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All Journal Indonesian Journal of Electronics and Instrumentation Systems TEKNIK INFORMATIKA Elkom: Jurnal Elektronika dan Komputer Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Jurnal CoreIT Jurnal SOLMA Jurnal TAM (Technology Acceptance Model) Jurnal Cendikia CCIT (Creative Communication and Innovative Technology) Journal Istech Journal (International Science And Technology Journal) Jurnal Algoritma Universal Raharja Community (URNITY Journal) Jurnal Ilmu Komputer, Sistem Informasi, Teknik Informatika (JILKOMSITI) Jurnal Teknologi dan Informatika (JEDA) Abdi Akommedia : Jurnal Pengabdian Masyarakat Seminar Nasional Teknologi dan Multidisiplin Ilmu Journal of Social Science Utilizing Technology Laporan Upaya Nyata Inovasi Ilmu Komputer (LUNIK) Journal of Social Science Utilizing Technology Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Jurnal TAM (Technology Acceptance Model) PENGAMATAN: Jurnal Pengabdian Masyarakat untuk Ilmu MIPA dan Terapannya Journal of Loomingulisus ja Innovatsioon Journal of Technology and Data Science
Fatimah Fahurian
Program Studi S-1 Sistem Informasi, Fakultas Komputer, Universitas Mitra Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Social Sciences Other

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PKM Dosen Umitra : Terapkan Hasil Inovasi Pertanian Berbasis IoT Untuk Pengusiran Hama Burung Sawah Zuhri, Khozainuz; Fahurian, Fatimah; Ananta, Regi Pramudia
ABDI AKOMMEDIA : JURNAL PENGABDIAN MASYARAKAT Vol. 3 No. 2 (2025)
Publisher : ABDI AKOMMEDIA : JURNAL PENGABDIAN MASYARAKAT

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Abstract

Salah satu hama padi adalah burung pipit, karena biasanya burung pipit ini akan mulai makan padi ketika padi berbuah sampai panen. Burung pipit selalu berkelompok ketika terbang dan makan padi, sehingga jika jumlahnya banyak tentu bulir padi yang di makan akan semakin banyak dan tidak hanya satu hari saja, melainkan setiap hari. Untuk mengatasi masalah tersebut maka tim PKM Fakultas Komputer Universitas Mitra Indonesia dengan memanfaatkan teknologi melakukan demonstrasi penggunaan teknologi Hasil Inovasi Pertanian berbasis IoT untuk Pengusiran Hama Burung Sawah. Selain itu kegiatan sosialisasi dan demontrasi dilakukan melalui beberapa sesi, sehingga peserta memiliki waktu yang cukup untuk memahami teknologi tersebut dan mengembangkan keterampilan dalam menggunakan produk hasil teknologi inovasi. Penerapan hasil Inovasi Pertanian berbasis IoT untuk Pengusiran Hama Burung Sawah dapat berjalan dengan baik. Kegiatan penerapan teknologi IOT melalui demontrasi alih teknologi secara langsung pendampingan (transfer ilmu) melalui kegiatan sosialisasi dan demontrasi alih teknologi IoT. Hasil pelaksanaan kegiatan pengabdian ini diharapkan dapat mengoptimalisasi produktivitas dan kapasitas sekaligus menjawab upaya-upaya yang telah dilakukan sebelumnya dan dapat meningkatkan hasil panen sekaligus akan berdampak positif bagi perekonomian mitra desa Tanjung Harapan Kecamatan Seputih Banyak Lampung Tengah.
PELATIHAN DASAR PYTHON UNTUK MENDUKUNG LITERASI PEMROGRAMAN DI SEKOLAH MENENGAH KEJURUAN PELITA PESAWARAN hartanto, budi; Fawaati, Teuku Muhammad; Fahurian, Fatimah; Yunita, Hilda Dwi; Zuhri, Khozainuz
Universal Raharja Community (URNITY Journal) Vol. 5 No. 2 (2025): URNITY (Universal Raharja Community)
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/urnity.v5i2.3613

