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Techno Nusa Mandiri : Journal of Computing and Information Technology
Published by Universitas Nusa Mandiri
ISSN : 19782136     EISSN : 2527676X     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal TECHNO Nusa Mandiri, merupakan Jurnal yang diterbitkan oleh Pusat Penelitian Pengabdian Masyarakat (PPPM) STMIK Nusa Mandiri Jakarta. Jurnal TECHNO Nusa Mandiri, berawal diperuntukan menampung paper-paper ilmiah yang dibuat oleh dosen-dosen program studi Teknik Informatika.
Arjuna Subject : -
Articles 223 Documents
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IMPLEMENTATION OF THE RIJNDAEL ALGORITHM ON WEB-BASED WHISTLEBLOWING SYSTEM Abdul Latif; Ai Ilah Warnilah; Siti Khotimatul Wildah
Techno Nusa Mandiri Vol 19 No 2 (2022): TECHNO Period of September 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i2.3861

Abstract

In carrying out its responsibilities, an employee works for an agency or company and also works with his colleagues, whether they are co-workers or their own superiors. So it is very important for an employee to gain trust in his work environment. If there is a violation or behavior that deviates from an employee in the work environment, then there must be someone who reports it but of course by protecting the identity of the reporter. Based on these problems, the authors make and design a web-based whistle blowing application to protect the identity of people who report violations that occur in their work environment. This whistle blowing web is created using cryptographic algorithm methods. Cryptographic algorithms work by disguising data or information into a form of password that has no meaning. The author uses the Rijndael algorithm to encrypt the complainant's data. So that by using the Rijndael algorithm on this web-based Whistleblowing system, the data or reporting information will be safe in the database and it is hoped that an optimal system will be created for data and information security
MEAT IMAGE CLASSIFICATION USING DEEP LEARNING WITH RESNET152V2 ARCHITECTURE Taopik Hidayat; Daniati Uki Eka Saputri; Faruq Aziz
Jurnal Techno Nusa Mandiri Vol 19 No 2 (2022): TECHNO Period of September 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i2.3932

Abstract

Meat is a food ingredient that can be consumed by humans and consists of essential nutrients, especially protein, which are needed for various physiological functions in the human body. Beef, goat and pork are meats that are commonly used by Indonesian people as daily processed foods. A very high level of meat consumption results in a high economic value of meat consumption. However, many people do not know how to distinguish between the types of beef, mutton and pork. This study aims to classify types of beef, goat and pork using the ResNet152V2 algorithm. The data used are 600 images with 200 images of beef, 200 images of mutton and 200 images of pork. The process carried out is pre-processing using 4 stages, namely image augmentation, image sharpness process, then the image is resized to adjust the size needed by the algorithm. The last pre-processing is to perform the image normalization process. After the pre-processing is done, then the data training stage is carried out using the ResNet152V2 algorithm to build a classification model and then the model is tested against data testing to get the results of the optimal classification of pork, goat and beef images by looking at the results of accuracy and loss values.
A PROTOTYPE OF DIGITAL LIBRARY APPLICATION USING MICROFRAMEWORK FLASK Ridha Sefina Samosir; Ester Lumba; Poltak Pancarian Situmorang
Techno Nusa Mandiri Vol 19 No 2 (2022): TECHNO Period of September 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i2.3006

Abstract

Covid-19 encourages the use of Digital Library sources. especially for students who are completing college assignments, students who are preparing their final project, lecturer in compling teaching material, including researchers. On the other hand, technology has developed rapidly. Technological developments have changed the pattern of human life and changed the business models of various organizations in order to survive in this digital era. However, there are still many organizations have not optimized the use of technology. One example is a university that does not yet have a Digital Library. This prompted the research team to conduct research on how to build a Digital Library. This study uses the Extreme programming (XP) software development method. This study aims to design a Digital Library prototype using a Microframework Flask. This research is expected to be a reference or model in developing digital libraries.
E-LEARNING IMPLEMENTATION BARRIER IN INDONESIA: A CASE STUDY Deki Satria; Neneng Rachmalia Feta; Fitria Fitria
Techno Nusa Mandiri Vol 19 No 2 (2022): TECHNO Period of September 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i2.3034

