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All Journal Jurnal Dedikasi Jurnal Ilmu Komputer Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Simantec Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Teknologi Informasi dan Ilmu Komputer SMATIKA Proceeding of the Electrical Engineering Computer Science and Informatics Fountain of Informatics Journal Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Informatika Jurnal Pilar Nusa Mandiri Network Engineering Research Operation [NERO] Jurnal Komputer Terapan Syntax Literate: Jurnal Ilmiah Indonesia Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control SINTECH (Science and Information Technology) Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURTEKSI EDUMATIC: Jurnal Pendidikan Informatika Jurnal Informatika Kaputama (JIK) JISKa (Jurnal Informatika Sunan Kalijaga) Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Repositor Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Jurnal Perempuan & Anak Jurnal Dinamika Informatika (JDI) Makara Journal of Technology Jurnal Sistem Informasi Jurnal Informatika: Jurnal Pengembangan IT

Yufis Azhar

Universitas Muhammadiyah Malang

Author-ID : 237577

Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Contraception Recommendations With Analytical Hierarchy Process (AHP) and Weighted Product Methods (WP) Audi Bayu Yuliawan; Nur Hayatin; Yufis Azhar
Jurnal Perempuan dan Anak Vol. 4 No. 1 (2021): Februari
Publisher : Universitas Muhammadiyah Malang

Planning Program (KB) as one way to reduce the high rate of pregnancy. Contraceptives used in family planning programs have various types. In addition to the presence of contraception for women, contraception is also available for men. It's just that the problem at this time, lack of knowledge will choose contraception in accordance with health conditions. The limited time, place and expertise of experts to always provide information is one of the obstacles to getting complete information. Decision Support System is a knowledge-based computer information system that is used to support decision making in a problem. This system will later use the Analytical Hierarchy Process method, this method is a method that makes decision makers to get priority scale or consideration of experience, views, intuition and original data. Not only that this system will also use the Weighted Product (WP) method to maximize the performance of AHP in ranking the final results. This application is made using the Android programming language with Android Studio as the platform. In this application will later display recommendations for selecting contraceptives that are suitable for a patient.

Digital Literacy for Hizbul Wathan Scout Movement Cadres in Batu City Yufis Azhar; Mahar Faiqurahman; Wildan Suharso
Jurnal Perempuan dan Anak Vol. 4 No. 2 (2021): Agustus
Publisher : Universitas Muhammadiyah Malang

Related to human resource development, Indonesia will take the advantage of demographics bonus in 2030-2040, which is the productive age of the Indonesian population is greater than the non productive age. Certainly, this becomes a challenge for Indonesian people to develop the human resources who are ready to face 4.0 Industry era, so that the good insight and abilities in digital literacy, which is the basic knowledge of the 4.0 Industry, are needed for young generation today. This is crucial considering the development of Information and Communication Technology (ICT) is very vulnerable to be misused, so it will not give benefit to the country. Hizbul Wathan (HW), one of the scouting organization, which develop the young generation, expected to play an active role in the development of 4.0 Industry era, so that the knowledge and skill in the field of ICT is absolutely needed. By this community service activity, we have given insight and deep knowledge about digital literacy to the Hisbul Wathan Scouting Organization, especially for Regional Quarters of Batu City members.

Analisis Sentimen Tweet Tentang UU Cipta Kerja Menggunakan Algoritma SVM Berbasis PSO Trifebi Shina Sabrila; Yufis Azhar; Christian Sri Kusuma Aditya
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 7 No. 1 (2022): Januari 2022
Publisher : UIN Sunan Kalijaga Yogyakarta

Support Vector Machine (SVM) is one of the most widely used classification algorithms for sentiment analysis and has been shown to provide satisfactory performance. However, despite its advantages, the SVM algorithm still has weaknesses in selecting the right SVM parameters to optimize the performance. In this study, sentiment analysis was done with the use of data called tweets about Undang-Undang Cipta Kerja which reap many pros and cons by the people in Indonesia, especially the laborers. The classification method used in this study is the Support Vector Machine algorithm which is optimized using the Particle Swarm Optimization method for the SVM parameters selection in the hope of optimizing the performance generated by the SVM algorithm in sentiment analysis. The results of the study using 10 k-fold cross-validations using the SVM algorithm resulted in an accuracy of 92,99%, a precision of 93,24%, and a recall of 93%. Meanwhile, the SVM and PSO algorithms produce an accuracy of 95%, precision of 95,08%, and recall of 94,97%. The results show that the Particle Swarm Optimization method can overcome the weaknesses of the Support Vector Machine algorithm in the problem of parameter selection and has succeeded in improving the resulting performance where the SVM-PSO is more superior to SVM without optimization in sentiment analysis.

