Abstract:Abstract: The rice plant, Oryza sativa, is a major food source in Indonesia. This plant is processed into rice, a staple food for the Indonesian people. Rice growth is crucial to ensure the rice produced is of good quality.…
ty. One part of the rice plant that is susceptible to disease is the leaves, which can inhibit growth and reduce rice quality. Therefore, early detection and accurate classification of rice diseases are crucial to minimize these negative impacts. This has driven the development of a Deep Learning model capable of high-performance automatic classification. This study aims to create a rice leaf classification model using the CNN algorithm and several transfer learning architectures such as ResNet101, VGG16, and Xception. A dataset of 859 rice leaf images collected from the Kaggle website was then processed using augmentation techniques to a total of 2,439 images, plus 215 smartphone photos for external data validation. Thus, the total dataset increased to 2,656 images, covering four categories: leafblast, brownspot, healthy, and hispa. The model was processed in two stages: on the initial dataset (Non-Augmented Dataset) and the Augmented Dataset. The best experimental results were obtained using the ResNet architecture, with a training accuracy of 96.17% and a validation accuracy of 95.22%. Based on the research results, the rice plant disease classification model using deep learning demonstrated good performance.
Keywords: convolutional neural network; deep learning; fine-tuning; image classification; resnet; rice plant
Abstract:Abstract: The management of veterinary drug stocks at the Veterinary Clinic Technical Implementation Unit (UPTD) of the North Sumatra Province Plantation and Livestock Service faces obstacles in the form of discrepancies…
between supply and demand, resulting in excess stock and budget waste. Uncertain demand for drugs is a factor that complicates decision-making in stock provision. This study aims to optimize drug stock management using the Mamdani fuzzy logic method, which is capable of handling data uncertainty and modeling information linguistically. Three input variables are used, namely initial stock, demand, and number of visits, with the output being the final stock. The process involves fuzzification, inference based on IF–THEN rules, and defuzzification using the centroid method. The results show that the developed system has a good accuracy level with a MAPE value of 17.52%, which means that this model is effective in providing optimal and efficient drug stock recommendations in a veterinary clinic environment.
Keywords: fuzzy mamdani; optimization; animal drug stock.
Abstract:Abstract: In agriculture, irrigation systems are vital for enhancing water management and maximising plant growth. Effective irrigation management involves distributing sufficient quantities of water evenly to condition…
soil fertility for plants. This study aims to design a prototype that can be monitored via the Telegram app. The research methodology employs a thinking framework approach. The system is implemented using an Arduino Uno microcontroller and supporting devices, including an ESP8266 Wi-Fi module, an ultrasonic sensor, a soil moisture sensor, a stepper motor and a servo motor. Telegram serves as the monitoring tool, sending notifications connected to the Arduino via a Wi-Fi network. Test results showed that the system operates effectively: the HC-SR04 ultrasonic sensor functions as a water level reader, and the stepper motor opens and closes the water gate. Soil moisture monitoring uses a soil moisture sensor to measure the water content in the soil. If the sensor detects dry soil conditions or a moisture level below 60%, the servo motor will rotate 15° to close the water channel. Conversely, if the sensor detects wet or moist soil conditions, the servo motor will rotate 0° to close the water channel.
Keywords: arduino uno; irrigation system; soil moisture; ultrasonic sensor;
Abstract:Abstract: Water irrigation is a crucial aspect of agriculture that often becomes the primary concern for farmers, especially because suboptimal management can lead to decreased crop yields and reduced income. So far, farmers…
mers have been practicing irrigation manually, where plants are watered twice a day, in the morning and evening, based on weather conditions without considering soil temperature or moisture levels. Based on the observations conducted, it was found that excessive water application increases water accumulation, resulting in nutrient loss from the soil and even root diseases. The objective of this study is to develop a system utilizing an ESP32 microcontroller and sensors to detect soil moisture, with a machine learning-based K-Nearest Neighbor (KNN) model, enabling farmers to remotely monitor and control their crops using an Android device. The testing results showed that with input data of 32°C temperature, 40% soil moisture, and 60% air humidity, the system produced a nearest distance of 0.000 and 0.541 from the closest k-nearest neighbors, with a status label of "needs water." As a result, the relay activates the water pump to irrigate the field. Meanwhile, for data with a nearest distance of 0.897, the system identified the status as "does not need water," indicating that the soil remains wet or moist. This study is expected to help reduce farmers' workloads by optimizing water usage according to plant needs and improving crop quality and yield.
