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All Journal Computer Engineering and Applications Journal Annual Research Seminar CCIT (Creative Communication and Innovative Technology) Journal Sriwijaya Journal of Informatics and Applications Jurnal Generic
Rizki Kurniati
Universitas Sriwijaya
Computer Science & IT Engineering

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Initial Centroid Determination Using Simulated Annealing Algorithm Osvari Arsalan; Rizki Kurniati; Elin Darnela
Generic Vol 13 No 1 (2021): Vol 12, No 1 (2021)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

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Initial randomly generated centroids are commonly used in k-Means clustering method. Random initial centroids k-Means to be trapped in optimum local solution which results in sub-optimal cluster quality. This study examines Simulated Annealing algorithm in determining initial centroids on k-Means. Each k-Means clustering will be tested on result of reduction and without dimension reduction. Based on the results evaluation of k-Means clustering results with initial centroid Simulated Annealing algorithm improve quality cluster with percentage change value 21.2% in the high dimensional data and 25.1% in the dimension reduction data, this shows that initial centroid calculated Simulated Annealing algorithm is able to obtain the best cluster with significant results.
Initial Centroid Determination Using Genetic Algorithm in Data Clustering Rizki Kurniati; Osvari Arsalan; Yulinda Ramadhana
Generic Vol 13 No 1 (2021): Vol 12, No 1 (2021)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

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Clustering K-Means using random initial determination centroid. Generated random centroids using K-Means trapped in optimum local which results in poor clustering quality. Initial centroids in k-means will examine effect of genetic algorithms are each tested on data with dimension reduction and without dimension reduction. Based on the results of initial centroid testing obtained from genetic algorithms, quality of cluster results increase 54.9% in high dimensional data and 52.4% in data had been carried out for dimensional reduction. This shows that K-Means clustering with initial centroids obtained from genetic algorithm calculations has best cluster with significant results.
Workshop Teknik Keamanan Dalam Menggunakan Internet Pada Siswa SMK Di Indralaya Tahun 2018 Ahmad Heryanto; Deris Stiawan; Osvari Arsalan; Rizki Kurniati
Annual Research Seminar (ARS) Vol 4, No 2 (2018): Special Issue : Pengabdian Kepada Masyarakat
Publisher : Annual Research Seminar (ARS)

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Pengabdian masyarakat tahun 2018 mememberikan workshop teknik keamanan dalam menggunakan internet pada siswa smk di Indralaya kepada masyarakat yang terdiri dari SMK N 1 Pemulutan Selatan.  Setiap aktifitas di internet selalu memiliki sisi positif dan negatif. Pada kegiatan workshop memerbikan pengetahuan kepada peserta untuk memproteksi diri terhadap konten-koten negatif dengan menggunakan router mikrotik.
Implementation of Facial Landmarks Detection Method for Face Follower Mobile Robot Ahmad Zarkasi; Fachrudin Abdau; Agung Juli Anda; Siti Nurmaini; Deris Stiawan; Bhakti Yudho Suprapto; Huda Ubaya; Rizki Kurniati
Generic Vol 14 No 1 (2022): Vol 14, No 1 (2022)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

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This paper presents a new technique for facesrecognition based on auto-extracted facial marks. Our landmarks are those related to the outer corner of the nose. With extracted landmarks, a triplet of areas and their associated geometric invariance are formed. Where later the points on the outer corners of the eyes and nose will be connected with lines that will form a triangle. Later the line length will be calculated using the Euclidean Distance formula so that the area value of the triangle can be obtained. Then the data obtained will be trained using the Support Vector Machine algorithm so that they can recognize faces. And later the system will be implanted into a mobile robot with raspberry.
Performance Comparison of Feature Face Detection Algorithm on The Embedded Platform Ahmad Zarkasi; Siti Nurmaini; Deris Stiawan; Bhakti Yudho Suprapto; Huda Ubaya; Rizki Kurniati
Computer Engineering and Applications Journal Vol 11 No 2 (2022)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (405.575 KB) | DOI: 10.18495/comengapp.v11i2.405

Abstract

The intensity of light will greatly affect every process carried out in image processing, especially facial images. It is important to analyze how the performance of each face detection method when tested at several lighting levels. In face detection, various methods can be used and have been tested. The FLP method automates the identification of the location of facial points. The Fisherface method reduces the dimensions obtained from PCA calculations. The LBPH method converts the texture of a face image into a binary value, while the WNNs method uses RAM to process image data, using the WiSARD architecture. This study proposes a technique for testing the effect of light on the performance of face detection methods, on an embedded platform. The highest accuracy was achieved by the LBPH and WNNs methods with an accuracy value of 98% at a lighting level of 400 lx. Meanwhile, at the lowest lighting level of 175 lx, all methods have a fairly good level of accuracy, which is between 75% to 83%.
Pemodelan Topik Menggunakan Metode Latent Dirichlet Allocation dan Gibbs Sampling Rizki Ramadandi; Novi Yusliani; Osvari Arsalan; Rizki Kurniati; Rahmat Fadli Isnanto
Generic Vol 14 No 2 (2022): Vol 14, No 2 (2022)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

