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Widyawati, Dewi Kania
Politeknik Negeri Lampung
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Classification Of Nutrient Deficiency In Lettuce Plants (Lactuca Sativa ) Using Machine Learning Algorithm Zuriati , Zuriati; Widyawati, Dewi Kania; Saputra, Kurniawan; Arifin, Oki
ABEC Indonesia Vol. 12 (2024): 12th Applied Business and Engineering Conference
Publisher : Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Plants require appropriate nutrients or nutrients for their growth and development. Inappropriate nutrient levelscan interfere with the plant growth process, resulting in less-than-optimal harvest results. Therefore, it is very importantfor farmers to know the nutrient levels of their plants, neither excessive nor lacking. Identification of nutrient deficienciesin plants such as Lettuce (Lactuca Sativa) traditionally requires careful observation of the physical characteristics of theplant, which is often long-drawn out and stand in need of a high level of accuracy. Leaf color is often used as an indication,for example if it is pale or yellow it can indicate a lack of nitrogen or iron. This requires expertise and experience incultivation for lettuce cultivators. So, a tool is needed that can identify nutrient deficiencies accurately, quickly, and easily.This study aims to overcome this challenge, namely identifying nutrient deficiencies in lettuce plants. This approach utilizesmachine learning technology to distinguish four main classes of deficiencies, namely: nitrogen (N), phosphorus (P), andpotassium (K), as well as normal or healthy lettuce leaf conditions. The proposed research method consists of the followingstages: 1). Lettuce leaf image dataset collection, 2). Preprocessing dataset, 3). Implementation of machine learning usingthe Support Vector Machine (SVM) algorithm. In the implementation of SVM, experiments were carried out by applyingvarious SVM kernel spesifically: Linear, Polynomial, Radial Basis Function (RBF), and Sigmoid, 4). Evaluation of modelperformance. Model performance was evaluated by measuring its level of accuracy in classifying nutrient deficiencies inLettuce leaf image data. The results of the experiment showed that SVM with the RBF kernel had the best accuracy, namely:92%. The findings of this study provide valuable insights into the effectiveness of machine learning approaches inclassifying nutrient deficiencies in Lettuce plants. This study can help farmers to optimize their crop production moreefficiently and accurately.
The Implementation of Internet of Things (IOT) for Aquaponic Cultivation Zuriati, Zuriati; Widyawati, Dewi Kania; Dulbari, Dulbari; Zarnelly, Zarnelly
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 10, No 2 (2024): December 2024
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v10i2.29541

Abstract

Aquaponic is a plant cultivation technique that is widely used by farmers and today’s communities due to its efficiency and ability to increase the agricultural productivity. The aquaponic cultivation in general still uses simple systems, such as manually feeding the fish by spreading the feed at predetermined times, monitoring water pH using a pH meter and monitoring water height or level through measurements, requiring farmers to spend time and special labor to care for and maintain plants and fish. Therefore, a solution is needed in the form of a system that can monitor and control plants and fish conditions automatically and continuously for 24 hours. The system should have the ability to control and monitor feeding activities, water pH, water and environmental temperature, water level and environmental humidity. The system in question is the internet of things (IoT) system that can be used as a tool for automatic control and monitoring through an application. The IoT system consists of several sensors that are connected to a microcontroller which can measure water pH, temperature, water level and environmental humidity. The data obtained by the sensor will be sent to a server via Wi-Fi protocol and stored in a database. The system is equipped with a web application that can be accessed through a computer device. The application provides a visual display of data: time, water pH, temperature, water level and environmental humidity, making it easier for farmers to monitor aquaponic conditions from a distance without having to come to the land. Through the implementation of IoT in aquaponic cultivation, farmers can increase efficiency and agricultural productivity by reducing the time, labor and costs required for control and monitoring.
PENDAMPINGAN PEMBUATAN MEDIA PEMBELAJARAN INTERAKTIF BERDIFERENSIASI KURIKULUM MERDEKA BERBASIS DIGITAL PADA SMA PGRI KATIBUNG Arifin, Oki; Widyawati, Dewi Kania; Wibowo, Yusep Windhu Ari; Ikhsan, Fathurrahman Kurniawan; Sylvia, Sylvia; Nurkhotimah, Jihan Susan; Romanda, Novandro; Djangkaru, Elliana
Jurnal Pengabdian Nasional Vol 6 No 1 (2025)
Publisher : Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25181/jpn.v5i2.4231

