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All Journal Kharisma Tech Journal of Technology Research in Information System and Engineering
Hasniati
STMIK KHARISMA Makassar
Computer Science & IT Engineering

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PERBANDINGAN METODE FUZZY SUGENO DENGAN FUZZY TSUKAMOTO PADA SISTEM PREDIKSI HARGA SMARTPHONE BEKAS BERBASIS ANDROID DI WILAYAH MAKASSAR Samuel Pinontoan; Izmy Alwiah Musdar; Hasniati
KHARISMA Tech Vol 14 No 1 (2019): Jurnal KHARISMA Tech
Publisher : STMIK KHARISMA Makassar

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Abstract

This study aims to compare the Fuzzy Sugeno and Fuzzy Tsukamoto methods in the used android smartphone price prediction system based on Android in the Makassar region. The expected benefits of this research are as a service to get used Smartphone price information and pricing before the transaction. The theorems / methods used in this study are Fuzzy Sugeno and Fuzzy Tsukamoto. The research began by designing the Unified Modeling Language (UML). This program is tested using the Black Box Testing and testing method directly in the field. Based on the results of the study it can be concluded that the Fuzzy Sugeno method produces a better predictive value than the Fuzzy Tsukamoto method, with the MAPE value of 11.8% compared to 25.67%.
RANCANG BANGUN SISTEM INFORMASI PENJUALAN MENGGUNAKAN METODE LINEAR SEQUENCE PADA TOKO REJEKI PERKASA MOTOR PALOPO Ferdinand Pangemanan; Sudirman; Hasniati
KHARISMA Tech Vol 14 No 1 (2019): Jurnal KHARISMA Tech
Publisher : STMIK KHARISMA Makassar

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Abstract

This study aims to develop a sales application that can help the Palopo Shop Rejeki Perkasa Motor process sales data and stock items by applying a sequential linear method so that it can support the sales activities of the store. The stages in this study are divided into five, namely analysis and definition of needs, system design and software, implementation and unit testing, integration and system testing, and operation and repair. To obtain data and information that supports the implementation of this research, an application needs analysis is carried out. System design which includes system modeling is done using DFD (Data Flow Diagram) and data modeling using ERD (Entity Relationship Diagram), then implemented using Visual studio 2013 programming language and mysql as its database.
IMPLEMENTATION OF MOTT-SN PROTOCOL IN HOME SECURITY SYSTEM USING MICROCONTROLLER NODEMCU Kevin Suharto; Mohammad Fajar; Hasniati
KHARISMA Tech Vol 16 No 1 (2021): Jurnal KHARISMA Tech
Publisher : STMIK KHARISMA Makassar

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Abstract

This study aims to apply the MQTT-SN communication protocol to a low-cost home security system based on the NodeMCU microcontroller. Data was collected through literature studies and experiments. The designed home security system consists of MQTT-SN client, MQTT-SN Gateway, and MQTT broker. Home security system application designed to run on Android Smartphone devices. Evaluation results of the system with a number of nodes from 2 to 10 nodes show that the MQTT-SN protocol QoS performance such as delay, packet loss, and throughput is good and acceptable. The average size of the delivery packet of MQTT-SN is smaller than that of the MQTT protocol. In addition, the designed home security system successfully sent notifications to the user's mobile device in response to the detection of movement around the sensor location points installed.
SISTEM INFORMASI PENGOLAHAN DATA PIUTANG PADA PT.LESTARI TOUR N’TRAVEL DENGAN MENGGUNAKAN METODE RAPID APPLICATION DEVELOPMENT Anastasia Veronica; Sudirman; Hasniati
KHARISMA Tech Vol 15 No 2 (2020): KHARISMA Tech Journal
Publisher : STMIK KHARISMA Makassar

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Abstract

This study aims to design a system of receivables at PT. Lestari Tour n'Travel becomes a computerized system using Rapid Aplication Development method. Stages in the research is divided into five parts, namely, Requirements Planning, Design Workshop, Implementation. Desktop-designed apps. In the process of making this application, the author uses Visual Basic 6.0 which is part of Visual Studio 2008 for desktop-based applications.
SISTEM DISTRIBUSI BARANG ELEKTRONIK DENGAN METODE DISTRIBUSI LANGSUNG PADA TOKO MULIA Aldy The; Sudirman; Hasniati
KHARISMA Tech Vol 13 No 1 (2018): Jurnal KHARISMA Tech
Publisher : STMIK KHARISMA Makassar

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Abstract

This research aims to assist and improve the distribution process at Toko Mulia in managing data distribution and stock data items that produce reports in the form of detailed information distribution. The research stages are divided into seven stages, that is library study, field study, problem identification, data processing, system design, implementation, and system testing. System design include data modeling using ERD (Entity Relationship Diagram), then implemented using programming language Visual Basic 6.0 and Microsoft Access as database then system testing using black box testing method. The results of this research is the developed information system can manage the data distribution and ordering of electronic that can obtain important information from the resulting distribution report, so it can be used as a reference in determining the distribution strategy and the addition stock by Toko Mulia.
SISTEM INFORMASI BERBASIS WEB UNTUK MONITORING BELAJAR MENGAJAR PADA SMA KRISTEN GAMALIEL Eunike Stacy Winardy; Marlina; Hasniati
JTRISTE Vol 4 No 1 (2017)
Publisher : STMIK KHARISMA Makassar

