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Jurnal RESISTOR (Rekayasa Sistem Komputer)
Published by STMIK STIKOM Indonesia
ISSN : 25987542     EISSN : 25989650     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Energy Engineering
Jurnal RESISTOR merupakan jurnal yang diterbitkan oleh Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK STIKOM Indonesia, dengan P-ISSN 2598-7542 dan E-ISSN 2598-9650. Jurnal RESISTOR diterbitkan pertama kali pada bulan Oktober 2017 dan memiliki periode penerbitan sebanyak dua kali dalam setahun, yaitu pada bulan April dan Oktober.
Arjuna Subject : -
Articles 106 Documents
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SISTEM REKOMENDASI MUSIK BERDASARKAN DATA KONTEKS PADA LISTENING HISTORY MUSIK DAN KETERKAITAN ARTIS INDONESIA Gst Ayu Vida Mastrika Giri; Made Leo Radhitya; Made Agung Raharja; I Wayan Supriana
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 1 (2022): Jurnal RESISTOR Edisi April 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i1.1044

Abstract

A large number of digital music circulates online today. It makes music listeners confused to choose which music is suitable to listen to in certain circumstances or contexts, for example certain time, weather, activity, and desired mood. Playlist creation can make it easy for music listeners to collect their favorite music for a particular context, but creating playlists is time consuming and of course a lot of playlists will have to be created to accommodate all combinations of contexts. In this study, an automated music recommendation system was built using context data consisting of time, weather, activities, and desired mood which were also adjusted for the listener's age, gender, and favorite artist. The method used is Case-Based Reasoning (CBR), using listeners' listening history data as a knowledge base and the artist relatedness of Indonesian artists to improve solutions at the revision stage. Output of this system is in the form of music playlist presented in a website. The overall precision average for music recommendations is 0.78.
IDENTIFIKASI AKTIVITAS ILLEGAL TRANSSHIPMENT BERBASIS KEPADATAN POINT LINTASAN PADA DATA AIS I Gede Sudiantara; I Made Oka Widyantara; Dewa Made Wiharta
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 1 (2022): Jurnal RESISTOR Edisi April 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i1.1048

Abstract

Illegal transshipment merupakan aktivitas pemindahan atau pertukaran kargo, persediaan kapal, personel, atau hasil tangkapan ikan antara dua kapal di laut jika tidak dilaporkan kepada otoritas pelayaran di pelabuhan. Dalam konteks IUU (Illegal, Unreported, Unregulated) Fishing, aktivitas illegal transshipment perlu diawasi untuk mengamankan devisa negara dari sektor perikanan laut dan mengamankan daerah tangkapan ikan untuk keberlangsungan mata pencarian nelayan tradisional. Dengan memanfaatkan cakupan dari teknologi pada Automatic Identification System (AIS) memungkinkan untuk melakukan pengawasan terhadap kegiatan illegal transshipment yang terjadi di laut. Pada penelitian ini, kami mengembangkan sebuah kerangka kerja yang mengekstrak pengetahuan dari data AIS untuk medapatkan aktivitas kapal yang terindikasi melakukan kegiatan illegal transshipment. Memanfaatkan teknik klasterisasi berbasis kepadatan mampu mengelompokkan titik lintasan kapal yang memiliki pola menyerupai aktivitas illegal transshipment. Berdasarkan pengujian dengan metode Silhouette Coefficient, kualitas klaster yang dihasilkan pada kerangka kerja yang dibangun memiliki hasil yang cukup kuat. Selain itu, pengujian skor Silhouette pada klasterisasi tanpa tahapan pada kerangka kerja juga dilakukan untuk membandingkan kualitas klaster. Dari hasil perbandingan tersebut, diketahui bahwa proses pada kerangka kerja yang dibangun mampu meningkatkan kualitas klaster dari DBSCAN.
IMPLEMENTASI METODE MEL-FREQUENCY CEPSTRAL COEFFICIENT DAN DTW PADA APLIKASI PENGENALAN SUARA TEMBANG SEKAR ALIT Made Agung Raharja; I Putu Gede Adiatmika; I Nyoman Adiputra; Susy Purnawati; I Wayan Supriana
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 1 (2022): Jurnal RESISTOR Edisi April 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i1.1081

