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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) JURTEKSI Majalah Ilmiah UPI YPTK Journal of Computer Scine and Information Technology Jurnal Ipteks Terapan : research of applied science and education Jurnal Komtekinfo Jurnal Teknologi
Sri Rahmawati
Universitas Putra Indonesia YPTK Padang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Pengenalan Teknologi Digital untuk Media Promosi Hadi Syahputra; Sri Rahmawati; Surmayanti
Majalah Ilmiah UPI YPTK Vol. 28 (2021) No. 2
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jmi.v28i2.87

Abstract

The digital era that is all internet or the cool term IoT (Internet of things), makes it like it or not, every school must take advantage of these opportunities and challenges. Digital technology is one that has an important role in all aspects that are starting to shift in the world of digitalization. The introduction of digital technology in the school environment is the right step for schools to reach wider targets, so it is possible to get students easily. In addition, digital promotion is also very supportive in improving school branding by utilizing various social media platforms and digital marketing applications. So that the Semen Padang Vocational School will be more widely known by the wider community, both within the region and outside the region though. This student talent development training program by utilizing digital technology aims to invite students to recognize their potential so that they are able to produce works and contribute to the school and its social environment. This training program was given to 30 students consisting of several majors at SMK Semen Padang. The results of the training showed that there was an understanding of students about the importance of gaining new knowledge, especially the use of digital technology in the use of social media to promote activities in schools. With digital promotion technology, it can introduce the quality of education and the quality of school facilities so that junior high school graduates can be interested in continuing their education at SMK Semen Padang.
PENGAMANAN DATABASE MENGGUNAKAN KOMBINASI ALGORITMA (CEST CRYPTOGRAPHY) DAN ALGORiTMA BASE64 Cendra Wadisman; Irohito Nozomi; Sri Rahmawati
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 7, No 1 (2020): Desember 2020
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v7i1.896

Abstract

Abstract: Combined algorithm (Cest Cryptography) is a combination of 3 algorithms such as Merklee-Hellman, Discrete Logarithm and ASCII Modification, using Base64 to hide 2 public keys and 2 private keys. Combination algorithms are used because of the increasing number of techniques in cryptography, making it easier to combine each other algorithms in order to get more complicated encryption that won't even be cracked in the near future. On large sites there has been database theft, if the stolen database has been encrypted it will be difficult for data thieves to take advantage of it, but if it is not encrypted it is very easy to use the data so that it creates huge losses, especially user trust from the site.            Keywords: algorithm combination; ascii modification; base64; merklee-hellman; discrete logarithm  Abstrak: Kombinasi algoritma (Cest Cryptography) merupakan kombinasi 3 algoritma seperti Merklee-Hellman, Logaritma Diskrit dan Modifikasi ASCII, menggunakan Base64 untuk menyembunyikan 2 kunci public dan 2 kunci private.. Kombinasi algoritma digunakan karena semakin banyaknya teknik-teknik dalam kriptografi sehingga mempermudah untuk saling mengkombinasikan algoritma agar mendapatkan enkripsi yang lebih rumit dan bahkan tidak bisa dipecahkan dalam jangka waktu dekat. Pada situs-situs besar telah terjadi pencurian database, jika database yang dicuri telah terenkripsi maka akan mempersulit pencuri data untuk memanfaatkannya tetapi jika tidak terenkripsi maka sangat mudah data tersebut di manfaatkannya sehingga membuat kerugian yang sangat besar terutama kepercayaan pengguna dari situs tersebut. Kata kunci: kombinasi algoritma; modifikasi ascii; base64; merklee-hellman;logaritma diskrit
EAR IMAGE SEGMENTATION WITH EDGE DETECTION METHOD ON CANNY AND LAPLACE ALGORITHMS Sri Rahmawati; Wifra Safitri; Devia Kartika
Jurnal Ipteks Terapan (Research Of Applied Science And Education ) Vol. 16 No. 4 (2022): Jurnal Ipteks Terapan : research of applied science and education
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (874.49 KB) | DOI: 10.22216/jit.v16i4.1764

Abstract

Technology in identifying ear shapes is the most important step in an automatic ear shape identification system. The purpose of this paper is to introduce an approach to image segmentation, color by determining the pixel values in the database and scanning results, the similarity results are formed, the error value of each image. The method used is color segmentation based on RGB(red, green, blue) values, edge detection with the canny and laplace methods and the results of the segmentation. The results obtained are that the program that has been created can identify the shape of the ear image in the database compared to the scanning results using the segmentation method and calculate the number of image pixels between the database image and the scanned image where the minimum number of pixels for the ear shape image in the database is 452 pixels, while the total the maximum pixels is 3028 pixels. For the image of the shape of the ear the result of scanning the minimum number of pixels is 419 pixels and the maximum number of pixels is 2742 pixels. The percentage of identification results for the shape of the ear has an average similarity level: 92%, the results of this study show a very high level of accuracy. The percentage of error in identifying the shape of the ear has an average error rate of: 8%, the results of this study indicate a very low error rate. a conclusion that comparing one image with another image will get a very high level of accuracy in the canny image results are better because the edge detection is clearer and the noise is less. While image laplace is worse because there is a lot of noise
Teknologi Internet of Things (IoT) dalam Penyemprotan Insektisida Aglonema pada Greenhouse Retno Devita; Ruri Hartika Zain; Ipriadi; Ondra Eka Putra; Sri Rahmawati
Jurnal Teknologi Vol. 11 No. 2 (2021): Jurnal Teknologi
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (695.06 KB) | DOI: 10.35134/jitekin.v11i2.50