Abstract

Abstract—Pandemic forces many educational institutions to change their learning delivery. One of the solutions is using eLearning. But, eLearning implementation faces a lot of barriers. This study tried to find the main barrier in eLearning in Indonesia. Systematic Literature Review and Descriptive statistics were used to collect and analyze our findings. The results of this study are separated into four categories: human, technology, organizational, and financial factors. Human factors include lack of interaction, hard to assimilate material, boredom, exhaustion, lack of preparation, and harder to meet the need. Technological factors include lack of technical advice, device, the internet, and power problems. The organizational factor is a lack of technical support. From the financial factors are expensive internet and device. These obstacles need to be addressed separately because each barrier has a different approach to solve. Keywords: Barriers, Covid-19, eLearning, SLR, Statistic Descriptive Intisari— Pandemi covid-19 memaksa banyak sekali institusi Pendidikan untuk mengubah pola pengajaran yang dilakukan. Salah satu cara yang paling banyak diterapkan adalah pembelajaran dalam jaringan (daring). Namun dalam pengimplementasia pembelajaran daring ini, ditemukan banyak kendala atau penghalang. Penelitian ini berusaha untuk menemukan kendala implementasi pembelajaran daring di Indonesia. Untuk menemukan penghalang tersebut digunakan systematic literature review (SLR) dan deskriptif statistic. Dari hasil penelitian yang dilakukan didapatkan empat kategori penghambat yaitu Manusia, teknologi, organisasi dan keuangan. Dari hasil penelitian tersebut didapatkan hasil hambatan manusia yaitu kurangnya interaksi, sulitnya memahami materi, kebosanan, kelelahan, kurang persiapan dan sulitnya memenuhi keinginan siswa. Dari faktor teknologi ditemukan kendala yaitu kurangnya perangkat, sering kali adanya kendala teknis, internet dan mati lampu. Dari faktor organisasi adalah kurangnya dukungan teknis dari organisasi. Sedangkan dari faktor keuangan adalah mahalnya perangkat dan internet yang dibutuhkan. Masing-masing faktor ini harus diselesaikan secara individu dikarenakan setiap faktor memiliki penyelesain yang unik Kata Kunci: Covid-19, eLearning, Penghambat Implementasi, Statistik Deskriptif, SLR.
CLASSIFICATION OF STUNTING STATUS IN TODDLERS USING NAIVE BAYES METHOD IN THE CITY OF MADIUN BASED ON WEBSITE Abdul Rozaq; Ari Joko Purnomo
Techno Nusa Mandiri Vol 19 No 2 (2022): TECHNO Period of September 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i2.3337

Abstract

Stunting pada balita merupakan masalah gizi kronis yang sedang dialami dunia kesehatan. Anak dengan kondisi stunting mengalami kecenderungan penurunan tingkat kecerdasan, gangguan berbicara dan kesulitan dalam menangkap pembelajaran dalam metode yang biasa. Kota Madiun masih menghadapi tantangan dalam permasalahan gizi stunting. Prevalensi angka stunting tahun 2020 sebesar 10,18 persen atau 814 anak dari total 7.996 yang diukur. Penggunaan data mining dapat digunakan dalam berbagai bidang yang berhubungan dengan sekumpulan data yang banyak. Terdapat beberapa teknik pengerjaan data mining dalam pengambilan suatu informasi, diantaranya adalah klasifikasi. Umumnya klasifikasi status stunting menggunakan indeks TB/U atau tinggi badan dibanding usia. Pada penelitian ini, metode yang digunakan adalah metode naive bayes, yakni metode yang digunakan untuk memprediksi berbasis probabilitas, sistem yang dibangun menggunakan bahasa pemrograman python dan flask sebagai framework-nya. Dari hasil pengujian yang dilakukan menunjukkan bahwa metode naive bayes dapat digunakan dalam melakukan klasifikasi terhadap status stunting pada balita. Algoritma Naïve Bayes yang diimplementasikan ini, memiliki performansi nilai rata-rata yaitu akurasi sebesar 58%, precision sebesar 68%, dan recall sebesar 58% dari hasil pengujian confusion matrix dengan 30% data testing dan 70% data training.
SATISFACTION ANALYSIS OF RESPONSIVE WEB DESIGN (RWD) USING PIECES METHOD IN YOBAGI: TECHNOLOGY PLATFORM BASED ON SOCIALPRENEURSHIP Dwi Yuny Sylfania; Rendy Rian Chrisna Putra; Fransiskus Panca Juniawan
Techno Nusa Mandiri Vol 19 No 2 (2022): TECHNO Period of September 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i2.3435

Abstract

The Covid-19 pandemic has had a huge impact on society. There have been layoffs for some people, which will have an impact on their economy, which is getting worse. Another impact was felt by MSMEs where their transactions also decreased. Yobagi is proposed to overcome this problem by becoming a social entrepreneurship-based media platform that becomes an intermediary media for anyone who has the desire to share their skills, knowledge, and experiences. Yobagi is also a marketplace for MSMEs to promote their products or services. The purpose of this research is for people to improve their skills, be able to innovate, so they can run new businesses to improve their economy. Likewise, MSMEs have increased their transactions. The research uses the prototype method which consists of five stages, namely Communication, Quick Plan, Modeling Quick Plan, Construction of Prototype, and Deployment. The result of the research is a web-based Yobagi application that functions well, as evidenced by functional testing using the Blackbox method. Furthermore, the Responsive Web Design feature on the Yobagi system was also tested to test the performance of the features on several different types of smartphones.
SENTIMENT ANALYSIS FOR PHARMACEUTICAL COMPANY FROM SOCIAL MEDIA USING ADAPTIVE COMPRESSION (ADACOMP) WITH RANDOM UNDER SAMPLE (RUS) AND SYNTHETIC MINORITY OVER-SAMPLING (SMOTE) Pamungkas Setyo Wibowo; Andry Chowanda
Techno Nusa Mandiri Vol 19 No 2 (2022): TECHNO Period of September 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i2.3441

