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All Journal JUITA : Jurnal Informatika JUSIFO : Jurnal Sistem Informasi JOIN (Jurnal Online Informatika) Journal of Economic, Bussines and Accounting (COSTING) INTECOMS: Journal of Information Technology and Computer Science INTEK: Informatika dan Teknologi Informasi International Journal of Engineering, Technology and Natural Sciences (IJETS) Indonesian Journal of Data and Science G-Couns: Jurnal Bimbingan dan Konseling Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science International Journal of Artificial Intelligence in Medical Issues
Umar Zaky
University Technology Of Yogyakarta
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Medicine & Pharmacology Physics Public Health Other

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METHOD COMPARISON ANALYSIS SIMPLE ADDITIVE WEIGHTING (SAW) WITH WEIGHTED PRODUCT (WP) METHOD IN SUPPORTING THE DECISION TO ACCEPT NEW EMPLOYEES Ramadhan, Idham; Zaky, Umar
Jurnal Internasional Teknik, Teknologi dan Ilmu Pengetahuan Alam Vol 2 No 1 (2020): International Journal of Engineering, Technology and Natural Sciences
Publisher : University of Technology Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (668.85 KB) | DOI: 10.46923/ijets.v2i1.66

Abstract

Employee selection is the first step in a company or agency that aims to obtain qualified and competent human resources that will serve and do all the work on an instinct. The process of selection of prospective employees has two decisions that are accepted and rejected. When an agency or company is unable to determine the human resources that fit the required criteria, it will be very detrimental for an agency or company more than the number of prospective employees who register will be troublesome in terms of calculation and determining competent human resources and in accordance with the required criteria. In this case to minimize or solve the problem, the author designed and built a system to help the agencies, especially Gunung Jati Regional Hospital (RSD) in terms of the selection of new employee admissions. The development of this system by analyzing two methods, namely Simple Additive Weighting (SAW) method with Weighted Product (WP) method with the specified criteria. These two methods will be compared to get a good method and relevant to be applied in the selection of new employees at Gunung Jati Hospital so that the human resources received really match the needs of the agency. Analysis is carried out using the accuracy of each method by referring to the original data owned by the institution. The result of saw method conformity or percentage level is 99.959996% with an accuracy value of 84% and wp method of 99.959992% with an accuracy value of 76%. Thus the SAW method is the most relevant method to solve the problem of receiving new employees.
RADIO FREQUENCY IDENTIFICATION AND IMAGE-BASED FACIAL IDENTIFICATION AS AN EMPLOYEE ATTENDANCE SYSTEM Raden Andy Kurniawan; Zaky, Umar
Jurnal Internasional Teknik, Teknologi dan Ilmu Pengetahuan Alam Vol 2 No 1 (2020): International Journal of Engineering, Technology and Natural Sciences
Publisher : University of Technology Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (987.254 KB) | DOI: 10.46923/ijets.v2i1.67

Abstract

The current development of microcontroller technology can be used to build a presence system for employees. The employee attendance system uses radio frequency identification and facial identification which is designed and built to make it easier to do attendance data recording, so that the data obtained can be precise and accurate. Data collection techniques, namely by interview and observation. The application development process uses the PHP and Python programming languages ​​with Visual Studio Code software applications, Arduino Uno, MySQL software as a database server, and XAMPP as a support. The input used in this system is the employee's personal data and the results of employee face data retrieval which are stored in the .jpg format. The faces taken were taken from 4 people where each face was taken 20 face samples. The results are in the form of web and applications that will provide solutions to existing problems. The conclusion of this application makes it easy to do the recording and attendance, and minimize the fraud committed by employees. Retrieval of face data was taken as much as 20 data with the highest level of accuracy was 87% when the presence test was carried out.
Klasifikasi Menggunakan Metode Naïve Bayes: Tingkat Pengaruh Penggunaan Gadget terhadap Kematangan Kecerdasan Emosi Mahasiswa Umar Zaky; Ari Prasetyoaji; Ilham Fathullah
JUSIFO : Jurnal Sistem Informasi Vol 6 No 2 (2020): JUSIFO (Jurnal Sistem Informasi) | December 2020
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v6i2.6605

Abstract

Gadgets are generally used by individuals to help increase their knowledge, facilitate communication, and also accelerate the development of scientific information. The use of gadgets such as smartphones, laptops, tablets, or iPads has become a habit among students. The students use gadgets for their daily needs. The convenience offered by using gadgets makes students need to be wise in using gadgets. The students can easily search for the lecture materials, take online classes, communicate in a virtual classroom, and see the results of their studies. However, gadgets also have a negative side. Some of the negative effects of the use of gadgets, such as addiction to playing online games, reduced face-to-face interaction, cheating on exams. This article aims to build a classification application for the level of influence of gadget use on the maturity of students' emotional intelligence using the Naïve Bayes method. From this research, the classification application for the level of influence of gadget use on the maturity of student's emotional intelligence using the Naïve Bayes method has been created. The test results of this application show an accuracy of 82%.
Poincaré Plot Method for Physiological Analysis of the Gadget Use Effect on Children Stress Level Umar Zaky; Afwan Anggara; Muhammad Zakariyah; Ilham Fathullah
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.809

