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INDONESIA
Jurnal Ilmu Komputer
Published by Universitas Udayana
ISSN : 19795661     EISSN : 2622321X     DOI : -
Core Subject : Science, Education,
Computer Science & IT Languange, Linguistic, Communication & Media Library & Information Science
JIK is a peer-reviewed scientific journal published by Informatics Department, Faculty of Mathematics and Natural Science, Udayana University which has been published since 2008. The aim of this journal is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of computer science. JIK is consistently published two times a year in April and September. This journal covers original article in computer science that has not been published. The article can be research papers, research findings, review articles, analysis and recent applications in computer science.
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Articles 189 Documents
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Implementasi Algoritma Naïve Bayes Berbasis Particle Swarm Optimization Untuk Memprediksi Penyakit Hepatitis Hilda Farida Husniah; Toni Arifin
Jurnal Ilmu Komputer Vol 14 No 1 (2021): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2021.v14.i01.p05

Abstract

Hepatitis disease is an inflammatory disease of the liver cells, caused by infections (viruses, bacteria, parasites), medicines (including traditional medicines), consuming alcohol, excessive fats and autoimmune diseases. The cause of hepatitis is often caused by Hepatitis B and C Virus. The Hepatitis prevalence in Indonesia in 2013 amounted to 1.2% increased twice compared to the year 2007 Riskesdas of 0.6%. East Nusa Tenggara is the province with the highest prevalence of Hepatitis in 2013 of 4.3%. Researchers are trying to make a breakthrough by making research for the prediction classification of Hepatitis patients with data mining technique. Naïve Bayes is a method used to predict the probability of the future based on past experience and proved to have a high level of accuracy and high speed of calculation. Particle Swarm Optimization is used to improve the accuracy of the method. The research aims to determine if the Naïve Bayes-based Particle Swarm Optimization method can improve the accuracy of the good. The results of using Naïve Bayes-based Particle Swarm Optimization has a confusion matrix accuracy of 91.90% and an AUC of 0946 proved that has good results than Naïve Bayes has a confusion matrix accuracy of 88.52% and AUC 0896.
Metode ROBPCA (Robust Principal Component Analysis) dan Clara (Clustering Large Area) pada Data dengan Outlier Bekti Endar Susilowati; Pardomuan Robinson Sihombing
Jurnal Ilmu Komputer Vol 13 No 2 (2020): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2020.v13.i02.p04

Abstract

Principal Component Analysis (PCA) merupakan salah satu analisis multivariat yang digunakan untuk mengganti variable dengan Principal Component yang sedikit jumlahnya namun tidak terlalu banyak informasi yang hilang. Atau dengan kata lain, it used to explain the underlying variance-covariance structure of the large data set of variables through a few linear combination of these variables. PCA sangat dipengaruhi oleh kehadiran outlier karena didasarkan pada matriks kovarian yang sensitive terhadap outlier. Oleh karena itu, pada analisis ini akan digunakan PCA yang robust terhadap outlier yaitu ROBPCA atau PCA Hubert. Selanjutnya, dari Principal Component yang terbentuk digunakan sebagai input (masukan) untuk cluster analysis dengan metode Clara (Clustering Large Area). Clustering Large Area merupakan salah satu metode k-medoids yang robust terhadap outlier dan baik digunakan pada data dalam jumlah besar. Dalam studi kasus terhadap variabel penyusun indeks kebahagiaan berdasarkan The World Happiness Report 2018 dengan metode Clara yang menggunakan jarak manhattan didapatkan nilai rata-rata Overall Average Silhouette Width yang terbaik pada 5 cluster.
KS IOT Based Automation System to Prevent Crop Vandalization by Rain Water in Agricultural Regions Kajal Saini; Hunny Saini; Ankush Kumar Gaur
Jurnal Ilmu Komputer Vol 14 No 2 (2021): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2021.v14.i02.p05

Abstract

India’s keystone is Agriculture. Around 70 percent of India’s revenue comes from Agriculture. Conversely the population of India amplifies each and every day which requires efficient and well planned decision making techniques for the production of crops. In this research paper we find the intensification of the structures which prevent destruction of crops due to uneven and heavy rainfall. The goal is achieved by the concept of Embedded System design using IOT technology. This is done automatically without any human interference. Here we first identifies the water level in the agriculture field during rainfall by using water level sensors , if the water level exceeds there limit that will cause spoilage of crop then the device are automatically cover the agriculture field. It also identifies the temperature of the crops by using temperature sensor during the sunny days, if the heat causes spoilage of crops due to intensive sun rays then the device will automatically covers the agriculture field. After covering the agriculture field it will send the alert message using GSM module to the farmer and simultaneously the water of rain is collected through piles that will be reuse later for irrigation. To achieve this we use microcontroller , Solar panels, GSM module, DC motor, sensors, Switched-mode power supply (SMPS), Rechargeable battery
Analisis Perbandingan Pengelompokan Indeks Pembangunan Manusia Indonesia Tahun 2019 dengan Metode Partitioning dan Hierarchical Clustering Arina Mana Sikana; Arie Wahyu Wijayanto
Jurnal Ilmu Komputer Vol 14 No 2 (2021): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2021.v14.i02.p01

