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INDONESIA
Tech-E
Published by Universitas Buddhi Dharma
ISSN : -     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Tech-E dikembangkan dengan tujuan menampung karya ilmiah Dosen dan Mahasiswa, baik hasil tulisan ilmiah maupun penelitian yang berupa hasil studi kepustakaan.
Arjuna Subject : -
Articles 116 Documents
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Clustering Analysis of Admission of New Students Using K-Means Clustering and K-Medoids Algorithms to Increase Campus Marketing Potential Amin, Hasan
Tech-E Vol. 7 No. 1 (2023): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v7i1.2264

Abstract

Acceptance of new students is a very important activity for a high school or university. The admissions data has not been utilized by the campus in making strategic decisions, marketing potential, and considering invitations through academic admissions. So, to assist in processing the new student admissions data, in this study the design and analysis of new student admissions data was carried out using stages in data mining. The clustering method approach can be applied in analyzing the potential level of PMB quality produced by utilizing the PMB recording dataset for the 2023 period. 86 data records. The K-Means and K-Medoids algorithm models that are applied have results that show a new insight, namely grouping based on 2 clusters, cluster 1 (C0) is a pass category while cluster 2 (C1) has not been determined. The results of the K-Medoids algorithm which has cluster 1 (C0) 60 results, cluster 2 (C1) has 26 results is a potential pass of 60 and has not yet been determined 26 of the data tested 86 while the results of the K-Means cluster 1 algorithm (C0) 40 , cluster 2 ( C1 ) 46 is a potential pass consisting of 40 and 46 undetermined data from the 86 datasets tested. Testing using the RapidMiner Studio application can also produce similar insights, namely each cluster has Davies Bouldin Index or DBI results from each K-Means and K-Medoids algorithm. K-Means has a Davies Bouldin Index result of -0.533 while K-Medoids has a Davies Bouldin Index result of -0.877
The IOT-Based Hydrogen Sulfide Monitoring at PT. Pertamina Geothermal Energy on Lumut Balai Area Dasmen, Rahmat Novrianda; Muhammad Adrian Saputra
Tech-E Vol. 7 No. 1 (2023): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v7i1.2287

Abstract

Geothermal Power Plants produce electricity energy from geothermal sources found in geothermal wells. Inside the geothermal well there is H2S content which is a toxic gas that can cause death to humans when human exposed the H2S content for 500-700 ppm within 30-60 minutes. Based on several literacies, in this research, H2S sensor type MQ-136 was used to monitoring H2S content in the geothermal environment. The Internet of Things system is used to read data parameters as a tool to display PPM values on the LCD of the transmitter and receiver device, as well as Adafruit IO website for reading parameter sensor data.. To transmit data from the transmitter to the receiver, Lora Ra-01 AI Thinker is used. The focus of this research is to be able to remotely monitor H2S content through the Adafruit IO website, the highest data was read is 0.54 ppm and the lowest at 0 ppm. This equipment will give "BHY" signal on the LCD display on the transmitter and from the Adafruit IO website it will send a notification "hazard of high ppm H2S" to mobile phones who installed IFTTT application if the H2S concentration was read for 10 ppm or higher, so that workers avoid being exposed to high concentrations of H2S when they want to monitor the parameters in the Geothermal well area.
Analisis sentiment komentar Instagram bakal calon presiden menggunakan metode Support Vector Machine Alqis Rausanfita; Ramadan, Arip; Dzulfikar Fauzi, Muhammad; Mafidah, Qori Emalia Putri; Ramona, Emilia; Mahardika Putra, Yudha
Tech-E Vol. 7 No. 1 (2023): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v7i1.2289

Abstract

The rising number of Instagram user affecting higher number of comments appear on post especially Instagram accounts of Indonesia's 2024 presidential candidates that made it difficult to understand the public sentiment towards presidential candidate. Therefore, this research aims to classify Indonesian sentiment on Instagram comments of 2024 Indonesian presidential candidates using the Support Vector Machine method. The classified sentiment is divided into three classes, namely positive, negative, and neutral. The results shows that Sentiment Analysis of Comments on Instagram Posts of Indonesia's 2024 Presidential Candidates Using The Support Vector Machine Method has a good accuracy value of 89.41%. This results also obtain recall and precision values of 89% and 87% respectively.
Online Criminal Record Monitoring System for Issuance Certificates of Good Conduct, Life, and Morals in Bukavu Lukendo David, Omari
Tech-E Vol. 7 No. 2 (2024): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v7i2.2601

