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All Journal Jurnal Ilmiah Informatika Komputer Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial IJCIT (Indonesian Journal on Computer and Information Technology) JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Scientific Journal of Informatics Infotek : Jurnal Informatika dan Teknologi Jurnal Teknologi Informatika dan Komputer Computer Science (CO-SCIENCE) Jurnal Aruna Mengabdi (ARMI) Indonesian Community Service Journal of Computer Science (IndoComs)
Ahmad Fauzi
Universitas Bina Sarana Informatika
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Attendance Mobile Application With Face Recognition and Detect Location Andika Bayu Hasta Yanto; Ahmad Fauzi; Novita Indriyani
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol 5 No 1 (2022): Jurnal Teknologi dan Open Source, June 2022
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v5i1.2187

Abstract

Every company must have an attendance policy for each of its employees for the purpose of employee attendance and performance reports in the performance of their work, but currently there are still many companies that still have an absence system that is not computerized, so the calculation and accounting process is still done manually, because everything is calculated manually, it is possible that there are errors in the calculations and take time to process data absence of all employees. Therefore, an application that can automatically process and record data is needed to avoid errors and speed up the data processing process. In addition, the application can facilitate employees' attendance as it can be accessed directly from cell phones by using facial recognition and location detection to prove the attendance of employees.
Application Of Simple Additive Weighting (SAW) For The Selection Of Breast Milk Pumps For Working Mothers Novita Indriyani; Ahmad Fauzi; Andika Bayu Hasta Yanto
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol 5 No 2 (2022): Jurnal Teknologi dan Open Source, December 2022
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v5i2.2626

Abstract

Optimal breastfeeding is very important because it can save more than 800,000 lives of children under five every year. Among the many reasons why mothers do not exclusively breastfeed is that they go back to work (22.5%). Homemakers have a greater chance of exclusively breastfeeding because they spend more time with the baby, allowing them to breastfeed optimally. Based on the results of previous studies, working mothers give breast milk directly (when they are at home or resting) and give milk from milk. Using a breast pump is considered more practical, easier and saves time. The breastpump method (MPA) for exclusive breastfeeding for working mothers also does not interfere with the work process and offers flexibility in working hours. What worries women who work while breastfeeding is maintaining breast milk production during working hours. However, according to research, there is no significant difference between the effectiveness and satisfaction of breast milk production when using an electric breast pump. The use of a breast pump does not affect the amount of breast milk produced, even though an electric breast pump provides more effectiveness and satisfaction in expressing breast milk. This study aims to select the type of breast pump for working mothers to facilitate exclusive breastfeeding of the baby. The result of the calculation of SAW method resulted in a recommendation for a breast pump Moom Uung with a value of 15.67 The result of the calculation of SAW method resulting in a recommendation for a breast pump Moom Uung with a value of 15.67.
Pengembangan Aplikasi E-learning dengan Metode Rapid Application Development Ahmad Fauzi; Ginabila Ginabila; Mochammad Abdul Azis
Infotek: Jurnal Informatika dan Teknologi Vol. 6 No. 1 (2023): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v6i1.7414

Abstract

The development of the E-learning application is part of the solution for convenience in carrying out teaching and learning activities, the process of receiving and sending a digital document in the form of learning videos and ebooks is the most important part so that information can be accessed quickly and easily. Special methods are needed to build e-learning applications more quickly and according to needs. Requirements Planning plays a very important role in the software development process, project management in software development and one of the processes is to estimate that the software produced is according to a predetermined schedule and cost. The Rapid Application Development Method is a life cycle strategy aimed at To provide development that is much faster and get results with better quality, UML (Unified Modeling Language) is a language that has become a decent standard in designing, visualizing and documenting software.
Pelatihan Google Spreadsheet Untuk Mempermudah Pekerjaan Bagi PKK Kelurahan Paledang Risa Wati; Ahmad Fauzi; Imam Nawawi; Hilda Rachmi; Silvy Nur Azizah
Jurnal Aruna Mengabdi Vol. 1 No. 1 (2023): Periode Mei 2023
Publisher : Lotus Aruna Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61398/armi.v1i1.4

