KLASIFIKASI PENENTUAN PENERIMA PROGRAM KELUARGA HARAPAN (PKH) MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) PADA KANTOR DINAS SOSIAL LOMBOK TIMUR

The Family of Hope Program (PKH) is a program of giving cash to Very Poor Households (RTSM) based on established terms and conditions. Where PKH was implemented in Indonesia in 2007, but in East Lombok PKH was only implemented in 2011. However, judging from the data of PKH recipient members, there are still many RTSM who do not get the PKH assistance. This situation identified the data collection method and the determination of priorities that were not yet on target. From these problems, it is necessary to utilize data mining techniques using the support vector machine (SVM) algorithm in determining PKH recipients. After testing 4 times using different K-Fold Validation on the cross validation operator. K-Fold Validation functions to divide the amount of training data and testing data on the data being tested. Then the accuracy results that have been tested are 95.41%.DOI : 10.29408/jit.v3i1.180

Identifikasi Kematangan Buah Mentimun Berbasis Citra Digital Menggunakan Jaringan Syaraf Tiruan Backpropagation

Cucumber, cucumber, or cucumber (Cucumis sativus L) are plants that produce edible fruit. Especially in NTB cucumber production in 2015 reached 5,224 tons with a harvest area of 326 hectares. It is at number five after onions, chili, tomatoes and cabbage [2]. There are several parameters that can affect the quality of cucumbers, one of which is the shape, level of planting age and maturity [5]. Maturity of cucumbers can be recognized physically in terms of skin texture and color. The identification process of physical properties conventionally still has many disadvantages including the time needed is relatively long and produces a variety of products due to the limitations of human visuals. This becomes an obstacle so that it requires the application of computer image processing technology, especially in agriculture. Because of this, the researchers proposed using GLCM as feature extraction and using Backpropagation artificial neural networks for testing and training so that the research resulted in an accuracy of 89.6%.DOI : 10.29408/jit.v2i1.97

Prototipe Robot Pemantau Suhu Dalam Zona Kebakaran Gedung Menggunakan Telemetri Jaringan Nirkabel

The building fire can be a serious problem that could Interfere economic stability. Firefighters often have problems in handling if they are in the building there is fog or smoke. Therefore, the presence of this monitoring system is expected to present the data in the form of temperature information in the fire zone to help them. This study starts from the collection of materials and equipment, hardware design stage in the form of a wheeled robot while the design of the software comprising a transmitter section is a microcontroller program and the interface program as a receiver. The research result mobile robot can move properly with the remote control within a distance of 20 m. Video on this robot can be displayed in realtime within a distance +15 m of the screen Because the raspberry pi 3 has a coverage area that is not so far away as well as a temperature sensor capable of measuring a very good accuracy in the range of 250C-500CDOI : 10.29408/jit.v1i2.90

Pengenalan Citra Logo Kendaraan Menggunakan Metode Gray Level Co-Occurence Matrix (Glcm) dan Jst-Backpropagation

A car is a vehicle that has a varied shape or model but the difference is the brand or logo. Vehicle logos have their own meaning and meaning for car industry companies. The logo should have a practical and effective or efficient function so that the logo form is part of the marketing and branding program of the car industry company [1]. There are three types of car logos that are now known, in the form of symbols, text, or a combination between the two. The logo is always in the front and back of the car body and usually has a lighter color than the color of the vehicle. One that supports the development of technology is how to recognize a vehicle either from the brand, shape, model and color of the vehicle. Some references that are deemed feasible to help this research include utilizing the weaknesses and weaknesses of the results of previous research, including a paper entitled. Scale Invariant Feature Transform (SIFT) [2]. SIFT is combined with Logistic Regression [3] based on Gradient Orientation Histogram (HOG). Logo Recognition Using Probabilistic Neural Networks [4]. Therefore, the researchers wanted to focus on the logo recognition using the extraction of the Gray Level Co-occurrence Matrix (GLCM) feature. Testing and training testing using ANN-Backpropagation. From the results of this study the best accuracy obtained 95.7%, so that GLCM and ANN-Backpropagation can recognize the image of the vehicle logo.DOI : 10.29408/jit.v1i1.89

