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All Journal Prosiding KOMMIT BERKALA SAINSTEK Majalah Geografi Indonesia INFORMAL: Informatics Journal TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) JKKI : Jurnal Kedokteran dan Kesehatan Indonesia Abdimas Indonesian Journal Jurnal Pengabdian Masyarakat
Achmad Maududie
Faculty Of Computer Science, Jember University, East Java, Indonesia
Religion Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences

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PERBAIKAN INISIALISASI K-MEANS MENGGUNAKAN GRAF HUTAN YANG MINIMUM Maududie, Achmad; Wibowo, Wahyu Catur
Prosiding KOMMIT 2014
Publisher : Prosiding KOMMIT

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

Abstract

K-Means adalah salah satu algoritma clustering yang sangat popular karena kesederhanaan dan kemampuannya dalam menangani data dengan skala besar. Namun demikian algoritma ini sangat sensitif terhadap centroid awal. Perbedaancentroid awal akan memberikan perbedaan hasil clustering dan apabila centroid awal yang diberikan adalah centroid yang tidak baik maka dapat dipastikan hasil clusteringnya juga tidak baik. Artikel ini memuat sebuah metode baru yang dikembangkan penulis untuk meningkatkan kualitas centroid awal melalui teknik perbaikan k yang didasarkan pada graf hutan yang minimum (minimum forest graf). Hasil percobaan yang telah dilakukan menunjukkan bahwa metode inisialisasi menggunakan graf hutan yang minimum menghasilkan centroid awal yang lebih baik dan konsisten dibandingkan metode Forgy. Disamping itu jumlah perulangan yang harus dilakukan dalam proses clustering dengan menggunakan metode ini adalah lebih sedikit (rerata 3,2) dibandingkan metode Forgy (rerata 6,4).
Implementasi Metode Fuzzy Sebagai Sistem Kontrol Kepekatan Nutrisi Otomatis Tanaman Hidroponik Berbasis Mikrokontroler Pasa Rangkaian Nutrient Film Technique (NFT) Kurniawan Dwi Yulianto; Achmad Maududie; Nova El Maidah
INFORMAL: Informatics Journal Vol 7 No 1 (2022): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v7i1.29386

Abstract

Hydroponics is a method of cultivating plants by utilizing water as a growth medium by emphasizing on meeting the nutritional needs of hydroponic plants. Hydroponics requires special treatment such as maintaining nutrient levels within the range so that the use of a control system is used. The implementation of the automatic nutrition control system aims to make it easier for farmers to regulate the mixing of AB mix + POC nutrients with water at the PPM value of lettuce plants automatically based on the age of plant growth, so that farmers can produce plants with optimal growth and maximum yields. The hydroponic nutrition control system uses the Fuzzy method. The system will also be integrated with the Arduino Uno microcontroller which is equipped with a Total Dissolved Solids (TDS) sensor. The results of this study can be seen that the success of the system can work well in detecting nutrients in the reservoir and can control pumps and water pumps in low, normal, and high conditions. The sensor used can also work well, where the TDS sensor has an error value of 4.81% and then calibration is carried out so that it gets the equation for the TDS value
The Implementation of Minimum Forest Graph for Centroid Updating Process on K-Means Algorithm Achmad Maududie; Wahyu Catur Wibowo
INFORMAL: Informatics Journal Vol 3 No 3 (2018): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v3i3.10239

