IMPLEMENTATION OF SUPPORT VECTOR REGRESSION IN THE PREDICTION OF THE NUMBER OF TOURIST VISITS TO THE PROVINCE WEST NUSA TENGGARA (NTB)

Abstract — Indonesia has a variety of interesting tourist destinations to visit in each region. One area that is used as a favorite tourist destination is the Province of West Nusa Tenggara (NTB). Data The number of tourists visiting the NTB province from 2014 to 2020 tends to change based on data obtained from the Website of the NTB Provincial Tourism Office. The data on the number of visitors will continue to change, even if there is a possibility that it will increase. This can lead to the unpreparedness of the government and other tourism actors in providing the facilities and infrastructure needed by visitors when there is an increase in the number of tourist visits coming to NTB. Therefore, it is necessary to predict the number of tourist visits to NTB with accurate results. In this study, predictions of the number of tourist visits to the Province of NTB were made using the support vector regression method. This research resulted in an application to predict the number of tourist visits to NTB based on Event, Month, and Year. so that it can provide predictive results that are close to the actual value under normal conditions. The data used in this study is data on the number of tourist visits in 2017-2021 and events held in 2017-2021

DESIGNING CLASS SCHEDULE INFORMATION SYSTEM BY USING TABOO-SEARCH METHOD

Drafting of class schedule at the Faculty of Information and Communication Technology, Mataram University of Technology (FTIK UTM) is still done manually. So that, there are some problems such as lecturer teaching schedule at the same time at one time as well as student learning time at the same time at one time and studying more than 3 times a day. Therefore, manual scheduling requires a lot of time and it must be done very carefully. The method used to solve this problem is the Taboo- Search Method which is used to solve the problem of scheduling. The Taboo-Search Method is a method that seeks the best solution from existing solutions by creating a list of solutions or taboo lists, solutions that have been used previously will no longer be displayed for the next problem. The research method used in this research is the method of research and research and development which starts from the preliminary stage to find problems that occur up to the implementation stage so that it is generated an information system of course schedule at the Faculty of Information and Communication Technology, Mataram University of Technology. The purpose of this research is to produce a class schedule information system so that it can help arrange class schedules more quickly and precisely

Disease Detection of Rice and Chili Based on Image Classification Using Convolutional Neural Network Android-Based

The current development of machine learning makes it easier for humans to obtain information, especially from images. The presence of processing assistance from machines can increase the accuracy of the information provided to further convince the recipient of the information. Rice and chili farmers in Indonesia have experienced many disease attacks from several types of plant diseases. Not many farmers understand and are good at guessing the diseases that attack their rice and chili plants. So many rice and chili farmers experienced crop failure. This research aims to build a disease-detection system for rice and chili plants based on Android-based image classification. The machine learning method used is Convolutional Neural Network (CNN) with the Mobile Net version one model combined with the Sequential CNN and Tensor Flow Lite models. The results of the transfer learning evaluation on the Mobile Net version 1 model and the sequential CNN model obtained training accuracy of 0.88% with a loss of 0.34%, validation accuracy of 0.84% with a loss of 0.40%, and testing accuracy of 86% with a loss of 43%. Each uses batch 69 of the total training data stopping at epoch 30 from epoch 100. The results of field testing on the application of rice and chili disease detection on 20 images of rice and chili plants can detect Rice Neck Blast disease with a probability of 75% to 100% and Rice Hispa with a probability of 97% to 100%. It can also detect chili plant diseases such as Chili Yellowish with a probability of 83%, Chili Leaf Spot with a probability of 99%, Chili Whitefly with a probability of 91% to 95, Chili Healthy with a probability of 78% to 99%, and Chili Leaf Curl with a probability 75 to 76%. The probability obtained varies according to how likely damage is to rice and chili plants. CNN with the Mobile Net version one model and the Sequential model can extract and classify images so that it has maximum information processing capabilities. This research can make it easier to help farmers identify diseases that attack their rice and chili plants. &nbsp

DATA MINING USING RANDOM FOREST, NAÏVE BAYES, AND ADABOOST MODELS FOR PREDICTION AND CLASSIFICATION OF BENIGN AND MALIGNANT BREAST CANCER

This study predicts and classifies benign and malignant breast cancer using 3 classification models. The method used in this research is Random Forest, Naïve Bayes and AdaBoost. The prediction results get Random Forest = 100%, Naïve Bayes = 80% and AdaBoost = 80%. Results using Test and Score with Number of Folds 2, 5 and 10. Number of Folds 2 Random Forest model Accuracy = 95%, Precision = 95% and Recall = 95%, Naïve Bayes Accuracy = 93%, Precision = 93% and Recall 93%, AdaBoost Accuracy = 90%, Precision = 90% and Recall = 90%. With Number of Folds 5 with Random Forest = 96%, Precision = 96% and Recall 96%. Naïve Bayes Accuracy value = 94%, Precision = 94% and Recall = 94%, AdaBoost Accuracy value = 93%, Precision = 93% and Recall = 93%. With Number of Folds 10 Random Forest model = 96%, Precision = 96% and Recall 96%. Naïve Bayes Accuracy value = 94%, Precision = 94% and Recall = 94%, AdaBoost Accuracy value = 92%, Precision = 92% and Recall = 92%. Of the 3 models used, Random Forest got the best classification results compared to the others

