Articles
<![CDATA[Peningkatan Dan Pengembangan Pengajaran Berbasis Teknologi Bagi Guru-Guru Di SMK Pariwisata Margarana ]]>
<![CDATA[Supriana, I Wayan]]>;
<![CDATA[Sukmana, IWK.Teja]]>
<![CDATA[ JURNAL WIDYA LAKSANA Vol 7, No 1 (2018) ]]>
Publisher : <![CDATA[Universitas Pendidikan Ganesha ]]>
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DOI: 10.23887/jwl.v7i1.12564
<![CDATA[Perkembangan teknologi informasi memberikan dampak yang besar pada berbagai bidang kehidupan manusia seperti pada bidang industri, kesehatan, pemerintahan dan bidang-bidang lainnya. Khususnya pada bidang pendidikan penggunaan teknologi masih belum dapat di manfaatkan secara optimal pada pendidikan menengah yang letaknya di pinggiran kota. Seperti halnya SMK Pariwisata Margarana proses pendidikan yang masih dilakukan secara konvensional dengan maraknya perkembangan teknologi saat ini. Hal ini mendorong program kemitraan masyarakat (PKM) Universitas Dhyana Pura melaksanakan program pelatihan pengembangan bahan ajar berbasis teknologi bagi para guru di SMK Pariwisata Margarana. Tujuan pelaksanaan program adalah peningkatan pemahaman pembuatan materi ajar berbasis teknologi serta pengembangan pemahaman konsep manajemen perhotelan. Program PKM dilakukan dalam bentuk pelatihan dan pendampingan bagi peserta. Secara menyeluruh kegiatan program ini terlaksana dengan baik dan mampu meningkatkan pengetahuan guru SMK Pariwisata Margarana. Kondisi ini ditunjukkan dengan persentase kehadiran guru sebesar 81% selama program ini dilaksanakan dan peningkatan kemampuan sebesar 80%.]]>
<![CDATA[Pengembangan Sistem Identifikasi Keluarga Miskin Di Kabupaten Tabanan Dengan Menggunakan Metode Naïve Bayes Dalam Pengentasan Kemiskinan ]]>
<![CDATA[Supriana, I Wayan]]>
<![CDATA[ JST (Jurnal Sains dan Teknologi) Vol 7, No 1 (2018) ]]>
Publisher : <![CDATA[Universitas Pendidikan Ganesha ]]>
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DOI: 10.23887/jst-undiksha.v7i1.12669
<![CDATA[Kemiskinan adalah isu klasik yang masih terjadi di berbagai daerah di Indonesia termasuk Bali, khususnya daerah Tabanan yang memiliki tinggkat kemiskinan lebih tinggi dari tingkat kemiskinan provinsi. Jumlah penduduk miskin di Kabupaten Tabanan masih cukup tinggi meskipun Bali manjadi salah satu tujuan wisata mancanegara. Berbagai program prorakyat diterapkan untuk mengurangi tingkat kemiskinan oleh pemerintah Kabupaten Tabanan, namun dalam prakteknya program kemiskinan seringkali salah sasaran. Dalam penelitian ini dilakukan penerapan pemanfaatan kemajuan teknologi informasai untuk mengidentifikasi sebuah rumah tangga, sistem yang dibangun akan menentukan tingkat kemiskinan rumah tangga berdasarkan indikator tingkat keluarga sejahtera. Metode identifikasi untuk mengetahui tingkat kesejahteraan rumah tangga dengan menggunakan analisis Bayesian yang dalam hal ini adalah Naïve Bayes Classifier. Hasil yang diperoleh berdasarkan analisis dan implementasi bahwa sistem yang dibangun mampu mengidentifikasi tingkat kesejahteraan rumah tangga sebesar 72% berdasarkan data uji yang digunakan, hal ini akan memudahkan program pengentasan kemiskinan dapat disalurkan tepat sasara sesuai rumah tangga miskin yang membutuhkan.Kata kunci: Kemiskinan, Rumah Tangga Miskin, Bayesian Analysis, Naïve Bayes Classifier]]>
<![CDATA[Sistem Informasi Prediksi Penilaian Kredit Perbankan Menggunakan Algoritma K-Nearest Neighbor Classification ]]>
<![CDATA[Supriana, I Wayan]]>;
<![CDATA[Raharja, Made Agung]]>;
<![CDATA[Gunawan, Putu Wida]]>
<![CDATA[ JST (Jurnal Sains dan Teknologi) Vol 8, No 1 (2019) ]]>
Publisher : <![CDATA[Universitas Pendidikan Ganesha ]]>
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DOI: 10.23887/jst-undiksha.v8i1.16470
<![CDATA[The existence of banking institutions is very important for people's lives, especially used for raise funds in the form of deposits, demand deposits, savings and others. Besides that, it is an institution banks can also play a role as channeling funds in the form of credit to the public and business entities that need it. Problems in credit disbursement cause bad loans from customers, causing losses to the bank. Credit assessment is one of the important stages that must be carried out by the bank before credit is given to the credit applicant. The credit appraisal process belongs to a semi-structured problem that is quite complex, therefore it is necessary to develop a system to predict the feasibility of applying for credit. The system built in this study uses the K-Nearest Neighbor Classification algorithm by assessing prospective borrowers from the training data used. Based on the research that has been done, the K-Nearest Neighbor Classification algorithm can be modeled in a bank credit assessment. System testing results show accuracy of calculation accuracy of 81,82%.]]>
