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

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

Prediksi Tingkat Kelancaran Kredit BSU BMT Tunas Harapan Syari’ah Pringgasela Kabupaten Lombok Timur Menggunakan Algoritma Neural Network

The role of credit in a cooperative is very important. With the credit can be a source of profit for the cooperative. The cooperative was founded with the aim of prospering its members. One of the advantages is that cooperative members can apply for credit loans. To approve the proposed loan, it is necessary to analyze the credit submitted by the members. This has become one of the difficulties for several cooperatives, one of which is KSU BMT Tunas Harapan Syari'ah which is located in thePringgasela village, Pringgasela District, East Lombok Regency. The problem that often arises is that the analysis conducted is often incorrect, resulting in a prolonged bad credit in installment payments. The reason is that cooperatives always use statistical data which is sometimes inaccurate because there is no processing using data processing methods. Therefore, the neural network data mining method can be used as a tool to analyze which customers are problematic and not problematic. From the results of the research that has been done, it produces an accuracy of 96.19% and an AUC of 0.97

Rancang Bangun Smart System Pendeteksi Air Layak Minum Pada Sumur di Daerah Pesisir Pantai Berbasis Internet Of Things (IoT)

Water is an important natural resource for human life, but in some coastal areas, the availability of clean water is often a serious problem. One source of water used by communities in these areas is wells, which often do not meet health standards for consumption. Manual methods for detecting well water quality still require long, expensive, and inefficient processes. Therefore, the development of a system that can detect water quality in real-time and provide fast and accurate information to the community is needed. The Internet of Things (IoT) technology, which allows objects to be connected to the internet, provides a solution that can be utilized. In this study, a Smart System was designed using salinity and manganese sensors to monitor the real-time quality of well water in coastal areas. Data from these sensors are sent to a server through the internet and analyzed to provide information to users via the Blynk application on their smartphones. With this system, communities can directly monitor the quality of well water, take appropriate actions, and safeguard the health of local residents. Additionally, this system can also assist relevant government or institutions in monitoring and taking quick actions in response to changes in well water quality in coastal area