Abstract

K-Means is a well known algorithms of clusteing. It generates some groups based on degree of similarity. Simplicity of implementation, ease of interpretation, adaptability to sparse data, linear complexity, speed of convergence, and versatile in almost every aspect are noble characteristics of this algorithm. However, this algorithm is very sensitive on defining initial centroids process. Giving a bad initial centroid always produces a bad quality output. Due to this weakness, it is recommended to make some runs with different initial centroids and select the initial centroid that produces cluster with minimum error. However, this procedure is hard to achieve a satisfying result. This paper introduces a new approach to minimize the initial centroid problem of K-Means algorithm. This approach focus on centroid updating stage in K-Means algorithm by applying minimum forest graph to produce better new centroids. Based on gain information and Dunn index values, this approach provided a better result than Forgy method when this approach tested on both well distributed and noisy dataset. Moreover, from the experiments with two dimentional data, the proposed approach produced consisten members of each cluster in every run, where it could not be found in Forgy method.
The Implementation of Minimum Forest Graph for Centroid Updating Process on K-Means Algorithm Achmad Maududie
INFORMAL: Informatics Journal Vol 3 No 3 (2018): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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Abstract

K-Means is one of algorithms based on partitioning clustering method, particularly on sum-of-squared error criterion. It generates a single partition data for a single group of data that has high degree in similarity. This method has some advantages such as linear complexity, ease of interpretation, simplicity of implementation, speed of convergence, adaptability to sparse data, and versatile in almost every aspect. However, this method also has some weaknesses, such as very sensitive to initial centroids (center) that drives the quality of clustering output. Although there is a recommendation to make some runs with different initial centroids and select the initial centroid that produces cluster with minimum error, frequently, this procedure does not achieve a satisfying result. This paper introduces a new method to overcome this problem through enhancing the refinement mechanism in K-Means algorithm. This method focuses on rebuilding new centroids using minimum forest graphs to reproduce better models in the refinement mechanism. Based on the conducted experiments, the proposed method yielded better value of gain information and Dunn index than Forgy method in both relatively well distributed and relatively noisy dataset. Furthermore, the members of each cluster in every run of the conducted experiments were consistent for the proposed method, while it was not happen for Forgy method.
Analisis spasial infeksi Cryptosporidium spp. terhadap penggunaan sumber air bersih pada balita stunting di Kabupaten Jember Utami, Wiwien Sugih; Pangestu, Ahmad Yudho Hadi; Purwandhono, Azham; Maududie, Achmad; Armiyanti, Yunita; Hermansyah, Bagus
Majalah Geografi Indonesia Vol 38, No 2 (2024): Majalah Geografi Indonesia
Publisher : Fakultas Geografi, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/mgi.93422