<![CDATA[Perancangan Sistem Chick Maintenance Cycle Menggunakan ERP Pada PT Charoen Pockphand ]]>
<![CDATA[Liana, Laurensia]]>;
<![CDATA[Supriana, I Wayan]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 1 (2019): JELIKU Volume 8 No 1, Agustus 2019 ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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DOI: 10.24843/JLK.2019.v08.i01.p08
<![CDATA[The development of the world of computers and information technology has been very rapid in recent years. A company needs an information system that can accommodate various needs of the company in carrying out business processes. With the application of information systems to companies, business processes can run more smoothly and faster. PT. Charoen Pockphand Indonesia wants to create a new system based on an existing system using an ERP or Enterprises Planning Resource. ERP was chosen because it has a wide operating area of functionality, namely Marketing and Sales, Supply Chain Management, Accounts and Finance, and Human Resources.]]>
<![CDATA[Case Based Reasoning And Naive Bayes Implementation In Laptop Purchasing Recommender System ]]>
<![CDATA[Dharmawangsa, I Gusti Ngurah Agung]]>;
<![CDATA[Supriana, I Wayan]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 3 (2021): JELIKU Volume 9 No 3, Februari 2021 ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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DOI: 10.24843/JLK.2021.v09.i03.p13
<![CDATA[Purchasing a new laptop will be difficult if we do not know what the ideal laptop specification for our needs. Especially with a wide selection of laptops. From this problem, system that can give a recommendation to choose the right laptop based on purchaser’s specification choice is needed. This research using two method, Case Based Reasoning and Naive Bayes. The concept of Case Based Reasoning is the process of solving new problems based on the solutions of similar past problems, While Naive Bayes assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature. Naive bayes will be implemented in retrive process of case based reasoning. The recommender system utilizing 7 feature, Kecepatan Processor, Kapasitas Ram, Tipe Grafis, Ukuran Layar, Ukuran Harddisk, Kecepatan Layar, and Harga. The percentage of respondents who said the system was successful in providing the right recommendations was 70 percent of the total respondents.]]>
<![CDATA[Case Based Reasoning System For Recommendation Of Restaurant In Jimbaran Using K-Nearest Neighbor ]]>
<![CDATA[Mahardika, I Gede Teguh]]>;
<![CDATA[Supriana, I Wayan]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 2 (2020): JELIKU Volume 9 No 2, November 2020 ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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DOI: 10.24843/JLK.2020.v09.i02.p14
<![CDATA[Culinary is one of the favorite businesses today. The number of considerations to choose a restaurant or place to visit becomes one of the factors that is difficult to determine the restaurant or place to eat. To get the desired place to eat advice, one needs a recommendation system. Decisions made by the recommendation system can be used as a reference to determine the choice of restaurants. One method that can be used to build a recommendation system is Case Based Reasoning. The Case Based Reasoning (CBR) method mimics human ability to solve a problem or cases. The retrieval process is the most important stage, because at this stage the search for a solution for a new case is carried out. The study used the K-Nearest Neighbor method to find closeness between new cases and case bases. With the selection of features used as domains in the system, the results of recommendations presented can be more suggestive and accurate. The system successfully provides complex recommendations based on the type and type of food entered by the user. Based on blackbox testing, the system has features that can be used and function properly according to the purpose of creating the system.]]>
<![CDATA[Implementation of the CBR (Case Based Reasoning) Method in Cases of Cesarean section ]]>
<![CDATA[Wiantari, Ni Wayan]]>;
<![CDATA[Supriana, I Wayan]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 2 (2019): Jeliku Volume 8 No 2, November 2019 ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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DOI: 10.24843/JLK.2019.v08.i02.p10
