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All Journal TEKNIK INFORMATIKA Syntax Jurnal Informatika Jurnal Ilmu Komputer dan Agri-Informatika SITEKIN: Jurnal Sains, Teknologi dan Industri CESS (Journal of Computer Engineering, System and Science) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Informatika Jurnal CoreIT JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Artificial Intelligence and Data Mining Seminar Nasional Teknologi Informasi Komunikasi dan Industri INOVTEK Polbeng - Seri Informatika JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Informatika Universitas Pamulang Jurnal Nasional Komputasi dan Teknologi Informasi JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JOISIE (Journal Of Information Systems And Informatics Engineering) Building of Informatics, Technology and Science Progresif: Jurnal Ilmiah Komputer Zonasi: Jurnal Sistem Informasi Journal of Applied Engineering and Technological Science (JAETS) Jurnal Tekinkom (Teknik Informasi dan Komputer) JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) JUKI : Jurnal Komputer dan Informatika TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) Jurnal Restikom : Riset Teknik Informatika dan Komputer Information System Journal (INFOS) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal UNITEK Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Teknik Indonesia Jurnal Informatika: Jurnal Pengembangan IT Jurnal Komtika (Komputasi dan Informatika)
Fadhilah Syafria
Universitas Islam Negeri Sultan Syarif Kasim Riau
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IMPLEMENTASI ALGORITMA FP-GROWTH UNTUK MENGETAHUI FAKTOR YANG BERPENGARUH TERHADAP KEMAMPUAN MEMBACA AL-QURAN SISWA Muhammad Alvin; Alwis Nazir; M Fikry; Jasril; Fadhilah Syafria
Jurnal RESTIKOM : Riset Teknik Informatika dan Komputer Vol 2 No 2 (2020): Agustus
Publisher : Program Studi Teknik Informatika Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/restikom.v2i2.67

Abstract

Rasulullah membekali Al-Quran dan Hadist kepada umat manusia sebagai pedoman hidup yang menuntun ke jalan yang baik dan benar. Al-Quran merupakan kitab suci yang mengandung ilmu yang wajib diberikan kepada anak terlebih dahulu. Memperkenalkan Al-Quran kepada anak harus dilakukan sejak berusia dini agar tumbuh sesuai dengan fitranya. Namun, sebelum Al-Quran dijadikan sebagai pedoman hidup maka langkah awal yang dilakukan adalah bagaimana membaca Al-Quran yang baik dan benar. Berdasarkan wawancara dengan Ketua Lembaga Pengambangan Tilahwatil Qur’an (LPTQ) kecamatan Pekanbaru Kota mengatakan persentase siswa Sekolah Dasar (SD), Madrasyah Diniyah Awaliyah (MDA) dan Taman Pendidikan Al-Quran (TPA) yang dapat membaca Al-Quran sampai ketingkat Tajwid hanya 40%. Penelitian ini bertujuan untuk meilhat faktor yang mempengaruhi terhadap kemampuan membaca Al-Quran siswa Sekolah Dasar (SD). Teknik yang digunakan pada penelitian ini yaitu teknik association rule algoritma FP-Growth. “Data yang digunakan merupakan data sekunder yang terdiri dari” 19 atribut dengan 214 record data. Hasil rule yang ditemukan dari penelitian ini sebanyak 163 rule “dengan menggunakan nilai minimum support” 30% dan “nilai minimum confidence” 50%. Hasil dari perhitungan ini hanya mengambil item makhroj, Panjang pendek dan tajwid. Dan menghasilkan rule dengan kombinasi 2 “itemset dengan nilai support dan confidence tertinggi adalah kombinasi jika Panjang Pendek buruk maka Makhroj Buruk dengan nilai support 66%, nilai confidence 99% dan nilai lift ratio” 1.47125
PENERAPAN ALGORITMA EQUIVALENCE CLASS TRANSFORMATION (ECLAT) DALAM PENCARIAN ADVERSE EVENT OBAT DIPHENHYDRAMINE Putri Mardatillah; Alwis Nazir; Muhammad Fikry; Elin Haerani; Fadhilah Syafria
Jurnal RESTIKOM : Riset Teknik Informatika dan Komputer Vol 2 No 3 (2020): Desember
Publisher : Program Studi Teknik Informatika Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/restikom.v2i3.74