Keywords: k-nearest neighbor (KNN); mikrokontroller ESP32; machine learning; water irrigation
Abstrak: Irigasi air merupakan aspek penting dalam pertanian yang menjadi perhatian utama petani, terutama karena pengelolaan yang kurang optimal berdampak pada penurunan hasil panen dan pendapatan. Selama ini, praktik irigasi oleh petani dilakukan secara manual, di mana penyiraman tanaman dilakukan dua kali sehari pada pagi dan sore berdasarkan kondisi cuaca tanpa memperhatikan suhu atau kelembaban tanah. Berdasarkan hasil observasi yang dilakukan, ditemukan masalah yaitu pemberian air secara berlebih menyebabkan akumulasi air meningkat mengakibatkan kehilangan nutrisi tanah dan bahkan penyakit akar. Tujuan penelitian ini menciptakan sistem yang dirancang menggunakan mikrokontroler ESP32 dan sensor untuk mendeteksi kelembaban tanah, dengan model K-Nearest Neighbor (KNN) berbasis machine learning sehingga memudahkan petani untuk mengontrol tanaman mereka dari jarak jauh menggunakan android. Hasil pengujian yang dilakukan dengan data inputan berupa suhu 32°C, kelembaban tanah 40% dan kelembaban udara 60%, sistem menghasilkan jarak terdekat sebesar 0.000 dan 0.541 dari k-nearest terdekat dengan label status "butuh air". Maka relay akan mengaktifkan pompa air untuk mengairi lahan. Kemudian, pada data dengan jarak terdekat 0.897, sistem mengidentifikasi status "tidak butuh air", menunjukkan bahwa kondisi tanah masih basah atau lembab. Penelitian ini diharapkan dapat membantu meringankan beban kerja petani mengoptimalkan penggunaan air sesuai dengan kebutuhan tanaman dan meningkatkan kualitas hasil panen.
Kata kunci: irigasi air; k-nearest neighbor (KNN); mikrokontroller ESP32; machine learning
Abstract:Abstract: Central Java has significant potential in the plantation sector with various commodities such as pepper, cloves, tobacco, tea, sugarcane, coffee, nutmeg, and patchouli. However, the abundance of commodities does…
s not guarantee that all of them provide maximum benefits. This study aims to recommend the most potential plantation commodities for development. The research utilizes plantation data from Central Java over the past few years, obtained from Satu Data Indonesia, covering land area, production, productivity, and the number of farmers. The evaluation criteria include land area, production, productivity, and the number of farmers. In the decision-making process, a Decision Support System (DSS) approach is applied using the Multi-Attributive Border Approximation Area Comparison (MABAC) method and the Preference Selection Index (PSI). The MABAC method is used to determine rankings, while PSI is used for criteria weighting. The results indicate that sugarcane, tobacco, and robusta coffee are the best commodities, with final scores of 0.419, 0.237, and 0.020, respectively. Therefore, it can be concluded that the most potential commodities for development in Central Java are sugarcane, tobacco, and robusta coffee.