IMPLEMENTASI WEB SERVICE DALAM PENGEMBANGAN SISTEM INFORMASI DESA BERBASIS ANDROID PADA DESA DARMASARI KECAMATAN SIKUR KABUPATEN LOMBOK TIMUR

The Village Office of Darmasari, Sub-district of Sikur is a fairly new office of the village. Darmasari Village is a part of the Semaya Village Expansion which was inaugurated on November 15, 2010. When the present researcher got the opportunity to observe it, the researcher took the initiative to develop an existing system which is called SID, became an android-based system which would help in the dissemination and get information quickly. After carrying out the analysis and conducting several interviews with the village staff, the Darmasari Village Office indeed needed an Android Application as a liaison medium between village officials and the community which would certainly be more efficient than its use and from the previous method of having to access the website in the browser. In realizing the development of this SID system, the present researcher used the SID Web server as the main ingredient, XAMPP as a server, and Android Studio as the media for making Android applications. This Android-based SID Darmasari can be used to help and make it easier for people to receive information quickly in public services to be more efficient.DOI : 10.29408/jit.v2i2.145

Pendataan Mitra Produk Herbal CV. Rinjani Tirta Lombok Timur Berbasis Geographic Information System (GIS)

The purpose of this research is to facilitate consumers in finding partners who sell herbal products from CV. Rinjani Tirta which is in East Lombok.Where the company is engaged in herbal products and has more than 86 products. In fact, it is one of the companies that has obtained a BPOM permit in East Lombok and has been recommended by the BPOM to continue to participate in activities held by the BPOM and the government related to permits, seminars, and product exhibitions The use of a Geographic Information System (GIS) can help provide information on the data collection of partners working with companies. The author researched with several stages, namely information gathering, planning, development of initial product formats, initial product trials, field trials, product revisions, and final results. The location of the research is CV. Rinjani Tirta located in the village of Ajani Timur, Suralaga subdistrict. The results of this study are very helpful CV. Rinjani Tirta in promotion and gathering information about partners and areas that have been widely spread and make it easier for consumers to find herbal products. Besides, to streamline the work of employees and of course indirect promotions from partners

LAPORAN PRAKTIK LAPANGAN TERBIMBING (PLT)

Praktik Pengalaman Terbimbing atau disebut dengan PLT merupakan salah satu mata kuliah praktik lapangan dengan bobot 3 SKS yang wajib ditempuh oleh semua mahasiswa jurusan kependidikan di Universitas Negeri Yogyakarta. PLT bertujuan agar mahasiswa mampu mengembangkan dan menerapkan ilmu yang dipelajari di lingkungan kampus kepada lingkungan atau lembaga pendidikan yang bersifat formal maupun non formal sebagai bekal untuk menjadi pendidik. Praktik Lapangan Terbimbing (PLT) ini memiliki bobot sebanyak 3 SKS lapangan. Pada tahun 2017, mahasiswa diwajibkan menempuh minimal 256 jam di sekolah untuk melakukan kegiatan baik mengajar maupun non mengajar. Sebelum pelaksanaan Praktik Lapangan Terbimbing, mahasiswa diwajibkan menempuh dan lulus dalam mata kuliah prasyarat yaitu microteaching. Kegiatan Praktik Lapangan Terbimbing dilaksanakan di SMK Muhammadiyah 3 Yogyakarta yang beralamat di Jl. Pramuka No. 62 Giwangan Yogyakarta mulai tanggal 15 September 2017 sampai dengan 15 November 2017. Rencana kegiatan PLT dengan total perencanaan yaitu 324 jam. Persiapan pengajar berupa penyusunan administrasi mengajar yang terdiri dari silabus, RPP, dan bahan mengajar. Sedangkan hasil kegiatan PLT yang terlaksana 330,5 jam total dari seluruh kegiatan, itu artinya total jam yang direncanakan sudah terpenuhi. Hasil persiapan mengajar adalah Rencana Pelaksanaan Pembelajaran (RPP), materi pembelajaran dan jobsheet