Abstract

Aglonema is a plant that is widely cultivated by ornamental plant lovers, because it has various species with varied and beautiful leaf patterns. Aglonema cultivation can be a business opportunity in agriculture because aglonema plants are in great demand but also because the prices offered vary from hundreds of thousands to millions of rupiah. Aglonema plant care is quite easy and simple. However, the wrong aglonema plant care such as irregular watering, excessive fertilizer application, and the wrong plant placement can make plants grow less optimally or even die. Greenhouse is a building that was formed to avoid and treat plants against various kinds of weather. Weather is the state of the atmosphere in a place at a certain time related to air temperature, sunlight, wind, rain and other air conditions. Thus, the types of plants that are not in accordance with the local climate, such as ornamental plants, vegetables and fruit, which have high economic value but are difficult to cultivate in outdoor areas, can be cultivated through climate control in the greenhouse. Various benefits such as controlling air temperature, adjusting humidity levels, to the interval between watering times can be adjusted easily. Internet of things (IoT) is a concept or program where an object has the ability to transmit or transmit data over a network without using the help of computer and human devices. With this IoT, spraying insecticides at the Greehouse for aglonema plants can be done automatically
Development of Signature Image Processing Using Shape and Texture Patterns Prihandoko; Rahmawati, Sri; Yuhandri, Muhammad Habib
Jurnal KomtekInfo Vol. 12 No. 1 (2025): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v12i1.635

Abstract

A signature is a sign in written form, a person's identity for whether a document is correct or not, commonly known as a Biometric system. The Biometric system is the most basic, crucial and considered a superb process for a signature in detecting a person's identification and security. Signature forgery is a fraud that often occurs, causing bigger and longer expenses. For reasons like these, a signature detection system must be able to quickly and accurately recognize genuine and dummy signatures. The purpose of this study was to present the original and dummy signature pattern recognition by grouping the original signature data. In this study, Image Segmentation was used to divide the image into several parts, the K-Means Clustering algorithm to group several parts according to the properties of each object, and Feature Extraction of Texture Patterns and Shape Patterns with Gray Level Co-Occurrence Matrix (GLCM) to obtain feature values such as Entropy, Energy, Homogeneity, Correlation, and Contrast which has resulted in a study to detect genuine and counterfeit signatures. Preliminary results show that the percentage of identification of the signature biometric system developed using Feature Extraction with signature shapes on texture patterns got an average similarity rate of: 92.74%, and signature shapes on shape patterns attained an average similarity rate of: 79.20%. Therefore, the texture extraction pattern can detect the degree of similarity between the original signature and the dummy signature with a higher percentage value compared to the shape extraction pattern. The proposed method can produce better accuracy
Expert System for Diagnosing Strawberry Plant Diseases Using the Forward Chaining Method Lavena, Deri; Rahmawati, Sri; Rahman, Sepsa Nur
Journal of Computer Scine and Information Technology Volume 11 Issue 1 (2025): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v11i1.131

Abstract

Farmers still do not really understand how to diagnose problems in plants, one example is strawberry farmers. This is proven by several farmers and strawberry plant cultivators, not all of whom can understand the disease where there are various types of diseases that can attack strawberry plants with almost the same symptoms , and if a farmer or cultivator is wrong in handling the type of strawberry plant disease, it is not impossible that it will cause the strawberry plant to die. Strawberry farmers need a tool to diagnose strawberry plant diseases so that they can find out the condition of the strawberry plants. Therefore, an expert system was created to diagnose diseases in strawberry plants and find solutions to deal with the damage that occurs. The system built for diagnosing diseases in strawberry plants uses the Forward Chaining method. Forward chaining is a forward tracking that starts from a set of facts by looking for rules that match the existing hypothesis towards a conclusion. In its implementation, this system has met these objectives by using a database and rule base. The system draws conclusions based on existing facts using the forward chaining method, the search starts from the facts from which new conclusions are obtained, the existing rules are traced one by one until the search is stopped because the last condition has been met.
Prediction of Graduation Accuracy Using the K-Means Clustering Algorithm and Classification Decision Tree Rahmawati, Sri; Defit, Sarjon
Jurnal Penelitian Pendidikan IPA Vol 10 No 4 (2024): April
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i4.7073

Abstract

Becoming a scholar at the right time for students is a very meaningful award for them if it is supported by seriousness and perseverance in their studies. Here, sample data was taken from 131 randomly taken in testing. Where there are still students who are not detected by the study program in completing their lectures, so research is carried out on clustering and classification with decision trees in determining the level of accuracy of lectures by clustering data, determining the initial centroid value and the centroid point. The results found were that there were 78 people grouped in cluster 0 and 53 people grouped in cluster 1, where those with potential for punctuality for their studies were in cluster 0 so they were students who could finish within the specified time. Meanwhile, students grouped in cluster 1 illustrate that these students need coaching and guidance both in the study program and with their supervisors. In the classification taken from the results of data clustering, two classes were obtained, namely class a and class b, with 73 and 58 data respectively, so that the results between clustering and classification did not differ too much in the data to predict the accuracy of a student's graduation.
Co-Authors Baharuddin Patandjengi Cendra Wadisman Devia Kartika Devita, Retno Hadi Syahputra Ipriadi Irohito Nozomi Lavena, Deri Prihandoko Putra, Ondra Eka Rahman, Sepsa Nur Ruri Hartika Zain Sarjon Defit Surmayanti, Surmayanti Wifra Safitri Yuhandri, Muhammad Habib