Abstract

Stress in children can affect the way they think, act, and feel. The habit of using gadgets has several advantages and disadvantages, but there has been no in-depth study of the effect of using gadgets on stress levels in children. This study aims to determine the representation of the physiological condition of using gadgets on stress levels in children. A total of 18 electrocardiogram data were extracted with poincaré plot features. This research has found that there is no difference in the level of stress in children between before and after using gadgets in terms of autonomic nervous activity (Sig. > 0.05). However, there is an increase in sympathetic activity that occurs in children even though they have finished using gadgets. Such conditions certainly need to get more attention, especially related to the duration of gadget use and accessible content.
Analysis of Machine Learning Algorithm for Sleep Apnea Detection Based on Heart Rate Variability Muhammad Zakariyah; Umar Zaky
JUITA : Jurnal Informatika JUITA Vol. 10 No. 2, November 2022
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1158.783 KB) | DOI: 10.30595/juita.v10i2.14575

Abstract

Sleep apnea is a common problem with health implications ranging from excessive daytime sleepiness to serious cardiovascular disorders. The method for detecting and measuring sleep apnea is through breathing monitoring (polysomnography), which is time consuming and relatively expensive. Cardiovascular which is closely related to heart performance activities allows the use of electrocardiogram (heart rate variability) features to detect sleep apnea. This study aims to compare the results of sleep apnea detection using several machine learning algorithms. A total of 2,445 data were divided into 1,834 data as learning sets and 611 data as test sets. Evaluation of 10-fold cross-validation using all HRV features shows that neural network algorithm has the best performance compared to decision tree algorithm, k-nearest neighbor, and support vector machine with an accuracy rate (82.44% in the learning set, 79.21% in the test set consecutively), precision (85.54% and 82.70%), f-measure (87.70% and 85.67%), and AUC (0.867 and 0.832). Based on the results of performance testing using only selected HRV features (CVRR, HF, SD1/SD2 Ratio, and S-Region), the K-Nearest Neighbors, Support Vector Machine, and Neural Network algorithms experienced a decrease in performance. The use of all HRV features is recommended compared to only using selected HRV features, so it can help detect the presence/absence of sleep apnea much better.
Peningkatan Pelayanan Penjualan Bagi Konsumen Dengan Aplikasi Berbasis Mobile Iman Yanuar; Umar Zaky; Muhammad Zakariyah
INTEK : Jurnal Informatika dan Teknologi Informasi Vol. 6 No. 1 (2023)
Publisher : Universitas Muhammadiyah Purworejo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37729/intek.v6i1.2935

Abstract

Ayam Goreng Kalasan dan Bebek Laos Ny.Jun merupakan restoran yang menjual berbagai menu makanan paket ayam goreng kalasan, bebek goreng dan tersedia juga menu makanan frozen yang sudah siap masak. Dalam proses pemesanan admin pernah mengalami kendala saat melakukan transaksi melalui aplikasi WhatsApp, kendala yang terjadi karena pelanggan melakukan pemesanan dengan jumlah besar namun pelanggan tidak melakukan pembayaran terlebih dahulu dengan alasan akan dibayar ditempat ketika pesanan sudah dikirim, hal tersebut untungnya masih dapat di atasi oleh pemilik restoran sehingga tidak memproses transaksi tersebut karena hal tersebut dapat mengakibatkan kerugian bagi restoran. Oleh karena itu penelitian ini dilakukan untuk meningkatkan keamanan dalam proses pemesanan makanan melalui pembuatan Sistem Pemesanan Berbasis Web dan Mobile Application, dengan adanya sistem ini diharapkan dapat menangani kekurangan sistem yang berjalan sebelumnya dan memberikan kemudahan bagi pemilik usaha dan pelanggan dalam melakukan pemesanan. Dalam implementasinya sistem ini menggunakan teknologi android dan website untuk sisi pelanggan dan untuk sisi admin dan karyawan hanya website, pembuatan aplikasi ini menggunakan teknologi React Native untuk bagian Android, Laravel untuk bagian website nya, dan untuk databasenya menggunakan database MySQL. Untuk menguji kesesuaian sistem, maka dilakukan pengujian menggunakan metode black box sebanyak 104 skenario untuk menguji fungsionalistasnya dan hasilnya sistem ini memiliki kemampuan menjalankan fungsinya sebesar 91,3 %, hal ini menunjukan sistem ini dapat menjalankan fungsi sesuai dengan proses bisnis di restoran Ayam Goreng Kalasan dan Bebek Laos Ny jun
Poincaré Plot Method for Physiological Analysis of the Gadget Use Effect on Children Stress Level Umar Zaky; Afwan Anggara; Muhammad Zakariyah; Ilham Fathullah
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.809