Keywords: central java; MABAC; plantation; PSI
Abstrak: Jawa Tengah memiliki potensi besar di sektor perkebunan dengan berbagai komoditas seperti lada, cengkeh, tembakau, teh, tebu, kopi, pala, dan nilam. Tetapi dengan banyaknya komoditas, tidak memastikan bahwa semua komoditas memberikan manfaat yang maksimal. Penilitian ini bertujuan membuat rekomendasi komoditas perkebunan yang paling potensial untuk dikembangkan. Penelitian ini menggunakan data perkebunan di Jawa Tengah dalam beberapa tahun terakhir yang diperoleh dari Satu Data Indonesia, mencakup luas lahan, produksi, produktivitas, jumlah petani. Kriteria evaluasi yang digunakan meliputi luas lahan, produksi, produktivitas, jumlah petani. Dalam proses pengambilan keputusan, digunakan metode SPK dengan pendekatan (MABAC) serta (PSI). Metode MABAC digunakan untuk menentukan peringkat, sementara PSI digunakan untuk pembobotan kriteria. Hasil yang diperoleh dari penilitian ini yaitu Tebu, Tembakau, Robusta merupakan tanaman terbaik dengan hasil akhir 0,419, 0,237, 0,020. Oleh karena itu, dapat disimpulkan tanaman yang dapat dikembangkan dengan potensial di wilayah Jawa Tengah dengan berbagai macam komoditas yaitu komoditas Tebu, Tembakau, dan Robusta.
Kata kunci: jawa tengah; MABAC; perkebunan ; PSI
Abstract:Abstract: PT. Perkebunan Nusantara IV (Persero) Tinjowan is a state-owned enterprise unit operating in the palm oil plantation industry. In an effort to increase production, the plantation company aims to enhance production…
ion efficiency so that palm oil product prices become more competitive by determining harvest yields. The company's harvest yield estimation still uses a traditional approach based on the average bunch weight (BJR), considering the year of planting and the planting area. However, this technique is less effective and efficient. If the company's estimates are incorrect, it can potentially lead to losses or increased production budgets. The purpose of this research is to obtain a comparison of forecast results for the next month with the best alpha accuracy measure using the Single Exponential Smoothing method. The research method used is based on qualitative and quantitative data from interviews and observations of data from December 2022 to November 2023. The forecasting results with an alpha accuracy value of 0.9 using the Single Exponential Smoothing method show a forecast for December 2023 of 13,835.57844 with a percentage error rate (MAPE) of 9.28%, MAD of 1,021,423.6, and MSE of 174,130,366.
Keywords: forecasting; palm oil; single exponential smoothing
Abstrak: PT. Perkebunan Nusantara IV (Persero) Tinjowan sebagai unit usaha BUMN yang beroperasi di industri perkebunan kelapa sawit. Dalam upaya meningkatkan produksi, perusahaan perkebunan, peningkatan efisiensi produksi agar harga produk sawit lebih kompetitif dengan menentukan hasil panen. Pada perkiraan hasil panen perusahaan masih menerapkan pendekatan tradisional berdasarkan berat janjangan rata-rata (BJR) dengan mempertimbangkan tahun tanam dan luas area tanaman. Namun, tehnik ini kurang efektif dan efisien, Apabila perkiraan yang dibuat perusahaan salah berpotensi menyebabkan kerugian atau peningkatan anggaran produksi. Tujuan dari penelitian ini untuk mendapatkan perbandingan hasil peramalan pada bulan berikutnya dengan ukuran akurasi alpha terbaik menggunakan metode Single Exponential Smoothing. Metode yang digunakan dalam penelitian ini adalah berdasarkan data kualitatif dan kuantitatif dari hasil wawancara dan observasi data bulan desember 2022 - november 2023. Hasil peramalan dari ukuran akurasi nilai alpha 0.9 menggunakan metode Single Exponential Smoothing diperoleh peramalan untuk periode desember 2023 sebesar 13.835578,44 dengan tingkat persentase error MAPE sebesar 9,28%, MAD 1021423.6 dan MSE 174130366.
Kata Kunci: kelapa sawit; peramalan; single exponential smoothing
Abstract:Abstract: This research aims to develop a method for detecting leaf spot disease in oil palm seedlings using Convolutional Neural Network (CNN). Leaf spot disease in oil palm seedlings can hinder growth and production. CNN…
NN has proven effective in image processing and classification, particularly in plant disease detection. In this study, we utilized a dataset of images containing oil palm seedling leaves infected with leaf spot disease and healthy leaves. We performed data processing, built a CNN model, and conducted hyperparameter tuning. The test results demonstrate that the developed CNN model achieves high accuracy in recognizing and distinguishing between oil palm seedling leaves infected with leaf spot disease and healthy ones. This research contributes to the development of plant disease detection technology that can support economic growth in the oil palm plantation sector.