Abstract

Abstrak. Cryptosporidium spp. adalah parasit intestinal yang secara global ditularkan melalui air (waterborne diseases), dengan banyak kejadian wabah di dunia yang dilaporkan terkait dengan sumber air konsumsi. Mayoritas penyakit ini tidak bergejala (asimptomatis) pada orang dewasa dengan rute penularan dari orang-ke-orang, hewan-ke-orang, melalui air dan makanan. Namun infeksi ini menyebabkan diare kronis hingga malnutrisi pada kelompok rentan yaitu balita dan merupakan faktor risiko terjadinya stunting.  Salah satu media transmisi Cryptosporidium spp. adalah air bersih yang dikonsumsi dan digunakan sehari-hari. Tujuan penelitian adalah untuk menganalisis risiko sumber air bersih yang digunakan sehari-hari terhadap infeksi Cryptosporidium spp. pada balita stunting secara spasial di Kabupaten Jember. Penelitian ini dilakukan pada populasi balita stunting di Kecamatan Kaliwates, Panti, Rambipuji dan Sukorambi Kabupaten Jember menggunakan desain cross sectional. Analisis spasial moran index dan nearest neigbor index (NNI) digunakan untuk mengetahui pola persebaran infeksi Cryptosporidium spp. terhadap suatu wilayah. Uji chi-square dilakukan untuk mengetahui hubungan faktor risiko sumber air  bersih  dengan infeksi Cryptosporidium spp. Hasil penelitian menunjukkan bahwa 18 dari 528 (3,41%) balita stunting diketahui terinfeksi Cryptosporidium spp. Nilai moran index menunjukkan adanya pola persebaran mengelompok (clustered) dengan autokorelasi positif di Kecamatan Sukorambi sedangkan daerah lainnya memiliki pola yang acak (random). Hasil NNI di Kecamatan Sukorambi menunjukkan pola yang acak, sedangkan 3 kecamatan lain menunjukkan pola menyebar (dispersed). Jenis sumber air bersih menunjukkan korelasi terhadap infeksi Cryptosporidium spp. Pola spasial infeksi Cryptosporidium spp. di Kecamatan Sukorambi dan korelasinya dengan jenis sumber air bersih ini menunjukkan bahwa pola infeksi ini cenderung mengelompok (clustered) karena penggunaan sumber air bersih yang sama pada penduduk di kecamatan ini yaitu sumber mata air alami yang digunakan bersama-sama seluruh warga, meskipun jarak antar penggunanya tidak berdekatan atau acak sesuai hasil NNI. Di 3 kecamatan lain, pola spasial cenderung menyebar (dispersed) karena penggunaan sumber air yang berbeda dan tidak digunakan secara bersama-sama. Kesimpulan, infeksi Cryptosporidium spp. cenderung meningkat pada sumber air bersih yang digunakan secara bersama-sama. Perlu edukasi pada kelompok masyarakat agar mengolah dulu air yang digunakan sebelum dikonsumsi untuk mengurangi risiko penyebarannya.Abstract. Cryptosporidium spp . are intestinal parasites that are transmitted worldwide by water(waterborne disease), with many of the reported outbreaks in the world associated with sources of drinking water. Most cases of the disease are asymptomatic in adults, and transmission is person-to-person, animal-to-person, waterborne, and foodborne. However, the infection causes chronic diarrhea and malnutrition in vulnerable children under the age of five and is a risk factor for stunting. One of the modes of transmission of Cryptosporidium spp . is through clean water, which is consumed and used daily. The study aimed to spatially analyze the risk of daily clean water sources on Cryptosporidium spp. infection among stunted children in Jember Regency. This study was conducted on a population of stunted young children in Kaliwates, Panti, Rambipuji and Sukorambi sub-districts of Jember Regency using a cross-sectional design. The Moran and NNI index were used to determine the distribution pattern of infection in a region. Chi-squared test was conducted to determine relationship between risk factors of clean water source and Cryptosporidium spp. It was found that 18 out of 528 (3.41%) stunted infants were known to have Cryptosporidium spp. infection. The Moran index value shows a clustered distribution pattern with positive autocorrelation in the Sukorambi sub-district, while the other areas show arandom pattern. The results of the NNI in Sukorambi sub-district show a random pattern, and 3 other sub-districts show adispersed pattern. The spatial pattern of Cryptosporidium spp . infection in Sukorambi subdistrict and its correlation with the type of clean water source shows that this infection pattern tends to cluster because the population in this subdistrict uses the same clean water source, natural springs, which are shared by all residents, although the distance between users is not close or random according to NNI results. In the other three sub-districts, the spatial pattern tends to be more dispersed due to the use of different water sources that are not shared. In summary, there is a tendency for the incidence of Cryptosporidium spp. to increase in shared water supplies. There is a need to educate community groups to treat the water they use prior to consumption in order to reduce the risk of its spread.Submitted: 2024-01-22  Revisions:  2024-09-11 Accepted: 2024-09-25 Published: 2024-09-25
Implementation of K-Means Clustering Method for Trend Analysis of Thesis Topics (Case Study: Faculty of Computer Science, University of Jember) Irianto, Maulana Rafael; Maududie, Achmad; Arifin, Fajrin Nurman
BERKALA SAINSTEK Vol 10 No 4 (2022)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v10i4.29524