Sistem Pendukung Keputusan Rekrutmen Karyawan PT. Sims Jaya KALTIM Menggunakan Motode SAW (Simple Additive Weighting) Yurizal Rizqon Rifani; Yufis Azhar; Wildan Suharso
Jurnal Repositor Vol 4 No 3 (2022): Agustus 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/repositor.v4i3.1457

PT. Sims Jaya Kaltim merupakan sebuah perusahaan jasa pertambangan yang menjadi salah satu kontraktor di PT. Kideco Jaya Agung yang merupakan produsen batu bara ketiga terbesar di Indonesia. SDM (Sumber Daya Manusia) adalah salah satu elemen terpenting dalam keberhasilan usaha dibidang pertambangan, maka dari itu PT. Sims Jaya Kaltim berupaya selektif saat perekrutan karyawan. Saat ini belum adanya sistem yang dapat membantu keputusan perusahaan tersebut pada saat perekrutan karyawan. Hal ini berdampak pada pengeluaran perusahaan yang sangat besar saat proses Medical Check Up pelamar, dikarenakan pelamar yang akan di Medical Check Up lebih banyak dari yang dibutuhkan nantinya. Untuk mengatasi masalah itu, PT. Sims Jaya Kaltim terutama pada Departemen HRD (Human Resources Departement) membutuhkan sistem yang dapat membatu mengambil keputusan pada proses Medical Check Up dan keputusan akhir penerimaan karyawan. Penelitian ini menggunakan metode Simple Additive Weighting sebagai pendukung keputusan. Sistem akan dibangun menggunakan bahasa pemrograman PHP menggunakan framework CodeIgniter, database MySQL, dan metode Black Box pada pengujiannya, serta melakukan perbandingan perhitungan manual dengan sistem pada metode Simple Additive Weighting. Pada pengujian fungsional sistem didapatkan hasil seperti yang diharapkan, ini menandakan sistem sudah berjalan sesuai dengan kebutuhan pengguna. Begitupun pada hasil perbandingan perhitungan metode Simple Additive Weighting secara manual dengan sistem yang didapatkan adalah sama.

Music Information Retrieval Based on Active Frequency Wibowo, Hardianto; Suharso, Wildan; Azhar, Yufis; Wicaksono, Galih Wasis; Minarno, Agus Eko; Harmanto, Dani
Makara Journal of Technology Vol. 25, No. 2
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Music is the art of combining frequencies. A balance of frequencies gives rise to a harmonious tone. Several features of music can be analyzed, and they include sociocultural background, lyrics, mood, tempo, rhythm, harmony, melody, timbre, and instrumentation. In this study, we use the frequency of instrumentation as a feature for classification because each instrument has a frequency range. To test this frequency range, we use five music genres and one music playing skill. The five genres are dangdut, electronic dance music (EDM), metal, pop/rock, and reggae. The music playing skill is acoustic. Active frequencies are tested using the k-nearest neighbor method, and the results serve as basis of the accuracy of music classification. The classification accuracy for EDM, metal, and acoustic is over 70%, whereas that for dangdut, pop/rock, and reggae is less than 60%. In sum, the accuracy of music classification is influenced by the similarities in the music instruments used and the tempo.

