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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 580 Documents
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Sentiment analysis of game product on shopee using the TF-IDF method and naive bayes classifier Rifki Kosasih; Anggi Alberto
ILKOM Jurnal Ilmiah Vol 13, No 2 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i2.721.101-109

Abstract

In every product sold on the E-commerce platform, there is a review column from consumers who have made transactions on the products. These reviews are in the form of comments and ratings (stars from one to five) written and given by consumers based on their assessment of the products purchased. With the product evaluation feature based on the rating, the consumer can find out how good or bad the quality of the product is. However, a problem arises when some consumers give negative comments with five stars or vice versa. This causes the product assessment feature based on the rating to be less good so that it does not represent the real value. Therefore, to determine the quality of the product, sentiment analysis was carried out using the TF-IDF method and the Naive Bayes Classifier based on reviews from buyers. The data collected is 1000 reviews which are divided into 700 training data and 300 test data. The next stage is the preprocessing text such as case folding (converting uppercase letters to lowercase), tokenizing (separating sentences into single words), stopwords (removing tokenizing conjunctions that have nothing to do with sentiment analysis), stemming (changing words into basic word forms), and word weighting with TF-IDF. The last step is to classify. Based on the classification results obtained an accuracy rate of 80.2223%.
Pengenalan Angka Tulisan Tangan Menggunakan Jaringan Syaraf Tiruan Herman Herman; Lukman Syafie; Dolly Indra
ILKOM Jurnal Ilmiah Vol 10, No 2 (2018)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v10i2.317.201-206

Abstract

Current technological developments spur the application of pattern recognition in various fields, such as the introduction of signature patterns, fingerprints, faces, and handwriting. Human handwriting has differences between one another and often handwriting is difficult to read or difficult to recognize and this can hamper daily activities, such as transaction activities that require handwriting. Even one of the biometric features of everyone is handwriting. One method that can be used to recognize handwriting patterns in the field of computer science is artificial neural networks (ANN) with the learning algorithm is backpropagation. Artificial neural networks are able to recognize something based on the past. This means that past data will be studied so as to be able to make decisions on new data. To recognize handwriting patterns using artificial neural networks, the characteristics of handwritten objects are extracted using an invariant moment. The results of training using artificial neural networks indicate that the correlation coefficient value is obtained on the number of hidden layer neurons by 30. The highest correlation coefficient value is 0.61382. The test results on the test data obtained an accuracy rate of 11.67% of the total test data.
Usability testing of intensive course mobile application using the usability scale system Manda Rohandi; Nurlaila Husain; Indri Wirahmi Bay
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.v13i3.821.252-258

Abstract

The mobile intensive course (MIC) application version 2 is an application created to assist the learning process of the English intensive course. Measurement of the usability of the MIC version 2 application has never been done before, so the effectiveness, efficiency, and user satisfaction for this application have not been measured. In addition, usability measurement can be used as a reference for the level of user loyalty, whether including net promoters, passive users, or detractors. One of the usability measuring tools that are easy to use, the calculation is simple and can be used on a small sample, but still valid and reliable is the System Usability Scale (SUS). The purpose of this study was to test the usability of the MIC version 2 application to determine the quality of this application using the SUS questionnaire. This research was conducted in four steps, namely 1) piloting the MIC version 2 application to the respondents; 2) distributing SUS questionnaires to respondents to be filled out manually or online; 3) calculating the average SUS score; 4) analyzing the mean SUS score. This study involved 37 respondents consisting of students and lecturers of EIC. The results of this study indicate that the usability of the MIC version 2 application can be accepted by users with an average SUS score of 70.61 and get category C based on the CGS assessment. When viewed from the level of user loyalty, the average SUS score for this application only results in passive users. The average value of the contribution to learnability obtained is still low, which is 1.9 from the maximum value of 4. Improvements are needed in future applications in terms of application learnability, such as simplifying the appearance of features and functions in the application, thus allowing users to be more familiar with applications and potential as net promoters.
PENDEKATAN HYPER HEURISTIC DENGAN KOMBINASI ALGORITMA PADA EXAMINATION TIMETABLING PROBLEM Vicha Azthanty Supoyo; Ahmad Muklason
ILKOM Jurnal Ilmiah Vol 11, No 1 (2019)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i1.420.34-44

