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All Journal Jurnal Computech & Bisnis (e-Journal) Seminar Nasional Informatika (SEMNASIF) KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer Jurnal Teknologi Informasi dan Komunikasi JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Anderias Eko Wijaya
Universitas Mandiri
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Library & Information Science

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IMPLEMENTASI METODE SAW (SIMPLE ADDITIVE WEIGHTING) untuk MENENTUKAN PRIORITAS KEBERSIHAN TOILET SEKOLAH BERBASIS Internet of Things Wijaya, Anderias Eko; Hakim, Muhammad Azizul
Jurnal Teknologi Informasi dan Komunikasi Vol 16 No 1 (2023): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/a.v16i1.242

Abstract

This research proposes the implementation of the Simple Additive Weighting (SAW) method as an approach to determine priorities for school toilet cleanliness based on IoT. The system integrates temperature, humidity, and ammonia gas sensors as key indicators to measure the cleanliness condition of toilets. The SAW method is employed to calculate the relative weight of each parameter, which is then used to assign priority scores. The system operates by utilizing temperature sensors to identify the toilet's environmental temperature, humidity sensors to measure humidity levels, and ammonia gas sensors to detect ammonia concentration, a crucial indicator of toilet cleanliness. Data from these sensors are collected and processed using the SAW method, enabling the automatic determination of toilet cleanliness priorities. The success of this implementation is tested through simulations and field testing. Experimental results demonstrate that the system is capable of providing priority scores with high accuracy, allowing for more efficient management of toilet cleanliness. Other advantages include the system's ability to provide real-time notifications to relevant parties through the IoT platform, facilitating prompt corrective actions. This research contributes to the development of intelligent solutions for school toilet cleanliness management, integrating IoT technology and the SAW method to provide a measurable and effective approach. With the adoption of this system, it is expected to enhance the quality of school toilet sanitation, support student health, and optimize school facility management.
SISTEM IDENTIFIKASI SAMPAH ANORGANIK BERBASIS IOT (Internet of Things) MENGGUNAKAN METODE SAW (Simple Additive Weighting) Wijaya, Anderias Eko; Rokhman, Febriana Nur
Jurnal Teknologi Informasi dan Komunikasi Vol 16 No 2 (2023): Oktober
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/a.v16i2.249

Abstract

Inorganic waste is one of the environmental issues that needs to be effectively managed. An Internet of Things (IoT)-based system using the Simple Additive Weighting (SAW) method is implemented to provide a solution for the more efficient management of inorganic waste. This system utilizes sensors connected to the IoT network to detect and identify the types of inorganic waste entering a specific area. The SAW method is employed to assign weights to each criterion applied in the identification process of inorganic waste, such as type, weight, and physical condition. The system assesses based on the predefined criteria weights, enabling high-accuracy categorization of inorganic waste. Identification results can be accessed in real-time through the IoT platform Thingspeak, allowing for quick monitoring and analysis. Implementing this system is expected to positively contribute to the management of inorganic waste, facilitating more efficient collection, categorization, and overall waste handling. Moreover, adopting IoT technology and the SAW method in this system is envisioned to provide sustainable solutions in waste management efforts to support environmental sustainability.
SISTEM CERDAS PENGURAS AIR AKUARIUM SECARA OTOMATIS BERBASIS INTERNET oF THINGS (IoT) MENGGUNAKAN ALGORITMA C4.5 pada PLATFORM BLYNK Nurhakim, Muhamad Wilvan; Wijaya, Anderias Eko; Hermawan, Rian
Jurnal Teknologi Informasi dan Komunikasi Vol 17 No 1 (2024): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/a.v17i1.258

Abstract

In general, fishkeeping has been a widely cherished activity among communities since ancient times, owing to its ease of maintenance and care, which encourages many individuals to engage in it. However, due to busy schedules or unforeseen circumstances, checking the water conditions in aquariums often poses a challenge. Therefore, there is a need for a tool capable of automatically controlling and draining aquarium water based on IoT technology using the C4.5 algorithm on the Blynk platform. This system can drain water if the aquarium water becomes cloudy, raise the temperature if it drops below optimal levels, and limit water filling. The ESP8266 and ESP32-S modules are utilized to receive, process, and transmit data to the aquarium owner via Wi-Fi. Relays serve as electrical power distributors for supporting components such as water pumps, water heaters, and solenoid valves. Testing results indicate that the water condition control component effectively operates in line with the system's functions and objectives. The existence of this tool can assist fishkeepers in maintaining real-time aquarium water quality, detecting water pollution, and monitoring the health of fish within the aquarium.
PENGEMBANGAN SISTEM IOT UNTUK PEMANTAUAN KESEHATAN DOMBA DENGAN ALGORITMA C4.5 BERBASIS THINGSPEAK Nugraha, Fahmi; Wijaya, Anderias Eko; Hermawan, Rian; Sobari, Dicky Iskandar
Jurnal Teknologi Informasi dan Komunikasi Vol 17 No 2 (2024): October
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/a.v17i2.266