Abstract

Obat merupakan zat yang dapat menyembuhkan suatu penyakit. Peredaran obat di Indonesia diatur ke dalam beberapa golongan seperti obat golongan bebas, obat bebas terbatas, obat wajib apotik, obat keras, psikotropika dan narkotika. Obat golongan bebas dapat dibeli secara bebas oleh masyarakat untuk menangani suatu penyakit secara singkat. Obat diphenhydramine merupakan salah satu jenis obat golongan bebas yang berguna dalam menangani alergi, batuk, pilek dan obat tidur. Obat diphenhydramine memiliki banyak manfaat namun risiko, efek samping dan adverse event masih belum diketahui. Pada penelitian ini menggunakan data obat diphenhydramine Adverse Event Reporting System milik Food and Drug Administration Amerika Serikat (FAERS FDA) dari tahun 2016 hingga 2020 dengan 4 quarter pertahun serta 8 atribut dari 3 tabel untuk mencari adverse event dengan menggunakan algoritma Equivalence Class Transformation (ECLAT) dengan menerapkan metode Knowledge Discovery in Database (KDD). Pengujian yang dilakukan pada hasil penelitian ini menggunakan lift ratio untuk mengetahui kekuatan rule yang dihasilkan. Penelitian ini menghasilkan 2 jenis itemset, yaitu dengan menggunakan pengujian 2 itemset dengan mininum support 0.1% minimum cofidence 0.1% menghasilkan 416 rule, dan pengujian minimum support 1% minimum cofidence 1% menghasilkan 43 rule. Kemudian dilakukan pengujian dengan menggunakan 3 item set menggunakan minimum support 0.1% dan minimum cofidence 0.1% menghasilkan 882 rule.
Optimization Learning Vector Quantization Using Genetic Algorithm for Detection of Diabetics Inggih Permana; Nesdi Evrilyan Rozanda; Fadhilah Syafria; Febi Nur Salisah
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i3.pp1111-1116

Abstract

This study proposed the method to improve the result of Learning Vector Quantization (LVQ) by optimizing the weight vectors using a genetic algorithm (GA) to detect the diabetics. Initial value of individuals for GA is taken from weight vectors which come from the last m iterations of LVQ training result. The result of experiment showed that there is a significant increase in sensitivity level, however there is a significant decrease in specificity level. It means the proposed method success in improving the LVQ ability to recognized the diabetics, but it lowers the ability of LVQ to recognize the people unaffected by diabetes.This study proposed the method to improve the result of Learning Vector Quantization (LVQ) by optimizing the weight vectors using a genetic algorithm (GA) to detect the diabetics. Initial value of individuals for GA is taken from weight vectors which come from the last m iterations of LVQ training result. The result of experiment showed that there is a significant increase in sensitivity level, however there is a significant decrease in specificity level. It means the proposed method success in improving the LVQ ability to recognized the diabetics, but it lowers the ability of LVQ to recognize the people unaffected by diabetes.
PREDIKSI DATA INDEKS HARGA KONSUMEN PROVINSI RIAU BERBASIS TIME SERIES DENGAN METODE DOUBLE EXPONENTIAL SMOOTHING Dina Septiawati; Siska Kurnia Gusti; Fadhilah Syafria; Yusra Yusra; Eka Pandu Cynthia
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 7, No 4 (2022)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v7i4.3209

Abstract

Indeks Harga Konsumen merupakan indeks yang menghitung rata-rata perubahan harga barang dan jasa. Penelitian ini menggunakan data Indeks Harga Konsumen Provinsi Riau bulan Januari tahun 1999 sampai dengan bulan Desember tahun 2021 yang bersumber dari website resmi Badan Pusat Statistik Provinsi Riau. Penelitian ini bertujuan untuk memberikan gambaran tentang perkembangan indeks harga konsumen apakah mengalami kenaikan atau penurunan sehingga dapat dijadikan sebagai bahan evaluasi kebijakan yang akan diambil oleh pihak pemerintah, swasta, maupun pemegang otoritas moneter. Tahapan untuk prediksi dengan menggunakan metode double exponential smoothing yaitu menghitung nilai pemulusan tunggal (single smoothing), menghitung pemulusan ganda (double smoothing), menghitung nilai konstanta pemulusan, menghitung nilai kofisien trend, dan melalukan prediksi. Untuk melakukan pengujian prediksi maka dilakukan dengan cara perhitungan mean absolute percentage error. Berdasarkan perhitungan yang telah dilakukan, diperoleh hasil prediksi nilai indeks harga konsumen sebesar 105,17 dengan alpha 0,6 bernilai 3,132646%. Dapat disimpulkan bahwa metode double exponential smoothing mempunyai kemampuan yang baik dalam prediksi nilai indeks harga konsumen.
Diagnosa Awal Disgrafia pada Anak Menggunakan Metode Bacpropagation Aji Pangestu Adek; Fadhilah Syafria; Elin Haerani; Elvia Budianita
JURNAL UNITEK Vol. 15 No. 2 (2022): Juli - Desember
Publisher : Sekolah Tinggi Teknologi Dumai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52072/unitek.v15i2.391