<![CDATA[CBR (Case Based Reasoning) method is a reasoning method that uses old knowledge to overcome new problems. CBR will provide solutions to new cases by looking at old cases that are closest to new cases. One case that can use the CBR method is a case of cesarean section because there are several factors that affect cesarean section as well as features in the system, including: age, number of pregnancies, time of delivery, blood pressure, and heart status so that not everyone can do surgery cesar. In this study a system was used to determine whether a patient could have a cesarean section or not by using the CBR method and calculate similarity using Naive Bayes. The percentage correlation value of each feature is sought using SPSS because each feature has a different effect on the results. The number of cesarean section data was 80 data, in this study were divided into 70% training data (56) and 30% testing data (24). Where the new case data will be compared with the old case data in the database, and then the similarity criteria are calculated based on the existing formula. The results of testing of 24 data testing there are 5 data whose results are incompatible and 19 data whose results are in accordance with the data before it is shared. So that the accuracy of the cesarean section with the CBR method using Nayve Bayes is 79%.]]>
<![CDATA[Sistem Informasi Management Absensi Pegawai CV. Avatar Solution ]]>
<![CDATA[Utama, I Putu Yasa]]>;
<![CDATA[Supriana, I Wayan]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 7 No 3 (2019): JELIKU Volume 7 No 3, Februari 2019 ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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DOI: 10.24843/JLK.2019.v07.i03.p06
<![CDATA[Pendigitalan pekerjaan yang masih manual sangat gencar gencar digunakan di setiap perusahaan, ini dikarenakan mempermudah pekerjaan yang dan menghemat waktu. Ini pun diterapkan di CV. Avatar Solution yang masih menggunakan absensi dengan platform yang sudah ada tetapi masih banyak terjadi kesalahan dalam platform tersebut. Pembuatan Sistem Informasi Management Absensi Pegawai ini ditujukan untuk membantu pegawai dalam melakukan absensi dengan efisien, dan tidak terjadi banyak kesalahan pada sistem ini. Sistem ini sudah dapat membantu melakukan management absensi pegawai pada CV. Avatar Solution.Keywords: Absensi, Digital, Sistem Informasi]]>
<![CDATA[Perancangan Sistem Pengaturan Suhu Ruangan Otomatis Berbasis Mikrokontroler ]]>
<![CDATA[Partamayasa, I Wayan Gede]]>;
<![CDATA[Gede Suhartana, I Ketut]]>;
<![CDATA[Supriana, I Wayan]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 1 (2019): JELIKU Volume 8 No 1, Agustus 2019 ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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DOI: 10.24843/JLK.2019.v08.i01.p12
<![CDATA[A server room is a room that is used to store servers, network communication devices such as routers and switches, and other operational related devices. Server rooms that have high temperatures and humidity will affect the performance of all devices, so the temperature and humidity of the server room must be maintained so that the device is not easily damaged. So from that, the company needs to implement a standard to protect the performance of the devices stored in it. To overcome this problem a device was developed that can automatically control and monitor temperature and humidity. The system will be built using temperature and humidity sensors that are used to monitor the temperature of the room, the condition of the room temperature and humidity of the room will be displayed through a website that can be accessed through the internet network.]]>
<![CDATA[Optimasi Pembobotan Jaringan Syaraf Tiruan Pada Klasifikasi Kanker Payudara ]]>
<![CDATA[Prebiana, Kiki Dwi]]>;
<![CDATA[Santi Astawa, I Gede]]>;
<![CDATA[Supriana, I Wayan]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 1 (2020): JELIKU Volume 9 No 1, Agustus 2020 ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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DOI: 10.24843/JLK.2020.v09.i01.p15
<![CDATA[Klasifikasi adalah proses membedakan sekumpulan model kedalam beberapa kelas data. Salah satu algoritma yang dapat digunakan untuk proses klasifikasi adalah Jaringan Syaraf Tiruan. Salah satu proses yang memepengaruhi proses Jaringan Syaraf Tiruan adalah proses pembobotan jaringan antar neuron pada Jaringan Syaraf Tiruan. Terdapat beberapa metode yang dapat digunakan dalam proses pencarian bobot, seperti algoritma genetika dan Particle Swarm Optimization atau PSO. PSO adalah salah satu metode optimasi pada Artificle Intelegent. Pada penelitian ini akan dilakukan proses pengujian pengaruh parameter PSO terhadap hasil akurasi yang diperoleh oleh Jaringan Syaraf Tiruan. Dari penelitian yang telah dilakukan nilai parameter terbaik PSO yang digunakan adalah w=0.8, c1=1.5, dan c2 = 2.2. Dari penelitian tersebut menunjukan bahwa optimasi pebobotan dengan Particle Swarm Optimization (PSO) dapat meningkatkan rata – rata nilai akurasi sebesar 0.5%.]]>