Abstract

Effective livestock health monitoring is one of the primary challenges in modern farming, especially in detecting early health disorders in sheep. This research aims to develop a sheep health monitoring system based on the Internet of Things (IoT) using the C4.5 algorithm and the ThingSpeak platform. The system collects vital sheep data such as body temperature, heart rate, sound, and physical activity in real time through sensors and microphones connected to IoT devices. The data is then transmitted to the ThingSpeak platform for analysis and storage. The C4.5 algorithm is used to build a decision model capable of classifying the health conditions of sheep based on collected parameters such as temperature, heart rate, and respiration. The processed data results are displayed in the form of graphs and warning notifications on the ThingSpeak platform, allowing farmers to monitor livestock health easily and responsively. The accuracy test yielded a 90% accuracy rate using a confusion matrix with a data sampling split of 80% for training data and 20% for testing data. This indicates that the system has a high level of accuracy in detecting sheep health conditions. Consequently, the system has the potential to assist farmers in improving the efficiency of livestock health monitoring automatically and in real time. Moreover, the application of IoT technology and the C4.5 algorithm in the livestock sector is expected to provide innovative solutions to support productivity and animal welfare.
Sistem Penentu Penilaian Siswa pada Kurikulum 2013 Menggunakan Algoritma Simple Additive Weighting (SAW) (Studi Kasus SDN Darmaga V Subang) Anderias Eko Wijaya; Dadan Marwan
Jurnal Teknik Informatika dan Sistem Informasi Vol 2 No 2 (2016): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v2i2.616

Abstract

The Curriculum of 2013 form students to conduct an observation, questioning and reasoning toward the lesson/ science which is taught. Students are given the subjects based on the theme that is integrated in order to have knowledge of the environment, life, and have a strong personal foundation in social life and had a better creativity. Teacher as a spearhead in the implementation of the curriculum supposedly able to draw on the curriculum of 2013 precisely in term of the process of assessment to improve students’ competencies and furthermore it is expected to improve the quality of its graduates  who are able to face the global challenge. In order to have an accurate assessment therefore it is needed / demanded a system to support an assessment decision by using Simple Additive Weighting method (SAW). Simple Additive Weighting method (SAW) is well-known as a weighted summation method.The basic concept of Simple Additive Weighting (SAW) is looking at every alternative of weighted sum of all attributes.  Simple additive weighting (SAW) method requires the normalization process of matrix (X) to a scale that can be compared with all the alternative ratings which is exist.This the system is built by using PHP programming language and DBMS MySQL. Keywords — DBMS MySQL, Kurikulum 2013, PHP, Simple Additive Weighting.
Penerapan Simulasi AI Sistem Drone Ganda untuk Optimasi Lintasan pada Pemantauan Perkebunan Sumardi, Tedi; Suhendra, M. Agung; Robiyana, Iqbal; Wijaya, Anderias Eko
Jurnal Teknologi Informasi dan Komunikasi Vol 18 No 1 (2025): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/jtik.v18i1.286

Abstract

Drone-based monitoring systems have emerged as an effective solution to improve the efficiency of large-scale agricultural land surveillance, particularly in oil palm plantations. This study proposes an artificial intelligence (AI)-based simulation using dual drones to map optimal and distributed flight paths. The simulation considers the random wind effect on trajectory accuracy using a grid-based waypoint approach across the plantation area. The results show that both drones successfully completed the land inspection mission with an average wind-induced deviation of ±0.14 meters, indicating system stability under dynamic environmental conditions. Drone 1 covered a total distance of 9244.10 meters, while Drone 2 covered 10602.47 meters. A 3D trajectory visualization illustrates that the path deviations remained controlled. This research provides a foundation for developing more adaptive and efficient autonomous drone systems in the context of smart farming.
Perbandingan Kinerja Algoritma Naïve Bayes dan C4.5 pada Sistem Web Klasifikasi Kelayakan PKH Jupriyanto, Jupriyanto; Apandi, Jamaludin; Wijaya, Anderias Eko; Hermawan, Rian; Siallagan, Timbo Faritcan Parlaungan; Udoyono, Kodar; Ahmad, Hermansyah Nur
Jurnal Teknologi Informasi dan Komunikasi Vol 18 No 1 (2025): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/jtik.v18i1.287

