Analysis of Food Ordering Information Systems and Web-Based Digital Payments for Cafes

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

PENERAPAN MACHINE LEARNING PADA DIFERENSIASI KUAH MENGANDUNG LEMAK BABI DAN LEMAK AYAM MENGGUNAKAN UV LED FLUORESCENCE IMAGING SYSTEM

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.Telah berhasil dilakukan deteksi dan differensiasi nilai RGB pada kuah terkontaminasi minyak babi dan kuah mengandung minyak ayam. Sampel kuah dideteksi menggunakan alat high power UV-LED Fluorescence imaging sedangkan differensiasi dilakukan melalui penerapan  machine learning system. . Data diolah menggunakan software RapidMiner dengan algoritma KNN. Deteksi berhasil dilakukan melalui spektrum nilai RGB yang dihasilkan, sedangkan diferensiasi berhasil dilakukan dengan nilai akurasi 100 %, presisi 100 %, recall 100% serta AUC 1.0

Online Criminal Record Monitoring System for Issuance Certificates of Good Conduct, Life, and Morals in Bukavu

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

Type 2 Diabetes Mellitus Diagnosis Model Using the C4.5 Algorithm

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

PERANCANGAN PROTOTYPE SMART HOME MENGGUNAKAN MIKROKONTROLER ESP32 BERBASIS IOT DAN TELEGRAM

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.Smarthome adalah kombinasi internet of things (IoT). Penggunaan smarthome yang dikontrol menggunakan telegram berfungsi memberikan kenyamanan yang lebih baik, memberikan efisiensi dalam beraktivitas dan menghemat penggunaan energi listrik. Dengan begitu, tidak akan ada lagi kelupaan mematikan AC atau menyalakan atau mematikan lampu, menyiram tanaman rumah dan lupa mengunci pintu karena dengan menggunakan perangkat Smarthome di rumah atau di gedung perkantoran, peralatan listrik akan terkuras habis. . mampu bekerja secara otomatis sesuai kebutuhan pengguna. Pengguna juga dapat mengontrol perangkat listrik di dalam maupun di luar ruangan menggunakan saluran komunikasi seperti melalui jaringan internet. Tujuan diciptakannya smarthome ini adalah untuk memberikan kenyamanan yang lebih baik, memudahkan dalam mengontrol perangkat elektronik rumah sehingga aktivitas menjadi lebih efisien. Model pengembangan yang digunakan dalam penelitian ini adalah desain untuk mencari penelitian yang serupa dengan alat yang akan digunakan kemudian analisis untuk mempelajari hal-hal yang berhubungan dengan penelitian setelah itu desain untuk membuat miniatur ruangan sejelas mungkin dan implementasi bertujuan untuk mengkaji dan mengetahui masing-masing apakah setiap sistem berfungsi sesuai yang diinginkan atau telah terjadi kesalahan. Berdasarkan hasil pengujian sistem dapat disimpulkan bahwa alat dapat bekerja sesuai dengan yang diharapkan

Clustering Analysis of Admission of New Students Using K-Means Clustering and K-Medoids Algorithms to Increase Campus Marketing Potential

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 -0.877Penerimaan siswa baru merupakan kegiatan yang sangat penting bagi sebuah sekolah menengah atau universitas. Data penerimaan belum dimanfaatkan kampus dalam pengambilan keputusan strategis, potensi pemasaran, dan pertimbangan undangan melalui jalur penerimaan akademik. Maka, untuk membantu dalam pengolahan data penerimaan siswa baru, pada penelitian ini dilakukan perancangan dan analisis data penerimaan siswa baru dengan menggunakan tahapan dalam data mining. Pendekatan metode clustering dapat diterapkan dalam menganalisis potensi tingkat kualitas PMB yang dihasilkan dengan memanfaatkan dataset rekaman PMB periode 2023. 86 rekaman data. Model algoritma K-Means dan K-Medoids yang diterapkan memiliki hasil yang menunjukkan wawasan baru yaitu pengelompokan berdasarkan 2 cluster, cluster 1 (C0) merupakan kategori lolos sedangkan cluster 2 (C1) belum ditentukan. Hasil algoritma K-Medoids yang cluster 1 (C0) hasil 60, cluster 2 (C1) 26 hasil merupakan potensi lolos 60 dan belum ditentukan 26 data yang diuji 86 sedangkan hasil K -Berarti algoritma cluster 1 (C0) 40 , cluster 2 ( C1 ) 46 merupakan pass potensial yang terdiri dari 40 dan 46 data yang belum ditentukan dari 86 dataset yang diuji. Pengujian menggunakan aplikasi RapidMiner Studio juga dapat menghasilkan insight serupa yaitu setiap cluster memiliki hasil Davies Bouldin Index atau DBI dari masing-masing algoritma K-Means dan K-Medoids. K-Means memiliki hasil Davies Bouldin Index sebesar -0,533 sedangkan K-Medoids memiliki hasil Davies Bouldin Index sebesar -0,87

