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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Komputer Terapan IT JOURNAL RESEARCH AND DEVELOPMENT INTECOMS: Journal of Information Technology and Computer Science Journal of Applied Engineering and Technological Science (JAETS) INFOKUM Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal UNITEK Jurnal Sistem Informasi dan Teknologi Jaringan Jurnal J-PEMAS JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) JI-Tech Jurnal Testing dan Implementasi Sistem Informasi JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Journal of System and Technology
Khairul Umam Syaliman
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Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Social Sciences

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Perbandingan Rapid Centroid Estimation (RCE) — K Nearest Neighbor (K-NN) Dengan K Means — K Nearest Neighbor (K-NN) Khairul Umam Syaliman; M. Zulfahmi; Aldi Abdillah Nababan
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 2, No 1 (2017): InfoTekJar September
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v2i1.166

Abstract

Teknik Clustering terbukti dapat meningkatkan akurasi dalam melakukan klasifikasi, terutama pada algoritma K-Nearest Neighbor (K-NN). Setiap data dari setiap kelas akan membentuk K cluster yang kemudian nilai centroid akhir dari setiap cluster pada setiap kelas data tersebut akan dijadikan data acuan untuk melakukan proses klasifikasi menggunakan algoritma K-NN. Namun kendala dari banyaknya teknik clustering adalah biaya komputasi yang mahal, Rapid Centroid Estimation (RCE) dan K-Means termasuk kedalam teknik clustering dengan biaya komputasi yang murah. Untuk melihat manakah dari kedua algoritma ini (RCE dan K-Means) yang lebih baik memberikan peningkatan akurasi pada algoritma K-NN maka, pada penelitian ini akan mencoba untuk membandingkan kedua algoritma tersebut. Hasil dari penelitian ini adalah gabungan RCE—K-NN memberikan hasil akurasi yang lebih baik dari K-Means—K-NN pada data set iris dan wine. Namun dalam perubahan nilai akurasi RCE—K-NN lebih stabil hanya pada data set iris. Sedangkan pada data set wine, K-Means—K-NN terlihat mendapati perubahan akurasi yang lebih stabil dibandingkan RCE—K-NN.
Sistem Prediksi Keberhasilan Siswa Menggunakan Metode Nearest Cluster Classifier Khairul Umam Syaliman; Edwil Jafri
Jurnal Sistem Informasi dan Teknologi Jaringan (SISFOTEKJAR) Vol 2 No 2 (2021): September : 2021
Publisher : Pustaka Timur Publisher

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Abstract

According to present curriculum, every unit of elementary education conduct 4 (four) evaluation stages. The first stage is the first midterm evaluation which is done at the first quarter year. Second, the first semester evaluation is done at the second quarter year. Third, the second midterm evaluation is done at the third quarter year. The last is the second semester evaluation which is done at the fourth quarter year. The first midterm evaluation, the first semester evaluation and the second midterm evaluation are done to see the students’ ability in learning. Moreover, to determine the students’ success or failure in learning process at each grade is the score of the second semester which is compared to their minimum passing grade. If the students’ score is higher than the minimum passing grade decided, the students are determined to be successful. In contrary, if the students’ score is lower than minimum passing grade, they will be determined to be failed in learning process.by considering the above condition, the writer is interested in designing a system which can predict the potential failure of students earlier. This system is built by analyzing the first midterm score, the first semester score and the second midterm score by using Nearest Cluster Classifier (NCC) Method. By the result of this prediction, parents and teachers still have time for about 3 months to help and guide students who are predicted to be potentially failed in learning process.
Seleksi Fitur Menggunakan Pendekatan k-Nearest Neighbor (k-NN) Khairul Umam Syaliman; Yuliska; Nina Fadilah Najwa
Jurnal Sistem Informasi dan Teknologi Jaringan (SISFOTEKJAR) Vol 3 No 1 (2022): Maret : 2022
Publisher : Pustaka Timur Publisher

