testudinata was produced by using 12S rRNA gene. However, analysis using 16S rRNA and both genes as markers confirmed that C. insculpta was located between the Chelonidae and the Trionychidae family.
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