Music is closely related to human psychology, this fact indicates that music can be associated with specific emotions and mood in humans. Any music that has been created has its own mood that radiates, and therefore has a lot of research in the field of Music Information Retrieval (MIR) has been developed to explore the mood of the music. This research resulted in a classification system of music on mood by using K-Nearest Neighbor algorithm. The system uses the data input in the form of music file formats mono * .wav in the refrain lasts 30 seconds, which in turn make the process of classification of music by using K-NN algorithm. The system generates output in the form of labels mood, contentment, Exuberance, depression and anxious. In general the results of the accuracy of the system by using K-NN is good enough ie 86.55% on the value of k = 3, and the processing time classification of the average 0.01021 seconds perfile of music. Index Term : Music, Mood, Classification, K-NN Intisari-Musik erat kaitannya dengan psikologi manusia, kenyataan ini mengindikasikan bahwa musik dapat terkait dengan emosi dan mood/ suasana hati tertentu pada manusia. Setiap musik yang telah tercipta memiliki mood tersendiri yang terpancar, maka dari itu telah banyak penelitian dalam bidang Music Information Retrieval (MIR) yang telah dilakukan untuk pengenalan mood terhadap musik. Penelitian ini menghasilkan sebuah sistem pengelompokan musik terhadap suasana hati dengan menggunakan algoritma K-Nearest Neighbor. Sistem menerima masukan data berupa file musik format mono *.wav, yang selanjutnya melakukan proses pengelompokan terhadap musik dengan mengggunakan klasifikasi K-NN. Sistem menghasilkan keluaran berupa label jenis mood yaitu, contentment/ kepuasan, exuberance/ gembira, depression/ depresi dan anxious/ cemas; kalut. Secara umum hasil akurasi sistem dengan menggunakan algoritma klasifikasi K-NN cukup baik yaitu 86,55% pada nilai k = 3, serta waktu pemrosesan klasifikasi rata-rata 0,01021 detik per-file musik.

The weakness of the orthogonal freuency division multiplexing (OFDM) system is susceptible to the existence of carrier frequency offset (CFO) which causes the emergence of inter carrier interference (ICI) which causes a degradation of performance OFDM systems. This study aims to apply the suggested rectangular (REC) pulse and improved sinc-power (ISP) pulse shaping methods on OFDM system and determines ICI reduction with the effects of CFO over flat fading Rayleigh channels. The performance of each pulse shaping method is evaluated and compared based on parameter ICI power vs. normalized frequency offset, signal to interference ratio (SIR) vs. normalized frequency offset and bit error rate (BER) vs. energy bit per noise (Eb/No). The simulation result in terms of BER vs. Eb/No indicated that REC and ISP pulse shaping has better performance dealing with ICI reduction compared to OFDM system no applied pulse shaping. In addition, the ISP is able to mitigate ICI better than REC.

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The problem that often occurs so far is the delay in the presence of the fire departmentat the fire site. So the authors make an early detection tool for forest fires based on the Internetof Things because forest fires occur in very large forests so that supervision from officers is notenough. This study aims to design a forest fire extinguishing system based on ESP8266NodeMCU. The research was conducted by designing a system and making it happen by usinga board and several sensors to obtain data. From the results of the design carried out in thisstudy, the prototype of forest fire detection systems based on NodeMCU ESP8266 andtemperature, fire and smoke sensors has been realized, which can send notifications ontelegram. And the pump can put out the fire. The actual application in the forest still needschanges to the pump construction and the addition of several sensors.