Jurnal Ilmu Komputer
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.
Articles
189 Documents
<![CDATA[Pengembangan Sistem Rekomendasi Lokasi Kegiatan Dengan Metode Augmented Reality ]]>
<![CDATA[I Gusti Agung Gede Arya Kadyanan]]>
<![CDATA[ Jurnal Ilmu Komputer Vol 15 No 2 (2022): Jurnal Ilmu Komputer ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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<![CDATA[The buildings owned by Udayana University are quite numerous by providing different facilities. So that in carrying out an activity, the implementer must adjust what facilities are needed in the activity. In addition, the implementers of the activity must also come and see first hand the condition of the building or room that wants to be used as the location of the activity, so that it will take a long time. There is a need for a system that can recommend the location of activities of Udayana University in accordance with the implementing needs of the activity. This study designed and built a recommendation system for the location of activities in the Udayana University using the Simple Additive Weighting (SAW) and Augmented Reality methods. The application will be used by the user to get the location that suits their needs. The results of this study, in the android application has been able to make recommendations and plotting the location of activities in the Udayana University, as well as display information in the form of 3D objects through Augmented Reality technology. Keywords: Recommendation System, Activity Location, Augmented Reality, Android, Udayana University]]>
<![CDATA[p Penerapan Sistem Pembelajaran Berbasis Peta Pikir ]]>
<![CDATA[Luh Putu Ida Harini]]>
<![CDATA[ Jurnal Ilmu Komputer Vol 15 No 2 (2022): Jurnal Ilmu Komputer ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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<![CDATA[The development of online learning systems is very rapid in the last ten years, various educational institutions have begun to use online learning systems to support the teaching and learning process. Along with this, students have become very fluent in using online learning systems, so this system can be an excellent choice for the learning process in the future. However, it will be very good when the learning system improves its capabilities, especially in helping teachers monitor the learning process carried out by students. In this study, a student function model was applied which is expected to be able to provide information to teachers about the character of their students in using the online learning system. This paper will discuss the assessment of the system designed, from a small-scale test of 5 teachers and 15 students, it was found that their opinion on the satisfaction of using the system reached 87%.]]>
<![CDATA[Rancang Bangun Sistem Otentikasi Terpusat Berbasiskan Model Single Sign On di IT Telkom Surabaya ]]>
<![CDATA[Kharisma Monika Dian Pertiwi]]>;
<![CDATA[Rizky Fenaldo Maulana]]>;
<![CDATA[Ardian Yusuf Wicaksono]]>
<![CDATA[ Jurnal Ilmu Komputer Vol 15 No 2 (2022): Jurnal Ilmu Komputer ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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<![CDATA[IT Telkom Surabaya is one of the campuses located in Surabaya City, East Java. Currently IT Telkom Surabaya has thousands of students and hundreds of employees consisting of staff and lecturers. Along with the development of information technology, the IT Telkom Surabaya campus has many information systems that support its business processes. However, the information system has not used a single authentication system. So a user must remember the account used in each of these information systems. Therefore, in this study, researchers developed a centralized authentication system based on the Single Sign On model in the IT Telkom Surabaya campus. The purpose of this study is to integrate the authentication and authorization processes of several information systems in the IT Telkom Surabaya Campus. This Centralized Authentication System was built using SDLC (System Development Life Cycle) development with the waterfall method and was built based on web applications using HTML, CSS, Javascript, PHP, and using MySQL as a DBMS (Database management system). Testing on this system uses the black-box testing method which is used to test the functionality of the system by trying the functions and menus provided. The results of system functionality testing show that all functionality can run according to the flow.]]>