Keywords: Convolutional Neural Network, image processing, leaf spot disease detection, oil palm seedlings.
Abstrak: Penelitian ini bertujuan untuk mengembangkan metode deteksi penyakit bercak pada bibit kelapa sawit menggunakan Convolutional Neural Network (CNN). Bibit kelapa sawit yang terinfeksi penyakit bercak dapat menghambat pertumbuhan dan produksi kelapa sawit. Metode CNN telah terbukti efektif dalam pengolahan citra dan klasifikasi, khususnya dalam deteksi penyakit pada tanaman. Dalam penelitian ini, kami menggunakan dataset citra daun bibit kelapa sawit yang terinfeksi penyakit bercak dan yang normal. Kami melakukan processing data, membangun model CNN, dan melakukan tuning hyperparameter. Hasil pengujian menunjukkan bahwa model CNN yang dikembangkan memiliki akurasi yang tinggi dalam mengenali dan membedakan citra daun bibit kelapa sawit yang terinfeksi penyakit bercak dan yang normal. Penelitian ini memberikan kontribusi dalam pengembangan teknologi deteksi penyakit tanaman yang dapat mendukung pertumbuhan ekonomi di sektor perkebunan kelapa sawit.
Kata kunci: bibit kelapa sawit, Convolutional Neural Network, deteksi penyakit bercak, pengolahan citra.
Abstract:Abstract: Grass is one of the plants that live on God's earth, even grass is also written in Al-quran. Grass is currently also a pest for plants, so sometimes to minimize grass growth, many farmers or people eradicate grass…
ass by cutting it even by poisoning the grass. Each method used has its own risk of work accidents, such as using grass poison can experience insecticide poisoning. To anticipate this, a remotecontrol robot that sprays automatic grass poison using the PID method is designed. The test results found that the robot works with a voltage of 11.1 VDC with a 5-12VDC motor with a speed of 3000rpm and a gearbox motor is used so that it turns into a 5Kg load torque. Meanwhile, for control using the HC-05 interface which is connected to Android, the maximum distance transmission system is 0-10m. For watering grass, it has 2 scala heights, grass with a height of 10-15 uses PID 1, which is watered with a voltage of 11.1VDC delay (t) 1.5s. Grass with a height of 25-30 using PID 2, watered with a voltage of 14.8VDC delay (t) 3s. All watering the grass uses a 16VDC pump motor with 1500 rpm. After the robotic watering system is applied using the PID method, the P value = 14.56. The value of I = 22.08 and the value of D = 15.5.
Keywords : Control Remote; PID method; Poison sprinkler robot
Abstrak: Rumput merupakan salah satu tumbuhan yang hidup dimuka bumi allah, bahkan rumput juga tertulis didalam Al-quran. Rumput saat ini juga sebagai hama bagi tumbuhan, sehingga terkadang untuk meminimalisir pertumbuhan rumput, banyak petani atau orang yang membasmi rumput dengan cara dipotong bahkan sampai dengan cara meracun rumput tersebut. Setiap cara yang digunakan memiliki resiko kecelakaan kerja tersendiri, seperti menggunakan racun rumput bisa mengalami Keracunan insektisida. Untuk mengantisipasi hal tersebut, maka dirancang robot kendali distance jauh penyiram racun rumput otomatis menggunakan metode PID. Hasil pengujian mendapati robot bekerja dengan tegangan 11.1 VDC dengan motor penggerak 5-12VDC dengan kecepatan 3000rpm dan dipakaikan motor gearbox sehingga berubah kedalam bentuk torsi beban 5Kg. Sementara untuk kendali menggunakan interface HC-05 yang terhubung ke Android, sistem pengiriman distance maksimal 0-10m. Untuk penyiraman rumput, memiliki 2 scala tinggi, rumput dengan tinggi 10-15 menggunakan PID 1, yaitu disiram dengan tegangan 11.1VDC delay (t) 1.5s. Rumput dengan tinggi 20-30 menggunakan PID 2, disiram dengan tegangan 14.8VDC delay (t) 3s. Seluruh penyiraman rumputmenggunakan motor pompa 16VDC dengan rpm 1500. Setelah sistem penyiraman robot diterapkan dengan metode PID, maka nilai P = 14,56. Nilai I = 22,08 dan nilai D = 15.5.
