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Techno Nusa Mandiri : Journal of Computing and Information Technology

techno
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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 270 Documents

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GARMENT EMPLOYEE PRODUCTIVITY PREDICTION USING RANDOM FOREST Imanuel Balla; Sri Rahayu; Jajang Jaya Purnama
Jurnal Techno Nusa Mandiri Vol 18 No 1 (2021): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i1.2210

Clothing also means clothing is needed by humans. Besides the need for clothing in terms of function, clothing sales or business is also very potent. About 75 million people worldwide are directly involved in textiles, clothing, and footwear. In this case, a common problem in this industry is that the actual productivity of apparel employees sometimes fails to reach the productivity targets set by the authorities to meet production targets on time, resulting in huge losses. Experiments were conducted using the random forest model, linear regression, and neural network by looking for the values of the correlation coefficient, MAE, and RMSE. This aims to predict the productivity of garment employees with data mining techniques that apply machine learning and look for the minimum MAE value. The results of testing the proposed algorithm on the garment worker productivity dataset obtained the smallest MAE, namely the random forest algorithm, namely 0.0787, linear regression 0.1081, and 0.1218 neural networks

IMPLEMENTATION OF THE SCRUM MODEL IN THE DEVELOPMENT OF ONLINE SALES SYSTEMS OF MSMEs DURING THE COVID-19 PANDEMIC Wahyutama Fitri Hidayat; Annida Purnamawati; Fajar Sarasati
Jurnal Techno Nusa Mandiri Vol 18 No 1 (2021): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i1.1896

A global pandemic or epidemic indicates a covid-19 infection that is very fast spreading throughout the world, including Indonesia. This has an impact on several sectors, one of which is the economic sector. There are various things that have caused the economic sector to be touched by the impact of the covid-19 virus, including government policies at both the central and regional levels that issued several regulations relating to restrictions on community mobility. Indirectly, things related to mobility restrictions or what is currently known as Pembatasan Sosial Berskala Besar (PSBB) have an impact on consumer behavior to switch to making purchases online. To address this, the online sales system is considered to be a solution for MSMEs to continue the buying and selling process. Using the Scrum model as a more efficient system development, feedback between users and developers who can work better to create a more interactive system. The results of this study are a website that can be used by UMKM as a means of selling their business products amid the Covid-19 pandemic.

SELECTION OF THE RIGHT MARKETPLACE FOR SALE OF ORNAMENTAL PLANTS USING ANALYTICAL HIERARCHY PROCESS (AHP) METHOD Syarif Hidayat HR; Melan Susanti; Mari Rahmawati
Jurnal Techno Nusa Mandiri Vol 18 No 1 (2021): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i1.2054

Basically, each marketplace has its own market, therefore as a seller who will start an online business, especially those who use the marketplace, they must know which marketplace is right to start their online business according to what category of goods to sell. This research is needed to help business people, in this case ornamental plant traders, choose the right marketplace for their online business activities. Decision Support System (DSS) is a computer-based system used to help make decisions from structured and semi-structured problems. Analytical Hierarchy Process (AHP) is a method that can be used to select from the specified criteria. This method can simplify the criteria that are considered in making decisions for marketplace selection to be simpler and easier to understand. The results of the study show that the decisions made using the AHP method are very effective, and are expected to help make objective decisions. After processing data and analyzing respondent data, with the criteria for the number of visitors, transaction system, features, and searc engine optimization (SEO), it was found that Lazada (0.428) has the highest priority, Tokopedia (0.235) with second priority, Shopee (0.204) with priority third, and Bukalapak (0.133) with the fourth priority

APRIORI ALGORITHM FOR DETERMINING THE DEMAND LEVEL OF STATIONARY PT. MAIN GAFA INDONESIA Sri Wahyuni; Wulan Dari; Lusa Indah Prahartiwi
Jurnal Techno Nusa Mandiri Vol 18 No 1 (2021): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i1.2223