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Abstract

Data preprocessing merupakan salah satu tahapan yang penting dalam proses data mining. Salah satu proses pada tahapan ini adalah seleksi fitur atau disebut juga dengan seleksi variabel. Seleksi fitur adalah proses pemilihan fitur yang paling relevan serta membuang fitur yang tidak relevan, ambigu, redudan dan noisy feature. Proses seleksi fitur sangat menentukan performa metode pada tahapan mining, artinya salah dalam memilih metode pada proses seleksi fitur tidak akan menghasilkan pengetahuan yang benar dan sesuai dengan harapan. Ada banyak metode yang dapat digunakan untuk melakukan seleksi fitur, diantranya Principal Component Analysis (PCA), Informasi Gain dan Gain Ratio, akan tetapi banyak metode dari seleksi fitur yang memiliki kompleksitas dan computation cost yang tinggi.Karena hal tersebut penelitian kali ini menyarankan seleksi fitur dengan pendekatan k-Nnearesst Neighbor (k-NN). Adapun hasil dari penelitian ini terbukti bahwa data yang telah melwati seleksi fitur dengan pendekatan k-NN mampu memberikan hasil akurasi yang lebih baik.
Enhance the Accuracy of k-Nearest Neighbor (k-NN) for Unbalanced Class Data Using Synthetic Minority Oversampling Technique (SMOTE) and Gain Ratio (GR) Khairul Umam Syaliman
INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (339.581 KB)

Abstract

k-Nearest Neighbor (k-NN) has very good accuracy results on data with almost the same class distribution, but on the contrary for information whose class distribution is not the same, the accuracy of k-NN will generally be lower. In addition, k-NN does not separate information for each class, implying that each class has an equal influence in determining the new information class, so it is important to choose a class that generally applies to information before characterizing the class assignments process. To overcome this problem, we will propose a structure that uses the Synthetic Minority Oversampling Technique (SMOTE) strategy to address class distribution problems and Gain Ratio (GR) to perform attribute selection to generate a new dataset with a reasonable class spread and significant class information attributes. E-Coli and Glass Identification were among the datasets used in this review. For objective results, the 10-fold-cross validation method will be used as an evaluation method with k values 1 to 10. The results of the research prove that SMOTE and GR can increase the accuracy of the k-NN method, where the highest increase occurred in the Glass Identification dataset by a difference increase of 18.5%. The lowest increase in accuracy occurred in the E-Coli dataset with an increase of 11.4%. The overall proposed method has given better performance, although the value of precision, recall, and F1-Score is not better than original k-NN when used in dataset E-Coli. To all datasets, an improvement from precision is 41.0%, recall is 43.4% and F1-Score is 41.5%.
Analisa Jenis Interaksi Masyarakat dengan Akuisisi Data Sosial Media Pemerintah KAB/Kota Provinsi Riau: Analisa Jenis Interaksi Masyarakat dengan Akuisisi Data Sosial Media Pemerintah Nina Fadilah Najwa; Yuliska Yuliska; Khairul Umam Syaliman
Jurnal Komputer Terapan  Vol. 6 No. 1 (2020): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (387.19 KB) | DOI: 10.35143/jkt.v6i1.3468

Abstract

This study aims to analyze the type of interaction which is done by acquiring City/District Government’s Facebook Fan page. The acquisition of Facebook Fan page is performed by identifying the number of followers, the number of likes of the page, the number of postings, the number of comments, the number of shared postings and the number of likes of postings. We perform the acquisition in 90 days. Based on the result of data acquisition on 13 Cities/Districts in Riau Province, it indicates that 100% City/District Governments have performed One-Way Push Interaction and 70% of them classified as Two-Way Pool interaction. As for network co-designer of service Interaction, we found that Bengkalis District is the most active in implementing this type of interaction. Based on the results of analyzing the type of interaction between citizens and local governments in Riau Province, most of the Social media Fan Page of local governments are passive. The Collaboration of governments and citizens, which is based on the number of shared postings is classified as low. The next study may discuss the strategy that can be implemented by the governments to maximize the use of social media as media to interact and communicate with the citizens.
APLIKASI UJI KEPRIBADIAN BERDASARKAN MULTIPLE INTELLIGENCES BERBASIS WEB MENGGUNAKAN METODE PROTOTYPING Gina Rahmadhany; Khairul Umam Syaliman bin Lukman
Jurnal Komputer Terapan  Vol. 7 No. 2 (2021): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (566.262 KB) | DOI: 10.35143/jkt.v7i2.4954

