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All Journal Jurnal Ilmiah KOMPUTASI Jurnal INSYPRO (Information System and Processing) JURNAL REKAYASA TEKNOLOGI INFORMASI Jurnal RESISTOR (Rekayasa Sistem Komputer) Jurnal Ilmiah Media Sisfo Kharisma Tech Journal of Technology Research in Information System and Engineering Agents: Journal of Artificial Intelligence and Data Science
Hasniati Hasniati
Prodi Informatika, STMIK KHARISMA Makassar
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering

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Journal : Journal of Technology Research in Information System and Engineering

 1 
IMPLEMENTASI METODE NAÏVE BAYES PADA APLIKASI SISTEM PAKAR BERBASIS WEB UNTUK MENDIAGNOSA KERUSAKAN PADA HARDWARE KOMPUTER Eric Agung Lestari Jiwono; Syaiful Rahman; Hasniati
JTRISTE Vol 4 No 1 (2017)
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (470.07 KB)

Abstract

Improper use on computer can cause a lot of damages especially on the hardware. Even though sometimes the damages are severe, there’s also simple damages. The goals of this study are to design and implement webbased expert system using Naïve Bayes method that can process the rules of computer condition to conclude final answer to the problem and then measure the performance. It begins with making data-flow diagram and entity-relationship diagram. Then, we implements that with PHP as programming language and MySQL as database. Based on research result, the author has managed to build expert system application to diagnose computer hardware problems with 100% accuracy based on 18 test samples with the average time of execution is 0.158845 seconds. With that, visitors can easily understand the nature of their computer problems and how to solve it.
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.
PENERAPAN METODE WHITEHAT SEO ON PAGE PADA WEBSITE WORKERS GUNA MENINGKATKAN TRAFIK WEBSITE Christuaji Nirbawono Atmojo; Abdul Munir; Hasniati
JTRISTE Vol 9 No 2 (2022): JTRISTE
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/jtriste.v9i2.375

Abstract

Tujuan dari penelitian ini adalah agar website terindeks pada mesin pencarian dan mendapatkan lalu lintas pengunjung. Workers adalah website penyedia lowongan pekerjaan yang penggunanya dapat memilih pekerjaan sesuai dengan preferensi mereka. Dalam perilisannya terdapat masalah yang dialami pengelola website Workers yakni tidak terindeksnya website pada mesin pencarian google yang mengakibatkan tidak adanya trafik pengunjung pada website. Masalah ini didasarkan pada data yang dikumpulkan secara kuantitatif melalui tools online seperti Google Analytics dan Google Search Console. Maka digunakan teknik SEO untuk mengatasi masalah tersebut. Dari hasil pengamatan dalam penelitian yang dilakukan, visitor organic website workers meningkat secara signifikan yang awalnhya hanya 17 pencarian organic search pada saat awal sebelum diterapkannya whitehat SEO dapat meningkat hingga 84 orang dari hasil penggunaan SEO whitehat selama 3 bulan yang penggunanya berupa pencarian dari organic search. Meskipun begitu peringkat website pada search engine Google belum optimal karena dipengaruhi tingkat persaingan yang tinggi pada kata kunci yang diterapkan.
Co-Authors Abdul Munir Aldy The Anastasia Veronica Arianti Caroline Layadi Christofer Veronica Wu Christuaji Nirbawono Atmojo Dhio Immanuel Salintohe Eric Agung Lestari Jiwono Eunike Stacy Winardy Ferdinand Pangemanan Hamdan Arfandy Husni Angriani Imin, Jonathan Hansen Ivan Pratama Yunus izmy alwiah musdar Kevin Lorenzo Kevin Suharto Marlina marlina Michael Julian Tannga Mohammad Fajar, Mohammad Randy Randy Sugito Djie Samuel Pinontoan Sudirman Suyono Syaiful Rahman Syaiful Rahman Syamsul Bahri Vivian Evania Liauren Wikarsa , Rex Roald William Philip Yeni Saharaeni Yessy Yessy