PT Gafa Utama Indonesia is one company that provides services in teaching and writing. Until now, PT Gafa Utama Indonesia already has 30 well-known branches in Jabodetabek. In the teaching and learning process, Gafa needs some stationery and teaching aids. The high demand for office stationery, and the mismatch of inventory in the warehouse, affects the fluency in the teaching and learning process. The data used in this study is the report data on the demand for office stationery for the period January-December 2018. This study uses a priori algorithm method and assessment with tanagra tools. The results of manual calculations with Microsoft Excel are the same as those using the tanagra tool. The final result shows the 2 items with the most demand, namely an eraser and a sharpener with at least 50% support, and 50% confidence. These results can be used as a reference for PT Gafa Utama Indonesia in the supply of office stationery

DIAGNOSIS DETECTION OF ACUTE RESPIRATOR INFECTION WITH FORWARD CHAINING METHOD Tri Wisnu Pamungkas; Resi Taufan; Petrus Damianus Batlayeri; Gabriel Vangeran Saragih; Tri Retnasari
Jurnal Techno Nusa Mandiri Vol 18 No 1 (2021): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i1.2225

Many acute respiratory infections or ARI are caused by viruses that attack the nose, trachea (breathing tube), or the lungs. It can be said that ARI is caused by inflammation that disrupts a person's breathing process. If not treated quickly, ARI can spread to all respiratory systems and prevent the body from getting proper oxygen, moreover it can cause the loss of a person's life. This research aims to diagnose ARI as an early step in practicing artificial intelligence in medicine, designing and apply an expert system that can diagnose ARI. The procedure used in this study uses forward chaining with tracking that begins with input data, and then creates a diagnosis or solution. The expert system used to diagnose acute respiratory inflammation uses the Forward chaining procedure with a data-driven approach, in this approach tracking starts from input data, and then seeks to draw conclusions, so that it can be used. diagnose the type of disease associated with the ARD disease experienced by showing the existing signs.

K-MEANS SEGMENTATION AND CLASSIFICATION OF SWIETENIA MAHAGONI WOOD DEFECTS Sri Rahayu; Dwiza Riana; Anton Anton
Jurnal Techno Nusa Mandiri Vol 18 No 2 (2021): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i2.2222

The potential and usefulness of wood to meet the needs of human life are not in doubt. Demands us to continue to maintain the quality. Wood quality is closely related to wood defects. Manual defect checks in the wood industry are unreliable because they are prone to human error, For example, due to acute symptoms of headaches and tired eyes, technology in the form of image processing can help identify wood defects Swietenia Mahagoni. In this case, the method used is Euclidean distance with a ratio of k-means segmentation and thresholding on 42 images of wood defects consisting of 3 types of defects, namely growing skin defects, rotting knots, and healthy knots, every 14 images with data sharing. training for 30 images and testing for 12 images. The results of the k-means segmentation are then extracted on 6 features including metric, eccentricity, contrast, correlation, energy, and homogeneity using the Gray Level Co-occurrence Matrix (GLCM) extractor and classified by calculating the closest distance using the euclidean distance between the results of data feature extraction. testing of the value of feature extraction in the training data which is used as a previous database. It is the smallest value that indicates the type of defect. The success calculation is presented in the confusion matrix calculation and gets a success or accuracy value of 91.67%.

ANALYSIS OF DEPRESSION IN COLLEGE STUDENT DURING COVID-19 PANDEMIC USING EXTREAM GRADIENT BOOST Agung Prabowo; Dharma Ajie Nur Rois; Amar Luthfi; Ultach Enri
Jurnal Techno Nusa Mandiri Vol 18 No 2 (2021): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i2.2399

The Covid-19 pandemic that spreads in Indonesia causes health, economic, and social problems in the community, including mental health. Of course, this mental health problem also hit students. Seeing these conditions, we conducted research on students of the Faculty of Computer Science, University of Singaperbangsa Karawang using the Patient Health Questionnaire-9 which measures a person's level of depression. In this study, we used Extreme Gradient Boost or XGBoost to classify students' depression tendencies. We break down the dataset into training data and testing data with 4 data sharing combinations, they are 80 : 20, 50 : 50, 90 : 10, 70 : 30. The combination of 90 : 10 data sharing has the best performance with accuracy, precision, recall, and F1-scores respectively 92.86%, 94.29%, 92.86% , and 92.06%. This method also has better performance than K-Nearest Neighbor, Random Forest, Multi Layer Perception, Support Vector Machine and Decision Tree .