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Pemodelan topik adalah suatu alat yang digunakan untuk menemukan topik laten pada sekelompok dokumen. Pada penelitian ini dilakukan pemodelan topik dengan menggunakan metode Latent Dirichlet Allocation dan Gibbs Sampling. Enam artikel berita Bahasa Indonesia telah dikumpulkan dari portal berita detiknews dengan menggunakan metode Web Scrapper. Artikel berita dibagi menjadi dua kategori utama yaitu, narkoba dan COVID-19. Analisis model LDA dilakukan dengan menggunakan metode koherensi topik pengukuran skor UCI dengan hasil penelitian menyebutkan diperoleh lima buah topik optimal pada kedua konfigurasi pengujian.
Comparison of Certainty Factor (CF) and Case Based Reasoning (CBR) to Diagnose Infertility in Women Risky Tama Putri; Yunita Yunita; Osvari Arsalan; Rizki Kurniati
Sriwijaya Journal of Informatics and Applications Vol 3, No 1 (2022)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

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Infertility has now become a terrible and serious problem for women. Limited information about infertility suffered by women makes it difficult for them to predict the disease they are suffering from. Therefore we need an expert system that can predict infertility in women. The methods used in this research are Certainty Factor (CF) and Case Based Reasoning (CBR) methods. Certainty Factor (CF) is one of the techniques used to overcome uncertainty in decision making. Case Based Reasoning (CBR) is a problem solving method by remembering similar events that happened in the past and then using that knowledge or information to solve new problems. Based on the test results using 25 test data, the accuracy of the expert system for diagnosing infertility in women using the Certainty Factor (CF) method is 92%, while the curation of the expert system for diagnosing infertility in women using the Case Based Reasoning (CBR) method is 76%. 
Aero-Track: Perangkat Lunak Perekam Data Penerbangan Aeronautika Muhammad Rifqi Fathan; Aditya Aditya; Indra Gifari Afriansyah; Rani Silvani Yousnaidi; Rossi Passarela; Osvari Arsalan; Rizki Kurniati; Marsella Vindriani
Generic Vol 15 No 1 (2023): Vol 15, No 1 (2023)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

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Kecelakaan pesawat terbang bisa terjadi pada semua fase penerbangan, Pada tahun 2014, di Indonesia sendiri sudah terjadi kecelakaan penerbangan berjumlah 84 kali. Maka dari itu, kami mengembangkan sebuah perangkat lunak bernama Aero-Track untuk merekam data penerbangan dengan kriteria spesifik mengenai area dan dan fase penerbangan. Perangkat lunak ini sudah diuji coba dengan merekam data penerbangan pada bandara Sultan Syarif Kasim II, bandara Sultan Mahmud Badaruddin II dan Bandara Sultan Hasanuddin. Data dari hasil perekaman tersebut sudah dapat dijadikan bahan analisis terkait pola dan karakteristik penerbangan.
Implementation of K-Means and SAW Methods in Determining Non-Cash Food Aid Recipients Yunita Yunita; Rizki Kurniati; Desty Rodiah; Allsela Meiriza; Luh Sri Mulia Eni
CCIT Journal Vol 16 No 2 (2023): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v16i2.2525

Abstract

Determination of prospective non cash food assistance recipients, especially in Air Talas village, still uses a manual system so that in the process of determining the recipient there is a risk that the recipient will be inaccurate, so that the village government needs a system that can assist the process of determining prospective non cash food assistance recipients. This study aims to implement the K-Means and SAW methods in determining recipients of non cash food assistance in Air Talas village. The benefits of this research can help the Air Talas village government in determining and recommending prospective non cash food assistance recipients in accordance with established criteria, making it easier to filter, group, and rank appropriate population data according to criteria. In addition, this research is also useful for providing convenience to the community through data collection, clustering, and ranking in a transparent, real, and fast and accurate manner using decision support system software. The K-Means clustering method and the Simple Additive Weighting Ranking method were used in this study with data collection techniques through interviewing sources, in this case the village government, the social section of the community, and through collecting village archive data and relevant journals. The research location is Air Talas village with 316 data used. The results of the study are clustering data as much as 77 data obtained from feasible clusters. The cluster data was then tested using the accuracy value and obtained a value of 80%. Then the research is also in the form of ranking data using clustered data which obtains an accuracy value of 64%.
Co-Authors Aditya Aditya Agung Juli Anda Ahmad Heryanto Ahmad Zarkasi Allsela Meiriza, Allsela Bhakti Yudho Suprapto Bhakti Yudho Suprapto Deris Stiawan Desty Rodiah Elin Darnela Fachrudin Abdau Huda Ubaya Huda Ubaya Indra Gifari Afriansyah Luh Sri Mulia Eni Marsella Vindriani Muhammad Rifqi Fathan Novi Yusliani Osvari Arsalan Rahmat Fadli Isnanto Rani Silvani Yousnaidi Risky Tama Putri Rizki Ramadandi Rossi Passarela Siti Nurmaini Yulinda Ramadhana Yunita Yunita