<![CDATA[Analysis of the Grouping of Provinces in Indonesia According to the Democracy Index With the Agglomerative Hierarchical Clustering Algorithm ]]>
<![CDATA[MOCHAMMAD YUSUF MAULANA]]>
<![CDATA[ Jurnal Ilmu Komputer Vol 15 No 2 (2022): Jurnal Ilmu Komputer ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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<![CDATA[The purpose of this study is to clustering the provinces in Indonesia based on the IDI dimensions in 2020. This study compares four methods of agglomerative hierarchical clustering, namely the single linkage method, average linkage, complete linkage, and the ward method. The evaluation criteria used are the silhouette index, dunn index, connectivity index, and agglomerative coefficient. The best method used is the average linkage hierarchy method with two clusters. The combination of two clusters and the ward’s method produces a silhouette index value of 0.34, a dunn index value of 0.28, a connectivity index value of 5.64 and an agglomerative coefficient of 0.891 which illustrates that the method is able to classify provinces in Indonesia based on the 2020 IDI. The results of this study can be used as a consideration for the government to take policies related to policies in Indonesia.]]>
<![CDATA[C Cover dan Daftar Isi ]]>
<![CDATA[I Gede Santi Astawa]]>
<![CDATA[ Jurnal Ilmu Komputer Vol 15 No 2 (2022): Jurnal Ilmu Komputer ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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<![CDATA[Analisa Kualitas Auditor Di Kantor Jasa Akuntansi Menggunakan Multi Layer Perceptron ]]>
<![CDATA[Muhammad Mizan Siregar]]>
<![CDATA[ Jurnal Ilmu Komputer Vol 15 No 2 (2022): Jurnal Ilmu Komputer ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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<![CDATA[Auditing practices are generally carried out by auditors who join a partner organization consisting of senior auditors and junior auditors. The quality of this audit is generally as-sessed from the ability of the auditor to find errors in the auditee's financial statements and report their findings. This study compares the results of the classification of auditor quality at the Accounting Services Office (KJA) Azhar Maksum & Partners between the multi-layer perceptron classification model that uses the ReLu, Tanh and Sigmoid activa-tion functions. Evaluation was measured using k-fold cross validation with variations in K values of 5 and 10 to measure accuracy, F1, precision and recall. The results obtained from the average cross validation value are that the ReLu activation function is the best activation function to be used in the quality classification model of KJA Azhar Maksum & Partners auditors, it can be seen from the average accuracy value of 82.7%, the average F1 value of 83.4%, the average precision value is 88.9% and the average recall value is 82.7%. Also, the Sigmoid activation function is the worst activation function to be used in the quality classification model of KJA Azhar Maksum & Partners auditors, it can be seen from the average accuracy value of 69.2%, the average F1 value of 56.6%, the average precision value of 47.9 % and the average recall value is 69.2%.]]>
<![CDATA[Implementasi Data Mining Menggunakan Algoritma Naïve Bayes Classifier Untuk Mendeteksi Minat Beli Pelanggan Terhadap Produk Paket Internet ]]>
<![CDATA[Saifur Rohman Cholil]]>;
<![CDATA[Swi Indriyaningtyas]]>;
<![CDATA[Aji Bagus Prasetya]]>;
<![CDATA[Rodhiyatu Robbi Al Marjuwah]]>