Abstract

Stress in children can affect the way they think, act, and feel. The habit of using gadgets has several advantages and disadvantages, but there has been no in-depth study of the effect of using gadgets on stress levels in children. This study aims to determine the representation of the physiological condition of using gadgets on stress levels in children. A total of 18 electrocardiogram data were extracted with poincaré plot features. This research has found that there is no difference in the level of stress in children between before and after using gadgets in terms of autonomic nervous activity (Sig. > 0.05). However, there is an increase in sympathetic activity that occurs in children even though they have finished using gadgets. Such conditions certainly need to get more attention, especially related to the duration of gadget use and accessible content.
Pengaruh Penyesuaian Diri Terhadap Motivasi Belajar Pada Mahasiswa Rantau Ari Prasetyoaji; Umar Zaky; Tati Indriani; Rizka Amanah
G-Couns: Jurnal Bimbingan dan Konseling Vol. 8 No. 3 (2024): Agustus 2024. G-Couns: Jurnal Bimbingan dan Konseling
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/gcouns.v8i3.5057

Abstract

Proses penyesuaian diri sangat penting, khusunya bagi mahasiswa rantau yang baru mengenal lingkungan baru. Ketidakmampuan dalam menyesuaian diri dengan baik dilingkungan baru berpengaruh pada motivasi belajar. Penelitian ini bertujuan untuk mengetahui pengaruh penyesuaian diri terhadap motivasi belajar pada mahasiswa rantau di Universitas Teknologi Yogyakarta. Metode penelitian ini yaitu metode kuantitatif dengan populasi seluruh mahasiswa rantau di Universitas Teknologi Yogyakarta dengan sampel sebanyak 126 mahasiswa rantau, dengan teknik Stratified Random Sampling. Instrumen yang digunakan yaitu skala penyesuaian diri dan skala motivasi belajar. Analisis data dalam penelitian ini yaitu menggunakan uji regresi linear sederhana. Hasil penelitian menunjukkan perolehan nilai signifikansi sebesar 0,000 < 0,05 dan t hitung > t tabel (13,218 > 1,979). Kesimpulan pada penelitian ini yaitu terdapat pengaruh yang signifikan penyesuaian diri terhadap motivasi belajar pada mahasiswa rantau di Universita Teknologi Yogyakarta. Kata kunci: penyesuaian diri, motivasi belajar, mahasiswa rantau
Performance Analysis of the Decision Tree Classification Algorithm on the Water Quality and Potability Dataset Zaky, Umar; Naswin, Ahmad; Sumiyatun, Sumiyatun; Murdiyanto, Aris Wahyu
Indonesian Journal of Data and Science Vol. 4 No. 3 (2023): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v4i3.113

Abstract

Ensuring water potability is paramount for public health and safety. This research aimed to assess the efficacy of the Decision Tree classification algorithm in predicting water potability using the Water Quality and Potability dataset. Employing a 5-fold cross-validation technique, the model showcased a moderate performance with an average accuracy of approximately 54.33%. While the Decision Tree provides a baseline and interpretable mechanism for classification, the results emphasize the need for further exploration using more intricate models or ensemble methods. This study contributes to the broader effort of leveraging machine learning techniques for water quality assessment and provides insights into the potential and limitations of such models in predicting water safety
Assessing the Predictive Power of Logistic Regression on Liver Disease Prevalence in the Indian Context Alwiah, Izmy; Zaky, Umar; Murdiyanto, Aris Wahyu
Indonesian Journal of Data and Science Vol. 5 No. 1 (2024): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v5i1.121

Abstract

This study delves into the application of Logistic Regression through a Voting Classifier to predict liver disease prevalence within the Indian demographic, specifically analyzing data from the NorthEast of Andhra Pradesh. Employing a dataset encompassing 584 patient records, the research utilizes a 5-fold cross-validation approach to evaluate the model's performance across accuracy, precision, recall, and F1-Score metrics. The findings reveal accuracy rates ranging from 69.23% to 74.14%, with variable precision and recall, indicating a promising yet improvable predictive capability of the model. The study significantly contributes to the existing body of knowledge by demonstrating the potential of Logistic Regression in medical diagnostics, especially in the context of liver disease, and highlighting the critical role of machine learning models in enhancing diagnostic processes. Through a detailed discussion, the research aligns with previous studies on the efficacy of machine learning in healthcare, advocating for the integration of more comprehensive data and suggesting further exploration into the model's applicability across diverse populations. The study's implications extend to healthcare professionals and policymakers, underscoring the necessity for advanced diagnostic tools in the early detection of liver diseases.
Co-Authors Afwan Anggara Alwiah, Izmy Ari Prasetyoaji Aris Wahyu Murdiyanto Diansah, Febri Nur Habibi, Farid Afif Hanggraini Dea Astuti Ilham Fathullah Ilham Fathullah Iman Yanuar Kholis, Muhammad Yunus Kusumojakti, Mochamad Aqsha Pasalewa Laksana, Danu Dwiki Muhammad Zakariyah Naswin, Ahmad Norfajriyah, Norfajriyah Prasetyo, Sushilo Pratama, Satria Yoga Purnamasari, Dwi Amalia Rabbani, Muhammad Riefky Raden Andy Kurniawan Ramadhan, Idham Rismayanti, Nurul Rizka Amanah Sumiyatun Tati Indriani