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ILKOM Jurnal Ilmiah
Published by Universitas Muslim Indonesia
ISSN : 20871716     EISSN : 25487779     DOI : -
Core Subject : Science,
Computer Science & IT
ILKOM Jurnal Ilmiah is an Indonesian scientific journal published by the Department of Information Technology, Faculty of Computer Science, Universitas Muslim Indonesia. ILKOM Jurnal Ilmiah covers all aspects of the latest outstanding research and developments in the field of Computer science, including Artificial intelligence, Computer architecture and engineering, Computer performance analysis, Computer graphics and visualization, Computer security and cryptography, Computational science, Computer networks, Concurrent, parallel and distributed systems, Databases, Human-computer interaction, Embedded system, and Software engineering.
Arjuna Subject : -
Articles 617 Documents
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ANALISIS EMPIRIS PERBANDINGAN KINERJA METODE HASHING PROGRESSIVE OVERFLOW DAN LINEAR QUOTIENT DALAM STUDI PEMBUATAN APLIKASI DEKSTOP ADMINISTRASI KEPEGAWAIAN Prianto, Eko; Yudhana, Anton; Fadlil, Abdul
ILKOM Jurnal Ilmiah Vol 8, No 3 (2016)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v8i3.66.174-181

Abstract

Administrasi merupakan kegiatan sehari-hari yaitu berupa kegiatan mencatat, mengumpulkan dan menyimpan suatu kegiatan atau hasil kegiatan sehingga membutuhkan memori guna menyimpan itu semua. Untuk memudahkan proses pencarian data yang telah disimpan dengan cepat, maka diperlukan suatu metode, yaitu menggunakan metode hashing. Penerapan manajemen memory bertujuan, agar mencegah adanya perulangan data yang sama, manajemen basis data yang baik, manajemen memori dan memberikan kemudahan untuk mengakses data dengan cepat walaupun data yang ada sangat banyak, dengan memasukkan kata kunci yang telah ditentukan dapat mencari data dan menampilkan dengan akurasi waktu yang dibutuhkan sebentar. Dengan metode progressive overflow dan linear quotient akan dianalisis nilai rata-rata dari setiap metode, nilai yang paling kecil dari metode tersebut adalah nilai yang terbaik akan digunakan sebagai pedoman seberapa besar nilai proses hashing dalam sebuat database suatu instansi dan sebagai studi kasus penentuan penyediaan memori yang dibutuhkan.
ANALISIS LAYANAN KEAMANAN SISTEM KARTU TRANSAKSI ELEKTRONIK MENGGUNAKAN METODE PENETRATION TESTING Azis, Huzain; Fattah, Farniawati
ILKOM Jurnal Ilmiah Vol 11, No 2 (2019)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i2.447.167-174

Abstract

Payment transactions developed along with technological developments, now days technology supports digital payment, each type of digital transaction has its own security services,  this study focus on the analysis of security services (confidentiality, integrity and availability) using the Penetration Testing method on magnetic stripe cards as a payment transaction playground facility, then comparing security services to the Radio Frequency Identification (RFID) electronic transaction tool. The results of this study are RFID electronic transaction cards that provide a more complete security service as an electronic payment transaction.
PREDIKSI KEBANGKRUTAN PERUSAHAAN MENGGUNAKAN ALGORITMA C4.5 BERBASIS FORWARD SELECTION Saleh, Hamsir
ILKOM Jurnal Ilmiah Vol 9, No 2 (2017)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v9i2.97.173-180