Perbandingan Model Logistic Regression dan Artificial Neural Network pada Prediksi Pembatalan Hotel Moch Shandy Tsalasa Putra; Yufis Azhar
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 1 (2021): Januari 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

Prediction for canceled booking hotels is an important part of hotel revenue management systems in the modern era. Because the predicted result can be used for the optimization of hotel performance. The application of machine learning will be very helpful for predicting canceled booking hotels because machine learning can process complex data. In this research, the proposed methods are Artificial Neural Network (ANN) and Logistic Regression. Later it will be done five times experiments with hyperparameter tuning to see which method is the most optimal to do prediction canceled booking hotel. From five times experiments, experiments number five (logistic regression with GridSearchCV) is the most optimal for predicting canceled booking hotels, with 79.77% accuracy, 85.86% precision, and 55.07% recall.

Segmentasi Pelanggan Berdasarkan Perilaku Penggunaan Kartu Kredit Menggunakan Metode K-Means Clustering Fatimah Defina Setiti Alhamdani; Ananda Ayu Dianti; Yufis Azhar
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 2 (2021): Mei 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

Credit card is one of the payment media owned by banks in conducting transactions. Credit card issuers provide benefits for banks with interest that must be paid. Credit card issuers also provide losses to banks that have agreed to pay not to pay their credit card bills. To request a loan from the bank, a cluster model is needed. This study, proposing a segmentation system in research using credit cards to determine marketing strategies using the K-Means Clustering method and conducting experiments using the 4 methods namely K-Means, Agglomerative Clustering, GMM, and DBSCAN. Clustering is done using 9000 active credit card user data at banks that have 18 characteristic features. The results of cluster quality accuracy obtained by using the K-Means method are 0.207014 with the number of clusters 3. Based on the results obtained by considering 4 of these methods, the best method for this case is K-Means.

Classification of Brain Tumors on MRI Images Using Convolutional Neural Network Model EfficientNet Muhammad Aji Purnama Wibowo; Muhammad Bima Al Fayyadl; Yufis Azhar; Zamah Sari
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 4 (2022): Agustus 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

A brain tumor is a lump caused by an imperfect cell turnover cycle in the brain and can affect all ages. Brain tumors have 4 grades, namely grades 1 to 2 are benign tumor grades, and grades 3 to 4 are malignant tumor grades. Therefore, early identification of brain tumor disease is very important in providing appropriate treatment and treatment. This study uses a dataset obtained through the Kaggle website titled Brain Tumor Classification (MRI). The number of data is 3264 images with details of Glioma tumors (926 images), Meningioma tumors (937 images), pituitary tumors (901 images), and without tumors (500 images). In this study, there are 4 scenarios with different testers. This study proposes the classification of brain tumors using Hyperparameter Tuning and EfficientNet models on MRI images. The EfficientNet model used is the EfficientNetB0 and EfficientNetB7 models with the architecture used are the input layer, GlobalAveragePooling2D layer, dropout layer, and dense layer as well as adding augmentation data to the dataset to manipulate the data in order to improve the results of the proposed model. After building the model, the results of accuracy, precision, recall, and f1-score will be obtained in each scenario. Accuracy results in Scenario 1 are 91%, scenario 2 is 95% accurate, scenario 3 is 95%, and scenario 4 is 98%.

Sistem Rekomendasi Produk Skincare Korea Berbasis Web Menggunakan Metode Collaborative Filtering Elsyah Ayuningrum; Yufis Azhar; Gita Indah Marthasari
Jurnal Repositor Vol 4 No 4 (2022): November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/repositor.v4i4.1418

Teknologi informasi saat ini sangat membantu dalam menunjang kehidupan manusia hampir di semua aspek kehidupan dan turut mempengaruhi pesatnya perkembangan industri kecantikan saat ini. Di Indonesia sendiri, brand skincare Korea dari A-Z sudah banyak beredar secara online seperti Laneige, Innisfree, The Saem, Klavuu, COSRX, Some by Mi, dan masih banyak lagi. Maka penulis pada penelitian ini ingin membuat suatu rancangan sistem rekomendasi skincare Korea. Dalam penelitian ini penulis menggunakan system rekomendasi metode collaborative filtering untuk menghasilkan sebuah sistem berbasis web yang dapat menghasilkan rekomendasi produk skincare korea berdasarkan rating produk. Selanjutnya setelah nilai rating berhasil diinput maka selanjutnya adalah Nilai similarity antar produk. Dari penelitian ini nilai yang dihasilkan cukup bagus antar produknya. Nilai similarity yang bagus adalah nilainya mendekati +1 maka artinya hubungan antar kedua produk tersebut cukup kuat, sebaliknya jika nilai yang dihasilkan -1 maka dapat diambil kesimpulan jika hubungan antara kedua produk sangat jauh / bertolak belakang. Hasil dari penelitian ini adalah dapat menyediakan rekomendasi daftar produk skincare sehingga nantinya pengguna dapat memilih produk skincare berdasarkan pendekatan terbaik. Sistem ini juga telah diuji menggunakan blackbox testing yang mana semua fungsi sistem telah valid dan nilai evaluasi MAE yang dihasilkan 0,25.