Abstract

Multiple intelligences (MI) was developed by Howard Gardner, a developmental psychologist and professor of Harvard University, United States. His theory of Multiple Intelligences (MI) was published in 1993. Gardner believes that as his name implies, multiple intelligences, human cognitive competencies are better described in terms of multiple intelligences such as abilities, talents, or mental skills, which are called intelligences. Everyone has their own abilities and has a certain level in each of these intelligences. From this research resulted in a web-based application that can identify the type of personality and suggestions for each personality then interesting info about each personality. Built using the Laravel framework, PHP and MYSQL programming languages, and using the prototyping method in two iteration, to make the requirements of user for the system can be fulfilled. The results of usability testing through 30 respondents stated that the system was very feasible to use, then using a validation test the results obtained on the system and manual calculations obtained accurate results from the ten samples used and finally the results of the user acceptance test, it was found that all functional systems were running according to which are expected.
Peningkatan Akurasi K-Nearest Neighbor Pada Data Index Standar Pencemaran Udara Kota Pekanbaru Yuliska Yuliska; Khairul Umam Syaliman
IT Journal Research and Development Vol. 5 No. 1 (2020)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2020.vol5(1).4680

Abstract

kNN adalah salah satu metode yang popular karena mudah dieksploitasi, generalisasi yang biak, mudah dimengerti, kemampuan beradaptasi ke ruang fitur yang rumit, intuitif, atraktif, efektif, flexibility, mudah diterapkan, sederhana dan memiliki hasil akurasi yang cukup baik. Namun kNN memiliki beberapa kelemahan, diantaranya memberikan bobot yang sama pada setiap attribut sehingga attribut yang tidak relevant juga memberikan dampak yang sama dengan attribut yang relevant terhadap kemiripan antar data. Masalah lain dari kNN adalah pemilihan tetangga terdekat dengan system suara terbanyak, dimana system ini mengabaikan kemiripan setiap tetangga terdekat dan kemungkinan munculnya mayoritas ganda serta kemungkinan terpilihnya outlier sebagai tetangga terdekat. Masalah-masalah tersebut tentu saja dapat menimbulkan kesalahan klasifikasi yang mengakibatkan rendahnya akurasi. Pada penelitian kali ini akan dilakukan peningkatan akurasi dari kNN tersebut dalam melakukan klasifikasi terhadap data Index Standar Pencemaran Udara di Pekanbaru dengan menggunakan pembobotan attribut (Attibute Weighting) dan local mean. Adapun hasil dari penelitian ini didapati bahwa metode yang diusulkan mampu untuk meningkatkan akurasi sebesar 2.42% dengan rata-rata tingkat akurasi sebesar 97.09%.
Literatur Review Terhadap Metode, Aplikasi dan Dataset Peringkasan Dokumen Teks Otomatis untuk Teks Berbahasa Indonesia Yuliska Yuliska; Khairul Umam Syaliman
IT Journal Research and Development Vol. 5 No. 1 (2020)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2020.vol5(1).4688

Abstract

Saat ini, kebutuhan akan mesin peringkas dokumen teks menjadi semakin nyata karena semakin banyaknya informasi digital yang tersedia baik online maupun offline. Mesih peringkas dokumen teks dibutuhkan agar pembacaan dan pencarian informasi menjadi lebih cepat. Literatur review ini membahas metode, aplikasi, dataset dan Teknik evaluasi yang dapat diimplementasikan untuk riset di bidang peringkasan dokumen untuk teks berbahasa Indonesia. Kami melakukan review terhadap berbagai teknik text summarization, baik unsupervised maupun supervised, dataset yang dapat digunakan sebagai baseline dalam pengembangan sebuah metode dan evaluation measure yang tepat. Literature review ini juga akan menjelaskan sejauh apa perkembangan riset di bidang text summarization untuk dokumen berbahasa Indonesia.
Chatbot Sebagai Wadah Informasi Perkembangan Covid-19 di Kota Pekanbaru Menggunakan Platform Whatsapp Khairul Umam Syaliman bin Lukman; Yuliska Yuliska; Nina Fadilah Najwa
IT Journal Research and Development Vol. 5 No. 2 (2021)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2021.vol5(2).5842