Abstract

Memprediksi kebangkrutan perusahaan adalah upaya yang penting dalam mengatasi masalah manajemen perusahaan dengan tujuan utamanya adalah mengoptimalkan pengelolaan fitur yang berpengaruh dalam memprediksi kebangkrutan perusahaan. Masalah mendasar dalam machine learning adalah proses optimasi keputusan untuk mendapatkan fungsi kombinasi yang optimal. Forward selection adalah pendekatan wrapper yang sering digunakan dalam seleksi fitur otomatis, forward selection mampu menghapus fitur yang tidak relevan, mengembangkan dan menambah kualitas data, serta meningkatkan performa dan akurasi model. Penelitian ini mengusulkan algoritma C4.5 berbasis forward selection untuk menemukan atribut yang berpengaruh dalam peningkatan akurasi prediksi kebangkrutan perusahaan. Hasil penelitian yang telah dilakukan dengan penerapan algoritma C4.5 berbasis forward selection menghasilkan beberapa fitur signifikan, dalam penelitian menggunakan 250 record atribut compettivenes dan credibility menjadi fitur yang signifikan dari 6 atribut yang ada. Dalam penelitian dengan 250 record algoritma C4.5 mendapatkan hasil akurasi sebesar 99.60% dan algoritma C4.5 berbasis forward selection  dengan akurasi sebesar 99.61%.
Perbandingan Metode Klasifikasi Support Vector Machine dan Naïve Bayes untuk Analisis Sentimen pada Ulasan Tekstual di Google Play Store Ilmawan, Lutfi Budi; Mude, Muhammad Aliyazid
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.597.154-161

Abstract

In this research, the performance of SVM classification method will be compared with other classification methods, by using the Naïve Bayes classification method. Naïve Bayes classification method is a light classification method and has a high accuracy if applied to the text classification according to some previous studies. The accuracy of the classifier is measured using the K-fold cross validation method whose results will be tabulated in a confusion matrix table, with a value of K = 3. In this study, the data processed are textual reviews of applications in the Indonesian language Google Play Store obtained from previous research. The test results obtained from the 3-fold cross-validation method produce that SVM Classifier has a higher value of accuracy when compared with the accuracy of the Naïve Bayes classifier, the SVM classifier gets an accuracy of 81.46% and Naïve Bayes classifier by 75.41%.
RANCANG BANGUN APLIKASI MOBILE UNTUK MENENTUKAN SOLUSI OPTIMAL PENCARIAN RUTE TERBAIK MENGGUNAKAN ALGORITMA ANT COLONY OPTIMIZATION Irawan, Budhi; Setianingsih, Casi; Arramsyah, Izzat
ILKOM Jurnal Ilmiah Vol 10, No 1 (2018)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v10i1.237.17-27

Abstract

Dampak dari musibah kebakaran bisa ditekan jika petugas dan kendaraan Damkar (pemadam kebakaran) bisa bekerja cepat. Selain faktor keterlambatan laporan kepada Damkar dan kondisi  jalan Kota Bandung yang macet ikut memperlambat laju petugas. Proses pengisian tangki air menjadi masalah utama, selain terbatas keberadaannya juga kualitas semburannya rendah sehingga petugas harus mencari sumber air selain hydrant. Dari permasalahan tersebut maka dibutuhkan suatu alat bantu yang praktis berupa aplikasi dengan memanfaatkan perangkat smartphone yang dapat membantu mencarikan solusi optimal guna mendapatkan rute perjalanan petugas Damkar dalam upaya menjangkau lokasi kebakaran dan mendapat sumber air didalam mendukung tugasnya memadamkan api di lokasi kebakaran. Adapun guna menentukan rute optimal sesuai kebutuhan diatas maka dipilih algoritma ACO (Ant Colony Optimization) dan Metode SAW (Simple Additive Weighting) yang diimplementasikan pada aplikasi mobile yang dibangun. Sehingga dengan aplikasi ini dapat membantu para petugas Damkar didalam menjalankan tugasnya terutama mendapatkan rute jalan yang optimal beserta sumber air yang diperlukan.
Header investigation for spam email forensics using framework of national institute of standards and technology Mustafa, Mustafa; Riadi, Imam; Umar, Rusydi
ILKOM Jurnal Ilmiah Vol 13, No 2 (2021)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i2.849.163-167

Abstract

Today's technology makes communication very easy and can be used anywhere, even a distance of hundreds to thousands of kilometres is not a barrier in communicating. One of the tools or media that is widely used is via email. However, there are many disadvantages that may be obtained from the email, one of which is spamming or mail. The purpose of this research is to know the stages of spamming email analysis through header analysis. The method used in this study is the National Institute of Standards and Technology (NIST) and this method uses 4 stages, namely collection, examination, analysis, and reporting. The results of this study are expected to be able to find out the spam sender's email address, the spam email sender's IP address, and other information needed.
OPTIMASI K-MEANS CLUSTERING UNTUK IDENTIFIKASI DAERAH ENDEMIK PENYAKIT MENULAR DENGAN ALGORITMA PARTICLE SWARM OPTIMIZATION DI KOTA SEMARANG Rustam, Suhardi; Santoso, Heru Agus; Supriyanto, Catur
ILKOM Jurnal Ilmiah Vol 10, No 3 (2018)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v10i3.342.251-259

