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All Journal Bulletin of Electrical Engineering and Informatics JURNAL MEDIA INFORMATIKA BUDIDARMA ILKOM Jurnal Ilmiah Journal of Soft Computing Exploration JURNAL REKAYASA INFORMASI SWADHARMA (JRIS) JURNAL ELEKTRO DAN INFORMATIKA SWADHARMA (JEIS) AMMA : Jurnal Pengabdian Masyarakat Jurnal Information System
Utomo, Wargijono
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Humanities Chemistry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing

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Penerapan Algoritma K-Means Untuk Pengelompokkan Penyakit Kronis pada Warga Lansia (Studi Kasus Pada: Posyandu Lansia RW 07) Utomo, Wargijono
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2410

Abstract

Health is very valuable for all humans, anyone can experience health problems, especially for the elderly. Posyandu elderly RW 07 Pulogebang sub-district is one of the health services available for elderly residents. One of the government's efforts to deal with health problems is by establishing posyandu for elderly residents, considering how elderly people are vulnerable to health problems. At this time, health problems have the potential to attack people who are elderly, and have a history of chronic disease and a weak immune system, more likely to develop disease. In order to provide proper treatment, the elderly posyandu officers classify elderly people who have a history of chronic disease so that they can provide appropriate education and treatment. The data collection and counseling methods carried out by the elderly posyandu are still random and take turns with elderly residents in RW 07, Pulogebang sub-district. However, this method has the risk of being less accurate with the resulting data, because each resident has a different history of disease. Therefore we need an analysis of the health data of the elderly, so that it can be seen the distribution of people who have a history of chronic disease. One solution is to use data mining. So that in this study the clustering technique was used using the K-Means algorithm to classify patients with chronic disease in the elderly residents of RW 07, Pulogebang Village.
Comparison of K-Means and K-Medoids Algorithms for Clustering the Spread of the COVID-19 Outbreak in Indonesia Utomo, Wargijono
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

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Abstract

The spread of Corono Virus 19 is very fast through effective human-to-human transmission through close contact and respiratory droplets such as coughing or sneezing. Various studies have been conducted to deal with COVID 19, but until now it has not been found how to stop the spread of this virus. Based on data obtained from the covid19.go.id page accessed on January 1, 2021 which was updated by the Ministry of Health, the overall number of confirmed cases was 1,078,314 active cases reaching 175,095 or 16.2% of confirmed cases, recovered 873,221 or 81.0% of cases confirmed, died 29,998 or 2.8% of the confirmed cases. In this study, comparing the two algorithms in the dataset which aims to analyze grouping patterns and determine the best method of data processing. The data used comes from the Ministry of Health, there are 4 attributes including confirmed cases, treatment, recovery and death, in this study only 2 attributes are used, namely confirmed cases and death.  From the results of data analysis and processing through a comparison between the K-Means method and the K-Medoids for grouping the spread of the corona 19 virus in Indonesia, with the Davies Boulden index value from the K2 to K9 values, it turns out that the K-Means method gets the smallest value at the K-value. 5 is 0.064, while K-Medoids at the k-2 value is 0.411. Thus, from the two methods used, it can be found that the best method for clustering the spread of the corona 19 virus outbreak in Indonesia is the K-Means method.
Mengklasifikasi Kematangan Buah Mangga Melalui Proses Pengolahan Citra Dengan Algoritma K-Nearest Neighbor Utomo, Wargijono
Jurnal Information System Vol 3 No 2 (2023): November 2023 : Jurnal Information System (JIS)
Publisher : Prodi. Sistem Informasi Fakultas Teknik Unkris

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Abstract

Dalam melakukan proses pengolahan citra, banyak metode serta algoritma yang dapat dipakai untuk mengklasifikasi data yang akan diuji diantaranya K-Means Clustering, Fuzzy Logic, K-Nearest Neighbor dan lain sebagainya. Penelitian terdahulu menyebutkan bahwa menggunakan klasifikasi K-Nearest Neighbor dengan transofrmasi warna HSV mendapatkan nilai akurasi di angka 55%, penelitian lain menyebutkan pengolahan citra menggunakan metode transformasi ruang warna HSI mendapatkan nilai akurasi di angka 87%. Aplikasi yang dibuat dipenulisan ini adalah aplikasi dengan menggunakan K-Nearest Neighbor sebagai proses klasifikasi nya dengan menggunakan metode HIS dan mencari nilai Mean, Variance dan Range untuk mengetahu nilai dari citra tersebut. Pada penelitian ini dilakukan 3 pemodelan pengujian yaitu dengan presentase 90% data latih dan 10% data uji sebagai pemodelan pertama, 80% data latih dan 20% data uji sebagai pemodelan kedua serta 70% data latih dan 30% data uji pada pemodelan ketiga dan didapatkan nilai akurasi 100% pada pengujian pertama, 90% pada pengujian kedua serta 80% pada pengujian ketiga.
Implementation of a reinforcement learning system with deep q network algorithm in the amc dash mark i game Utomo, Wargijono
Journal of Soft Computing Exploration Vol. 5 No. 1 (2024): March 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i1.271