Abstract

Gangguan belajar merupakan suatu gangguan dasar dalam psikologis yang meliputi penggunaan pemahaman bahasa tulisan. Gangguan belajar yang termasuk dalam klasifikasi gangguan belajar akademik adalah disgrafia. Disgrafia merupakan gangguan khusus dimana anak tidak dapat mengekspresikan pikirannya kedalam bentuk tulisan, karena tidak dapat mengkoordinasikan motorik halusnya untuk menulis dan menyusun kata dengan benar. Diagnosa awal disgrafia pada anak terdiri atas disgrafia dan tidak disgrafia. Diagnosa ini menggunakan 31 variabel inputan menggunakan metode Backpropagation dengan menggunakan data yang berjumlah 150 data. Dari pengujian yang dilakukan didapatkan hasil menggunakan learning rate 0.1 dan 0.01, maks epoch 500 dengan arsitektur jaringan syaraf tiruan 31-31-1 dengan pembagian data 90:10 menghasilkan nilai akurasi sebesar 100% serta pada pembagian data 80:20 menggunakan learning rate 0.1, maks epoch 500 dengan arsitektur jaringan syaraf tiruan 31-31-1 menghasilkan nilai akurasi sebesar 100%. Maka dapat disimpulkan bahwa diagnosa disgrafia pada anak dengan backpropagation dapat dilakukan sangat baik.
KLASIFIKASI PENYAKIT PARU-PARU DENGAN MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Muhammad Yusril Haffandi; Elin Haerani; Fadhilah Syafria; Lola Oktavia
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 2 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i2.649

Abstract

The lungs are one of the organs of the human body that are very important in the process of respiration. There are several types of lung diseases, including Asthma, Bronchitis, Dyspnea, Pneumonia, COPD, and Tuberculosis. There are difficulties in the classification process, because the symptoms shown by sufferers have similarities between diseases. The purpose of this research is to classify lung disease using the Naive Bayes Classifier method. The choice of this method is because it only requires a small amount of training data to determine the estimated parameters needed in the classification process. This research was conducted at the Regional General Hospital Major General HA Thalib City of Sungai Full from August 3 2022 to September 3 2022. The data taken was in the form of medical records of lung disease patients from July to August as many as 134 patient data containing 19 symptoms disease and 6 disease diagnoses. From the test results using the Rapidminer application and data separation in the form of 34 testing data and 100 training data with a data comparison of 7:3, an accuracy value of 97.06 was obtained.
DESAIN ARSITEKTUR DATA WAREHOUSE PADA DATA TRANSAKSI PENJUALAN ROTTE BAKERY Devi Julisca Sari; Siska Kurnia Gusti; Alwis Nazir; Elin Haerani; Fadhilah Syafria
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 2 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i2.605

