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SMARTICS Journal
Published by Universitas Kanjuruhan Malang
ISSN : -     EISSN : 24769754     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering
SMARTICS Journal's aims is to disseminate research on applied computer science or information technology by publishing the original articles. The scope of SMARTICS are electrical, electronics, controls, information system, and applied technology.
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "Vol 9 No 2 (2023): SMARTICS Journal (Oktober 2023)" : 5 Documents clear
Marketplace Entrepreneur Sorgum Menggunakan Klastering K Medoid Saurina, Nia; Noerhartati, Endang; Revitriani, Marina
SMARTICS Journal Vol 9 No 2 (2023): SMARTICS Journal (Oktober 2023)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v9i2.8323

Abstract

Marketplace is a virtual market where the market is a meeting place for buyers and sellers to make transactions. Wijaya Kusuma University Surabaya has established an Entrepreneurship Sorghum Unit (UES) starting in 2009 and is collaborating with Sorghum Entrepreneurs in several areas in East Java. The objectives of this research are: (1) creating a marketplace for Sorghum Entrepreneurs who have joined UES, (2) Classifying using the K-Medoid method to group Sorghum Entrepreneurs based on the income that has been obtained by UES, (3) Conducting mapping based on clustering results so that UES can provide assistance to sorghum entrepreneurs. From the results of the questionnaire, obtained data on the level of desire for UES for each variable from 35 sorghum entrepreneurs as respondents. Quantitative data obtained is then entered and then proceed with the clustering stage. The data is divided into several clusters based on the type of sorghum, products sold and sales results. After that, the cluster performance calculation is carried out by calculating the k-fold value. analysis of the results of testing the effect of the k-fold value is the best percentage found in the k-fold value = 6 with an accuracy value of 34.597%.
Rancang Bangun Sistem Aplikasi Monitoring Daya Listrik Rumah Berbasis Android Budianto, Alfa Wahyu; Utama Endriansyah, Rizki Putra; Firmansyah, Muhammad Ferrari; Tri Sulistyanto, Muhammad Priyono; Aditya Nugraha, Danang; Ghufron, Muhammad; Azhiman, Fauzan; Pranata, Kurriawan Budi
SMARTICS Journal Vol 9 No 2 (2023): SMARTICS Journal (Oktober 2023)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v9i2.8592

Abstract

The need for household-scale electricity consumption is very closely dependent on household appliances that use electrical energy. The demand for household electricity has increased along with the Work From Home (WFH). If this is not managed optimally based on the aspect of its use, it will unconsciously have an impact on economic spending. The purpose of this study focuses on a prototype monitoring system for electrical quantities in the form of voltage, current strength and electric power in real time via the Android platform. The prototype that was created was able to collect realtime data every 1 minute and 5 minutes, respectively, resulting in a measurement accuracy of 92.99% and 81.85%. As well as reading accuracy of (36.60 + 2.42) Watt and (27 + 4.96) Watt. Based on the error results and the results of the reading accuracy of the prototype, a comparison was made between the delay of data retrieval per 1 minute and 5 minutes, it can be concluded that it has a higher reading accuracy per 1 minute. So that the suggestions and recommendations from further researchers regarding the design of electrical energy monitoring management use a delay time of more than one minute so as not to lose a lot of data information from the measurement results.
Perancangan Aplikasi Sistem Penilaian Kinerja Karyawan Metode TOPSIS Berbasis Website Ardiansyah, Fatur Rachman
SMARTICS Journal Vol 9 No 2 (2023): SMARTICS Journal (Oktober 2023)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v9i2.8767

Abstract

Technological advancements have a profound impact on various aspects of human life, including the world of work. The range of technologies used in work settings is extensive, ranging from simple to complex systems. However, many areas within the current scope of work have yet to fully embrace technological advancements. Recruitment, development, improvement, and evaluation processes are among those that can benefit from technology integration. At PT Sanjayatama Lestari, employee appraisals are still carried out manually, relying on supervisor assessments recorded in notes or word processing and number processing application files. These assessments may lack objectivity and transparency. This research aims to address the issue by designing a decision support system for employee evaluation at PT. Sanjayatama Lestari Surabaya. The waterfall method will be used to develop the application, utilizing a web-based programming language for user convenience and device compatibility. The application's design aims to enhance user experience, ensure valid data, and promote transparency in the employee evaluation process.
Implementasi Metode Extreme Programming Pada Aplikasi Pengelolaan Sewa Mobil Berbasis Web Moh. Fauzan; Noor Al Azzam, Mohammad
SMARTICS Journal Vol 9 No 2 (2023): SMARTICS Journal (Oktober 2023)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v9i2.8890

Abstract

To design and develop a web-based car rental management application for the case study of Zalfa Rent Car writer uses the Extreme Programming (XP) method. The main objective of this research is to increase the efficiency and effectiveness of the car rental management process within the company. The first step in this research is to analyze the needs at Zalfa Rent Car related to car rental management. Next, application development begins using the XP cycle. After development is complete, final testing is carried out to verify that the application has met the needs and requirements that have been needed. The test results will be evaluated to identify deficiencies and make the necessary improvements. It is hoped that the results of this research will produce a web-based car rental management application that is efficient, reliable, and in accordance with the needs of Zalfa Rent Car. This research also contributes to an understanding of the application of the Extreme Programming method in developing web-based software for the car rental industry. Keywords: Car Rental Management Application, Web Based, Extreme Programming
Pemanfaatan Metode Multiclass Support Vector Machine dalam Klasifikasi Penyakit Daun Kacang Tanah Fakhrunnia, Brahma Ratih Rahayu; Aziz, As'ad Shidqy; Sesoca, Jendra
SMARTICS Journal Vol 9 No 2 (2023): SMARTICS Journal (Oktober 2023)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v9i2.9077

Abstract

Peanuts are one type of agricultural crop from commodity crops that can provide additional income opportunities for farmers in Indonesia. In addition, the benefits of peanuts are as a source of protein and vegetable fat for human body, so they are also much needed by the food industry. However, in increasing soil productivity there is a decrease in quality and quantity caused by one of the factors, namely plant diseases. Efforts that can be made in maintaining peanut productivity are to prevent early by applying early detection technology. This study presents the application of digital image processing application-based technology using the Multiclass SVM One-Against-One (OAO) strategy to classify the types of leaf disease of peanut plants based on texture feature extraction on the diseased parts of peanut leaves using the Gray Level Co-Occurrence Matrix (GLCM) method. In the classification process using the M-SVM method the OAO strategy will use three kernels, namely polynomial kernel, linear kernel and RBF kernels. Based on the experimental results, the best accuracy is obtained, namely by using GLCM texture feature extraction with a distance of d = 1 and angle 90 degree of and classified using the M-SVM method, the OAO strategy with polynomial kernels provides the highest accuracy results, namely 96.39% for leaf spot class, 92.79% for leaf rust class, 96.39% for eye spot class and 100% for normal class

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