Abstract

Reinforcement learning is a branch of artificial intelligence that trains algorithms using a trial-and-error system. Reinforcement learning interacts with its environment and observes the consequences of its actions in response to rewards or punishments received. Reinforcement Learning uses information from every interaction with its environment to update its knowledge. The problem identified from this research is the lack of consistency, which is not always the same for Non-Player Characters (Agents) in the process of exploring an environment (Game environment). This research uses the Software Development Life Cycle (SDLC) Waterfall model method to train Non Player Characters (Agents) in the Amc Dash Mark I Game which uses the Deep Q Network (DQN) algorithm in several stages. Training results show improvements in model performance over time. The average duration of the episode and average reward episode showed an increase of 7.75 to 24.7, while the exploration rate decreased to 0.05. This indicates that the model has experienced learning and is improving to achieve better rewards by performing fewer actions. The lower loss also shows that the model has succeeded in reducing prediction errors and improving prediction capabilities.
Rancang Bangun Aplikasi Monitoring Tumbuh Kembang Anak Balita Pada Posyandu Kelurahan Duren Sawit Junaidi; Devia, Elmi; Wahyu Rhamadani, Mega; Utomo, Wargijono
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 9 : Oktober (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Children are one of the valuable assets for a family. Children's growth and development can run well if their nutritional needs are met. Stunting is one of the disorders caused by poor parenting practices. Lack of parental knowledge about child growth and development can increase the risk of stunting. Duren Sawit Village is a village located in Duren Sawit District, East Jakarta Administrative City, DKI Jakarta Province. From interviews conducted with sources at the RW. 015 Posyandu, Duren Sawit Village, it is known that the process of recording child growth and development data is still done manually by recording child data in the Maternal and Child Health (KIA) record book. Based on the statement above, we are interested in creating an application for monitoring the growth and development of toddlers at the RW. 015 Posyandu, Duren Sawit Village, to make it easier for Posyandu cadres to send toddler nutritional status data to the Duren Sawit Sub-dept.
RANCANG BANGUN APLIKASI MONITORING STATUS GIZI ANAK MENGGUNAKAN ALGORITMA C4.5 Dharmalau, Andy; Utomo, Wargijono; Suryantoro, Hari
JRIS : Jurnal Rekayasa Informasi Swadharma Vol 5, No 1 (2025): JURNAL JRIS EDISI JANUARI 2025
Publisher : Institut Teknologi dan Bisnis (ITB) Swadharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56486/jris.vol5no1.685

Abstract

The research aims to design an application for child nutrition monitoring using the C4.5 Algorithm, focusing on measurement data from the Puskesmas in Jati Padang, Pasar Minggu District, South Jakarta. The data used amounted to 291 records over one year, which were processed to determine the nutritional status of children based on the Body Mass Index according to Age (BMI/A). The research methodology uses a quantitative approach with stages including problem analysis, application of the C4.5 algorithm for data classification, and proposed system design. The research results in a prototype of an application for child nutrition monitoring that can classify children's nutrition status with an accuracy level of 38.46%. This research is expected to significantly contribute to the development of more effective and efficient health information systems, improve the efficiency of data delivery to the Directorate of Community Nutrition of the Ministry of Health, and provide accuracy in determining children's nutrition status in real-time. This application is expected to support efforts to address malnutrition in Indonesia and benefit researchers and users in managing children's health data.Penelitian yang dilakukan ini bertujuan untuk merancang aplikasi monitoring status gizi anak menggunakan Algoritma C4.5, dengan fokus pada data pengukuran dari Puskesmas di Jati Padang, Kecamatan Pasar Minggu, Jakarta Selatan. Data yang digunakan berjumlah 291 record selama satu tahun, yang diolah untuk menentukan status gizi anak berdasarkan Indeks Massa Tubuh menurut Umur (IMT/U). Metodologi penelitian menggunakan pendekatan kuantitatif dengan tahapan mencakup analisis permasalahan, penerapan algoritma C4.5 untuk klasifikasi data, dan perancangan sistem usulan. Hasil penelitian berupa purwarupa Aplikasi monitoring status gizi anak yang mampu mengklasifikasikan status gizi anak dengan tingkat akurasi mencapai 38,46%. Penelitian ini diharapkan berkontribusi terhadap pengembangan sistem informasi kesehatan yang lebih efektif, efisien dan meningkatkan efisiensi pengiriman data ke Direktorat Gizi Masyarakat Kementerian Kesehatan, serta memberikan akurasi dalam penentuan status kondisi gizi anak secara real-time. Aplikasi ini diharapkan dapat mendukung upaya penanganan gizi buruk di Indonesia dan memberikan manfaat bagi peneliti serta pengguna dalam pengelolaan data kesehatan anak.
PROTOTYPE SISTEM PENYIRAMAN OTOMATIS TERUKUR PADA TABULAMPOT MENGGUNAKAN MOISTURE SENSOR DAN FLOW METER BERBASIS ARDUINO Suryantoro, Hari; Sari, Jamah; Ar-Rasyid, Harun; Dharmalau, Andy; Suhanda, Yogasetya; Sucahyo, Nur; Utomo, Wargijono
JEIS: Jurnal Elektro dan Informatika Swadharma Vol 5, No 2 (2025): JEIS EDISI JULI 2025
Publisher : Institut Teknologi dan Bisnis Swadharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56486/jeis.vol5no2.805