Abstract

The increasingly fierce competition between competitors requires companies to be able to compete and maintain their existence in order to continue to grow, for that utilizing information technology such as data warehouses will play a large enough role, because optimal data processing will produce quality information in supporting companies to take appropriate policies. as well as increasing the productivity and effectiveness of the company's performance. The application of the data warehouse can be started by making an architectural design that will be made, for that the researcher aims to provide recommendations for the design of the data warehouse architecture on the sales transaction data of Rotte Bakery by applying the Nine Steps Kimball method. The final result of this research is the application of the Nine Steps Kimball method and the integration of transaction data through the ETL process (extract, transform, load) successfully produces data stored in the data warehouse only the data that is needed and has been uninformed, so that data processing only takes a long time. shorter time in supporting appropriate policy making and achieving business strategies in order to be able to keep pace with the business competition
Penerapan Metode Clustering Dalam Pengelompokan Kasus Perceraian Pada Pengadilan Agama di Kota Pekanbaru Menggunakan Algoritma K-Medoids Satria Bumartaduri; Siska Kurnia Gusti; Fadhilah Syafria; Elin Haerani; Siti Ramadhani
JURIKOM (Jurnal Riset Komputer) Vol 10, No 1 (2023): Februari 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i1.5560

Abstract

Divorce is the breaking of a husband and wife relationship from a marriage. When a couple does not want to continue their marriage relationship, one of the factors causing divorce is that the husband and wife do not carry out their duties properly. Divorce cases also occur in the city of Pekanbaru and have increased from 2020 to 2022. In connection with this problem, researchers conducted research with the aim of classifying districts in Pekanbaru that have the most divorces. The method used in this study is K-Medoids Clustering, because this method can divide a dataset into several groups. The advantage of this method is that it can overcome the weaknesses of the K-Means algorithm which are sensitive to outliers. The tests used in this study use the RapidMiner tools and the Davies Bouldin Index to ensure cluster accuracy. Attributes used in this research are region/regency, age difference between spouses, plaintiff's and defendant's education, and reasons for divorce. The results of this study can be used as information for the government to reduce the divorce rate in the city of Pekanbaru so that appropriate programs can be developed for each sub-district in overcoming the divorce rate in Pekanbaru. From testing using the K-Medoids algorithm, the cluster results obtained showed that the highest divorce rate was in cluster 1 with 565 items, while cluster 2 had 395 items and cluster 3 had 288 items. The results of the study show that the use of 3 clusters is the best cluster with a DBI value of 0.884.
Klasifikasi Clickbait Menggunakan Transformers Mori Hovipah Mori Hovipah; Elin Hearani; Jasril Jasril; Fadhilah Syafria
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4713

Abstract

Clickbait is a news title created by the author with the aim of attracting the getting to get readers so they Never miss a headline. Clickbait headlines are typically quirky, confusing, and use exaggerated sentences to entice readers to click on links. However, clickbait headlines that look very attractive often do not match the information in the headlines and the content of the news, which can lead to the spread of fake news and hoaxes. Then classification of clickbait news titles is carried out, for this research, clickbait classification was carried out for news titles will be carried out using the Transformers method. The number of news titles used in this study amounted to 6632 news titles. The process of classification of news titles in this study includes: collecting data, labeling data, preprocessing, EDA, and classification using transformers. The best accuracy value obtained in this study was 63% for precision of 0.63 and recall of 1 using a data division of 10%: 90%.
Penerapan Data Mining untuk Menentukan Penyebab Kematian di Indonesia Menggunakan Metode Clustering K-Means Lili Rahmawati; Alwis Nazir; Fadhilah Syafria; Elvia Budianita; Lola Oktavia; Ihda Syurfi
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 3 (2023): Maret 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i3.5912