Abstract

Human Development Index (HDI) is an important indicator in measuring the level of success of the development of the quality of human life. Human Development Index clustering aims to divide the regions into groups based on Human Development Index for the region in 2019. Human Development Index clustering compares Partitioning Clustering and Hierarchical Clustering method to divide Human Development Index Indonesia in 2019. Partitioning Clustering method uses K-Means Clustering algorithm and Hierarchical Clustering method uses Agglomerative Ward Clustering algorithm. The results obtained are the best method for grouping provinces in Indonesia based on Human Development Index in 2019 is K-Means Clustering method with the optimum number of clusters is 6. This method gives Silhoutte Score o0,6291, Calinski-Harabasz Index 241,8875, dan Davies-Bouldin Index 0,3038. While the best method for grouping regencies in Indonesia based on Human Development Index in 2019 is K-Means Clustering method with the optimum number of clusters is 6. This method gives Silhoutte Score 0,5511, Calinski-Harabasz Index 1525,4007, dan Davies-Bouldin Index 0,5234.
Sistem Pengendalian Persediaan Barang Berbasis Website dengan Metode Economic Order Quantity dan Reorder Point Muhammad Nur Faiz; Seppy Ayu Rachmawati; Lutfi Syafirullah
Jurnal Ilmu Komputer Vol 14 No 2 (2021): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2021.v14.i02.p06

Abstract

Inventory of goods is one of the important factors in developing a business. This inventory affects operational costs. Excess inventory will also lead to greater storage and maintenance costs. Meanwhile, a lack of inventory will cause stock out. Website Inventory information system with the Economic Order Quantity (EOQ) and ReOrder Point (ROP) method can be an alternative to overcome this problem. This information system was developed using the SDLC (System Development Life Cycle) development method. The programming language used is PHP Hypertext Preprocessor, MySQL as database, and Xampp as a web server. EOQ method can determine the level of inventory required by the company. Meanwhile, the ROP to determine the time an item is in the warehouse must be added to the inventory before it runs out. This research results that the determination of the quantity of purchase inventory using the EOQ method and the ROP method is more efficient and the inventory becomes more optimal so that the store can get maximum profit. The results of the system functionality test show that this system works very well
Sentimen Analisis Terhadap Pembelajaran Jarak Jauh Menggunakan Metode Naïve Bayes Classifier dan Lexicon Based Cahyo Prianto; Nurul Izza Hamka
Jurnal Ilmu Komputer Vol 14 No 2 (2021): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2021.v14.i02.p02

Abstract

Since the beginning of the COVID-19 pandemic, all fields have been affected, especially in the field of education, where the learning process is currently carried out remotely. This research was conducted to find out the responses from the community within the scope of education such as students, students and teachers. The number of respondents who gave their responses as many as 265 through filling out a questionnaire in the form of a google form. Based on this research, it is known that of the 265 people who responded with a total of 6 statements, then obtained 1,590 different answers. From 1,590 data were reprocessed so that the final data was 1,468. As for the results of labeling with this Lexicon based dictionary, 162 were positive, 516 were negative, and 790 were neutral. The test results with nave Bayes obtained an accuracy rate of 53.8% by using the measurement of the effectiveness of the confusion matrix.
Implementasi Data Mining Menggunakan Algoritma Apriori Pada Penjualan Suku Cadang Motor Ainul Mardiaha; Yulia Yulia
Jurnal Ilmu Komputer Vol 14 No 2 (2021): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2021.v14.i02.p07

Abstract

This research was carried out to simplify or assist Candra Motor workshop owners in managing data and archives of motorcycle parts sales by applying a data mining a priori algorithm method. Data mining is an operation that uses a particular technique or method to look for different patterns or shapes in a selected data. Sales data for a year with the number of 15 items selected using the priori algorithm method. A priori algorithm is an algorithm for taking data with associative rules (association rule) to determine the associative relationship of an item combination. In a priori algorithm, it is determined frequent itemset-1, frequent itemset-2, and frequent itemset-3 so that the association rules can be obtained from previously selected data. To obtain the frequent itemset, each selected data must meet the minimum support and minimum confidence requirements. In this study using minimum support ? 7 or 0.583 and minimum confidence of 90%. So that some rules of association were obtained, where the calculation of the search for association rules manually and using WEKA software obtained the same results.By fulfilling the minimum support and minimum confidence requirements, the most sold spare parts are inner tube, Yamaha oil and MPX oil.
Kombinasi Metode Naive Bayes dan K-Medoid dalam Memprediksi Penjurusan Siswa di Sekolah Menengah Atas Devi Dwi Hariyanti; Gede Aditra Pradnyana; I Gede Mahendra Darmawiguna
Jurnal Ilmu Komputer Vol 14 No 2 (2021): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2021.v14.i02.p03