Abstract

Plant lovers utilise their yards, and some even have upper floors of buildings where they plant trees, using pots popularly known as Tabulampot. A common problem is forgetting to water the plants, which, if it persists for a long time, can cause the plants to dry out and die. However, if there is too much water, the plants are susceptible to disease, rot, and eventual death. Plants need consistent and sufficient water intake to meet their needs. Excessive watering results in wasteful water and loss of nutrients in the planting medium. For this reason, a system is needed that automatically waters plants with measured doses. The purpose of this study is to design an automatic and measured watering system. Using the research and development method with a field research technique. The case study used is a water apple tree planted in a pot measuring 30 cm in height and 40 cm in width, using soil as the planting medium. The test results of this design indicate that the soil moisture sensor system and water flow meter function correctly as planned.Para pecinta tanaman memanfaatkan pekarangan mereka, bahkan ada yang menanam pohon di lantai atas gedung, menggunakan pot yang dikenal sebagai Tabulampot. Masalah umum yang sering terjadi adalah lupa menyiram tanaman, yang jika dibiarkan dalam waktu lama dapat menyebabkan tanaman mengering dan mati. Namun, jika terlalu banyak air, tanaman rentan terhadap penyakit, pembusukan, dan akhirnya mati. Tanaman membutuhkan asupan air yang konsisten dan cukup untuk memenuhi kebutuhannya. Penyiraman yang berlebihan mengakibatkan pemborosan air dan hilangnya nutrisi pada media tanam. Oleh karena itu, diperlukan sistem yang secara otomatis menyiram tanaman dengan dosis terukur. Tujuan penelitian ini adalah merancang sistem penyiraman otomatis dan terukur. Penelitian ini menggunakan metode penelitian dan pengembangan dengan teknik penelitian lapangan. Studi kasus yang digunakan adalah pohon jambu yang ditanam dalam pot berukuran tinggi 30 cm dan lebar 40 cm, dengan menggunakan tanah sebagai media tanam. Hasil pengujian perancangan ini menunjukkan bahwa sistem sensor kelembapan dan flow meter air berfungsi dengan baik sesuai rencana.
Combination of item response theory and k-means for adaptive assessment Utomo, Wargijono; Kamdi, Waras; Sutadji, Eddy; Agus Sudjimat, Dwi
Bulletin of Electrical Engineering and Informatics Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i4.8962

Abstract

This study focuses on developing an adaptive assessment system for basic programming courses using a combination of item response theory (IRT) and the K-mean. The main objective is to enhance the precision of assessments by adapting the difficulty of questions to students' cognitive levels while grouping them based on both cognitive and affective characteristics. The key contribution is the creation of a more personalized assessment framework, addressing the shortcomings of traditional assessments, which often fail to accommodate varying student abilities. Methodologically, the study employs IRT to dynamically assess students' abilities, and students are categorized into different groups based on their answer patterns using K-means. The research design involves a student motivation survey and a programming skills test. Data is collected through the Google Quiz platform and analyzed using R Studio Software to apply the algorithms. The results demonstrate that combining IRT and K-means successfully adjusts the difficulty of questions and more accurately clusters students, providing more relevant feedback. In conclusion, this method enhances adaptive assessments' effectiveness and fosters personalized learning experiences. The findings have implications for broader application in courses with diverse student competencies.
Co-Authors Agus Sudjimat, Dwi Ar-Rasyid, Harun Devia, Elmi Dharmalau, Andy Eddy Sutadji Junaidi Junaidi Sari, Jamah Sucahyo, Nur Suhanda, Yogasetya Suryantoro, Hari Wahyu Rhamadani, Mega