Abstract

This study discusses the development of a web-based classification system for determining the eligibility of recipients of the Family Hope Program (PKH), by comparing two data mining algorithms: C4.5 and Naïve Bayes. The dataset used includes various attributes relevant to eligibility assessment for social assistance. The C4.5 algorithm is employed to generate an interpretable decision tree, while the Naïve Bayes algorithm is used for probabilistic classification. The results show that Naïve Bayes achieved the highest accuracy at 98%, excelling in processing large datasets more efficiently. Meanwhile, C4.5 achieved an accuracy of 93.33% and offered better interpretability through its decision tree visualization. Both algorithms proved effective in classifying PKH eligibility and can be implemented in social assistance information systems to improve the accuracy and efficiency of the beneficiary selection process. This research concludes that the choice of algorithm should be based on system priorities—whether the focus is on processing speed or result interpretability.
Evaluasi Performa Naive Bayes dan CART pada Klasifikasi Kualitas Tahu Nugraha, Luthfy Akmal; Jupriyanto, Jupriyanto; Haq, Haris Nizhomul; Wijaya, Anderias Eko; Ahmad, Hermansyah Nur
Jurnal Teknologi Informasi dan Komunikasi Vol 18 No 2 (2025): October
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/jtik.v18i2.328

Abstract

Untuk tetap bersaing di pasar global, produsen tahu harus memastikan kualitas produk yang konsisten. Pabrik Tahu Sumber Barokah, sebagai pemasok tahu bernutrisi tinggi yang telah lama beroperasi, menghadapi tantangan dalam menjaga kualitas sepanjang proses produksi. Penelitian ini membandingkan kinerja algoritma Naïve Bayes dan Classification and Regression Trees (CART) dalam mengklasifikasikan kualitas tahu menggunakan dataset yang dikumpulkan dari pabrik, yang berisi sampel tahu berkualitas tinggi dan rendah. Metodologi penelitian mencakup identifikasi masalah, pengumpulan data, preprocessing, klasifikasi, validasi, evaluasi, dan penarikan kesimpulan. Cross-validation digunakan untuk validasi model, dan confusion matrix digunakan untuk menilai precision, recall, dan F1-score. Hasil eksperimen menunjukkan bahwa Naïve Bayes mencapai akurasi 91%, precision 100%, recall 85%, dan F1-score 92%, sedangkan CART mencapai akurasi 86%, precision 70%, recall 100%, dan F1-score 82%. Hasil ini menunjukkan bahwa Naïve Bayes lebih cocok untuk mengklasifikasikan kualitas tahu dalam konteks ini.
SISTEM MONITORING KUMBUNG JAMUR TIRAM OTOMATIS BERBASIS IoT (Internet of Things) MENGGUNAKAN METODE K-NEAREST NEIGHBOUR Wijaya, Anderias Eko; Sobari, Dicky Iskandar; Munandar, Haris
Jurnal Teknologi Informasi dan Komunikasi Vol 16 No 1 (2023): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/a.v16i1.239

Abstract

In response to the growing market demand for oyster mushrooms, effective monitoring of the growth environment becomes crucial. This research aims to develop an automated Internet of Things (IoT)-based monitoring system for oyster mushroom cultivation, utilizing Wemos D1 R1 hardware, DHT22 temperature and humidity sensor, LM35 temperature sensor, and the K-Nearest Neighbour (KNN) method for data analysis. The IoT platform employed in this study is Antares. The system is designed to monitor real-time temperature and humidity within the mushroom cultivation chamber. The DHT22 sensor is employed for simultaneous measurement of air temperature and humidity, while the LM35 sensor gauges the soil temperature in the mushroom growth substrate. Data collected by these sensors are automatically transmitted to the Antares platform through Wemos D1 R1 via WiFi connectivity. The K-Nearest Neighbour (KNN) method is applied to analyze the accumulated temperature and humidity data. KNN provides the capability to identify patterns and trends in oyster mushroom growth based on environmental conditions. The results of this analysis offer valuable insights for oyster mushroom farmers to optimize growth conditions and enhance harvest yields. Through the implementation of this system, it is anticipated that efficiency and productivity in oyster mushroom cultivation will be improved. This IoT-based automated monitoring system provides an effective and practical solution for real-time monitoring of oyster mushroom growth conditions, offering farmers the opportunity to take prompt and informed actions to enhance their harvest yields.
Co-Authors Ade Irfan Ahmad, Hermansyah Nur Apandi, Jamaludin Dadan Marwan Dadan Marwan, Dadan Dede Sopian Deni Alfian Deni Rahmat G. Eby Syaepudin R. Evi Werdi Utami Fahmi Nugraha, Fahmi Fahru Roji Ishaq Hakim, Muhammad Azizul Haq, Haris Nizhomul Haris Munandar Haris Nurjaman Ibnu Juniar Pamungkas Iqbal Robiyana Jupriyanto . Kodar Udoyono, Kodar Lukman Maulana Moch. Tohira Abdul Malik Muhamad Agung Suhendra Nugraha, Luthfy Akmal Nur Imam Iskandar Nurhakim, Muhamad Wilvan Purnama Insan Rian Hermawan Rijal Bani Salam Sukarni Roby Muhromi Rokhman, Febriana Nur Siallagan, Timbo Faritcan Parlaungan Siti Nurlaelah Sobari, Dicky Iskandar Sunendra, Ali Tedi Sumardi Wulan Maelia Maspupah