Abstract

Tropical regions is a region endemic to various infectious diseases. At the same time an area of high potential for the presence of infectious diseases. Infectious diseases still a major public health problem in Indonesia. Identification of endemic areas of infectious diseases is an important issue in the field of health, the average level of patients with physical disabilities and death are sourced from infectious diseases. Data Mining in its development into one of the main trends in the processing of the data. Data Mining could effectively identify the endemic regions of hubunngan between variables. K-means algorithm klustering used to classify the endemic areas so that the identification of endemic infectious diseases can be achieved with the level of validation that the maximum in the clustering. The use of optimization to identify the endemic areas of infectious diseases combines k-means clustering algorithm with optimization particle swarm optimization ( PSO ). the results of the experiment are endemic to the k-means algorithm with iteration =10, the K-Fold =2 has Index davies bauldin = 0.169 and k-means algorithm with PSO, iteration = 10, the K-Fold = 5, index davies bouldin = 0.113. k-fold = 5 has better performance.
The implementation of forward chaining and certainty factor methods to examine the covid-19 vaccination eligibility Herlina, Herlina; Yosephi, Valensa; Hazriani, Hazriani
ILKOM Jurnal Ilmiah Vol 13, No 3 (2021)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i3.973.307-313

Abstract

Screening for the COVID-19 vaccination is an important and mandatory step to ensure the eligibility status of each candidate for vaccination. The main obstacle experienced was the ineffective screening process (a long process) that resulted in the accumulation of patients. Sometimes it takes one to two hours from registration to receiving the vaccination paper. This situation certainly causes discomfort for both participants and vaccinators. Therefore, the presence of an expert system is needed to overcome these obstacles. The expert system plays a role in simplifying service flow and shortening service time. This article discusses the application of the Forward Chaining method to formulate screening parameters so that they can be used to accurately determine vaccination eligibility. Based on the results of interviews with experts (expert doctors who handle vaccination), 12 rules were obtained from the formulation of 20 historical parameters, which will then serve as a knowledge base for the Covid-19 vaccination screening expert system. The test is carried out by comparing the results of expert screening diagnoses with an expert system using 15 samples of test data. The test results using the Certainty Factor method show that the confidence level is 84% to 99%.
PENGEMBANGAN SISTEM MEMBACA AL-QUR’AN DENGAN METODE MULTIMEDIA DEVELOPMENT LIFE CYCLE Herman, Suherman; Samsuni, Sunny; Fathurohman, Fathurohman
ILKOM Jurnal Ilmiah Vol 11, No 2 (2019)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i2.406.95-101

Abstract

Al-Qur'an is the Holy Book which is the main and first source in Islamic teachings. It is important for us as Muslims to learn about how to read the Qur'an properly. This research  uses two method approach namely Multimedia System Development method and learning method used is to use Tartil method. By using this two-method approach it is hoped that it will be more interesting for students to read and be able to accelerate how to read the Qur'an properly. The results of this research are in the form of an android-based application that can help to learn and read the Al-Qur’an properly. This application is tested using the Black Box method that shows all functions are running properly 100% according to what is expected.. The results show 85% progressed after using the application and only 15% did not progress.
KLASIFIKASI NASABAH ASURANSI JIWA MENGGUNAKAN ALGORITMA NAIVE BAYES BERBASIS BACKWARD ELIMINATION Betrisandi, Betrisandi
ILKOM Jurnal Ilmiah Vol 9, No 1 (2017)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v9i1.116.96-101

Abstract

Pendapatan untuk perusahaan asuransi ditentukan oleh jumlah premi yang dibayar oleh nasabah. Banyaknya nasabah yang tidak lancar membayar premi berpengaruh terhadap kinerja serta eksistensi perusahaan sehari-hari. Algoritma Naive Bayes berbasis Backward Elimination bertujuan untuk melakukan klasifikasi nasabah asuransi dengan hasil akurasi 85,89 % dengan delapan atribut weight yaitu umur, jangka waktu, cara bayar, premi, jumlah hari, pekerjaan, penghasilan dan mata uang

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