Abstract

Pelatihan dasar Python menjadi langkah strategis untuk meningkatkan literasi pemrograman di kalangan pelajar Sekolah Menengah Kejuruan (SMK) sebagai persiapan menghadapi tantangan Revolusi Industri 4.0. Bahasa pemrograman Python dipilih karena sintaksisnya sederhana, fleksibel, dan banyak digunakan di berbagai bidang seperti data science, kecerdasan buatan (AI), dan Internet of Things (IoT). Program ini dirancang untuk memperkenalkan konsep pemrograman dasar kepada siswa SMK Pelita Pesawaran melalui pendekatan berbasis proyek. Materi pelatihan meliputi pengenalan sintaks dasar Python, implementasi logika pemrograman sederhana, hingga pembuatan aplikasi dasar berbasis data.Metode pelaksanaan terdiri atas pembelajaran teori secara daring dan praktik langsung melalui lokakarya tatap muka. Pelatihan ini bertujuan tidak hanya untuk meningkatkan pemahaman siswa tentang pemrograman, tetapi juga untuk memotivasi mereka agar dapat menerapkan Python dalam proyek inovatif di sekolah maupun dunia kerja. Hasil kegiatan menunjukkan peningkatan signifikan pada pemahaman siswa tentang pemrograman dan kemampuannya mengimplementasikan Python untuk menyelesaikan masalah nyata. Dengan dukungan dari pihak sekolah dan komunitas lokal, pelatihan ini diharapkan menjadi program berkelanjutan untuk mendukung pengembangan SDM yang siap bersaing di era digital. Basic Python training serves as a strategic step to enhance programming literacy among vocational high school (SMK) students, preparing them to face the challenges of the Fourth Industrial Revolution. Python was chosen due to its simple syntax, flexibility, and extensive applications in fields such as data science, artificial intelligence (AI), and the Internet of Things (IoT). This program is designed to introduce fundamental programming concepts to students of SMK Pelita Pesawaran through a project-based approach. The training materials include an introduction to Python syntax, implementation of basic programming logic, and the development of simple data-driven applications.The implementation method involves theoretical online learning and hands-on practice through in-person workshops. This training aims not only to enhance students' understanding of programming but also to motivate them to apply Python in innovative projects at school and in their future careers. Results from the activity demonstrated a significant improvement in students' programming comprehension and their ability to implement Python in solving real-world problems. With support from the school and the local community, this program is expected to become a sustainable initiative to foster the development of human resources ready to compete in the digital era.
Sentiment Analysis of Twitter Discussions About Lampung Robusta Coffee: A Comparative Study of Machine Learning Algorithms with SVM as The Optimal Model Yuniarthe, Yodhi; Syarif, Admi; Shofi, Imam Marzuki; Fatimah Fahurian
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i2.41316

Abstract

Lampung Robusta coffee is an important commodity in Indonesia, particularly in terms of local economic potential and global recognition. However, public perception of this product on social media, particularly Twitter, remains underexplored. This study addresses the need for a deeper understanding of consumer sentiment towards Lampung Robusta coffee, which could inform branding and marketing strategies. To approach this issue, we used five supervised machine learning algorithms-KNN, Naive Bayes, SVM, Decision Tree, and Logistic Regression-to perform sentiment classification on a dataset of tweets containing relevant keywords. The dataset was pre-processed using standard natural language processing techniques, including tokenization, stopword removal, and TF-IDF feature extraction. The SVM achieved the best performance on the unbalanced dataset for all metrics, with high and consistent accuracy and F1 scores. Logistic regression followed closely with similarly strong and stable results. Therefore, SVM is recommended as the final model. These results suggest that machine learning approaches can effectively classify sentiment in social media discussions about regional agricultural products and that random forest may provide the most robust performance in this context  
Implementation of Information Technology in Increasing the Efficiency and Effectiveness of MSME Business Processes Pong, Ming; Oswari, Teddy; Fahurian, Fatimah; Winarko, Triyugo
Journal of Loomingulisus ja Innovatsioon Vol. 2 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/innovatsioon.v2i1.1978

