Article Per Year (5 Year)
p-Index From 2021 - 2026
5.999
P-Index
This Author published in this journals
All Journal Syntax Jurnal Informatika Scan : Jurnal Teknologi Informasi dan Komunikasi Proceeding International Conference on Information Technology and Business Jurnal Informatika dan Teknik Elektro Terapan JOIV : International Journal on Informatics Visualization INTEGER: Journal of Information Technology Jurnal Penelitian Pendidikan IPA (JPPIPA) JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) bit-Tech JATI (Jurnal Mahasiswa Teknik Informatika) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Jifosi Jurnal Pengabdian kepada Masyarakat Nusantara Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) East Asian Journal of Multidisciplinary Research (EAJMR) Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Publikasi Teknik Informatika (JUPTI) J-Icon : Jurnal Komputer dan Informatika TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Inspiration: Jurnal Teknologi Informasi dan Komunikasi Jurnal Sistem Informasi dan Ilmu Komputer Jurnal Elektronika dan Teknik Informatika Terapan Jurnal Informatika Polinema (JIP) VISA: Journal of Vision and Ideas Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika
Firza Prima Aditiawan
Universitas Pembangunan Nasional Veteran Jawa Timur
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Physics Public Health Social Sciences Other

Published : 56 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 56 Documents
Search

 2   3   4   5   6 
PERANCANGAN SISTEM KLINIK KESEHATAN DAN INVENTORI OBAT DI KLINIK KESEHATAN GRATIS AL-MUHAJIRIN Winata, Chycik Ayu; Mumpuni, Retno; Aditiawan, Firza Prima
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5242

Abstract

Penelitian ini bertujuan untuk merancang dan mengembangkan sistem klinik kesehatan dan inventori obat di Klinik Kesehatan Gratis Al-Muhajirin. Sistem ini dirancang untuk meningkatkan efisiensi operasional klinik dengan memudahkan pengelolaan data pasien, kunjungan, dan stok obat. Menggunakan pendekatan Model-View-Controller (MVC), sistem ini diimplementasikan dengan fitur utama yang meliputi manajemen data pasien, pencatatan kunjungan, dan pengelolaan inventori obat. Uji coba sistem menunjukkan bahwa penerapan sistem ini dapat mengurangi kesalahan pengelolaan data dan meningkatkan efisiensi klinik secara keseluruhan. Hasil penelitian ini penting karena memberikan solusi praktis bagi klinik yang memiliki keterbatasan sumber daya dalam pengelolaan operasional harian.
Prediksi Gangguan Kesehatan Mental pada Kalangan Mahasiswa Menggunakan Metode Pseudo-Labeling dan Algoritma Regresi Logistik Sari, Anggraini Puspita; Prasetya, Dwi Arman; Aditiawan, Firza Prima; Al Haromainy, Muhammad Muharrom
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp40-48

Abstract

Mental illness is a health condition that alters a person's thoughts, feelings, or behaviors, leading to distress and difficulty in maintaining a normal life. Mental health issues should not be taken lightly due to the challenges associated with diagnosis. Many students tend to experience mental health problems at various stages of their education, from diploma programs to doctoral studies. This situation becomes more critical as students approach the end of their studies and anticipate future prospects. This article explores the mental health status of students through symptoms, using logistic regression methods for prediction based on the dataset used. In this study, two types of data are employed: labeled dataset and unlabeled dataset, which are combined to create a semi-supervised learning approach. Labeled dataset is classified using a logistic regression algorithm, while unlabeled dataset employs the pseudo-labeling method. The analysis and modeling of the dataset indicate that the comparison between labeled and unlabeled dataset can significantly affect accuracy and processing time. Furthermore, the use of the pseudo-labeling method with the logistic regression algorithm is well-suited for the mental health case study, achieving an accuracy of 98% with a labeled to unlabeled dataset ratio of 1:2.
PENERAPAN DATA MINING UNTUK PREDIKSI HASIL PANEN BUDIDAYA PERIKANAN DARI MITRA PANEN MENGGUNAKAN ALGORITMA SUPPORT VECTOR REGRESSION Suprapto, Claudia Millennia; Saputra, Wahyu Syaifullah Jauharis; Aditiawan, Firza Prima
J-Icon : Jurnal Komputer dan Informatika Vol 12 No 2 (2024): Oktober 2024
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v12i2.13187

