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All Journal International Journal of Electrical and Computer Engineering Jurnal Silvikultur Tropika (JST) JREC (Journal of Electrical and Electronics) Jurnal Ilmu Komputer dan Agri-Informatika Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIN (Jurnal Online Informatika) Petir JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Journal of Applied Engineering and Technological Science (JAETS) Sinar Sang Surya: Jurnal Pusat Pengabdian kepada Masyarakat Jurnal Sistem Informasi
Hendra Rahmawan Hendra Rahmawan
Departemen Ilmu Komputer, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Institut Pertanian Bogor
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Physics Public Health Social Sciences

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Klasifikasi Kanker Tumor Payudara Menggunakan Arsitektur Inception-V3 Dan Algoritma Machine Learning Supriyanto, Arif; Kusuma, Wisnu Ananta; Rahmawan, Hendra
JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Vol 7, No 3 (2022): September 2022
Publisher : Universitas Al Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/sst.v7i3.1284

Abstract

Breast cancer is a disease that arises due to breast tissue cells that grow abnormally and continuously. This disease is a disease with a large increase in number of around 13 million per year, with a mortality rate of 9.6% from a total of 65,858 cases. Early detection of breast cancer for prevention needs to be done, with the hope that breast cancer is easier to treat and cure and can even be prevented before it enters an advanced stage. In this research, build a model with transfer learning technique for breast cancer classification. There are 4 methods tested, namely Inception-V3 feature extraction with the Radial Basic Function Neural Network classification method, FeedForward Neural Network, Logistic Regression and feature extraction by making changes to the hyperparameter layer. This study compares the four models to get the best one to solve the problem of breast cancer classification. The data used in this study are breast cancer image data with a zoom scale of 40X, 100X, 200X and 400X. The dataset was sourced from The Laboratory University of Parana with P&D Laboratory Pathological Anatomy and Cytopathology, Parana, Brazil. The results of this study indicate that the Inception-V3 feature extraction method with the Logistic Regression classification method on the 40X zoom scale data provides the best accuracy (93.00%), precision (94.00%), and recall (91.00%) F1-score (92.00%).
Analisis Kinerja Komunikasi Data Berbasis LoRa pada IoT untuk Pemantauan Lingkungan Kandang Ayam Akbar, Auriza Rahmad; Maxiwinata, Maxdha; Rahmawan, Hendra; Wahjuni, Sri
Jurnal Ilmu Komputer dan Agri-Informatika Vol. 11 No. 2 (2024)
Publisher : Sekolah Sains Data, Matematika, dan Informatika. Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jika.11.2.195-204

Abstract

Teknologi IoT dapat mempermudah peternak dalam memantau kandang ayam dari jauh. Teknologi LoRa cocok untuk diterapkan untuk implementasi IoT pada lingkungan kandang yang umunya berada jauh dari pemukiman penduduk, karena memiliki jarak jangkauan yang jauh dan hemat dalam penggunaan daya. Penelitian ini bertujuan untuk mengimplementasikan dan menguji kinerja IoT menggunakan LoRa dengan modul RFM95W pada lingkungan kandang ayam. Kinerja yang diamati berupa jarak, kekuatan sinyal, dan keberhasilan transmisi data. Pengujian yang dilakukan adalah pengujian fungsional dan pengujian kinerja dengan antena 3 dBi dan 5 dBi pada SF7. Hasil pengujian fungsional berhasil mengirimkan data ke Thingspeak. Hasil pengujian menggunakan antena 5 dBi mendapatkan hasil yang lebih baik dibandingkan dengan antena 3 dBi. Untuk skenario tanpa halangan, jarak terjauh adalah 400 m dengan error rate 15% dan untuk skenario dengan halangan jarak terjauh adalah 80 m dengan error rate 5%.
Development of a Penetration Testing Framework for Identifying Security Vulnerability Solutions in WiFi Networks: Pengembangan Framewok Penetration Testing untuk Proses Pencarian Solusi Kerentanan Keamanan pada Jaringan Wifi Imran, Ali; Neyman, Shelvie Nidya; Rahmawan, Hendra
Telematika Vol 22 No 1 (2025): Edisi Februari 2025
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v22i1.14767