COMPARISON OF ACCURACY MEASUREMENTS IN MOTION SENSORS AND HEART RATE MEASUREMENTS USING ANALYTICAL HIERARCHY PROCESS METHODS Tomi Lifti Novier; Nurmalasari Nurmalasari; Widi Astuti; Siti Masturoh; M. Rangga Ramadhan Saelan
Jurnal Techno Nusa Mandiri Vol 18 No 2 (2021): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i2.2547

The use of motion sensors in measuring heart rate using smartwatch applications is currently a trend. Everyone is very helpful for measuring their own heart rate. This research is about the comparison of accuracy in motion sensors and measuring heart rate using the Analytical Hierarchy Process (AHP) method. Every technology and application in motion sensor measurement in heart rate measurement has almost the same features and uses as Xiaomi, Samsung, and Apple Inc. From the calculations carried out by the researcher, it shows that the field/stadium that is the most chosen by the community (respondents) is by Random Sampling, with the acquisition of a value of 0.490 aka 49.00%. The second is Treadmill with a value of 0.294 aka 29.40%. the overall value is 0.216 aka 21.60% The alternative that is most chosen by the community (respondents) is the field/stadium. The Analytical Hierarchy Process method can make it easier for prospective technology users to be able to measure the accuracy of motion sensors and detect heart rates, the AHP method makes product decisions based on criteria and alternatives contained in the hierarchy, the results of the study are Apple Inc. as the respondent's choice for technology that is trusted to measure better accuracy on the motion sensor and measure heart rate.

APPLICATION OF CALCULATION METHODS MULTI ATRIBUTTE UTILITY THEORY (MAUT) IN SELECTION OF YARN SUPPLIER Susliansyah Susliansyah; Yahdi Kusnadi; Heny Sumarno; Hendro Priyono; Linda Maulida
Jurnal Techno Nusa Mandiri Vol 18 No 2 (2021): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i2.2706

The main objective of the yarn supplier selection process is to determine suppliers who have efficiency in meeting the company's needs consistently and minimize risks related to the procurement of yarn and components needed. In solving problems in supplier selection using the Multi Attribute Utility Theory (MAUT) method which consists of calculating matrix normalization and attribute normalization. The results obtained in this study are to find out the best supplier from other suppliers, namely GSM suppliers with a value of 0.87.

COMPARATION OF CLASSIFICATION ALGORITHM ON SENTIMENT ANALYSIS OF ONLINE LEARNING REVIEWS AND DISTANCE EDUCATION Lila Dini Utami; Siti Masripah
Jurnal Techno Nusa Mandiri Vol 18 No 2 (2021): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i2.2715

As of January 27, 2021, confirmed cases of COVID-19 nationally stood at 1,024,298 people, this data is data that has been officially announced by the Indonesian Ministry of Health. Meanwhile, in Jakarta, there are 256,416 confirmed cases of COVID-19. In July 2021, there was a very significant increase, seeing the data caused the Central government to make a decision to continue the Large-Scale Social Restrictions (PSBB), followed by the Enforcement of Restrictions on Community Activities (PPKM), which affected all aspects, especially the education aspect. In the education aspect, the government applies distance and online learning. Of course, many people agree or disagree with this decision, because there must be sacrifices, both in terms of time and cost. Seeing these conditions makes the authors interested in discussing and processing public opinions on distance and online learning systems which certainly have positive and negative responses from learning implementers, to process the data the author uses Data Mining, namely using the Text Mining Classification method with several The classification algorithms are the Naïve Bayes Algorithm (NB), the k-Nearest Neighbor (k-NN) Algorithm and the Support Vector Machine (SVM) Algorithm to see which classification algorithm has the highest accuracy and diagnostic value in processing this opinion. After the calculations are done, the algorithm that is more suitable for analyzing reviews or opinions in this study is to use the Support Vector Machine (SVM) classification algorithm with the highest accuracy value of 87.67% and an AUC value of 0.939 with an Excellent Classification diagnostic level.

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