Abstract

Pharmaceutical company has become the most highlight company across the world lately because of the pandemic. Despite of the high demand market in pharmaceutical company, about 94% of large company across the world having difficulty in their supply chain that indirectly affect their services. The purpose of this research is to compare word embedding with compression model by doing sentiment analysis about the entity to find the best model that give better accuracy rates based on the opinion of Twitter, Instagram and Youtube, as they are the largest platform that its many users to express their opinions about an individual or an instance. Data is retrieved from Twitter, Instagram and Youtube using the R-Studio application by utilizing their API library, then preprocessing and stored in a database. Next step is labeling the data and then train the data using word2Vec and LSTM, GloVe and LSTM and lastly using Adaptive Compression (adaComp) to compress the both model word embedding. Unfortunately, we got imbalanced dataset after labeling process, so we add sampling technique to sampling the dataset using Random Under Sample (RUS) and Synthetic Minority Over-sampling Technique (SMOTE). After the data are trained and tested, the results will be evaluated using Confusion Matrix to get the best Accuracy. With several models that have been carried out,applying adaComp is proven to increase accuracy. In the Word2Vec word embedding with LSTM model, applying adaComp increasing its accuracy from 77% to 81%.
COMPARISON OF EIGENFACE AND FISHERFACE METHODS FOR FACE RECOGNITION Elly Firasari; F Lia Dwi Cahyanti; Fajar Sarasati; Widiastuti Widiastuti
Techno Nusa Mandiri Vol 19 No 2 (2022): TECHNO Period of September 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i2.3470

Abstract

Abstract— Biometric information systems have been widely used in the fields of government, shopping centers, education and even security, which offer biological authentication so that the system can recognize its users more quickly. The parts of the human body are identified by a biometric system that has unique and specific characteristics, one of which is the face. Adjustment of facial image deals with objects that are never the same, due to the parts that can change. These changes are caused by facial expressions, light intensity, shooting angle, or changes in facial accessories. With this, the same object with several differences must be recognized as the same object. In this study, the data used were 388 face images and the sata test consisted of 30 face images. Before the face is tested, preprocessing and feature extraction are carried out using the Haar Cascade Classifier and then detected using Eigenface and Fisherface. Based on the research results, the Fisherface method is an algorithm that is accurate and efficient compared to the Eigenface algorithm. The Fisherface algorithm has an accuracy of 88%. while the Eigenface method has an accuracy rate of 76%. Keywords – Haar Cascade Classifier, Eigenface, Fisherface,.
IMPLEMENTATION OF THE WEIGHT PRODUCT METHOD IN THE SYSTEM NEW STUDENT ADMISSION Siti Nurhasanah Nugraha; Rangga Pebrianto; Fani Nurona Cahya; Irwan Herliawan
Techno Nusa Mandiri Vol 19 No 2 (2022): TECHNO Period of September 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i2.3678

Abstract

The development of information technology is something that cannot be separated from life today. The development of information technology, especially the internet, is certainly welcomed by all circles, and has even penetrated the world of education since the last few years, thus creating competitive competition in every educational institution. Currently, there are not many schools in Indonesia that hold new student admissions (PPDB) by utilizing the online system. Of course, this will take a very long time, because after selecting the prospective students, the committee must recap the names and grades of the students accepted. We need a system that will support decisions in the selection of new student admissions so that the resulting output is more accurate. To solve this problem, it is necessary to have a decision support system for the selection process for new admissions using the Weight method Products . With this method the PPDB selection calculation will be more objective because the calculation is based on predetermined weights and assessment criteria. So that the creation of an optimal system that will facilitate the PPDB selection process.
RECOGNITION OF REALTIME BASED PRIMITIVE GEOMETRY OBJECTS USING PERCEPTRON NETWORK Cut Lika Mestika Sandy; Taufik Ismail Simanjuntak; Ajulio Padly Sembiring; Reyhan Achmad Rizal; Ona Rizal Fahmi
Techno Nusa Mandiri Vol 20 No 1 (2023): TECHNO Period of March 2023
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v20i1.4104

Abstract

The purpose of this study is to analyze the perceptron model on pattern recognition of primitive geometric objects in real time based on video images. The samples used in this study were cubes, prisms, tubes and balls. The system was built using the Delphi 7 programming language with pre-processing stages system training includes the process of calculating matrix values from the original image, then proceed with the grayscale and edge detection processes using convolution with a kernel, namely the sobel operator and then the matrix results from the edge detection process are transformed using a perceptron network to obtain energy from the image of the object, then the resulting energy The transformation is stored in the database as a system test reference pattern recognition energy. Measurement of system performance evaluation in this study uses two parameters, namely detection rate and false positive rate. The recognition rate of primitive geometric objects using the perceptron network model in this study reaches 60.00% to 80.00%. The detection rate percentage shows that this model can be used as a supporting approach for the recognition of geometric objects in video.

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