Abstract

PT. Adma Digital Solusi is a company that serves as a harvest partner for cultivators in the fields of agriculture, animal husbandry and fisheries which is used for planning and controlling supply chain results. Planning and controlling PT fishery supply chain results. Adma Digital Sousi in the digital era needs to utilize various technologies and information systems. This aims to ensure that planning and controlling fish resources fulfill aspects of effectiveness and efficiency in decision making. In this research, a machine learning method will be implemented using the Support Vector Regression (SVR) algorithm to predict the harvest results of PT's fishery cultivation partners. Adma Digital Solutions. The SVR algorithm is a theory used to solve a regression classification problem using a Support Vector Machine (SVM). The SVR forecasting process uses the SVR() model by filling in the parameters, namely the kernel using polynomials, C is filled with the value 100, gamma is filled with auto, degree is filled with the value three, epsilon is filled with the value 0.1, and finally coef0 is filled with the value one. Then, using the fit function to train the model using x train and y train data to produce a MAPE error rate value of 0.12865018182566176 and an R2 value of 0.9998831470091238 with very good and accurate prediction capabilities. By knowing the estimated harvest results of aquaculture, the benefits obtained by harvest partners are adjusting production and marketing strategies to maximize profits. And can help harvest partners in managing risks, because they can prepare themselves well for situations where harvest results do not match estimates.
Sistem Pakar untuk Mendeteksi Awal Gangguan Kecemasan pada Remaja (Anxiety Disorder) Menggunakan Metode Forward Chaining Eriyansyah Yusuf Suwandana; Eka Prakarsa Mandyartha; Firza Prima Aditiawan
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 2 (2025): Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i2.705

Abstract

Health is important for every human being. Health, education and income of each individual are three important factors that greatly influence the quality of human resources. Anxiety disorders are a significant mental health problem and can affect an individual's quality of life. Early detection of anxiety disorders is important to provide appropriate intervention and prevent the development of more serious conditions. This research aims to develop an expert system that is able to detect anxiety disorders based on symptoms reported by penggunas. This system uses a forward chaining method and a knowledge base compiled from medical literature and consultations with mental health experts. Several stages of system creation include collecting data on symptoms of anxiety disorders, preparing a knowledge base, implementing a forward chaining inference algorithm, and kuatating the system using test data and expert consultation. The expert system developed in this research is able to provide accurate initial information regarding the symptoms of anxiety disorders in adolescents based on the symptoms input by the pengguna. By utilizing a knowledge base and appropriate diagnostic rules, the system can identify key symptoms that indicate the presence of an anxiety disorder.
Pemanfaatan Model ResNet50 dan SVM untuk Klasifikasi Penyakit Daun Tebu Yunizar, Sri Fatmawati; Sari, Anggraini Puspita; Aditiawan, Firza Prima
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 11 No 1 (2025): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v11i1.3506

Abstract

Indonesia is an agrarian country with an economy that heavily relies on the agricultural sector, including the sugarcane plantation sub-sector for sugar production. Although domestic sugar production continues to increase, the demand for sugar consumption also grows, leading to dependency on imports and fluctuating sugar prices in the domestic market. Therefore, efforts to maintain and enhance the productivity of sugarcane crops are crucial. One of the main challenges in sugarcane cultivation is the attack of pests and diseases such as yellow disease, redrot, mosaic, and rust, which often affect sugarcane plants and reduce their productivity. These diseases must be detected promptly as they significantly impact the quality and quantity of the sugarcane to be harvested. However, manual identification processes are prone to human error and are inefficient for large-scale plantations. To address this, machine learning technology using Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) was employed. This approach uses CNN for feature extraction and SVM for classification. Through a series of experiments, the study shows that the CNN and SVM models can achieve high accuracy of 90.32% with a computational time of 181.53 seconds.
Pendampingan Digitalisasi Usaha Koperasi Unit Desa Sedya Mulya Bojonegoro Berbasis Web Soedarto, Teguh; Aditiawan, Firza Prima; Yuliastuti, Gusti Eka
JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Vol 6, No 2 (2022)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.jpp-iptek.2022.v6i2.3411

Abstract

Kabupaten Bojonegoro juga dikenal dengan potensi lahan pertanian yang cukup luas sehingga Kabupaten Bojonegoro menjadi lumbung pangan untuk menjaga ketahanan pangan nasional. Dengan tingginya produksi beras di Kabupaten Bojonegoro, tentunya harus diimbangi dengan pengelolaan yang baik. Dalam hal ini, pemasaran beras masih menggunakan cara konvensional, yakni petani menjual hasil pertanian ke perantara. Cara konvensional tersebut memiliki permasalahan, yakni kurang meluasnya penyebaran informasi, termasuk pemasaran produk, sehingga perlu dilakukan upaya agar hasil produksi pertanian lebih menjangkau pasar yang luas. Salah satu upaya yang dilakukan adalah melakukan digitalisasi usaha Koperasi Unit Desa (KUD) Sedya Mulya. Digitalisasi yang dimaksud ialah mengubah metode pemasaran konvensional menjadi digital berbasis internet berupa website. Tujuan dari dilakukannya digitalisasi itu yakni untuk meningkatkan daya saing pemasaran produk, kemasan, serta promosi.
PENGEMBANGAN GIM EDUKASI SEBAGAI MEDIA PELATIHAN PENCEGAHAN DAN PENANGGULANGAN KEBAKARAN BERBASIS AUGMENTED REALITY DAN ESCAPE ROOM Pradana Ariando, Aldo; Wirya Atmaja, Pratama; Prima Aditiawan, Firza
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13590