Abstract

In the Democratic Republic of the Congo, the Ministry of Justice maintains criminal records for individuals with legal antecedents. However, certificates of good conduct, life, and morals are issued by local or district authorities without prior verification of the applicant's criminal record. This is due to the lack of a shared information system between the Ministry of Justice and these authorities. This paper describes the implementation of a platform that allows the Ministry of Justice to share criminal record information with local and district authorities. The system was modeled using the UP7 methodology and the Unified Modeling Language (UML). This platform ensures the reliability of the information provided on certificates of good conduct, life, and morals. Thanks to this new system, anyone with a criminal record is no longer able to hide their past by obtaining a certificate of good conduct, life, and morals that does not mention their criminal record. The results of the tests confirm that the system is user-friendly and meets the requirements of the users.
PERANCANGAN PROTOTYPE SMART HOME MENGGUNAKAN MIKROKONTROLER ESP32 BERBASIS IOT DAN TELEGRAM Yosua, Lucky; Rino
Tech-E Vol. 7 No. 2 (2024): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v7i2.2651

Abstract

Smarthome is a combination of internet of things (IoT). The use of a smarthome controlled using telegram functions to provide better comfort, provide efficiency in activities and save on electrical energy use. That way, there will be no more forgetting to turn off the AC or turning on or off the lights, watering house plants and forgetting to lock the door because by using a Smarthome device at home or in an office building, electrical equipment will be drained. able to work automatically according to user needs. Users can also control electrical devices indoors and outdoors using communication channels such as via the internet network. The aim of creating this smarthome is to provide better comfort, make it easier to control home electronic devices so that activities become more efficient. The development model used in this research is design to look for research that is similar to the tools that will be used then analysis to study things related to the research after that design to make a miniature room as clear as possible and implementation aims to examine and find out each whether each system is functioning as desired or whether an error has occurred. Based on the results of system testing, it can be concluded that the tool can work as expected.
Type 2 Diabetes Mellitus Diagnosis Model Using the C4.5 Algorithm Ruaida Susanti; Dewi Marini Umi Atmaja; Arif Rahman Hakim; Amat Basri
Tech-E Vol. 7 No. 2 (2024): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v7i2.2676

Abstract

Type 2 Diabetes Mellitus (DM) is a metabolic disorder characterized by elevated blood sugar resulting from decreased insulin secretion by pancreatic beta cells and/or impaired insulin function (insulin resistance). Over the last 50 years, there has been a rapid increase in the prevalence of diabetes, paralleling the rise in obesity rates. This study aims to develop a diagnostic model for type 2 DM using C4.5, incorporating feature selection and analyzing age and gender parameters of Type II DM patients. The research employs the Cross-Industry Standard Process for Data Mining (CRISP-DM). Based on the dataset used, the C4.5 model demonstrated superior performance compared to SVM and Random Forest, achieving an AUC value of 72.5%, indicating a reasonably good classification level. The predominant gender among Type II DM patients is female, comprising 210 patients or 54.8% in the age range of 18-94 years, while 173 male patients or 45.2% fall within the age range of 23-80 years.
PENERAPAN MACHINE LEARNING PADA DIFERENSIASI KUAH MENGANDUNG LEMAK BABI DAN LEMAK AYAM MENGGUNAKAN UV LED FLUORESCENCE IMAGING SYSTEM Widayanti; Ayazya N F, Friesca; Agung R, Frida
Tech-E Vol. 7 No. 2 (2024): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v7i2.2717

Abstract

In Indonesia, individuals have been found engaging in fraud for selling soupy dishes by adding pork fat to the broth. It is quite challenging to identify the pork fat contaminated soup from other halal broth. Using Machine learning, this studi attemps to identify and differentiating between RGB (Red Green Blue) values in picture of broth tainted with chicken and pork fat. The successful detection and differentiation of RGB values in broth contaminated with pork fat and chicken fat have been achieved. The broth samples were detected using a high-power UV-LED (Ultra Violet-Light Emitting Diode) Fluorescence Imaging System, while differentiation was accomplished through the implementation of a machine learning system. The data were processed using RapidMiner software with the K-NN algorithm. Detection was successfully performed through the spectrum of RGB values generated, while differentiation achieved a accuracy of 100%, precision of 100%, recall of 100%, and an AUC of 1.0.
Analysis of Food Ordering Information Systems and Web-Based Digital Payments for Cafes Jatmikho, Shendra; Riki
Tech-E Vol. 7 No. 2 (2024): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v7i2.2763