Kata kunci: Kendali Jarak Jauh; Metode PID; Robot penyiram racun
Abstract:Abstract: Pests are a major problem for citrus farmers, until now the pests that attack citrus plants vary widely. One of the pests on citrus plants is the trunk beetle where this pest attacks the old leaves on the lower…
branches or branches as a result of which the leaves fall and the young branches die. For this reason, an expert system was designed to identify pests in citrus plants The method used in this research is the certainty factor method. The results based on the symptoms experienced by the citrus plants showed that the pests affected on the citrus plants were Aphids with an expertise level of 0.8 and a percentage of 80% and had a fairly good aquaculture value.
Keywords: citrus plant pest; certainty factor; expert system
Abstrak: Hama merupakan masalah utama bagi para petani jeruk, hingga saat ini hama yang menyerang tanaman jeruk sangat bervariasi. Salah satu hama pada tanaman jeruk adalah kumbang belalai dimana hama ini menyerang daun tua pada ranting atau dahan bagian bawah akibatnya daun gugur dan ranting muda mati. Untuk itu dirancang suatu sistem pakar mengidentifikasi hama tanaman jeruk. Metode yang digunakan pada penelitian kali ini ialah metode faktor kepastian (CF),. Hasil bedasarkan gejala-gejala yang dialami oleh tanaman jeruk tersebut bahwa hama yang terkena pada tanaman jeruk adalah Kutu Daun dengan tingkat kepakaran 0,8 dan persentase 80 % dan memiliki nilai akuasi yang cukup baik.
Kata kunci: faktor kepastian; hama tanaman jeruk; sistem pakar;
Abstract:Abstract : Coconut plantation palm has a very strategic role in the development of the Indonesian economy. Coconut palm that is processed becomes oil cook and material burn. To produce product quality derivatives from coconut…
conut palm this needs proper handling in its maintenance. On plantation coconut palm lots were found to cause coconut infected palm disease, so this will hinder productivity of the plantation. Handling is not appropriate to coconut infected palm disease and can result in losses that don't little. To overcome the problem, they make it a system android based expert. System experts can diagnose disease with detect the symptoms shown coconut palm moment attacked disease, so taking decision for handling furthermore will be more accurate that will impact on results maximum harvest.
Keywords : android; coconut palm; disease; system expert.
Abstrak : Perkebunan kelapa sawit memiliki peranan yang sangat strategis dalam pembangunan ekonomi Indonesia. Kelapa sawit ini banyak diolah menjadi minyak masak dan bahan bakar. Untuk menghasilkan produk turunan yang berkualitas dari kelapa sawit ini maka membutuhkan penanganan yang tepat dalam pemeliharaannya. Pada perkebunan kelapa sawit banyak ditemukan kasus kelapa sawit yang terserang penyakit, sehingga hal ini akan menghambat produktivitas perkebunan. Penanganan yang tidak tepat terhadap kelapa sawit yang terserang penyakit dapat mengakibatkan kerugian yang tidak sedikit. Untuk mengatasi masalah tersebut dibuatlah sistem pakar yang berbasis android. Sistem pakar dapat mendiagnosis penyakit dengan mendeteksi gejala-gejala yang ditunjukan kelapa sawit saat terserang penyakit, sehingga pengambilan keputusan untuk penanganan selanjutnya akan lebih akurat yang akan berdampak pada hasil panen yang maksimal.
Kata Kunci : android; kelapa sawit; penyakit; sistem pakar.