Abstract

Di Kecamatan Bogor Tengah, Kota Bogor terdapat Kelurahan Paledang. Salah satu kegiatan kelompok Ibu-ibu PKK di Kelurahan Paledang adalah melakukan sensus terhadap jenis pekerjaan seluruh warga Kelurahan Paledang. Pengolahan data masih dilakukan secara manual yang memakan waktu lama dan kurang efisien. Oleh karena itu, diperlukan kegiatan Pengabdian kepada Masyarakat. Kegiatan ini bertujuan untuk membantu kelompok Ibu-ibu PKK di Kelurahan Paledang dalam pengolahan data menggunakan Microsoft Excel melalui Google Spreadsheet melalui media handphone, sehingga pengolahan data dapat dilakukan oleh siapa saja, kapan saja, dan di mana saja, sambil tetap menjaga kerahasiaan informasi. Pengabdian masyarakat dilaksanakan dengan cara penyampaian materi secara langsung dan memberikan pelatihan dalam penggunaan Google Spreadsheet
Analisis Sentimen Terhadap Pemutar Musik Online Spotify Dengan Algoritma Naive Bayes dan Support Vector Machine Ginabila Ginabila; Ahmad Fauzi
Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Vol 6, No 2 (2023): Juli
Publisher : Akademi Ilmu Komputer Ternate

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47324/ilkominfo.v6i2.180

Abstract

Abstrak: Manusia memiliki kebutuhan preferensi musik yang yang sangat beragam, oleh karena itu pemutar musik online menjadi salah satu solusi untuk memenuhi kebutuhan ini dengan menyediakan katalog musik yang luas. Analisis sentimen adalah proses untuk mengevaluasi dan mengklasifikasikan sentimen atau perasaan di balik teks atau data yang diberikan. Dalam konteks ini, analisis sentimen dilakukan pada pemutar musik online Spotify. Dua algoritma yang umum digunakan untuk analisis sentimen adalah Naive Bayes dan Support Vector Machine (SVM). Kedua algoritma ini dapat diterapkan dalam analisis sentimen pada pemutar musik online. Data teks seperti ulasan atau komentar pengguna dikumpulkan dan dilabeli dengan sentimen yang sesuai. Hasil dari penelitian menggunakan kedua algoritma ini menghasilkan nilai akurasi yang hampir sama baiknya. Algoritma Support Vector Machine menghasilkan tingkat akurasi sebesar 82,42%, sedangkan untuk Algoritma Naive Bayes mencapai 84,73%.Kata kunci: Analisis Sentimen, Naive Bayes, Support Vector MachineAbstract: Humans have diverse music preferences and online music players are a solution to meet these needs by providing a wide music catalog. Sentiment analysis is the process of evaluating and classifying sentiments or feelings behind given texts or data. In this context, sentiment analysis is performed on Spotify online music players. Two common algorithms used for sentiment analysis are Naive Bayes and Support Vector Machine (SVM). Both algorithms can be applied in sentiment analysis for online music players. Text data such as user reviews or comments are collected and labeled with corresponding sentiments. The results of the research using both algorithms yielded similar high accuracy. The Support Vector Machine algorithm achieved an accuracy rate of 82.42%, while the Naive Bayes algorithm reached 84.73%.Keywords: Sentiment Analysis, Naive Bayes, Support Vector Machine
Measuring the Quality of the General Election Commission Website in Central Jakarta Using the WebQual 4.0 Method Naufal Brilianto; Ahmad Fauzi; Artika Surniandari; Hilda Rachmi
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 7 No. 2 (2024): Jurnal Teknologi dan Open Source, December 2024
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v7i2.3876