<![CDATA[ Jurnal Ilmu Komputer Vol 15 No 2 (2022): Jurnal Ilmu Komputer ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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<![CDATA[AM Cell merupakan salah satu unit bisnis yang bergerak di bidang penjualan kartu perdana internet yang bertahan dalam persaingan di Kabupaten Jepara. AM Cell menawarkan berbagai jenis dan harga paket Internet, namun tidak mengetahui seberapa besarnya minat konsumen terhadap paket internet tersebut. Hal ini akan memungkinkan konsumen beralih ke perusahaan usaha serupa yang menurut konsumen paling menguntungkannya. Sehingga penelitian ini untuk memberikan gambaran mengenai minat beli konsumen terhadap produk paket internet di AM Cell, mendeteksi dengan algoritma Naïve Bayes Classifier pada usaha penjualan paket Internet dan klasifikasi terkait deteksi minat beli pelanggan terhadap penjualan paket Internet. Berdasarkan data penjualan paket internet pada bulan Juni 2021, metode Naïve Bayes dapat mengklasifikasikan 52 data produk paket internet dengan 986 data transaksi sebagai data training dan 52 data produk internet dengan 422 data transaksi sebagai data uji. Sehingga untuk mengetahui minat beli pelanggan paket internet didapatkan hasil dari perhitungan Naïve Bayes menggunakan software RapidMiner dengan akurasi sebesar 78.85%. Sedangkan, perhitungan Naïve Bayes menggunakan software Microsoft Excel memperoleh hasil akurasi sebesar 88%.]]>
<![CDATA[Aplikasi Penilaian Kinerja Karyawan Menggunakan Key Performance Indicator ]]>
<![CDATA[Ricky Alexander Bianco]]>;
<![CDATA[Vivine Nurcahyawati]]>;
<![CDATA[Tony Soebijono]]>
<![CDATA[ Jurnal Ilmu Komputer Vol 16 No 1 (2023): JIK Edisi April 2023 ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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DOI: 10.24843/JIK.2023.v16.i01.p01
<![CDATA[Sumber Daya Manusia (SDM) adalah aset terpenting bagi sebuah perusahaan. Ruang lingkup sumber daya manusia meliputi karyawan, pekerja/buruh, manajer dan pekerja lain yang dapat mendukung kegiatan perusahaan atau organisasi. Menjaga kualitas sumber daya manusia memerlukan penilaian kinerja sumber daya manusia. Permasalahan yang sering terjadi adalah proses penilaian dilakukan secara manual sehingga memakan waktu 3 hari dan banyaknya penilaian kinerja karyawan yang menumpuk. Penilaian kinerja pegawai harus konsisten dengan kejadian yang sebenarnya. Jika karyawan mendapatkan nilai terbaik, mereka akan mendapatkan reward yaitu kenaikan pangkat. Jika pegawai tersebut mendapatkan penilaian yang di bawah standar, maka ia akan mendapatkan hukuman berupa mutasi. Solusi yang dapat diberikan dari permasalahan diatas adalah dibuatnya aplikasi penilaian kinerja karyawan dengan metode key performance indicator(KPI) untuk mempercepat penilaian karyawan, mengurangi penyimpanan kertas penilaian karyawan]]>
<![CDATA[c Cover dan Daftar Isi JIK April 2023 ]]>
<![CDATA[I Gede Santi Astawa]]>
<![CDATA[ Jurnal Ilmu Komputer Vol 16 No 1 (2023): JIK Edisi April 2023 ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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<![CDATA[KLASIFIKASI TINGKAT KEMATANGAN DAN KUALITAS BUAH PISANG BERDASARKAN FITUR WARNA, TEKSTRUR DAN BENTUK MENGGUNAKAN METODE TRANSFORMASI RUANG WARNA HSV ]]>
<![CDATA[bayu Ketut Erna ariska]]>
<![CDATA[ Jurnal Ilmu Komputer Vol 16 No 1 (2023): JIK Edisi April 2023 ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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DOI: 10.24843/JIK.2023.v16.i01.p02
<![CDATA[Pisang memiliki sifat yang mudah rusak, pengelolaan yang tidak tepat pada buah pisang dapat mengakibatkan penuruan mutu dan kualitas. Pada umumnya, untuk mengukur kematangan masih dilakukan secara konvensional, kelemahan dari metode tersebut adalah tingkat akurasi yang tidak konsisten dan cenderung mengalami kesalahan. Pemanfaatan citra sangat penting untuk mengetahui kematangan buah pisang dengan memanfaatkan citra digital. Dengan adanya citra digital maka untuk menentukan kematangan buah pisang berdasarkan warnanya bisa dilakukan secara computing (berbasis teknologi), yaitu dengan menerapkan pengolahan citra menggunakan metode transformasi ruang warna HSV (Hue, Saturation, Value). Model warna HSV (Hue, Saturation, Value) mengelompokkan komponen intensitas dari informasi warna yang dibawa (hue dan saturation) dalam warna citra. Berdasarkan hasil penelitian pada analisis tingkat kematangan buah pisang diperoleh akurasi pelatihan tertinggi sebesar 100% dan akurasi pengujian tertinggi sebesar 100%. Sedangkan pada analisis kualitas biji kopi diperoleh akurasi pelatihan tertinggi sebesar 87,5% dan akurasi pengujian tertinggi sebesar 90%. Akurasi tersebut menunjukkan bahwa metode yang dikembangkan pada penelitian ini cukup baik dalam menganalisis tingkat kematangan dan kualitas buah pisang. Sistem yang dikembangkan juga dibuat dalam tampilan antarmuka sehingga memudahkan pengguna dalam pengoperasian. Kata Kunci : Transformasi Ruang Warna HSV; Pengolahan Citra.]]>