Abstract

The development of information technology causes a large number of digital documents, especially thesis documents, so that it can create opportunities for students to take the same and not varied topics. Thesis documents can be grouped by topic by identifying the abstract section. The results of the grouping can be seen with the trend with data visualization so that it can be analyzed to find out the trend of each topic. Retrieval of data in the repository of the University of Jember through a web scraping process as many as 490 thesis documents for students of the Faculty of Computer Science, University of Jember. The preprocessing stage is carried out by text mining methods which include cleaning, filtering, stemming, and tokenizing. Then calculate the weight of each word with the Term Frequency - Inverse Document Frequency algorithm, followed by the dimension reduction process using the Principal Component Analysis algorithm, which is normalized by Z-Score first. The outliers removal process is carried out before classifying documents. Furthermore, document grouping uses the K-Means Clustering method with Cosine Similarity as the distance calculation and the Silhouette Coefficient algorithm as a test. The test results were carried out with various k values and the optimal value was obtained at k = 2 with a Silhouette value of 0.80. Then the topic detection uses the Latent Dirichlet Allocation algorithm for each cluster that has been formed. Each cluster is visualized with a line chart and Trend Linear algorithm and analyzed to find out the trend. From the results of the analysis, it can be concluded that the topic of Decision Support System Development is trending down, and the topic of IT Performance Measurement and Forecasting is trending up. It can be concluded that the topic of Decision Support System Development needs to be reduced so that other topics can emerge.
Klasifikasi Berita Politik Menggunakan Algoritma K-nearst Neighbor Fauziah, Difari Afreyna; Maududie, Achmad; Nuritha, Ifrina
BERKALA SAINSTEK Vol 6 No 2 (2018)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v6i2.9256

Abstract

Klasifikasi konten berita politik menggunakan algoritma K-Nearest Neighbor merupakan suatu proses untuk mengklasifikasikan berita politik ke dalam tiga subkategori yang lebih spesifik yaitu pilkada, UU ORMAS dan reshuffle kabinet. Algoritma yang digunakan dalam penelitian ini adalah algoritma K-Nearest Neighbor. Algoritma K-Nearest Neighbor merupakan suatu pendekatan klasifikasi yang mencari semua data training yang paling relatif mirip atau memiliki jarak yang paling dekat dengan data testing. Algoritma ini dipilih karena K-Nearest Neighbor merupakan algoritma yang sederhana dengan mencari kategori mayoritas sebanyak nilai K yang telah ditentukan sebelumnya. nilai K yang digunakan pada penelitian ini adalah K=3, K=5, K=7 dan K=9. Mekanisme dari sistem klasifikasi konten berita ini dimulai dengan tahap preprocessing. Berita politik yang dimasukkan kedalam sistem akan melewati empat tahap preprocessing yaitu case folding, tokenizing, stopword dan stemming. Tahap selanjutnya yaitu tahap pembobotan term. Pembobotan atau term weighting merupakan proses mendapatkan nilai term yang berhasil diekstrak dari proses sebelumnya yaitu proses preprocessing. Algoritma yang digunakan untuk tahap pembobotan pada penelitian ini adalah algoritma TFIDF. Setelah didapatkan nilai dari bobot term, kemudian dicari nilai jarak antar dokumen menggunakan algoritma cosine similarity. Langkah berikutnya adalah melakukan pengurutan data dalam data training berdasarkan hasil perhitungan nilai jarak. Selanjutnya, dari hasil pengurutan tersebut diambil sejumlah K data yang memiliki nilai kedekatan. Tujuan dari penelitian ini adalah sistem mampu mengimplementasikan algoritma KNN pada dokumen yang memiliki similarity yang tinggi. Pada penelitian ini dilakukan 3 pengujian dengan tiga variasi dataset yang berbeda dengan empat nilai K. Hasil akurasi yang terbaik didapatkan ketika sistem menggunakan nilai K=9 yang menunjukkan nilai precision sebesar 100%, recall sebesar 100% dan nilai f-measure sebesar 100%. Kata Kunci: klasifikasi, algoritma K-Nearest Neighbor, TFIDF, cosine similarity, confusion matrix.
Penguatan Pengelola Lahan Kelengkeng di Perkebunan Sentool melalui Teknologi Berbasis IoT Maududie, Achmad; Swasono, Dwiretno Istiyadi; Adiwijaya, Nelly Oktavia
JURNAL PENGABDIAN MASYARAKAT (JPM) Vol 4 No 2 (2024)
Publisher : Institut Teknologi dan Sains Mandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31967/jpm.v4i2.1231