Abstract

This study aims to analyze the application of the Webqual 4.0 method in measuring the quality of the Central Jakarta City General Election Commission (in Indonesia it is abbreviated as KPU) website. This method focuses on three dimensions of usability quality, information quality, and interaction quality. This study uses a quantitative method with primary data. The sample of this study were employees and the general public. The data analysis technique used was multiple linear analysis processed using the SPSS version 26 program. The results of the study showed that the usability variable did not have a significant effect on website quality measurement. The Information Quality variable did not have a significant effect on website quality measurement. And the Interaction Quality variable had a significant effect on website quality measurement.
PENERAPAN METODE K-MEANS DALAM PENGKLASTERAN WILAYAH DI INDONESIA BERDASARKAN PEMBERIAN ASI EKSKLUSIF PADA BAYI Zulia Imami Alfianti; Ginabila Ginabila; Ahmad Fauzi
Jurnal Ilmiah Informatika Komputer Vol 29, No 3 (2024)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2024.v29i3.12781

Abstract

Breast milk is a fluid that comes out of a mother's breast glands which contains a variety of nutrients needed to support the development and growth of toddlers. Exclusive breast milk (ASI) is breastfeeding that is not accompanied by any other food or drink supplementation except medication. Currently, exclusive breastfeeding is influenced by many factors, namely working mothers, low maternal education, incessant advertising about the use of formula milk, breast milk not coming in and many other factors causing not all babies to receive exclusive breast milk. In this research, regional clustering will be carried out based on the percentage of exclusive breastfeeding for 6 month old babies from 34 provinces in Indonesia. Clustering was carried out to group 34 provinces in Indonesia into provinces with high, medium and low cases. The results of this research are that 31% of provinces have the highest percentage, 40% have a medium percentage and 29% have a low percentage.
ANALISIS KINERJA METODE GLCM DAN LS-SVM DALAM KLASIFIKASI CITRA SAMPAH ORGANIK DAN ANORGANIK Michelyn Angela Sabatini Rajagukguk; Ahmad Fauzi; Bambang Wijonarko
Jurnal Ilmiah Informatika Vol. 10 No. 2 (2025): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v10i2.105-111

Abstract

Waste management, particularly in distinguishing organic and inorganic types, remains a major environmental challenge. Manual sorting processes are inefficient and prone to errors. This study aims to develop an automated waste image classification system using a combination of Gray Level Co-occurrence Matrix (GLCM) and Least Squares Support Vector Machine (LS-SVM). A total of 1,060 images were used, divided equally between organic and inorganic categories. Texture features such as contrast, correlation, energy, and homogeneity were extracted using GLCM and combined with mean RGB color features. The LS-SVM model with the Radial Basis Function (RBF) kernel achieved an accuracy of 87 percent, outperforming conventional SVM. The model’s effectiveness aligns with previous studies that used SVM-based waste classification and texture feature enhancement with GLCM descriptors. The model was implemented using a Flask web application for real-time predictions.
PEMANFAATAN GOOGLE FORM DALAM PENDATAAN KESEHATAN BALITA DI LINGKUNGAN POSYANDU MAWAR MELATI Robi Aziz Zuama; Hamdun Sulaiman; Ahmad Fauzi; Minda Septiani
Indonesian Community Service Journal of Computer Science Vol. 2 No. 1 (2025): Periode Januari 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/indocoms.v2i1.8227