Abstract

Perkembangan penularan Covid-19 ini cukup signifikan karena penyebarannya sudah mendunia dan seluruh negara merasakan dampaknya termasuk Indonesia.Pemerintah Indonesia baik pemerintah pusat maupun pemerintah daerah telah memberikan kebijakan Work from Home (WFH), belajar dari rumah, beribadah di rumah dan membatasi kegiatan yang mengundang khalayak ramai. Kebutuhan informasi terkait perkembangan Covid-19 juga sangat dibutuhkan oleh masyarakat. Akan tetapi, informasi yang berkembang di kalangan masyarakat masih dipertanyakan keabsahan informasinya. Sehingga, dibutuhkan sumber terpercaya dan informasi yang berasal dari pemerintah daerah dan pemerintah pusat. Peran media massa memberikan informasi yang baik dan benar, sehingga tidak menimbulkan kericuhan akibat isu-isu yang belum jelas kebenarannya. Chatbot atau chatterbot merupakan program yang mampu memproses masukan dari pengguna dan menghasilkan tanggapan yang kemudian dikirim kembali ke pengguna. Kebutuhan informasi akan penyebaran Covid-19 yang bisa diperoleh dengan chatbot di platform whatsapp tentunya sangat dibutuhkan oleh masyarakat khususnya masyarakat di Pekanbaru. Layanan chatbot yang mampu memberikan informasi terkini terkait jumlah pasien positif Covid-19, jumlah Pasien Dalam Pengawasan (PDP), jumlah Orang Dalam Pemantauan (ODP), hingga informasi berupa pengetahuan untuk pencegahan Covid-19. Pembangunan chatbot ini akan menggunakan metode string matching dengan metode pengembangan sistem prototype. Dengan implementasi chatbot dengan platform whatsapp ini diharapkan mampu memberikan informasi terpercaya yang bersumber dari data milik pemerintah Kota Pekanbaru dan dapat menyediakan informasi pengetahuan tentang Covid-19 yang benar dan valid. Dengan aplikasi chatbot bagi para praktisi dapat menjadi bahan pertimbangan dan pencegahan agar melakukan social distancing untuk memutus rantai penyebaran Covid-19.
Educational Game as An Effort to Accelerate Learning After The Covid-19 Pandemic Khairul Umam Syaliman; Nina Fadilah Najwa; Jan Alif Kreshna
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v4i1.1322

Abstract

The Covid-19 pandemic that occurred forced us to carry out the learning process through the internet network (online or online). Learning carried out online creates many problems, so it is considered ineffective and causes learning loss. Various methods have been taken to overcome this learning loss, including collaborating with various parties and issuing various regulations. In addition, teachers are also required to provide a new spirit in creating and innovating to provide effective, efficient, and competitive learning media. One way is to do educational game-based learning. Educational games are considered adequate for overcoming learning losses because learning media with educational games require players to participate in determining outcomes, have an entertainment side, and can increase creativity and problem-solving skills. The planned research method stages for collecting the required data are observation, interviews, and literature study. As for the development of educational games in this study, the prototype development method will be used. This study's result is that the Educational Game design has produced output that meets the needs. In future research, when this design is implemented, it is hoped that it will be an alternative medium for accelerating post-pandemic learning.
Co-Authors Aldi Abdillah Nababan Ardianto Wibowo Ardiyanto Ardiyanto Ause Labellapansa, Ause Dadang Syarif Sihabudin Sahid Dini Hidayatul Qudsi Disa Putri, Tiara Ayu Dwi Gunawan, Dwi Dwi Putra, Nanda Edwil Jafri Fikri, Asyrul Gina Rahmadhany Hanifah, Puja Hartanto, Boby Hidayat, Erzi Ibnu Surya Ibnu Surya Jan Alif Kreshna Juanda Hakim Lubis Kartina Diah K. W. Lidia Maysofa M. Zulfahmi Mona Elviyenti Muhammad Crystandy Najwa, Nina Fadila Najwa, Nina Fadilah Nina Fadhilah Najwa Oktavian, Kurnia Eka Rafif, Nabily Ramdani Hadi Nst, Andika Sapriadi Sapriadi Sapriadi, Sapriadi Satria Perdana Arifin Surya, Ibnu Yohana Dewi Lulu Widyasari Yuliska Yuliska Yuliska Yuliska Yuliska Yuliska Yuliska Yuliska Yuliska, Yuliska