Abstract

Death in medical science is studied in a scientific discipline called tanatology. death is not only experienced by elderly people, but also can be experienced by young people, teenagers, or even babies. Death can be caused by various factors, namely, due to illness, old age, accidents, and so on. Based on information provided by the World Health Organization (WHO), there are five highest causes of death including ischemic heart disease, Alzheimer's, stroke, respiratory disorders, neonatal conditions. In this study, k-means is used to group causes of death in Indonesia based on the number of deaths that occur to determine the cases of death that have the most impact on the high mortality rate in Indonesia. Knowing what these death cases are will provide early preparation in anticipating the causes of death in Indonesia. The purpose of this study was to classify mortality rates based on the number of causes of death which were included in the low, medium, and high clusters by applying the K-Means method. In this study the authors used the K-Means clustering algorithm to classify death rates in data on causes of death in Indonesia from 2017-2021. The results of this study formed 3 clusters which were evaluated using the Davies Bouldin Index (DBI) in Rapidminer with a value of 0.259. Clustering results from a total of 21 cases obtained high, medium and low clusters. This cluster grouping was obtained according to the number of deaths per case, namely the first cluster (C0) was low with 17 cases, the second cluster (C1) was moderate with 3 cases and the third cluster (C2) was high with 1 case.
Co-Authors Abdul Aziz Abdullah, Said Noor Abdussalam Al Masykur Adrian Maulana Adzhima, Fauzan Afriyanti, Liza Agung Syaiful Rahman Agus Buono Agustina, Auliyah Ahmad Paisal Aji Pangestu Adek Akbar, Lionita Asa Alfin Hernandes Alwaliyanto Alwis Nazir Alwis Nazir Alwis Nazir Alwis Nazir Alwis Nazir Alwis Nazir Amalia Hanifah Artya Aminuyati Andre Suarisman Aprima, Muhammad Dzaky Ariq At-Thariq Putra Baehaqi Bib Paruhum Silalahi Boni Iqbal Che Hussin, Ab Razak Darmila Dede Fadillah Deny Ardianto Devi Julisca Sari Dina Septiawati Dodi Efendi Eka Pandu Cynthia Elin Haerani Elin Haerani Elin Haerani Elin Haerani Elin Haerani Elin Haerani Elin Haerani Elin Hearani Ellin Haerani Elvia Budianita Faska, Ridho Mahardika Fatma Hayati Fauzan Adzim Febi Nur Salisah Febi Yanto Felian Nabila Fitra Lestari Fitri Insani Fitri Insani Fitri Wulandari Fratiwi Rahayu Gusrifaris Yuda Alhafis Gusti, Siska Kurnia Guswanti, Widya Habibi Al Rasyid Harpizon Hafez Almirza Hafsyah Hara Novina Putri Harni, Yulia Hertati Ibnu Afdhal Ihda Syurfi Iis Afrianty Iis Afrianty Ikhsan, Tomi Ikhsanul Hamdi Indrizal, Habibi Putra Inggih Permana Irma Sanela Ismail Marzuki Ismar Puadi Isnan Mellian Ramadhan Israldi, Tino Iwan Iskandar Iwan Iskandar Iwan Iskandar Iwan Iskandar Iwan Iskandar Jasril Jasril Jasril Jasril Karina Julita Khair, Nada Tsawaabul Lestari Handayani Lestari Handayani Lili Rahmawati Liza Afriyanti Lola Oktavia Lola Oktavia M Fikry M. Afif Rizky A. Ma'rifah, Laila Alfi Masaugi, Fathan Fanrita Maulana Junihardi Mawadda Warohma Mazdavilaya, T Kaisyarendika Mhd. Kadarman Mori Hovipah Mori Hovipah Morina Lisa Pura Muhammad Affandes Muhammad Alvin Muhammad Fahri Muhammad Fikry Muhammad Hanif Abdurrohman Muhammad Ichsanul Bukhari Muhammad Irsyad Muhammad Syafriandi, Muhammad Muhammad Taufiq Muhammad Yusril Haffandi Muhammad Yusuf Fadhillah Mulyono, Makmur Muslimin, Al’hadiid Nabyl Alfahrez Ramadhan Amril Nailatul Fadhilah Nazir, Alwis Nazruddin Safaat H Negara, Benny Sukma Neni Sari Putri Juana Nesdi Evrilyan Rozanda Nining Nur Habibah Novriyanto Novriyanto Nurainun Nurainun Okfalisa Okfalisa Permata, Rizkiya Indah Pizaini Pizaini Puspa Melani Almahmuda Putra, Fiqhri Mulianda Putri Mardatillah Putri, Widya Maulida Rahmad Abdillah Rahmad Abdillah Rahmad Kurniawan Rahmadhani, R. Raja Sultan Firsky Ramadhan, Aweldri Ramadhan, Muhammad Ilham Ramadhani, Siti Reski Mai Candra Reski Mai Candra Reski Mai Candra Reski Mei Candra Riska Yuliana Roni Salambue Said Nanda Saputra Satria Bumartaduri Silfia Silfia Siti Ramadhani Siti Sri Rahayu Suswantia Andriani Suwanto Sanjaya Syaputra, Muhammad Dwiky Teddie Darmizal Vitriani, Yelvi Wulandari, Fitri Yaskur Bearly Fernandes Yusra, Yusra Yusril Hidayat Zabihullah, Fayat Zulastri, Zulastri