LOMBOK PEARL QUALITY CLASSIFICATION USING A COMBINATION OF FEATURE EXTRACTION AND ARTIFICIAL NEURAL NETWORKS BASED ON SHAPE

Lombok is attracted to the Moto GP event, which is held annually. Various tourism brands are owned by the island of Lombok, one of which is Mutiara. The ideal Pearl is perfectly round and smooth, but there are a variety of other shapes as well. One method that can be used to process Pearl's image is Computer Vision. For that, it is necessary to have a way to classify the quality of a Pearl based on its shape. The purpose of this study is to propose a system for pearl image classification by combining feature extraction with artificial neural networks. The method used in this study is GLCM feature extraction and Neural Networks. The proposed system can provide good classification results by combining the GLCM method and the Neural Network. This study uses Epochs 5, 10, 15, 30, 50, 100, 200, 300, and 500 with a learning rate of 0.5. The results of this study indicate that Epoch 100 gives the highest accuracy, 91.66%

Pelatihan Pengelolaan Website Pada Kantor Desa Duman

Tujuan kegitan Pengabdian kepada Masyarakat (PkM) adalah untuk meningkatkan kemampuan perangkat desa duman dalam mengelola website. Mitra kegitan adalah Desa Duman (perangkat desa) yang berjumlah 7 orang. Metode pelaksanaan knowledge transfer melalui kegiatan Ceramah dan praktik. Tahapan kegitan penagbdian perencanaan, pelaksanaan dan evaluasi. Kegitan pengabdian telah memberikan pengalaman, pemahaman dan keterampilan mitra dalam mengelola website dengan indikator mitra dapat membuat akun, mengisi konten dalm bentuk teks, foto, dan video secara mandiri. Kegitan pelatihan perlu dilakaukan secara berkesinambungan agar perangkat desa dapat secara mandiri dalam pengelolaan website sehingga dapat memberikan dampak pada pelayanan informasi kepada masyarakat dan pemerintah tentang kemajuan dan kedala-kendala di desa. Website Management Training in the Office Duman Village  The purpose of this training is to improve the ability of Duman village officials in managing websites. The activity partner is Duman Village (village apparatus) which consists of 7 people. The method of implementing knowledge transfer is through lectures and practice activities. Stages of activity planning, implementation, and evaluation. Service activities have provided partners experience, understanding, and skills in managing websites with indicators that partners can create accounts, fill out content in the form of text, photos, and videos independently. Training activities need to be carried out on an ongoing basis so that village officials can independently manage the website so that they can have an impact on information services to the community and government about progress and obstacles in the village.

STRATEGI CROSSWORD PUZZLE UNTUK MENINGKATKAN MOTIVASI BELAJAR SISWA PADA MATA PELAJARAN SEJARAH KEBUDAYAAN ISLAM DI KELAS III MI AL-MA’RIFATUL ISLAMIYAH DASAN AGUNG MATARAM TAHUN AJARAN2018/2019

Guru adalah pendidik profesional dengan tugas utama mendidik, mengajar membimbing, mengarahkan, menilai dan mengevaluasi peserta didik. Dengan tugas mendidik seorang peserta didik. Begitu halnya dengan motivasi belajar, khususnya pada pelajaran Sejarah Kebudayaan Islam. Akan tetapi pada kenyataannya, terlihat bahwa motivasi belajar peserta didik khususnya kelas III di MI Al-Ma’rifatul Islamiyah pada mata pelajaran SejarahKebudayaan Islam tergolong rendah, sedangkan pendidik sudah berusaha untuk meningkatkan hasil belajar peserta didik dengan menggunakan metode pembelajaran yaitu ceramah dan mencatat, namun hasil belajar peserta didik kelas III masih saja banyak peserta didik yang belum bisa mencapai KKM. Maka penulis dalam penelitian ini mencoba menerapkan Strategi Crossword Puzzle untuk meningkatkan motivasi belajar peserta didik yang dilihat dari hasil belajar yang diperoleh peserta didik. Penelitian ini bertujuan untuk meningkatkan motivasi belajar Sejarah Kebudayaan Islam melalui penerapan strategi Crossword Puzzle.Permasalahan yang akan dibahas yaitustrategi Crossword Puzzle dan motivasi belajar peseta didik. Jenis penelitian tindakan kelas (PTK). Urutan kegiatan penelitian mencakup: (1) perencanaan, (2) pelaksanaan, (3) observasi, (4)refleksi. Dalam pengumpulan data, Penulis menggunakan teknik observasi, dokumentasi, pengukuran tes hasil belajar dan angket. Sedangkanuntuk analisisnya, penulis menggunakan teknik analisis deskriptif kualitatif di dukung kuantitatif. Hasil penelitian menunjukkan penerapan strategi Crossword Puzzlepadapembelajaran Sejarah Kebudayaan Islam dapatmeningkatkan motivasi belajar peserta didik. Hal itu dilihat berdasarkan pesentase skor hasil belajar yang diperoleh pada observasi awal yaitu ketuntasan klasikal 44% dan nilai rata-rata 73. Dan presentase skor yang diperoleh pada siklus I yaitu observasi aktivitas siswa 71%, observasi aktivitas guru 89%, hasil belajar ketuntasan klasikal 72% dan nilai rata-rata 79. Dan presentase skor yang diperoleh pada siklus II yaitu observasi aktivitas siswa 89%, observasi aktivitas guru 91%, hasil belajar 94% dan nilai rata-rata siswa 84. Kata kunci : StrategiCrossword puzzle, Motivasi Belaja

SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN LANSUNG TUNAI MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING BERBASIS WEB PADA DESA TEMPOS

Bantuan lansung tunai (BLT) adalah program bantuan pemerintah berjenis pemberian uang tunai atau beragam bantuan lainnya, baik bersyarat maupun tak bersyarat untuk masyarakat miskin. Penelitian ini menggunakan model manajemen metode Simple Additive Weighting (SAW) dengan menentukan keriteria-kriteria yang dijadikan acuan dalam pengambilan keputusan yaitu jumlah penghasilan, status perkawinan, jumlah tanggungan, dan umur. Hasil proses analisis berupa data keluarga miskin yang berhak menerima BLT. Sistem yang dapat membantu pengambilan keputusan untuk menentukan keluarga yang berhak menerima BLT. Oleh karna itu dipenelitian ini dibangun sistem pendukung keputusan untuk pemberian BLT. Dengan adanya Sistem ini, dapat mempermudah dan mempercepat pengolahan data serta mempengaruhi kinerja sehingga menjadi lebih optimal. Hasil yang diharapkan adalah tersedianya sistem pendukung keputusan menggunakan metode SAW yang dapat menentukan keluarga miskin yang berhak menerima bantuan lansung tunai sehingga dana tersebut jatuh kepada keluarga yang benar-benar membutuhkan

SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN LANSUNG TUNAI MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING BERBASIS WEB PADA DESA TEMPOS

Bantuan lansung tunai (BLT) adalah program bantuan pemerintah berjenis pemberian uang tunai atau beragam bantuan lainnya, baik bersyarat maupun tak bersyarat untuk masyarakat miskin. Penelitian ini menggunakan model manajemen metode Simple Additive Weighting (SAW) dengan menentukan keriteria-kriteria yang dijadikan acuan dalam pengambilan keputusan yaitu jumlah penghasilan, status perkawinan, jumlah tanggungan, dan umur. Hasil proses analisis berupa data keluarga miskin yang berhak menerima BLT. Sistem yang dapat membantu pengambilan keputusan untuk menentukan keluarga yang berhak menerima BLT. Oleh karna itu dipenelitian ini dibangun sistem pendukung keputusan untuk pemberian BLT. Dengan adanya Sistem ini, dapat mempermudah dan mempercepat pengolahan data serta mempengaruhi kinerja sehingga menjadi lebih optimal. Hasil yang diharapkan adalah tersedianya sistem pendukung keputusan menggunakan metode SAW yang dapat menentukan keluarga miskin yang berhak menerima bantuan lansung tunai sehingga dana tersebut jatuh kepada keluarga yang benar-benar membutuhkan

RANCANG BANGUN SISTEM PAKAR DIAGNOSA PENYAKIT PADA TANAMAN CABAI DENGAN METODE CERTAINTY FACTOR

Teknologi telah menjadi kebutuhan yang sangat penting bagi keberlangsungan hidup setiap manusia. Mulai dari hal-hal yang sederhana hingga hal-hal rumit teknologi selalu memegang peranan penting, tak terkecuali pada bidang pertanian. Munculnya berbagai masalah yang dialami oleh para petani khususnya petani cabai seperti masalah penyakit tanaman dan hama tanaman membuat para petani kesulitan dalam mengatasinya. Tak jarang masalah-masalah tersebut mengakibatkan para petani mengalami kerugian besar karena gagal panen. Penelitian ini bertujuan untuk membuat suatu Sistem Pakar Diagnosa Penyakit pada Tanaman Cabai dengan Metode Certainty Factor. Dimana sistem pakar ini merupakan aplikasi berbasis website yang berisi pengetahuan pakar ahli tanaman cabai. Aplikasi ini dapat diakses oleh para petani untuk mendiagnosa dan mengetahui penyakit pada tanaman cabai mereka. Pada aplikasi ini sistem mampu mengidentifikasi 7 jenis penyakit berdasarkan pengetahuan pakar serta terdapat solusi mengenai penyakit pada tanaman cabai, sehingga dapat dilakukan penanganan yang sesuai untuk mengatasi permasalahan tersebut. Selain itu diagnosa penyakit dengan aplikasi ini memilki tingkat akurasi yang cukup baik dan sesuai dengan pengetahuan pakar ahli