Abstract

Kegiatan Pengabdian kepada Masyarakat (PkM) dengan melibatkan mitra yaitu SMA PGRI Katibung yang merupakan salah satu sekolah penggerak jenjang SMA yang berlokasi di Desa Tarahan, Kecamatan Katibung, Kabupaten Lampung Selatan, Lampung. Kegiatan PKM dilatar belakangi oleh hasil studi awal bahwa guru di SMA PGRI Katibung belum semuanya mengetahui konsep pembelajaran terdifernsiasi kurikulum merdeka dan belum pernah mendapatkan pelatihan mengenai media pembelajaran interaktif. Selain itu, guru belum memahami konsep dan implementasi pembelajaran terdiferensiasi, guru masih menggunakan pendekatan, media, dan metode mengajar konvensional tanpa melibatkan atau menggunakan media pembelajaran digital. Kemudian yang terakhir, guru belum pernah mengikuti pelatihan pembuatan dan pengembangan media pembelajaran digital interaktif apalagi berbasis teknologi. Tujuan PKM ini adalah untuk mengembangkan media pembelajaran interaktif yang menarik dan relevan untuk meningkatkan kemampuan literasi siswa. Integrasi teknologi dalam pembelajaran diharapkan dapat menciptakan pengalaman belajar yang lebih menarik dan mendukung peningkatan literasi serta numerasi siswa di SMA PGRI Katibung. Metode Pembelajaran yang digunakan adalah 1) Edukasi dan pelatihan, 2) Diskusi dan ceramah, dan 3) Pendampingan pembuatan media pembelajaran interaktif digital. Kata kunci: media pembelajaran, diferensiasi, kurikulum merdeka
BRAND EQUITY DEVELOPMENT STRATEGY TO ENHANCE THE COMPETITIVENESS OF FOOD SMALL-MEDIUM ENTERPRISE'S (SMES): CASE STUDIES ON FUDIA-POLINELA AGRI-FOOD CENTRE Fitriani, Fitriani; Sutarni, Sutarni; Unteawati, Bina; Apriyani, Marlinda; Widyawati, Dewi Kania; Berliana, Dayang
Jurnal AGRISEP JURNAL AGRISEP VOL 20 NO 02 2021 (SEPTEMBER)
Publisher : Badan Penerbitan Fakultas Pertanian, Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (899.65 KB) | DOI: 10.31186/jagrisep.20.2.289-304

Abstract

The competitiveness of local agri-food needs through various marketing strategies. An essential part of the company's marketing strategy and tactics is recognizing product brand equity in the market. This study aims to identify brand entities, brand communication, and process to build Brand Equity toward local SMEs' competitiveness. A case study approach did at one of the SMEs in Bandar Lampung on the "FUDIA-Center of Agri-Food Polinela," that produce FUDIA cake & bakery.  The research has conducted from April to July 2020. Data analysis used a qualitative descriptive approach using SWOT analysis and a brand development model for SMEs. The analysis results concluded that FUDIA's brand recognition is the initial stage.  Development of the Fudia brand equity must take into account an existing market and expanding market share.  Enhancement market share could trough sales force distribution. Develop more product variants of Fudia Cake & Bakery based on the local source. Strengthen brand equity and develop a remarkable brand image program. Design and setting promotions systematic & massively is a priority.
PENINGKATAN KOMPETENSI DIGITAL GURU MELALUI PELATIHAN KODING DAN KECERDASAN ARTIFISIAL BERBASIS DEEP LEARNING DI SMAN 2 KALIANDA Kania Widyawati, Dewi; Arifin, Oki; Maulini, Rima; Zuriati, Zuriati; Sahlinal, Dwirgo; Pratama, Yoga; Ari Wijaya Saputra, I Komang; Bulan Nayla, Amanda
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 8, No 11 (2025): MARTABE : JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v8i11.4100-4108

Abstract

Implementasi Kurikulum Merdeka di SMAN 2 Kalianda memerlukan pendekatan inovatif seperti pembelajaran mendalam (Deep Learning) yang berfokus pada tiga pilar yaitu pembelajaran sadar (Mindful Learning) menyesuaikan materi dengan kebutuhan siswa dan mendorong fokus penuh,  pembelajaran bermakna (Meaningful Learning) melatih berpikir kritis dan mengaitkan konsep dengan kehidupan nyata, serta pembelajaran menyenangkan (Joyful Learning) menciptakan pengalaman belajar yang interaktif dan memotivasi. Namun, pengintegrasian teknologi seperti pemrograman Python dan kecerdasan artifisial masih terhambat oleh keterbatasan kompetensi guru. Program pengabdian ini bertujuan untuk melatih guru dalam penguasaan koding, kecerdasan artifisial, membimbing pendidik merancang modul berbasis proyek, serta mengembangkan bahan ajar digital yang sesuai dengan Kurikulum Merdeka. Pengabdian ini dilaksanakan melalui pendekatan partisipatif kolaboratif yang melibatkan mitra secara aktif. Metode pelaksanaan melalui lima tahapan yaitu sosialisasi, pelatihan, penerapan teknologi, pendampingan dan evaluasi, serta keberlanjutan program. Peserta dilatih untuk memahami algoritma pemrograman, pemrograman Python, pembuatan model AI sederhana, dan bahan ajar digital melalui Learning Management System (LMS) sekolah. Pelatihan dan evaluasi berbasis pre-test dan post-test menunjukkan hasil peningkatan signifikan dalam pemahaman peserta dengan rata-rata nilai sebesar 64,88 menjadi 96,63 dan N-gain score sebesar 91,36%. Hal ini menunjukkan efektivitas program dalam meningkatkan pengetahuan peserta tentang koding dan kecerdasan artifisial.
Peningkatan Daya Saing Produk Kelompok Wanita Tani Tepian Melalui Pemasaran Digital dan Inovasi Kemasan Arifin, Oki; Widyawati, Dewi Kania; Desfaryani, Rini; Billah, Muhammad Fahry Arief; Loriko, Hendra Agus; Sari, Chika Imelda
Amal Ilmiah: Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 3 (2025)
Publisher : FKIP Universitas Halu Oleo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36709/amalilmiah.v6i3.562