Abstract

The province of Bali has various types of songs that have different structures and functions, one of which is the Sekar Alit song. Seeing current technological advances, conservation efforts should follow the development of existing technology. This study recognizes the singer's voice with the MeliFrequency iCepstrum Coefficients (MFCC) method used to perform feature extraction, i.e. to obtain a parameter and information regarding the characteristics of a person's voice and the training of voice pattern matching against the voice of the DTW Singer Alit (Dinamic) and the Time Warping Alit method. . So that the final result of this research is an android-based tembang sekar alit learning application that can be used by students to learn more easily and effectively which is called the SekARAI application. The results of usability testing on the application found that the average value was above 3, which means that the SekARAI software that has been implemented has met the Usability element and besides that the software is easy to use and understand by users. The Sekar Alit Song Voice Recognition application has been evaluated using the confusion matrix method, it is found that the MFCC algorithm test results in an accuracy of 76.6%.
RANCANG BANGUN CHILLER BERBASIS MIKROKONTROLER UNTUK EVAPORASI SENYAWA BAHAN ALAM Ni Putu Rahayu Artini; I Made Agus Mahardiananta; I Made Aditya Nugraha
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 1 (2022): Jurnal RESISTOR Edisi April 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i1.1082

Abstract

Chemical analysis uses a variety of solvents based on their level of polarity, such as non-polar, semipolar, and polar solvents. The solvent is used in the extraction process, both liquid-liquid extraction and solid-liquid extraction. Common extractions carried out in the fields of chemistry, pharmacy and other health sciences are solid-liquid extraction using samples in the form of simplicia from plants that are dried so that they become simplicia. Simplicia extracted with solvent. Extraction is carried out to concentrate the active compound and separate the solvent, so that it can be reused. Concentration was carried out using a rotary evaporator. A chiller-based rotary evaporator, namely a microcontroller-based chiller, is designed to accelerate temperature reduction, so that the evaporation and condensation process with the condenser is faster. Based on the results of the study, it was concluded that the chiller that was made was able to reduce the temperature of the water connected to the condenser section of the rotary evaporator and the heat from the waterbath with the duration of decreasing the temperature in the inlet-outlet reservoir between 183±2.88 seconds to 302±2.52 seconds from a water bath temperature of 40-600C.
ANALISIS UTILISASI RESOURCE CLUSTERS PADA HADOOP MENGGUNAKAN VIRTUALIZATION I Kadek Susila Satwika; I Putu Susila Handika; Made Hanindia Prami Swari
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 1 (2022): Jurnal RESISTOR Edisi April 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i1.1088

Abstract

Large amounts of data processing necessitate the use of a dependable infrastructure. Using clustering technology in Big Data processing is a solution for faster processing times. This study evaluated the performance of the Hadoop server using virtualization technology. A varying number of query requests are sent to Hadoop server clusters at the same time. Then, the CPU and memory (RAM) utilization was calculated. According to the test results, the CPU usage on the namenode reached 100% at the start of the process, followed by an increase in CPU usage on the datanode the next time. Meanwhile, the namenode uses the most memory when it receives 25 requests at once. This demonstrates that the namenode can only serve a maximum of 25 requests at the same time.
KLASIFIKASI MOOD MUSIK BERDASARKAN MEL FREQUENCY CEPSTRAL COEFFICIENTS DENGAN BACKPROPAGATION NEURAL NETWORK Patriaji Ibrahim Maulana; Arik Aranta; Fitri Bimantoro; I Gede Andika
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 1 (2022): Jurnal RESISTOR Edisi April 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i1.1089

Abstract

In music industry, each music is grouped by type, including music genre, artist identification, instrument introduction, and mood. Then came a field of research called Music Information Retrieval (MIR) which is a field of science that retrieves and processes the metadata of music files to perform the grouping. This research is based on the uniqueness of music that has its own mood implied in it. By creating a Machine Learning model using Backpropagation Neural Network (BPNN) based on the Mel Frequency Cepstral Coefficients (MFCC) input feature, it will be able to classify types of music based on mood. Grouping is carried out on four mood classes based on Thayer's model. Based on several previous studies, the use of MFCC in voice processing produces very good accuracy as well as the use of BPNN for classification, which is expected to result in better machine learning model performance. The data used in this study were obtained from the Internet with a total dataset of 200. The results obtained from this study are the classification of music mood using BPNN based on the MFCC feature capable of producing 87.67%. accuracy.
KNOWLEDGE BASED SYSTEM UNTUK REKOMENDASI DEWASA PENGABENAN PADA DESA ADAT MAMBAL I Putu Arya Putra; Emmy Febriani Thalib; Ida Bagus Ary Indra Iswara
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 1 (2022): Jurnal RESISTOR Edisi April 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i1.1091