Abstract

Sentool Plantation is one of the plantations in Jember Regency that is currently promoting longan as one of its superior products. From the results of previous observations, two problems were found, namely workers having difficulty in monitoring the land and inefficient use of water resources. To overcome these problems, an appropriate technology for controlling irrigation and monitoring land conditions based on the Internet of Things (IoT) is prepared that can help Sentool plantation workers in managing the longan plantation area. The implementation of this activity is divided into three stages, namely: development of irrigation control system and monitoring of land conditions, system integration, and implementation and socialization to plantation employees as the use of the system. This activity has succeeded in realizing the intended system in the form of hardware and software to control the irrigation system and monitoring with four required indicators, namely soil moisture, air humidity, air temperature, wind speed, and rainfall measurements. At the socialization stage, the enthusiasm of the Sentool plantation employees can be seen from the liveliness in participating in the socialization stage of the use of the system to assist land management. Currently, the plantation employees also know how to operate the system so that they can reduce the constraints of the irrigation system and can see the condition of the longan fields through the application.
Pelatihan Teknologi Drone untuk Pemetaan Pertanian Berkelanjutan Kelompok Tani Kemiri Santoso Desa Kalibaru Manis Arief, M. Habibullah; Segara, Akbar Pandu; Kartiko, Erik Yohan; Maududie, Achmad; Auliya, Yudha Alif; El Maidah, Nova; Swasono, Dwiretno Istiyadi
Abdimas Indonesian Journal Vol. 4 No. 2 (2024)
Publisher : Civiliza Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59525/aij.v4i2.533

Abstract

This community service program aims to overcome the low efficiency of agricultural land management in Kalibaru Manis Village, Banyuwangi, by focusing on increasing farmers' knowledge in utilizing drone technology for mapping. This training provides theory and practice of drone operation and processing aerial image data using Geographic Information System (GIS) software. The implementation method includes preparation, training, and evaluation stages. Participants were trained to operate drones, retrieve image data, and analyze it to produce land maps. A collaborative approach between lecturers, students, and practitioners was applied to ensure the success of the program. As a result, participants are able to use drones independently and utilize the data for more effective land management. This program increases agricultural productivity and supports environmental sustainability through the application of modern technology.
Pengembangan Konten Digital Sebagai Upaya Peningkatan Literasi Masyarakat Jember Tentang Covid-19 Maidah, Nova El; Maududie, Achmad; Amalia, Karina Nine
TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat Vol. 1 No. 2 (2021): TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat
Publisher : Fakultas Teknik, Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (381.794 KB) | DOI: 10.36526/tekiba.v1i2.1599

Abstract

The development of digital content on the CovidCare page is carried out as an effort to increase public awareness of Jember about Covid-19. Through the content on the CovidCare page, apart from making it easier for people to register as vaccination participants, it also makes it easier for health facilities to provide vaccination services. Digital content development is carried out through the stages of needs assessment, design, development, and implementation, as well as evaluation and revision.
Co-Authors Akbar Pandu Segara Amalia, Karina Nine Amrina, Adinda Putri Yusri Arifin, Fajrin Nurman Azham Purwandhono Bagus Hermansyah Dharmawan, Tio Dwiretno Istiyadi Swasono El Maidah, Nova Fauziah, Difari Afreyna Ifrina Nuritha Irianto, Maulana Rafael Kartiko, Erik Yohan Kinanti, Virli Galuh Kurniawan Dwi Yulianto M. Habibullah Arief Nova El Maidah Nova El Maidah, Nova El Oktavia, Nelly Pangestu, Ahmad Yudho Hadi Wahyu Catur Wibowo Wiwien Sugih Utami Yudha Alif Auliya, Yudha Alif Yunita Armiyanti