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in driving economic growth, particularly in emerging economies. However, MSMEs often face challenges related to limited resources, outdated business processes, and inefficient operational practices. The implementation of information technology (IT) has emerged as a potential solution to improve business processes, streamline operations, and enhance competitiveness. This study aims to examine the impact of information technology implementation on the efficiency and effectiveness of business processes in MSMEs. The research seeks to identify key factors that influence the adoption of IT, as well as assess how it contributes to improving operational efficiency, decision-making, and overall business performance in MSMEs. The findings revealed that MSMEs that integrated IT solutions experienced notable improvements in process efficiency, reduced operational costs, and enhanced decision-making. Over 70% of surveyed businesses reported better inventory management and faster response times to customer needs. Moreover, businesses leveraging IT tools showed a significant increase in productivity and profitability. The implementation of information technology significantly enhances the efficiency and effectiveness of MSME business processes.
TEACHER CERTIFICATION DECISION SUPPORT SYSTEM Sutriana, Sutriana; Zuhri, Khozainuz; Fahurian, Fatimah; Yuniarthe, Yodhi
Journal of Technology and Data Science Vol. 1 No. 1 (2022): 2022
Publisher : PT. Alesha Media Digital

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Abstract

Technology in education in Indonesia has continued to improve throughout the 21st century. This results in a continuous evaluation of the education system, which in turn provides information on educational gaps. SMK Persada Bandar Lampung is an educational institution that has problems in assessing the feasibility of teacher certification, which does not yet have a system where errors often occur in the assessment process. Evaluating the feasibility of teacher certification, which is subjective will take time to process the results. In the process of assessing the feasibility of teachers, certification errors may occur. SMK Persada Bandar Lampung requires a decision support system that is expected to find a solution in the process of determining the best teacher. The decision system for assessingthe feasibility of teacher certification can facilitate data processing of the results of the teacher certification feasibility assessment at SMK Persada Bandar Lampung.Therefore, the researcher proposes a decision support system software engineering by applying Simple Additive Weighting (SAW). This system can later be used to assess the feasibility of teacher certification at SMK Persada Bandar Lampung to assist schools in evaluating the shortcomings and strengths of teacher performance
Pendampingan Strategi Marketing Berbasis Digital pada Kelompok Usaha Perajin Tapis dan Batik di Kabupaten Pringsewu Lampung Dwi Yunita, Hilda; Fahurian, Fatimah; Yuniarthe, Yodhi; Winarko, Triyugo; Sukri, Hamdan
ABDI AKOMMEDIA : JURNAL PENGABDIAN MASYARAKAT Vol. 3 No. 4 (2025)
Publisher : ABDI AKOMMEDIA : JURNAL PENGABDIAN MASYARAKAT

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Abstract

Pringsewu Regency is one of the regencies in Lampung Province that has a creative economy. There are many business groups there, almost all of whom sell their craft products or superior products such as bamboo weaving, tapis crafts, batik crafts, clay crafts, snack businesses, brick and tile industries. However, the marketing or sales process is still carried out conventionally, namely sales can only be done within the region due to the limited promotional or marketing area. Less than optimal marketing of a product can result in high or low income or earnings for the business group or craftsman. All of this is due to the lack of media that can be used for online marketing. To address these issues, the PKM team of the Faculty of Computer Science, Mitra Indonesia University, utilized technology to conduct mentoring and training activities on Digital-Based Marketing Strategies. Furthermore, these training and mentoring activities were conducted through several sessions, so that participants had sufficient time to understand the technology and develop skills in using innovative technology products. The results of this community service activity are expected to inspire participants on how to market products more creatively using technology media so as to increase sales access and access to higher income for micro-businesses in general and especially for micro-businesses of Tapis and Batik artisans in Pringsewu Regency, Lampung.
Analisis Performansi Pendekatan Machine Learning pada Deteksi Penyakit Daun Tanaman Kopi Yodhi Yuniarthe; Rosyana Fitria Purnomo; Hilda Dwi Yunita; Fatimah Fahurian; Ahmad Ikhwan
Seminar Nasional Teknologi dan Multidisiplin Ilmu (SEMNASTEKMU) Vol. 5 No. 1 (2025): SEMNASTEKMU
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/p2t2nm71