Abstract

Suak merupakan salah satu desa di Kabupaten Lampung Selatan memiliki KWT Tepian yang mengolah tepung pisang sebagai produk unggulan. Namun, pemasaran produk masih dilakukan secara konvensional dengan kemasan yang kurang menarik dan terbatas pada pasar lokal. Program pengabdian ini bertujuan untuk meningkatkan daya saing produk melalui pelatihan pemasaran digital dan inovasi kemasan produk. Metode yang diterapkan terdiri dari lima tahapan utama, yaitu sosialisasi, pelatihan, penerapan teknologi, pendampingan dan evaluasi, serta keberlanjutan program. Peserta dilatih untuk memanfaatkan website e-commerce, media sosial, dan content creation untuk memperluas jangkauan pasar. Selanjutnya, pelatihan desain kemasan agar menarik minat konsumen. Pelatihan dan evaluasi berbasis pre-test dan post-test. Hasil menunjukkan peningkatan rata-rata nilai pengetahuan peserta dari 58.13 menjadi 95.74, dengan n-gain score sebesar 90.18%, sehingga program ini efektif dalam meningkatkan pemahaman peserta. Mitra mampu meningkatkan daya tarik kemasan produk tepung pisang dan memanfaatkan media digital secara efektif untuk memperluas pasar dan meningkatkan penjualan. Program ini memberikan kontribusi nyata dalam mendorong terbukanya akses pasar yang lebih luas dan memperkuat kemandirian ekonomi KWT Tepian di desa Suak.
Hybrid Machine Learning Approach for Nutrient Deficiency Detection in Lettuce Zuriati, Zuriati; Widyawati, Dewi Kania; Arifin, Oki; Saputra, Kurniawan; Sriyanto, Sriyanto; Ahmad, Asmala
TIERS Information Technology Journal Vol. 6 No. 2 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v6i2.7143

Abstract

Early detection of nutrient deficiencies in lettuce is essential for precision agriculture. However, this task remains challenging due to limited data availability and class imbalance, which reduce model sensitivity toward minority classes and hinder generalization. This study introduces a hybrid machine learning approach integrating SMOTE, Optuna, and SVM to enhance the accuracy of nutrient deficiency classification using digital leaf image analysis. The dataset, obtained from Kaggle, includes four categories: Nitrogen Deficiency (-N), Phosphorus Deficiency (-P), Potassium Deficiency (-K), and Fully Nutritional (FN). Image features were extracted using MobileNetV2 pretrained on ImageNet and classified with a Support Vector Machine. Three scenarios were tested: (1) SVM before SMOTE, (2) SVM after SMOTE, and (3) Optuna-SVM after SMOTE, evaluated using accuracy, precision, recall, and f1-score. The hybrid model achieved the best performance with accuracy 0.929, precision 0.946, recall 0.835, and f1-score 0.869, outperforming the other scenarios. This hybrid framework effectively addressed class imbalance and improved classification margin stability through adaptive hyperparameter tuning using the Tree Structured Parzen Estimator within Optuna. The novelty of this study lies in combining MobileNetV2 based feature extraction with SMOTE and Optuna-SVM for small agricultural datasets. The proposed approach offers an efficient, accurate, and practical solution for automated nutrient deficiency diagnosis and contributes to the development of AI-driven smart agriculture systems.
Co-Authors Agiska Ria Supriyatna Agus Ambarwari Agus Buowo Ahmad, Asmala Ambarwari, Agus Anung Wahyudi Ari Wijaya Saputra, I Komang Arifin, Oki Billah, Muhammad Fahry Arief Bulan Nayla, Amanda Dani Rofianto Dayang Berliana Desfaryani, Rini Djangkaru, Elliana Dulbari, Dulbari Dwirgo Sahlinal Dwirgo Sahlinal, Dwirgo Fathurrahman Kurniawan Ikhsan Fitriani Fitriani Fitriani Henry Kurniawan Henry Kurniawan Kurniawan Saputra Loriko, Hendra Agus Marlinda Apriyani Marlinda Apriyani mutiara mutiara Noer, Irmayani Nurkhotimah, Jihan Susan Nursandi, Juli Nurul Qomariyah Oki Arifin Putra, Septafiansyah Dwi Rima Maulini Romanda, Novandro Sari, Chika Imelda Siswahyudianto Sitanggang, Imas S. Sriyanto, Sriyanto Sutarni Sutarni, Sutarni Sylvia, Sylvia Unteawati, Bina Wibowo, Yusep Windhu Ari Yoga Pratama Yuniarti, Evi Zarnelly Zarnelly Zuriati, Zuriati