The IOT-Based Hydrogen Sulfide Monitoring at PT. Pertamina Geothermal Energy on Lumut Balai Area

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.Pembangkit Listrik Tenaga Panas Bumi menghasilkan energi listrik yang bersumber dari panas bumi yang terdapat pada sumur geothermal. Di dalam sumur geothermal terdapat kandungan H2S yang merupakan gas beracun yang dapat menyebabkan kematian kepada manusia apabila terkena paparan konsentrasi H2S 500-700 ppm dalam waktu 30-60 menit. Berdasarkan beberapa literasi, pada penelitian ini digunakan sensor H2S type MQ-136 untuk memonitor kadar H2S yang ada di lingkungan Geothermal. Untuk parameter pembacaan data sensor MQ-136 digunakan sistem Internet of Things sebagai alat untuk menampilkan nilai PPM pada LCD di transmitter dan receiver, serta pada website Adafruit IO. Untuk Menyalurkan data dari transmitter ke receiver digunakan Lora Ra-01 AI Thinker. Fokus penelitian ini adalah dapat melakukan monitoring kandungan H2S di lokal dari jarak jauh melalui website Adafruit IO, untuk data tertinggi yang terbaca yaitu 0,54 ppm dan yang terendah di 0 ppm. Selain itu juga alat akan memberikan sinyal “BHY” pada tampilan LCD di transmitter serta dari website Adafruit IO akan mengirimkan notifikasi “bahaya ppm H2S tinggi” pada handphone yang telah teinstal aplikasi IFFT apabila konsentrasi H2S yang terbaca sebesar 10 ppm atau lebih, sehingga pekerja terhindar terpapar H2S dalam kadar yang tinggi ketika hendak memonitor parameter di area sumur Geothermal

Air Quality Monitoring System And Air Neutralizer In Hotel Rooms With Notification Via Telegram

Indonesia is rich in natural beauty, and in various regions it presents many tourist objects that attract visitors from various regions and foreign countries. Hotels, as a form of public accommodation, are extremely beneficial to tourists who are traveling by providing lodging services in the form of hotel rooms. The article aims to design a carbon dioxide (CO2) gas detector because CO2 gas is included in air quality and uses the MQ 135 sensor to detect gas in order to provide comfort to hotel visitors. carbon dioxide (CO2), DC fans as air neutralizers in hotel rooms, and with notifications via telegram to find out the levels of carbon dioxide (CO2) gas in hotel rooms

Analisis sentiment komentar Instagram bakal calon presiden menggunakan metode Support Vector Machine

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

Application Integration for Sustainability Smart Tourism Model in Indonesia

The existence of the COVID-19 pandemic over the past few years has made the tourism world slump, and Indonesia is no exception. However, this creates a potential use of IT not only for managing tourism activities but also for managing risks and conflicts that arise due to pandemics or others. The existence of various integrated managements on the economic, socio-cultural, and ecological dimensions can create tourism sustainability that is supported by technological advances. The purpose of this study is to provide a comprehensive and integrated model of sustainable tourism activities supported by the use of IS/IT infrastructure. The methods used in the formation of this model are Interpretative Structural Modeling (ISM) and smart thinking. From ISM, four key components are produced, namely innovation, local wisdom, local residents resources, and revitalization of tourist destinations due to disasters. The results of this study are in the form of a smart tourism sustainability model in Indonesia which is supported by an integrated application derived from the four key component