Abstract

Abstract. Detection and identification of plant diseases is critical to the success and efficiency of agricultural production. Plant disease outbreaks are becoming more frequent throughout the world, and the presence of these diseases in cultivated plants has a significant impact on productivity. Therefore, researchers are focusing on developing effective and reliable plant disease detection methods. Thus, farmers can take advantage of early detection of this disease to minimize future losses. This article discusses machine learning approaches as well as decision trees, K-nearest neighbors, naive Bayes, support vector machines (SVM), and random forests for detecting coffee leaf diseases using leaf images. The above-mentioned classifications were researched and compared to determine the most suitable plant disease prediction model with the highest accuracy. Compared with other classification algorithms, the SVM algorithm achieves the highest accuracy of 99.75%. All the models trained above will be used by farmers to quickly identify and classify new diseases in images as a prevention strategy. As a preventive measure, farmers can detect and classify new diseases in images early.   Keywords: Coffee Classification, Image Processing, Machine Learning, Plant Disease Detection.  
Pemanfaatan Teknologi Komputasi untuk Solusi Permasalahan Masyarakat di Bandar Lampung Hartanto, M. Budi; Fahurian, Fatimah
PENGAMATAN: Jurnal Pengabdian Masyarakat untuk Ilmu MIPA dan Terapannya Vol 3 No 2 (2025): PENGAMATAN: Jurnal Pengabdian Masyarakat untuk Ilmu MIPA dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pengamatanv3i2p37-43

Abstract

This community service activity aims to apply computational technology as a solution to various problems faced by the community in Bandar Lampung City. The identified issues include low digital literacy, limited use of software for economic activities, and the need for simple information systems to support local initiatives. The implementation method involved basic computational training, development of simple applications based on local needs, and mentoring in digital technology utilization. The results showed an improvement in participants’ ability to use computational tools, understand basic programming concepts, and apply technology to increase efficiency and productivity in daily activities. The implications indicate that the application of computational technology has significant potential to empower communities and strengthen digital transformation at the local level.
Analisis Performansi Pendekatan Machine Learning Pada Deteksi Penyakit Daun Tanaman Kopi Purnomo, Rosyana Fitria; Yodhi Yuniarthe; Hilda Dwi Yunita; Fatimah Fahurian; Ahmad Ikhwan
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3302

Abstract

Detection and identification of plant diseases is critical to the success and efficiency of agricultural production. Plant disease outbreaks are becoming more frequent throughout the world, and the presence of these diseases in cultivated plants has a significant impact on productivity. Therefore, researchers are focusing on developing effective and reliable plant disease detection methods. Thus, farmers can take advantage of early detection of this disease to minimize future losses. This article discusses machine learning approaches as well as decision trees, K-nearest neighbors, naive Bayes, support vector machines (SVM), and random forests for detecting coffee leaf diseases using leaf images. The above-mentioned classifications were researched and compared to determine the most suitable plant disease prediction model with the highest accuracy. Compared with other classification algorithms, the SVM algorithm achieves the highest accuracy of 99.75%. All the models trained above will be used by farmers to quickly identify and classify new diseases in images as a prevention strategy. As a preventive measure, farmers can detect and classify new diseases in images early.
Co-Authors Adit Kusnandar Admi Syarif Ahmad Ihkwan Ahmad ikhwan Amelia Hayati Ananta, Regi Pramudia Arief Rahman Wahid Budi Hartanto Deni Hardiannata Dirayati, Fadhilah Fathurrahman Kurniawan Ikhsan Fawaati, Teuku Muhammad Febi Andika Putra Ferry Susanto Hafiz, Aliy Hartanto, M Budi Hartanto, M.Budi Hartantom, Budi Hilda Dwi Yunita Icha Nuari Iin Marliana ikhwan, Ahmad Inuz, Khozainuz Khozainuz Zuhri Kusnadi Kusnadi M. Budi Hartanto, M. Budi marliana, iin Maulidun Nur Nitin, Mahon Pong, Ming Pramana, Ahmad Abilah Putra, Billy Sistian Romi Hendri Rosyana Fitria Purnomo Shofi, Imam Marzuki Sri Ipnuwati Sukri, Hamdan Sutriana, Mrs Sutriana, Sutriana Teddy Oswari Triyugo Winarko Triyugo Winarko, Triyugo Wati, Deva Imelda Setia Wijayanti, Mira Winarko , Triyugo Yodhi Yuniarthe