Abstract

Generally, exam scheduling is still done manually and definitely will take a long time. Many researches have developed various studies to find a more appropriate strategy. Hyperheuristic was proposed in this study. In Hyperheuristic, Simple Random is used as a strategy for selecting low-level-heuristic while Hill Climbing and Simulation Annealing as move acceptance strategy. The Carter dataset is used as a test for the algorithms. We proposed testing datasets with a time limit of 15 minutes up to 1 hour and the results were compared with the research conducted by Carter et al (1996) as an initial study using that dataset. In addition, dataset, the number of iterations, and the time limit are as same as one of the literatures which will then be compared. The results obtained show that one pair of algorithms proposed in this study is better than the literature while other algorithms also provide significant results.
BERDASARKAN FITUR BENTUK BERBASIS WEB MENGGUNAKAN METODE GRADIEN VEKTOR FLOW SNAKE Iradatil Wahdaniah; Harlinda Harlinda
ILKOM Jurnal Ilmiah Vol 9, No 1 (2017)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v9i1.109.49-56

Abstract

Proses pencarian berupa file digital merupakan hal sangat penting dalam menggunakan teknologi, sehingga ketika seseorang ingin menemukan file yang terdapat pada komputer namun tidak dapat diketahui lokasi penyimpanannya sehingga sulit ditemukan, terlebih lagi teknik pencarian yang disediakan saat ini, terbatas pada teks, dimana keyword yang dapat diberikan hanya sebatas teks berupa nama file dari gambar tersebut, dengan adanya information retrieval, diharapkan dapat membantu proses pencarian menjadi lebih spesifik ke arah gambar, dimana proses pencarian gambar dari gambar yang dicari, dengan bantuan metode content based image retrieval (CBIR) diharapkan mampu melakukan template maching sehingga mudah dikenali objek yang sama, proses pengenalan objek menggunakan Gradien Vektor Flow Snake (GVFS) sebagai alat untuk mengenali kurva yang berupa objek dari sebuah gambar. Dengan adanya aplikasi ini diharapkan mampu mengurangi kesulitan dalam melakukan proses pencarian untuk sebuah gambar, hanya dengan memasukkan gambar yang berisi gambar untuk dijadikan sebagai objek pengenal untuk proses pencarian gambar yang memiliki objek yang sama.
Case Based Reasoning Method untuk Sistem Pakar Diagnosa Penyakit Sapi Irvan Muzakkir; Marniyati Husain Botutihe
ILKOM Jurnal Ilmiah Vol 12, No 1 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i1.506.25-31

Abstract

This study discusses about the Application of Case Based Reasoning (CBR) Method for Expert Systems in Diagnosing Cattle Disease. Beginning with data collection by consulting experts in the Department of Agriculture in Animal Health, Pohuwato Regency. The data obtained in the form of data names of disease and symptom data. The data is obtained based on the steps of the CBR method calculation in order to obtain the results of the diagnosis and the solution provided for handling the disease. Researcher have analyzed and create program listings to build a system that will be used by farmers. Based on CBR calculations Scours case which has the lowest weight is 0.09 while the highest weight is owned by the Pink Eye case 1. In this process provides a solution to the similarity of the case weight from the old case to the new higher case. In the case of Pink Eye having a higher weight and positive exposure to pink eye disease, the solution given is the provision of anti-allergic, anti-biotic and vitamin. Based on the results obtained, it can be concluded that the application of the CBR method is good for using cattle disease and is very helpful for farmers in dealing with cattle disease. 
PENERAPAN METODE TOPSIS UNTUK SISTEM PENDUKUNG KEPUTUSAN PENENTUAN KELUARGA MISKIN PADA DESA PANCA KARSA II Irvan Muzakkir
ILKOM Jurnal Ilmiah Vol 9, No 3 (2017)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v9i3.156.274-281