Abstract

Health data collection of toddlers that is still done manually at Posyandu Mawar Melati is often time-consuming, inefficient, and prone to errors in recording. . This unstructured data management is a major obstacle in providing optimal health services to toddlers in the neighborhood. In addition, the manual recording process makes it difficult to store and analyze data, making it difficult for posyandu officers to compile accurate and timely health reports. As a solution to these problems, this community service activity focuses on the application of digital technology, namely the use of Google Forms for toddler health data collection. Google Form was chosen because it is a tool that is easy to use, free, and can be accessed from various devices, making it very suitable for use in the posyandu environment. Through the use of Google Form, the process of collecting data on the health of toddlers can be done more quickly and accurately. Digitally collected data also makes it easier for posyandu officers to process information, so that the results can be analyzed and stored better. In addition, this technology enables faster and more efficient data processing, so that officers can compile reports in real-time and reduce the risk of data loss. Pendataan kesehatan balita yang masih dilakukan secara manual pada Posyandu Mawar Melati sering memakan waktu, tidak efisien, dan rawan kesalahan dalam pencatatan. Pengelolaan data yang kurang terstruktur ini menjadi kendala utama dalam memberikan layanan kesehatan yang optimal kepada balita di lingkungan tersebut. Selain itu, proses pencatatan manual mempersulit penyimpanan dan analisis data, sehingga menyulitkan petugas posyandu dalam menyusun laporan kesehatan yang akurat dan tepat waktu. Sebagai solusi atas permasalahan tersebut, kegiatan pengabdian masyarakat ini berfokus pada penerapan teknologi digital, yaitu penggunaan Google Form untuk pendataan kesehatan balita. Google Form dipilih karena merupakan alat yang mudah digunakan, gratis, dan dapat diakses dari berbagai perangkat, sehingga sangat cocok untuk digunakan dalam lingkungan posyandu. Melalui pemanfaatan Google Form, proses pendataan kesehatan balita dapat dilakukan dengan lebih cepat dan akurat. Data yang terkumpul secara digital juga memudahkan petugas posyandu dalam mengolah informasi, sehingga hasilnya dapat dianalisis dan disimpan dengan lebih baik. Selain itu, teknologi ini memungkinkan pengolahan data yang lebih cepat dan efisien, sehingga petugas dapat menyusun laporan secara real-time dan mengurangi risiko kehilangan data.
PEMANFAATAN ARTIFICAL INTELLIGENCE (AI)  UNTUK BIMBINGAN BELAJAR PADA ANAK ASUH YAYASAN NAELUL KHAIR KOTA BEKASI Ahmad Fauzi; Minda Septiani; Nila Hardi; Verra Sofica
Indonesian Community Service Journal of Computer Science Vol. 2 No. 2 (2025): Periode Juli 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/indocoms.v2i2.9438

Abstract

The Artificial Intelligence (AI) Training Program at Yayasan Naelul Khair, Bekasi, is a strategic initiative aimed at enhancing the technological literacy and skills of foster children in response to the evolving demands of digital-based education. The program introduces fundamental AI concepts applicable to learning processes, particularly in assisting with subjects perceived as challenging. Beyond technical proficiency, the training emphasizes the development of critical thinking, collaboration, and technology-driven problem-solving capabilities. This initiative reflects the synergy between education and technology in cultivating an adaptive, competitive younger generation capable of contributing meaningfully to inclusive and sustainable development. Pelatihan Pemanfaatan Artificial Intelligence (AI) di Yayasan Naelul Khair Kota Bekasi diselenggarakan sebagai upaya strategis untuk meningkatkan literasi dan keterampilan teknologi anak-anak asuh dalam menghadapi dinamika pendidikan berbasis digital. Program ini memperkenalkan konsep dasar AI yang dapat diterapkan dalam proses pembelajaran, terutama untuk membantu pemahaman terhadap mata pelajaran yang dianggap sulit. Selain penguasaan teknis, pelatihan ini juga menekankan pada pengembangan kemampuan berpikir kritis, kolaboratif, dan pemecahan masalah berbasis teknologi. Inisiatif ini mencerminkan sinergi antara pendidikan dan teknologi dalam menciptakan generasi muda yang adaptif, berdaya saing, dan mampu berkontribusi secara aktif dalam pembangunan yang inklusif dan berkelanjutan.  
Co-Authors Andika Bayu Hasta Yanto Artika Surniandari Aziz Setyawan Hidayat, Aziz Setyawan Bambang Wijonarko Erniawati Erniawati Febri Ainun Jariyah Ginabila Ginabila Hamdun Sulaiman Hilda Rachmi Imam Nawawi Michelyn Angela Sabatini Rajagukguk Minda Septiani Mochammad Abdul Azis Naufal Brilianto Nila Hardi Novita Indriyani Pas Mahyu Akhirianto Risa Wati - AMIK BSI Tasikmalaya Risa Wati - AMIK BSI Tasikmalaya Robi Aziz Zuama Safitri Linawati Silvy Nur Azizah Taufik Hidayatulloh Verra Sofica Wandy Ubleeuw Zulia Imami Alfianti