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All Journal Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Information Systems and Technology (JISTech)
Mohamad Arif Suryawan
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Computer Science & IT Control & Systems Engineering

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Penerapan Algoritma Stemming Nazief-Adriani dengan Metode Cosine Similarity Dalam Aplikasi Ujian Esai Mohamad Arif Suryawan; LM. Fajar Israwan; Ferdianto Arland
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Essay exam assessment using an exam application takes a long time to check. Answer checking is done by reading carefully. The answers given are some that match the answer key, and some are very different. Therefore, an exam application is needed that can directly assess the essay question answers and then give a score according to the answers written. This study aims to apply the Nazief-Adriani stemming algorithm with the Cosine Similarity method to the high school essay exam application. The research method used in this study consists of two stages, first the Nazief-Adriani algorithm carries out several processes, namely normalizing lowercase letters, punctuation, separating into individual words, removing common words, stemming by removing affixes from root words, mapping synonyms and finally calculating the frequency of word occurrence. Furthermore, the second stage, the Cosine Similarity method is used to compare the level of similarity with the answer key. This study produces an exam application that applies the Nazief-Adriani stemming algorithm in checking essay answers. This exam application is Android-based so that it makes it easier to answer exam questions, the answers are written in the box provided. The essay exam questions that are given are first equipped with the answer key stored in the application. From testing three essay answers, the calculation results using the Cosine Similarity method were obtained, namely: the first answer is 94.3, the second answer is 94.3, and the third answer is 74.5. The first and second answers produce a value of 94.3, indicating a high level of similarity to the answer key. Thus, the application created is expected to make it easier to check answers to essay questions quickly and accurately.
Analisis Keputusan Multi-Kriteria Menggunakan SAW dengan Pendekatan Interpretabilitas Model Mohamad Arif Suryawan; Ery Muchyar Hasiri
JISTech : Journal of Information Systems and Technology Vol. 2 No. 2 (2025): Desember 2025
Publisher : Perhimpunan Ahli Teknologi Informasi dan Komunikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71234/jistech.v2i2.102

Abstract

Pengambilan keputusan dalam berbagai bidang sering kali melibatkan banyak kriteria dengan tingkat kepentingan yang berbeda, sehingga diperlukan metode yang mampu menghasilkan keputusan secara objektif dan transparan. Penelitian ini bertujuan untuk menganalisis pengambilan keputusan multi-kriteria menggunakan metode Simple Additive Weighting (SAW) dengan pendekatan interpretabilitas model. Metode SAW dipilih karena kesederhanaan proses perhitungan serta kemampuannya dalam memberikan hasil keputusan yang mudah dipahami oleh pengguna. Penelitian ini menggunakan data dummy yang terdiri atas lima alternatif dan empat kriteria, yang mencakup kriteria benefit dan cost. Tahapan penelitian meliputi penyusunan matriks keputusan, normalisasi nilai kriteria, pembobotan, perhitungan nilai preferensi, dan perangkingan alternatif. Hasil penelitian menunjukkan bahwa metode SAW mampu menghasilkan peringkat alternatif secara konsisten dan transparan, di mana setiap nilai preferensi dapat ditelusuri kontribusinya berdasarkan bobot dan nilai masing-masing kriteria. Pendekatan interpretabilitas yang diterapkan memberikan pemahaman yang lebih jelas mengenai alasan di balik peringkat alternatif yang dihasilkan, sehingga meningkatkan kepercayaan pengambil keputusan terhadap sistem pendukung keputusan. Dengan demikian, metode SAW dengan pendekatan interpretabilitas model dapat dijadikan sebagai solusi yang efektif dan akuntabel dalam pengambilan keputusan multi-kriteria.
Implementasi Algoritma Deep Learning YOLO dan OpenCV untuk Mendeteksi Perbedaan Buah Ery Muchyar Hasiri; Fahmi; Mohamad Arif Suryawan; Nurfida Ain
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The development of computer vision technology and artificial intelligence has driven innovation in automation in various fields, including the agricultural sector and fruit trading. The process of identifying fruit quality, which is generally done manually, is still vulnerable to human error and inconsistencies. Based on these problems, this study aims to develop an automated system to detect the difference between fresh and rotten fruit using a deep learning-based You Only Look Once (YOLO) algorithm integrated with the OpenCV library. The system is designed in the form of a web application that is easy for fruit sellers to use. The dataset used consists of images of apples, mangoes, and bananas labeled through Roboflow into two categories, namely fresh and rotten. The model was trained using YOLOv11, then tested with new data that had never been used before. The test results showed high performance with an accuracy of 99.01%, mAP@50 of 0.925, precision of 0.93, recall of 0.90, and F1-score of 0.91. Based on these results, the system is able to detect the condition of the fruit automatically and in real-time with an excellent level of accuracy. This implementation proves that the integration between YOLO and OpenCV is effective in improving the efficiency, accuracy, and consistency of the fruit quality identification process.
Pengembangan Sistem IoT Berbasis Sensor untuk Analisis Kesuburan Tanah pada Lahan Pertanian Ery Muchyar Hasiri; Fahmi; Mohamad Arif Suryawan; Marselfa Nasir
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The development of Internet of Things (IoT) technology has had a significant impact in various fields, including the agricultural sector. One of the main challenges in modern agriculture is the efficient and accurate measurement of soil fertility, including temperature, humidity, and nutrient content parameters such as nitrogen (N), phosphorus (P), and potassium (K). Manual measurements take considerable time, effort, and cost, and often result in less accurate data because they are subjective and not real-time. This research aims to design and build an IoT-based soil fertility measuring device that integrates NPK sensors, Soil Moisture sensors, and DHT22 sensors with ESP32 microcontrollers as the system control center. The methods used include hardware and software design, ESP32 programming using Arduino IDE, and integration with the Firebase platform for online data storage. It reads the soil conditions in real-time and displays the measurement results on the LCD, as well as transmitting data to a smartphone application over the internet. The test results show that the tool can distinguish fertile and infertile soil conditions well. In fertile soils, a temperature of 29°C, humidity of 89%, and NPK content of Nitrogen 20–23 ppm, Phosphorus 32 ppm, and Potassium 190–195 ppm, respectively. Meanwhile, in infertile soils, a temperature of 23–32°C, humidity below 75%, and a Nitrogen content of 12 ppm, Phosphorus 22 ppm, and Potassium 118–120 ppm. This system provides benefits in remote monitoring, resource efficiency, and increased agricultural productivity.
Co-Authors Ery Muchyar Hasiri Fahmi Ferdianto Arland LM. Fajar Israwan Marselfa Nasir Nurfida Ain