Abstract

Applications for a good day to carry out the pengabenan ceremony of the mambal traditional village often encounter obstacles, with a process that is still manual, it certainly has a fairly high risk of error because it is caused by physical factors from a bendesa as an expert, including fatigue and forgetfulness. In this study, we will provide solutions to problems or obstacles experienced by the bendesa as an expert by designing and building a system that can represent a bendesa in the dewasa pengabenan application process by adopting the mindset of a bendesa in recommending dewasa pengabenan. The parameters used in this system consist of 54 conditions with 20 conditions that must be avoided. The parameters used are sasih, tri wara, panca wara, sapta wara, penanggal, panglong and wuku. The system that was built provides output in the form of recommendations for dewasa pengabenan, which are web-based, using the PHP framework Laravel programming language, and the database is managed with mysql. This system has been tested by the Bendesa as an expert and several users, the results obtained from the test can be concluded that the function of the features in the system is in accordance with what is expected
Implementasi Sistem Cerdas Menggunakan Case Base Reasoning Sebagai Rujukan Terpadu Penerima Bantuan Kemiskinan di Kabupaten Tabanan I Wayan Supriana; Gst. Ayu Vida Mastrika Giri; I Made Satria Bimantara
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 2 (2022): Jurnal RESISTOR Edisi Oktober 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i2.1097

Abstract

Strategi dan inovasi mempercepat penanggulangan kemiskinan pemerintah Kabupaten Tabanan semakin digalakkan, tahun 2020 diperkirakan persentase kemiskinan mengalami peningkatan karena banyak sektor parisiwata dan sektor industri lainnya terdampak covid-19. Sampai saat ini distribusi program-program pengentasan kemiskinan berpusat pada database terpadu, sementara dilapangan terdapat banyak kendala. Identifikasi rumah tangga miskin perlu ditingkatkan sehingga dapat menentukan jenis bantuan utama yang dibutuhkan berdasarkan komponen kriteria yang sudah dipenuhi. Melalui penelitian ini dikembangkan aplikasi berupa sistem cerdas yang dapat menentukan bantuan prioritas rumah tangga miskin. Sistem yang dikembangkan menggunakan metode case base reasoning yaitu identifikasi rumah tangga sasaran didasari oleh penalaran berbasis kasus. Model penilaian menggunakan 23 fitur identifikasi rumah tangga miskin dan 18 fitur bantuan kemiskinan. Berdasarkan penelitian yang sudah dilakukan, model CBR dengan kluster K-Means lebih baik dibandingkan CBR tanpa kluster. Komposisi data training 80% dan data testing 20%, sistem CBR dengan indexing K-mean memiliki akurasi sebesar 0.48% dan tanpa indexing sebesar 0.46%
Stasiun Pengisian Energi Baterai Ramah Lingkungan Berbasis Panel Surya Aprisal Surya Ananda; Lilis Nur Hayati Hayati; Ihwana As’ad
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 2 (2022): Jurnal RESISTOR Edisi Oktober 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i2.1104

Abstract

The used of electrical power on gadgets is classified as minimal. However, if it is multiplied by the number of users, the electrical energy that required is not small. In the Sea Village, Latambaga, Kolaka, the courier services have sprung up and usually gathers to rest and charged their gadget batteries. However, couriers often charged their gadget batteries at restaurants or coffee shops, it could be detrimental to the restaurants or coffee shops owner because their electricity costs will increase. According to these problems, we need a device that is able to store the alternative energy, namely an Environmentally Friendly Battery Energy Charging Station. This research is based on solar panels, with the used of adequate battery capacity and an inverter as a DC-AC current converter so that it can be used to charge the couriers gadgets, the Telegram API bot as an IoT application for notification of device and battery power conditions to the admin device. This system is expected to help the couriers which operate in the villages of Sea, Latambaga, Kolaka in meeting the needs of environmentally friendly and inexpensive electrical energy.
Sentimen Analisis Inisiatif Vaksin Nasional Menggunakan Naïve Bayes dan Laplacian Smoothing Pada Komentar Video Youtube I Putu Agus Eka Darma Udayana; I Gede Iwan Sudipa; Risaldi Risaldi
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 2 (2022): Jurnal RESISTOR Edisi Oktober 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i2.1108

Abstract

COVID-19 pandemic that has been declared by who in march 2020 Has been Indonesia biggest health crisis end in the decade. WHO said one of the quickest way to end the pandemic is through immunity through vaccine thu's theory is a national vaccine program initiated by the government in the middle of 2021. YouTube is of de facto public space in Indonesia cyberspace for its netizen for various conversation. from gossiping to discuss in public policy YouTube has been a gold mine for social media data mining enthusiast since 2010. but has been not utilized much by Indonesia Academic. do lack of popularity compared to Twitter which has been a media darling what Indonesian Acdemic ever since This research is focused on sentiment analysis pantydeal YouTube about the national vaccine initiation on a news channel in YouTube. This research is primarily consist of naive bayes classifier a a popular algorithm Indonesian data mining enthusiast which has some limitation such as the problem known as zero probability problem and also the use of non-public data which can be fixed by the use of Laplacian smoothing algorithm which when tested Using 100 of random comments as a data testing has resulted in 71% percent of succes rate and when we do a statistical analysis the precision , recall rate and the F-meassurement score of the classifier all resulted in above 75% score which is satisfactory.

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