Abstract

The rapid increase in internet users has driven the development of WiFi networks, which play a crucial role in providing secure internet access, especially within Industry 4.0 and Industry 5.0 environments that rely on efficient data exchange. Penetration testing (pentest) is a vital approach for auditing and evaluating the security level of WiFi networks. Several frameworks such as PTES, PETA, and ISSAF are often used as references, although only a few are explicitly designed for WiFi networks. This study proposes a modification of the PTES framework to better align with the security characteristics of WiFi networks by providing relevant solution recommendations. The integration of the Boyer-Moore algorithm is employed as an efficient method to identify solutions for detected vulnerabilities. The implementation of this framework is demonstrated through testing the suggestion process, which produces solution recommendations based on vulnerabilities found during the pentest. The Boyer-Moore algorithm exhibits high efficiency in generating recommendations with a response time of 0.0000087 seconds.
Pengembangan Sistem Manajemen Pelatihan Kerja di Kota Surakarta Agus Putra, Affriza Brilyan Relo Pambudi; Neyman, Shelvie Nidya; Rahmawan, Hendra
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 4: Agustus 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2024107167

Abstract

Program pelatihan kerja di Pemerintah Kota Surakarta yang ditawarkan oleh Dinas Tenaga Kerja, Dinas Pendidikan, Dinas Perdagangan, Dinas Pemberdayaan Perempuan, Perlindungan Anak dan Pemberdayaan Masyarakat dan Dinas UMKM Koperasi & Industri. Saat ini beberapa instansi pemerintah yang memiliki program pelatihan kerja yang sama masih menggunakan sistem konvensional. Data pengangguran diambil melalui dari Dinas Sosial Kota Surakarta dikirim melalui media sosial WhatshApp sehingga terjadinya tumpang tindih data pengangguran dan pelaksanaan pelatihan kerja. Instansi yang terlibat dalam program pelatihan kerja belum memiliki rencana strategis dan beberapa proses bisnis dilakukan secara manual. Melihat kondisi permasalahan tersebut maka dibutuhkan suatu perencanaan pengembangan sistem pada instansi pemerintah (dalam hal ini Dinas terkait) sistem informasi dianalisis dan dirancang dengan metode prototyping, merupakan bagian proses untuk membagikan program pelatihan kerja di setiap dinas terkait merealisasikan tujuannya. Untuk dapat menerapkan perencanaan yang mengintegrasikan dan menyinkronkan data menjadi sarana Pemerintah Kota Surakarta dapat mengelola sistem manajemen pelatihan kerja. Dari hasil penelitian ini melalui pengujian dengan metode black box untuk mengukur efisiensi, akurasi, validitas data dan kegunaan sistem manajemen pelatihan kerja untuk memastikan tidak terjadinya kembali tumpang tindih data. AbstractJob training programs in the Surakarta City Government are offered by the Department of Manpower, the Office of Education, the Office of Commerce, the Office for Women's Empowerment, Child Protection and Community Empowerment, and the Office for MSME, Cooperatives, and Industry. Several government agencies with the same job training program are still using the conventional system. The response data was taken through the Surakarta City Social Service and sent via WhatsApp social media so that there was an overlapping of the response data and the implementation of job training. The agencies involved in the job training program do not yet have a strategic plan and some business processes are carried out manually. Seeing the condition of the problem, it is necessary to have a system development plan for government agencies (in this case the related Office). Information systems are analyzed and designed using the prototyping method, which is part of the process for distributing job training programs in each Service related to utilization. To be able to implement planning that integrates and synchronizes data becomes a means for the Surakarta City Government to manage a job training management system. the results of this study through testing with the black box method for efficiency, accuracy, data validity, and the use of job training management systems to ensure data overlap does not occur again.
Scalability Testing of Land Forest Fire Patrol Information Systems Khusaeri, Ahmad; Sitanggang, Imas Sukaesih; Rahmawan, Hendra
JOIN (Jurnal Online Informatika) Vol 8 No 1 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i1.977