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Abstract

This research aims to help Gamaliel Christian high school curriculum part in monitoring the continuity of learning materials given by the teacher in teaching and learning in the classroom in compatible with the schedule is by using applications that support. Applications that use web-based so as to facilitate the curriculum and teachers in providing information to all parties involved.
ANALISIS PERBANDINGAN ALGORITMA LEVENSHTEIN DISTANCE DAN JARO WINKLER UNTUK APLIKASI DETEKSI PLAGIARISME DOKUMEN TEKS Michael Julian Tannga; Syaiful Rahman; Hasniati
JTRISTE Vol 4 No 2 (2017)
Publisher : STMIK KHARISMA Makassar

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Abstract

The goal of this study is to measure the performance comparison between Levenshtein Distance and Jaro Winkler algorithms to detect plagiarism in text documents. The test data that were being used in this study consisted of two test data, the test data to measure the similarity algorithms and test data to measure the processing time of the algorithms. The algorithm was tested by using plagiarism detection application to calculate the value of similarity and processing time by both algorithms. After testing, the results of the two tests are averaged and then analyzed the comparison. Results obtained for the comparative analysis of the average similarity of Jaro Winkler algorithm is 80.92%, while for the algorithm Levensthein Distance is 49.43%. Then, comparative analysis of the average processing time of Jaro Winkler algorithm is 0.054 seconds, while the average processing time of Levensthein Distance algorithm is 0.138 seconds. Based on the comparative analysis that has been done, Jaro Winkler algorithm is shown to have a higher similarity accuracy and the processing time is faster than the Levenshtein Distance algorithm in detecting plagiarsime document.
APLIKASI PREDIKSI KERUSAKAN SMARTPHONE MENGGUNAKAN METODE NAIVE BAYES DAN LAPLACE SMOOTHING Randy; Hasniati; Izmy Alwiah Musdar
JTRISTE Vol 5 No 2 (2018)
Publisher : STMIK KHARISMA Makassar

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Abstract

This study aims to build and implement prediction system of smartphone damage on the android platform. This application was built using android studio 2.0 and SQLite database. The recommendation system is a software that aims to assist users by providing recommendations to users when users are faced with large amounts of information. Recommendations are expected to help users in the decision-making process, such as what items to buy, what laptops will be used, or what songs will be heard, and more. This system serves to provide prediction of damage to the smartphone built from the calculation of user input parameters in the form of questions about the symptoms experienced by users on their smartphone, then will generate predictions about the possibility of damage experienced by using methods naïve bayes and laplace smoothing, this method is used in determining an event using previously collected data. The results of this study indicate that the accuracy is not satisfactory with an accuracy rate of 20%.
Implementasi Metode Fuzzy Tsukamoto dalam Menangani Ketersediaan Barang Randy Sugito Djie; Syaiful Rahman; Hasniati
JTRISTE Vol 3 No 2 (2016)
Publisher : STMIK KHARISMA Makassar

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Abstract

This research aims to predict the amount of goods (aluminum casement type) which must be ordered to deal with the availability of goods in the PT. Happy Aluminium. For that aims, it is proposed to use fuzzy Tsukamoto method. Fuzzy Tsukamoto can be applied to predict the amount of goods and tolerate data that is both flexible and volatile. Data collection techniques in this research was conducted through interviews with sources and literature studies. Applications designed using Unified Modeling Language (UML), use case diagrams, class diagrams and activity diagrams. The design of the database using the Entity Relationship Diagram (ERD). Furthermore, the design is implemented using Visual Basic 6.0 programming language and uses MySQL database storage. Results of the research were able to make predictions about the amount of goods (aluminum casement type) to be ordered so it can handle the availability of goods.
IMPLEMENTASI MACHINE LEARNING UNTUK MENGIDENTIFIKASI TANAMAN HIAS PADA APLIKASI TIERRA Dhio Immanuel Salintohe; Hasniati; Izmy Alwiah Musdar
JTRISTE Vol 9 No 1 (2022): JTRISTE
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.845 KB) | DOI: 10.55645/jtriste.v9i1.360

Abstract

Machine learning adalah sebuah teknologi yang dapat dimanfaatkan untuk mendeteksi suatu objek. Pada penelitian ini machine learning digunakan untuk mengidentifikasi tanaman hias pada aplikasi Tierra dan akan memanfaatkan website teachable machine yang menerapkan algoritma convolutional neural network sebagai tools dalam membuat sebuah model machine learning. Teknik pengumpulan data menggunakan metode observasi dan studi dokumen, selanjutnya dihitung persentasi akurasi hasil pengujian. Untuk proses training data pada website teachable machine akan menggunakan 30 gambar tanaman hias dan hasil yang didapat setelah melakukan pengujian menunjukkan tingkat akurasi machine learning menggunakan tools teachable machine adalah sebesar 89% yang artinya machine learning cukup baik untuk diimplementasikan dalam mengidentifikasi tanaman hias pada aplikasi Tierra.
Co-Authors Abdul Munir Aldy The Anastasia Veronica Christofer Veronica Wu Christuaji Nirbawono Atmojo Dhio Immanuel Salintohe Eunike Stacy Winardy Ferdinand Pangemanan izmy alwiah musdar Kevin Suharto Marlina marlina Michael Julian Tannga Mohammad Fajar, Mohammad Randy Randy Sugito Djie Sampurna Panjiwinata Samuel Pinontoan Sudirman Syaiful Rahman