Abstract

Kebakaran merupakan bencana yang disebabkan oleh titik api yang tidak terkendali. Risiko bencana ini sangat tinggi terjadi di kawasan industri, terutama karena banyaknya bahan mudah terbakar yang dapat mempercepat penyebaran api dan meningkatkan potensi kerugian besar. Meskipun pelatihan tanggap darurat kebakaran wajib dilakukan, namun pekerja ditemukan kurang memperhatikan skenario pelatihan. Untuk mengatasi permasalahan tersebut, penelitian ini bertujuan untuk mengembangkan gim edukasi berbasis Augmented Reality dan konsep escape room sebagai media pembelajaran interaktif untuk meningkatkan pemahaman dalam menangani kebakaran. Metode yang digunakan dalam pengembangan gim ini adalah Multimedia Development Life Cycle (MDLC) yang mencakup enam tahapan utama, yaitu Concept, Design, Material collecting, Assembly, Testing, dan Distribution. Pengujian efektivitas menggunakan GUESS-18 dengan skala Likert 7-point menunjukkan rata-rata persentase 75%, menandakan gim ini efektif dalam menyampaikan materi pembelajaran, serta memungkinkan pemain dapat mengekspresikan kreativitas dan imajinasinya selama bermain.
KLASIFIKASI TUTUPAN LAHAN PADA CITRA SENTINEL-2 DI KAWASAN IKN MENGGUNAKAN GOOGLE EARTH ENGINE Al Fathoni, Hanif; Junaidi, Achmad; Prima Aditiawan, Firza
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13652

Abstract

Pemerintah Indonesia telah meresmikan pemindahan Ibu Kota Negara (IKN) ke Nusantara melalui Undang-Undang Nomor 3 Tahun 2022. Nusantara dirancang sebagai simbol identitas nasional dan pusat pertumbuhan ekonomi dengan konsep keberlanjutan. Pemindahan ini berdampak pada tata ruang, infrastruktur, dan lingkungan, sehingga analisis tutupan lahan menjadi krusial untuk memastikan perencanaan yang efisien. Penelitian ini bertujuan untuk mengklasifikasikan tutupan lahan di kawasan IKN menggunakan citra satelit Sentinel-2 dan teknologi Google Earth Engine (GEE). Algoritma yang digunakan adalah Random Forest (RF) dan Support Vector Machine (SVM), dengan ekstraksi fitur berbasis indeks spektral NDVI, NDBI, dan NDWI. Teknik cloud masking dengan QA Band diterapkan untuk meningkatkan kualitas data sebelum analisis lebih lanjut. Tahapan penelitian meliputi pengumpulan dan pre-processing data citra Sentinel-2, ekstraksi fitur, pembuatan dataset latih dan validasi, serta proses klasifikasi menggunakan algoritma RF dan SVM. Evaluasi dilakukan dengan metrik akurasi, presisi, recall, dan F1-score untuk menentukan model terbaik. Hasil penelitian menunjukkan bahwa model RF dengan 100 pohon (RF_100trees) dan SVM dengan kernel linear (SVM_LINEAR) memiliki akurasi validasi terbaik sebesar 88%. RF unggul dalam kestabilannya dengan jumlah pohon yang besar, sementara SVM lebih sensitif terhadap pemilihan parameter kernel. Kesimpulannya, kedua model ini efektif dalam klasifikasi tutupan lahan kawasan IKN.
Design and Development of a Counseling Service System Using Extreme Programming Methodology Nobrian, Ikhsan; Nurlaili, Afina Lina; Aditiawan, Firza Prima
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2928