Implementasi Convolutional Neural Network Untuk Ekstraksi Fitur Citra Daun Dalam Kasus Deteksi Penyakit Pada Tanaman Mangga Menggunakan Random Forest Riksa Adenia; Agus Eko Minarno; Yufis Azhar
Jurnal Repositor Vol 4 No 4 (2022): November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/repositor.v4i4.1436

Penyakit daun mangga tidak hanya mempengaruhi pentingnya dari proses perkembangan pada tumbuhan, namun juga berdampak terhadap segala aspek, mulai dari hasil perkembangbiakan pada tanaman mangga seperti kualitas dari buah, daun, dan batang, namun juga berpengaruh terhadap nilai kuantitas Tujuan utama dari dari penelitian ini adalah untuk mengembangkan metode serta fitur-fitur yang akan mendukung proses dari penelitian. Seperti klasifikasi, memprediksi serta mendeteksi adanya suatu penyakit pada objek yang diteliti. Oleh karena itu, pada penelitian ini mengusulkan metode CNN untuk klasifikasi daun mangga yang terinfeksi oleh penyakit dan dikombinasi dengan metode Random Forest masuk dalam kategori Supervised Learning yang merupakan sebuah pendekatan yang dimana sudah terdapat data yang dilatih, dan terdapat variabel yang sudah ditargetkan sehingga tujuan dari pendekatan tersebut adalah mengelompokan sebuah data ke data yang sudah ada. Sehingga algoritma Random Forest akan digunakan sebagai penguji algoritma pembelajaran mesin konvensional di dalam penelitian. Penelitian ini mendapatkan hasil yang baik pada hasil pengujian dengan tingkat akurasisebesar 100% dari kedua metode yang digunakan CNN dan Random forest.