Abstract

Penjurusan merupakan suatu proses penempatan atau penyaluran dalam pemilihan program pengajaran kepada siswa. Tujuan dari penentuan penjurusan itu sendiri adalah agar kelak dikemudian hari pelajaran yang diberikan kepada siswa lebih terarah. SMA Laboratorium Undiksha memiliki permasalahan dalam penentuan penjurusan dan pembagian kelas siswa. Proses penentuan jurusan membutuhkan waktu yang cukup lama, masih menggunakan perhitungan manual di excel dalam menentukan penjurusan siswa.. Permasalahan tersebut dapat diatasi dengan Pengembangan Sistem Prediksi Penjurusan Kelas Siswa Menggunakan Kombinasi Metode Naive Bayes Dan K-Medoid. Ada 22 kriteria yang digunakan dalam penentuan jurusan kelas siswa yaitu, jenis kelamin, nilai raport semester 3 sampai dengan semester 5, nilai matematika semester 3 sampai dengan semester 5, nilai ipa semester 3sampai dengan semester, nilai ips semester 3 sampai dengan semester 5, nilai bahasa indonesia semester 3 sampai dengan semester 5, nilai bahasa inggris semester 3 sampai dengan semester 5, minat siswa 1, minat siswa 2 dan minat orang tua. Berdasarkan hasil perhitungan kinerja metode, didapatkan nilai akurasi sebesar 76% yang menunjukkan bahwa metode yang digunakan memiliki nilai akurasi yang cukup baik dalam memprediksi jurusan siswa. Precision yang dihasilkan sebesar 84,33% menunjukkan kategori data yang diklasifikasi telah sesuai dengan kategori yang sebenarnya. Recall yang dihasilkan sebesar 70,67% menunjukkan tingkat keberhasilan metode dalam mengenali suatu kategori sudah baik.
Sistem Informasi Penilaian Kinerja Dosen dengan MVC Framework menggunakan Simple Additive Weighting Methods Liza Angriani; Abd. Rachman Dayat
Jurnal Ilmu Komputer Vol 14 No 2 (2021): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2021.v14.i02.p08

Abstract

Kinerja dosen dalam melaksanakan Tri Darma adalah suatu hal untuk mendukung pengambilan keputusan Pimpinan dalam kenaikan jabatan seorang Dosen di Perguruan Tinggi. Decisions Support System (DSS) dengan metode Simple Additive Weighting (SAW) dapat membantu dalam proses pengolahan data dan memperbaiki kekurangan seperti kesalahan dalam perhitungan dan dalam penyajian laporan selama ini. Tujuan dari penelitian ini adalah untuk memanfaatkan metode SAW dalam penilaian kinerja dosen. Metodologi yang digunakan dalam melakukan penelitian adalah diawali dengan pengumpulan data dan dilanjutkan dengan tahap mengembangkan menjadi suatu sistem informasi. Hasil penelitian ini adalah menghasilkan Sistem Informasi Penilaian Kinerja Dosen memanfaatkan teknologi MVC Framework dengan metode SAW sebagai sarana penunjang pengambilan keputusan di AMIK Umel Mandiri.
Usage analysis of SVD, DWT and JPEG compression methods for image compression Dewa Ayu Indah Cahya Dewi; I Made Oka Widyantara
Jurnal Ilmu Komputer Vol 14 No 2 (2021): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2021.v14.i02.p04

Abstract

Through image compression, can save bandwidth usage on telecommunication networks, accelerate image file sending time and can save memory in image file storage. Technique to reduce image size through compression techniques is needed. Image compression is one of the image processing techniques performed on digital images with the aim of reducing the redundancy of the data contained in the image so that it can be stored or transmitted efficiently. This research analyzed the results of image compression and measure the error level of the image compression results. The analysis to be carried out is in the form of an analysis of JPEG compression techniques with various types of images. The method of measuring the compression results uses the MSE and PSNR methods. Meanwhile, to determine the percentage level of compression using the compression ratio calculation. The average ratio for JPEG compression was 0.08605, the compression rate was 91.39%. The average compression ratio for the DWT method was 0.133090833, the compression rate was 86.69%. The average compression ratio of the SVD method was 0.101938833 and the compression rate was 89.80%.

Page 14 of 19 | Total Record : 189

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