Abstract

This study addresses the inefficiency and error-prone nature of manual counseling and student violation point recording processes in schools, which often result in delays and inaccuracies. To overcome these challenges, we propose the development of a digital guidance and counseling service system designed to improve data management and enhance service accessibility for school administrators and counselors. The innovation lies in the creation of an integrated, browser-accessible application built using the MERN (MongoDB, Express.js, React, Node.js) stack, which ensures robust functionality and scalability. By applying modern development and testing methodologies, the system is designed to be both reliable and user-friendly. The core objective of this system is to streamline processes such as counseling appointment scheduling, alumni tracking, certificate submission, and student behavior reporting. It was developed using the Extreme Programming (XP) methodology, which encourages flexibility and iterative planning through close collaboration with end users. White Box Testing techniques, including cyclomatic complexity analysis and independent path testing, were employed to validate the system's internal logic. The system’s usability was assessed using the System Usability Scale (SUS), achieving an excellent score of 93.25, indicating high user satisfaction. Furthermore, the Lighthouse performance test yielded a perfect score of 100, confirming the system's high responsiveness. These results demonstrate that the developed system significantly enhances the efficiency, accuracy, and accessibility of guidance services, reduces administrative burdens, and enables better monitoring of student development, making it ideal for deployment in real-world school environments.
Application of IoT-based Intelligent Control Devices Empowered with Fuzzy Inference System in the Garment Industry Rizki, Agung Mustika; Ashari, Faisal; Yuliastuti, Gusti Eka; Haromainy, Muhammad Muharrom Al; Aditiawan, Firza Prima; Amnur, Hidra
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.3344

Abstract

The garment industry in Indonesia has experienced significant development in recent years. A critical aspect of this development is the increasing role of Micro, Small, and Medium Enterprises (MSMEs). Swari Garment Industries (SGI) is an example of an MSME that focuses on the garment sector. In practice, various problems and negligence can affect the course of the production process. One potential issue is using the machine inappropriately or excessively, which can lead to a short electrical circuit. Short electrical circuits are one of the problems that must be faced because they can cause various severe impacts, including equipment damage and even fire. Based on this risk analysis, a possible solution to be applied to SGI, one of the MSMEs in the garment sector, is the implementation of an intelligent control device. The implementation of intelligent control tools based on the Internet of Things (IoT) can enhance the efficiency of the production process and mitigate significant risks to workers and the environment. The Fuzzy Inference System, in which the equity, temperature, and humidity are the input values of the Intelligent Control Device. A hardware device for temperature and humidity control, accessible through an Android phone application, was implemented in SGI. Experiments have verified that we can achieve excellent results. The average percentage of temperature measurement error was 0.2% and for humidity, 0.26%. The average percentage of measurement error from the comparison between the system and MATLAB is 0.49%.
Co-Authors Achmad Junaidi Adzanil Rachmadhi Putra Agil Sakinah, Fenti Agung Mustika Rizki Agung Mustika Rizki Agung Mustika Rizki, Agung Mustika Akbar, Fawwaz Ali Akhmad Fauzi Al Fathoni, Hanif Alit, Ronggo Andreas Nugroho Sihananto Anggraini Puspita Sari Anggriawan, Teddy Prima Aniisah Eka Rahmawati Ardilla, Aufa ASHARI, FAISAL Boy Diego Lumwartono Davila Erdianita Dimas Putra Andaru Dwi Arman Prasetya Dwi Rahma Putri, Septiani Eka Prakarsa Mandyartha Eka Zuni Selviana EKO WAHYUDI Eko Wahyudi Eriyansyah Yusuf Suwandana Fetty Tri Anggraeny Firmansyah Firdaus Anhar Gusti Eka Yuliastuti Hamidah Hendrarini Hardianto, Eragradiansyah Henni Endah Wahanani Herdi Rofaldi Hidra Amnur I GEDE SUSRAMA Idhom, Mohammad Iriansah, Ogy Rachmad Ismiati, Suci Khairil Amin, Mohammad Lina Nurlaili, Afina Made Hanindia Prami Swari Mafaza, Rima Muttaqina Mahanani, Anajeng Esri Edhi Maulana, Hendra Mubarokah Muhammad Eko Prasetyo Muhammad Izdihar Alwin Muhammad Izdihar Alwin Muhammad Muharrom Al Haromainy Mustika Rizki, Agung Muttaqin, Faisal Muttaqin, Faisal Nobrian, Ikhsan Nugroho Gultom, Wahyu Nugroho Sihananto, Andreas Nur Aini Ersanti Nurlaili, Afina Lina Pradana Ariando, Aldo Pratama Wirya Atmaja Puspaningrum, Eva Y Rahmawati, Aniisah Eka Raviy Bayu Setiaji Retno Mumpuni Rizqulloh Zain, Muhammad Dhiya'ulhaq Samdono, Arif Saputra, Wahyu Syaifullah Jauharis Shabika Aqmarina, Azzuraa Soedarto, Teguh Suprapto, Claudia Millennia Vita Via, Yisti Wardana, Nabila Sya’bani Wicaksa Putra Pribadi, Achareeya Widoretno, Astrini Aning Winata, Chycik Ayu Wirya Atmaja, Pratama Yunizar, Sri Fatmawati