Abstract

Menentukan keluarga miskin adalah salah satu upaya pemerintah untuk melakukan intervensi pembangunan dalam bentuk bantuan terhadap keluarga miskin. Tepat sasaran adalah suatu keharusan sehingga benar-benar dapat berdaya guna bagi yang membutuhkan. Perkembangan penduduk Desa Panca Karsa II rata-rata 2% pertahun, sedangkan angka kelahiran dan kematian rata-rata 1% pertahun. Mayoritas mata pencaharian penduduk adalah petani dan buruh tani. Hal ini disebabkan karena sudah turun temurun dan juga minimnya tingkat pendidikan. Model yang digunakan dalam sistem pendukung keputusan ini adalah FMADM dengan menggunakan Metode TOPSIS. Metode TOPSIS tersebut, diharapkan penilaian akan lebih tepat karena didasarkan pada nilai kriteria dan bobot yang sudah ditentukan sehingga akan mendapatkan hasil yang lebih akurat. Untuk itu peneliti mencoba membantu permasalahan tersebut di atas dengan membuatkan suatu sistem pendukung keputusan menggunakan Bahasa Pemrograman PHP dengan Database MySQL, sehingga Penerapan Metode TOPSIS untuk sistem ini dapat memberikan hasil yang maksimal dalam hal pengambilan keputusan.
The comparison of k-means and k-medoids algorithms for clustering the spread of the covid-19 outbreak in Indonesia Wargijono Utomo
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i1.763.31-35

Abstract

The coronavirus spreads quickly through human-to-human transmission via close contact and respiratory droplets such as coughing or sneezing. Various studies have been carried out to deal with Covid-19. However, the cure for this virus has not been found until now. Based on data from the covid19.go.id page retrieved on January 1st, 2021, which was updated by the Ministry of Health, the overall number of confirmed cases was 1,078,314 active cases reaching 175,095 or 16.2% of confirmed cases, recovered 873,221 or 81.0% of confirmed cases, and death 29,998 or 2.8% of the confirmed cases. This study compares the two algorithms of data groups to analyze clustering patterns to determine the best data processing method. The data in this study sourced from the Ministry of Health, contained 4 attributes, including confirmed cases, treatment, recovery, and death cases. In this study, only 2 attributes were used: the confirmed and death cases. From the data analysis and processing results through a comparison between the K-Means method and the K-Medoids for clustering the spread of the coronavirus in Indonesia, a conclusion is derived. With the Davies Boulden index value from K2 to K9 values, it turns out that the K-Means method gets the smallest value at the K-5 of 0.064, while K-Medoids at the k-2 value of 0.411. Thus, from the two methods used, it can be concluded that the best method for clustering the spread of the coronavirus outbreaks in Indonesia is the K-Means method.
SISTEM KONTROL MESIN PENUKARAN UANG KERTAS RUPIAH BERBASIS PENGOLAHAN CITRA DAN RASPBERRY PI Abdul Jalil
ILKOM Jurnal Ilmiah Vol 10, No 2 (2018)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v10i2.272.128-135

Abstract

The research purpose is to build a machine control system for exchange nominal of rupiah's paper money from big nominal to small nominal based on image processing and Raspberry Pi. The method for money exchange is detecting the authenticity of money, nominal of money, and amount of money exchange. The money authenticity was detected by the invisible image and nominal of money was detected by money color. Technique for detection the authenticity and nominal of money are using image processing that is processed on the Raspberry Pi. The algorithm used for detecting the authenticity and nominal of money are using template color algorithm and for exchange amount of money using the greedy algorithm. The research result is system able to detect the authenticity and nominal of paper money IDR 100.000, IDR 50.000, and IDR 20.000 then exchange it with the small nominal of money in accordance with the user choice.
Rancangan Sistem Pendukung Keputusan Penentuan Penerima Bantuan Program Pemerintah Harlinda Lahuddin
ILKOM Jurnal Ilmiah Vol 8, No 1 (2016)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v8i1.24.63-68

Abstract

Sistem Pendukung Keputusan Penentuan Penerima Bantuan Program Pemerintah merupakan program aplikasi yang dapat digunakan oleh pemerintah (Badan Pusat Statistik) guna menyeleksi rumah tangga miskin yang akan diberikan bantuan dana secara tunai dalam rangka peningkatan pelayanan kesehatan dan pendidikan bagi warga miskin.Hal ini dimungkinkan karena sistem ini memiliki berbagai kriteria penilaian dari rumah tangga miskin  yang diperoleh dan dirumuskan dengan memperhatikan berbagai faktor yang dianggap relevan dan perlu, selanjutnya dimodelkan secara matematis guna menghasilkan suatu penilaian yang membantu para pengambil keputusan di dalam membuat keputusan penentuan penerima bantuan Program Pemerintah bagi warga miskin.

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