Co-Authors A.A. Ketut Agung Cahyawan W Achmad Fauzi Saksenata Adhigana Priyatama Aditya Dwi Maryanto Adnan Burhan Hidayat Kiat Afdian, Riz Agus Eko Minarno Agus Zainal Arifin Ahmad Annas Al Hakim Ahmad Darman Huri Ahmad Hanif Nurfauzi Ahmadu Kajukaro Akbi, Denar Regata Akmal Muhammad Naim Al asqalani, Sheila Fitria Al-rizki, Muhammad Andi Alfin Yusriansyah Ali Sofyan Kholimi Amelia, Putri Juli Ananda Ayu Dianti Andhika Ade Verdiyanto Andhika Pranadipa Andi Shafira Dyah Kurniasari Andreawana, Andreawana Andriani Eka Pramudita Annisa Annisa Annisa Fitria Nurjannah Aria Maulana Aripa, Laofin Aris Muhandisin arrafiq, ubay hakim Arya, Tri Fidrian Audi Bayu Yuliawan Aulia Ligar Salma Hanani Bagas Aji Aprian Basuki, Setio Bayu Yuliawan, Audi Bintang, Rahina Chandranegara, Didih Rizki Chita Nauly Harahap Christian Sri Kusuma Aditya Christian Sri kusuma Aditya, Christian Sri kusuma Cokro Mandiri, Mochammad Hazmi Denny Risky Delis Putra Dewi Agfiannisa Diana Purwitasari Doni Yulianto Dwi Anggraini Puspita Rahayu Dwi Kurnia Puspitaningrum DWI RAHMAWATI Dyah Anitia Dyah Ayu Irianti Eko Budi Cahyono Elsyah Ayuningrum Elza Norazizah Evi Febrion Rahayuningtyas Fahrur Rozi Faizun Nuril Hikmah Faldo Fajri Afrinanto Fatimah Defina Setiti Alhamdani Fenny Linsisca Putri Feny Novia Rahayu Feranandah Firdausi Ferin Reviantika Ferin Reviantika Fikri, Ulul Fiqri Azmi Fachir Firdausi, Feranandah Firdausita, Nuris Sabila Firdausy, Aidia Khoiriyah Firdhansyah Abubekar Fitri Bimantoro Galang Aji Mahesa Galang Aji Mahesa Gita Indah Marthasari Hanung Adi Nugroho Haqim, Gilang Nuril Hardianto Wibowo Haris Diyaul Fata Harmanto, Dani Hasanuddin, Muhammad Yusril Hermansyah Adi Saputra Hiu Adam Abdullah Hussin Agung Wijaya Ibrahim, Zaidah Ilham Rahmana Syihad Imam Halimi Irfan, Muhammad Ivan Dwi Nugraha Jahtra Hidayatullah Jalu Nusantoro Khoirir Rosikin Kiki Ratna Sari Lina Dwi Yulianti Linggar Bagas Saputro Lusianti, Aaliyah M Syawaluddin Putra Jaya M. Randy Anugerah Mahar Faiqurahman Maskur Maskur Maskur Maskur Masluha, Ida Maulina Balqis Meilina Agustina Mentari Mas'ama Safitri Moch Shandy Tsalasa Putra Moch. Chamdani Mustaqim Mochammad Hazmi Cokro Mandiri Moh. Badris Sholeh Rahmatullah Muhammad Aji Purnama Wibowo Muhammad Al Reza Fahlopy Muhammad Andi Al-Rizki Muhammad Athaillah Muhammad Bima Al Fayyadl Muhammad Fadliansyah Muhammad Hussein Muhammad Misbahul Azis Muhammad Nuchfi Fadlurrahman Muhammad Riadi Muhammad Rifal Alfarizy Muhammad Rivaldi Asyhari Muhammad Rizki Muhammad Rizky Iman Permana Muhammad Shalahuddin Zulva Mujaddid Izzul Fikri Nabillah Annisa Rahmayanti Nina Mauliana Noor Fajriah Novandha Yudyanto Noviani Sintia Duwi Trisna Nur Hayatin Nur Putri Hidayah Nuryasin, Ilyas Oktavia Dwi Megawati Otto Endarto Prakoso, Rahmat Pratama, Dhimas Rama Anthony Navy Putri, Ira Ekanda Rahma Ningsih Rangga Kurnia Putra Wiratama Ratna Sari Rifky Ahmad Saputra Riksa Adenia Riska Septiana Putri Rista Azizah Arilya Riz Afdian Rizal Arya Suseno Rizal Rakhman Mustafa S, Vinna Rahmayanti Saputri, Indah Sari Wahyunita Sari, Veronica Retno Sari, Zamah Satrio Hadi Wijoyo Septiyan Andika Isanta Setiono, Fauzan Adrivano Shintya Larasabi , Auliya Tara Silcillya Ayu Astiti Siti Maghfiroh Sucia, Dara Suryani Rachmawati Suseno, Jody Ririt Krido Susi Ekawati Syaifuddin Syaifuddin Syaifudin Zuhri Taufik Nurahman Tri Fidrian Arya Trifebi Shina Sabrila Trifebi Shina Sabrila Ujilast, Novia Adelia Ulfah Nur Oktaviana Veronica Retno Sari Vinna Utami Putri Wahyu Priyo Wicaksono Wana Salam Labibah Wicaksono, Galih Wasis Widya Rizka Ulul Fadilah Wildan Suharso Wildan Suharso Wildan Suharso Yesicha Amilia Putri Yuda Munarko Yudhono Witanto Yurizal Rizqon Rifani Yusuf, Achmad Zamah Sari Zulva, Muhammad Shalahuddin

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