Abstract

The Patrol Information System for the Prevention of Forest Land Fires (SIPP Karhutla) in Indonesia is a tool for assisting patrol activities for controlling forest and land fires in Indonesia. The addition of Karhutla SIPP users causes the need for system scalability testing. This study aims to perform non-functional testing that focuses on scalability testing. The steps in scalability testing include creating schemas, conducting tests, and analyzing results. There are five schemes with a total sample of 700 samples. Testing was carried out using the JMeter automation testing tool assisted by Blazemeter in creating scripts. The scalability test parameter has three parameters: average CPU usage, memory usage, and network usage. The test results show that the CPU capacity used can handle up to 700 users, while with a memory capacity of 8GB it can handle up to 420 users. All users is the user menu that has the highest value for each test parameter The average value of CPU usage is 44.8%, the average memory usage is 69.48% and the average network usage is 2.8 Mb/s. In minimizing server performance, the tile cache map method can be applied to the system and can increase the memory capacity used.
Inovasi Pembelajaran Digital: Pengenalan Komputer sebagai Upaya Peningkatan Kompetensi Teknologi Informasi Siswa SDN 2 Endang Rejo Pratama, Aditya Agung Budi; Anggaraini, Anjeli Preti; Prasetia, Bayu; Abrori, Farid; Nugraha, Farid Adi; Ardiansyah, Feri; Rahmawan, Hendra; Ismail, Hilyan Taufik; Prasetyawan, Ibnu; Pujijayanti, Ovita; Kartika, Shofiana; Firmansyah, Syahrul Haris; Yudistira, Wildan Eka; Siregar, Guna Yanti K. S
SINAR SANG SURYA Vol 9, No 2 (2025): Agustus 2025
Publisher : UM Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/sss.v9i2.4092

Abstract

Program pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kompetensi teknologi informasi siswa SD Negeri 2 Endang Rejo melalui implementasi inovasi pembelajaran digital berbasis pengenalan komputer. Metode pelaksanaan mencakup pendekatan partisipatif yang diimplementasikan dalam empat tahapan: persiapan, pelaksanaan, evaluasi, dan keberlanjutan. Program melibatkan delapan mahasiswa sebagai fasilitator pembelajaran dan dieksekusi selama empat bulan (Januari-Mei 2025). Strategi pembelajaran mengintegrasikan metode demonstrasi, praktik langsung, dan gamifikasi untuk mengoptimalkan transfer pengetahuan dan keterampilan. Hasil evaluasi menunjukkan peningkatan signifikan pada kompetensi teknologi informasi siswa, dengan rata-rata kenaikan 104,9% dari kondisi awal. Peningkatan tertinggi terjadi pada aspek kemampuan aplikatif (118,2%), diikuti keterampilan pengoperasian (112,9%), dan pemahaman konseptual (85,8%). Variasi peningkatan kompetensi teridentifikasi berdasarkan jenjang kelas, dengan siswa kelas 6 menunjukkan peningkatan tertinggi pada aspek pemahaman konseptual (89,2%), sementara siswa kelas 4 unggul dalam peningkatan keterampilan pengoperasian (119,7%). Program ini berdampak pada tiga dimensi: akademik (peningkatan kompetensi), sosial (terbentuknya komunitas pembelajaran), dan institusional (transformasi kebijakan sekolah). Keberlanjutan program dijamin melalui pengembangan repositori digital, pembentukan kelompok "Duta Teknologi", dan perjanjian kerjasama berkelanjutan antara tim pengabdian dengan sekolah mitra. Pendekatan holistik yang mengintegrasikan aspek teknologi, pedagogi, dan konteks sosial-budaya lokal menjadi faktor kunci keberhasilan program ini.
Co-Authors Abrori, Farid Affriza Brilyan Relo Pambudi Agus Putra Ahmad Khusaeri Albar, Israr Ali Imran Anggaraini, Anjeli Preti Ardiansyah, Feri Auriza Rahmad Akbar Bayu Prasetia, Bayu Dary Muzhar Muhammad Eko Kuncoro Adiyanto Farianto Firman Ardiansyah Firmansyah, Syahrul Haris Heru Sukoco Imas Sukaesih Sitanggang Ismail, Hilyan Taufik Kartika, Shofiana Krisnanto, Ferdian Lailan Syaufina Maxiwinata, Maxdha Muhammad Ilyas Sikki Muhammad Ilyas Sikki Muhammad Ilyas Sikki Muhammad Ilyas Sikki Nugraha, Farid Adi Prasetyawan, Ibnu Pratama, Aditya Agung Budi Pujijayanti, Ovita Purwanti, Endang Yuni Refianto Damai Darmawan Refianto Damai Darmawan Satyawan, Verda Emmelinda Shelvie Nidya Neyman Siregar, Guna Yanti K. S Sri Wahjuni Sugi Guritman Supriyanto, Arif Trisminingsih, Rina Wisnu Ananta Kusuma WULANDARI Yan Mitha Djaksana Yudistira, Wildan Eka