PENDAMPINGAN PEMBELAJARAN NUMERASI DAN KEPEMIMPINAN MENGGUNAKAN TEKNOLOGI DIGITAL UNTUK SISWA SB KEPONG MALAYSIA

Numerasi atau yang lebih dikenal dengan pembelajaran angka saat ini menjadi dasar fundamental pembelajaran di sekolah. Numerasi menjadi bagian penting dalam menunjang bidang ilmu lain dan dapat diterapkan secara aplikatif di kehidupan sehari-hari. Berdasarkan hal tersebut, dibutuhkan suatu pendekatan teknologi yang dapat menunjang proses pembelajaran numerasi sekaligus literasi kepemimpinan menggunakan teknologi digital. Pengabdian ini dilakukan secara luring dengan melakukan kegiatan di Sanggar Bimbingan (SB) Kepong Malaysia. Kegiatan pengabdian ini dibagi menjadi dua sesi yaitu pembelajaran numerasi dan literasi kepemimpinan menggunakan teknologi digital. Sesi numerasi menggunakan teknologi digital berupa game interaktif yang dapat dimainkan secara berkelompok. Sedangkan untuk sesi pembelajaran digital menggunakan video interaktif sekaligus pemaparan. Metode evaluasi yang digunakan adalah angket dengan butir tingkat penerimaan teknologi terhadap dua topik numerasi dan kepemimpinan. Hasil kegiatan pengabdian menunjukan bahwa sebesar 82,7% anak-anak memahami pembelajaran numerasi menggunakan teknologi digital dan 86,5% terkait pemahaman kepemimpinan. Implementasi penggunaan teknologi dalam menunjang pembelajaran numerasi dan kepemimpinan di SB Kepong memberikan dampak positif terhadap penerimaan terhadap anak-anak Sanggar Bimbingan

Character Translation on Plate Recognition with Intelligence Approaches

In recent years, the number of automobiles in Indonesia has expanded. This rise has a knock-on impact on street crime. On this problem based, a preventative road safety prevention system is required. This research contribution is to develop an efficient algorithm for detecting vehicle license plates. This study's technique incorporates artificial intelligence technology with character translation. Yolov3 and Yolov4 are the artificial intelligence systems employed in this study. The detection of objects in the form of license plates is the result of this approach. In artificial intelligence, object detection results are utilized as input for image processing. The image processing method is used to translate characters. Optical Character Recognition (OCR) is used to decode the characters in the image precisely. The artificial intelligence data training resulted in a 76.53% and 89.55% mean average precision (mAP) level. Using OCR, the system is capable of character translation. These results give an opportunity to develop more complex image-processing applications

Penerapan Metode Naïve Bayes Untuk Penentuan Penerima Beasiswa Program Indonesia Pintar (PIP).

PIP is the provision of educational cash assistance to school-aged children from underprivileged families who are marked with a smart Indonesia card (KIP). The purpose of this research is to determine the performance of the Naïve Bayes method in classifying data on students who are eligible and who are not eligible to receive a PIP scholarship at SMAN 1 Sukamulia, because this school is still experiencing problems in the decision-making process for determining potential PIP scholarship recipients, because there are no a system that can assist in processing student data that is eligible and not eligible to get the PIP scholarship. Therefore, for data processing, researchers tried to implement a new system with the Data Mining concept using the Naïve Bayes method, by carrying out 9 tests using Cross Validation starting from K-Fold Validation 2 to 10, obtaining the highest accuracy results in the 9th test. using K-Fold Validation 10 which is equal to 92.81%. Also obtained was an Area Under Curve (AUC) value of 0.973%, where AUC is a parameter used in classification analysis to determine the best model for predicting a class or attribute. AUC itself has a value range of 0-1, which means that the closer the AUC value is to 1, the better the prediction or diagnosis of the attribut