Abstract

Cafe is a place of business engaged in culinary. Currently, the café is a place that is quite in demand by all circles, because it can be used as a place to relax or do assignments for students. However, many cafes have difficulty in serving reservations and still use conventional systems. With a menu ordering information system and web-based digital payments applied to this café, it aims to speed up the menu ordering process, facilitate payments with digital wallets and make the ordering process more efficient. With this information system, café sales report data becomes computerized, so that data can be stored properly. The method used in this study uses data collection methods, namely by observation, interviews, and literature studies. As for system development using a methodology or prototype approach. Based on the research conducted, it produced a menu ordering information system and web-based digital payments using PHP and Mysql. And from testing the system with blackbox testing conducted by 2 testers, the system made was able to make the ordering process at the café more efficient.
Implementing and Monitoring Water Consumption Using IoT-Based Smart Dispensers Dasmen, Rahmat Novrianda; Yahya, M.
Tech-E Vol. 8 No. 1 (2024): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v8i1.2769

Abstract

Conventional dispensers have limitations in providing drinking water tailored to user preferences and do not focus on efficient resource use. This research aims to address these issues by designing and implementing a smart, efficient automatic dispenser. An experimental method was used to develop an Arduino-based prototype consisting of several components: flow sensor, color sensor, fingerprint sensor, proximity sensor, DC pump, motor driver, NodeMCU, and LCD. The flow sensor measures water volume, the color sensor detects glass color, the fingerprint sensor identifies the user, and the proximity sensor detects the presence of the glass. The DC pump flows water from the tank to the glass, relays and solenoids control the water flow, NodeMCU processes sensor data and connects to IoT, and the LCD displays the required information. A battery backup ensures functionality during power outages. The research results show that the automatic dispenser performs well and meets the research objectives. It provides drinking water according to user preferences: warm water for red glasses, cold water for blue glasses, and room temperature water for green glasses. Additionally, it identifies users through fingerprints and sends notifications via Telegram chatbots. This smart dispenser offers a more efficient and user-friendly solution compared to conventional dispensers.
Implementasi dan Perbandingan Performa Algoritma Fuzzy Tsukamoto dan Mamdani pada Sistem Exhaust Fan Berbasis IoT Nadia Putri; Lindawati; Aryanti
Tech-E Vol. 8 No. 1 (2024): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v8i1.3169

Abstract

Dalam produksi kerupuk, proses penggorengan sering menghasilkan asap dan panas berlebih yang dapat berdampak buruk pada kesehatan pekerja. Asap dapur mengandung senyawa berbahaya seperti sulfur oksida, nitrogen dioksida, dan karbon monoksida. Diperlukan kipas pembuangan untuk mengeluarkan asap dan menstabilkan suhu, namun kontrol manual kurang efektif. Sistem kontrol otomatis, termasuk mikrokontroler, set points, PID, dan logika fuzzy, telah dikembangkan. Kontrol berbasis fuzzy dianggap paling baik untuk beradaptasi dengan kondisi lingkungan. Penelitian ini mengevaluasi perbedaan antara metode fuzzy Mamdani dan fuzzy Tsukamoto dalam mengontrol kipas pembuangan. Pengujian dilakukan dengan 100 titik data selama 5 kali percobaan untuk masing-masing metode. Hasil penelitian menunjukkan bahwa metode logika fuzzy Tsukamoto mencapai akurasi lebih baik yaitu 99,35%, dibandingkan dengan logika fuzzy Mamdani yang hanya mencapai 95,45%. Oleh karena itu, sistem kontrol kipas pembuangan lebih efektif menggunakan metode logika fuzzy Tsukamoto. Metode fuzzy Tsukamoto memberikan respon yang lebih cepat dan tepat dalam menyesuaikan kecepatan kipas terhadap perubahan kondisi asap dan suhu di dapur. Hal ini dikarenakan metode Tsukamoto mampu menangani perubahan input yang lebih kompleks dan menghasilkan output yang lebih halus. Di sisi lain, metode fuzzy Mamdani memiliki kelebihan dalam hal kesederhanaan dan kemudahan implementasi, namun kurang responsif terhadap perubahan kondisi yang cepat.

Page 10 of 12 | Total Record : 116

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