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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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IMPLEMENTATION OF K-NEAREST NEIGHBOR AND GINI INDEX METHOD IN CLASSIFICATION OF STUDENT PERFORMANCE Tyas Setiyorini; Rizky Tri Asmono
Jurnal Techno Nusa Mandiri Vol 16 No 2 (2019): Techno Nusa Mandiri : Journal of Computing and Information Technology Periode Se
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Predicting student academic performance is one of the important applications in data mining in education. However, existing work is not enough to identify which factors will affect student performance. Information on academic values or progress on student learning is not enough to be a factor in predicting student performance and helps students and educators to make improvements in learning and teaching. K-Nearest Neighbor is a simple method for classifying student performance, but K-Nearest Neighbor has problems in terms of high feature dimensions. To solve this problem, we need a method of selecting the Gini Index feature in reducing the high feature dimensions. Several experiments were conducted to obtain an optimal architecture and produce accurate classifications. The results of 10 experiments with values of k (1 to 10) in the student performance dataset with the K-Nearest Neighbor method showed the highest average accuracy of 74.068 while the K-Nearest Neighbor and Gini Index methods showed the highest average accuracy of 76.516. From the results of these tests it can be concluded that the Gini Index is able to overcome the problem of high feature dimensions in K-Nearest Neighbor, so the application of the K-Nearest Neighbor and Gini Index can improve the accuracy of student performance classification better than using the K-Nearest Neighbor method.

IMPLEMENTATION OF DECISION SUPPORT SYSTEM FOR SELECTION OF DEPARTMENTS WITH VIKOR METHOD IN SMK PARIWISATA DEPOK Muhammad Nur; Susliansyah Susliansyah
Jurnal Techno Nusa Mandiri Vol 16 No 2 (2019): Techno Nusa Mandiri : Journal of Computing and Information Technology Periode Se
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

The choice of majors is very important for vocational high school students. There are several factors that influence the decision making of majors. Therefore the writing of this thesis has the purpose of, among others, helping vocational high schools to be able to choose majors in accordance with the wishes and abilities of students. The purpose of writing this thesis is one of the graduation requirements for the Strata Satu (S1) program for the Nusa Mandiri Jakarta (STMIK) program. To achieve the objectives in this study, the authors used quantitative analysis methods. Quantitative analysis in this research is to process the normalization of each criterion value from each alternative that can produce a value and rank in seeing the best majors for students by using the Vise Kriterijumska Optimizacija I Kompromisno Resenje (Vikor) method. Method of Vise Kriterijumska Optimizacija I Kompromisno Resenje (Vikor) helps solve complex problems by determining from the criteria, final score results in vikor and by drawing various considerations to develop weights or priorities.

ANDROID-BASED MOSQUITO LARVA RECORDING SYSTEM DESIGN USING CERTAINTY FACTOR METHOD FOR DBD ENDEMIC CONTROL Sukmawati Anggraeni Putri; Sita Anggraeni
Jurnal Techno Nusa Mandiri Vol 16 No 2 (2019): Techno Nusa Mandiri : Journal of Computing and Information Technology Periode Se
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Dengue Fever (DHF) or Demam Berdarah (DBD) is an endemic disease in Indonesia. In 2015, there were 126,675 dengue cases occurred in Indonesia. This extraordinary event of DHF can be avoided if the early alert system is carried out well, such as counseling about dengue fever, periodic eradication of mosquito nests or pemberantasan sarang nyamuk (PSN) by the community, administration of abate drugs in water reservoirs and fogging (Fogging). The success of an early alert system can be measured by the larva free rate (ABJ). The use of the certainty factor method in determining the certainty presentation of ABJ and the endemic DHF early alert system, due to the certainty factor method shows good accuracy results of a certainty level of up to 92%. So that when applied to the larva note system (SICANTIK) mobile application. it is expected to be able to predict accurate and fast ABJ and early alert systems. So that through the larva note system (SICANTIK) mobile application, health workers can quickly find out the value of ABJ in a residential area of citizens. Based on this, health workers can take quick action by fogging in areas with low ABJ values. Where the act of fumigation is an act of controlling dengue outbreaks

COMPARISON OF NAIVE BAYES ALGORITHM AND C.45 ALGORITHM IN CLASSIFICATION OF POOR COMMUNITIES RECEIVING NON CASH FOOD ASSISTANCE IN WANASARI VILLAGE KARAWANG REGENCY Yuris Alkhalifi; Ainun Zumarniansyah; Rian Ardianto; Nila Hardi; Annisa Elfina Augustia
Jurnal Techno Nusa Mandiri Vol 17 No 1 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Non-Cash Food Assistance or Bantuan Pangan Non-Tunai (BPNT) is food assistance from the government given to the Beneficiary Family (KPM) every month through an electronic account mechanism that is used only to buy food at the Electronic Shop Mutual Assistance Joint Business Group Hope Family Program (e-Warong KUBE PKH ) or food traders working with Bank Himbara. In its distribution, BPNT still has problems that occur that are experienced by the village apparatus especially the apparatus of Desa Wanasari on making decisions, which ones are worthy of receiving (poor) and not worthy of receiving (not poor). So one way that helps in making decisions can be done through the concept of data mining. In this study, a comparison of 2 algorithms will be carried out namely Naive Bayes Classifier and Decision Tree C.45. The total sample used is as much as 200 head of household data which will then be divided into 2 parts into validation techniques is 90% training data and 10% test data of the total sample used then the proposed model is made in the RapidMiner application and then evaluated using the Confusion Matrix table to find out the highest level of accuracy from 2 of these methods. The results in this classification indicate that the level of accuracy in the Naive Bayes Classifier method is 98.89% and the accuracy level in the Decision Tree C.45 method is 95.00%. Then the conclusion that in this study the algorithm with the highest level of accuracy is the Naive Bayes Classifier algorithm method with a difference in the accuracy rate of 3.89%.

THINNING STENTIFORD ALGORITHM FOR KINTAMANI INSCRIPTION IMAGE SEGMENTATION Christina Purnama Yanti; I Gede Andika
Jurnal Techno Nusa Mandiri Vol 17 No 1 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

In the copper, inscription contained writing strokes that have high historical value. Age and environmental factors cause damage to the inscription surface and also reduce the appearance of images and letters. One way to preserve it is to carry out the process of converting it into digital format. The use of the morphological operation method is very suitable to be used to improve the shape of the letters in the copper inscription. The morphological operations performed in this study were the Thinning Stentiford algorithm. Based on research that has been done, it was concluded that the Thinning Stentiford algorithm has succeeded in segmenting the letters that exist in the Kintamani copper inscription. However, there are some letters are not well segmented. This is due to the inscription background color and carved letter colors that don't have significant differences. Testing the time it was concluded that the greater the size of the image and the more letters will be segmented, the longer the processing computing.

DECISION SUPPORT SYSTEM FOR SELECTION OF CHAIRMAN OF OSIS USING ELECTRE METHOD IN SMK PGRI 35 WEST JAKARTA Mia Rosmiati; Nur Atika Sari
Jurnal Techno Nusa Mandiri Vol 17 No 1 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

In an organization choosing a leader who is highly dedicated, responsible and responsive to every problem is not easy. A leader is not only required to have intelligence and skill but also must have a soul of leadership, a great sense of responsibility and can be a role model. The purpose of this study was to determine the student council president using the ELECTRE method based on 4 (four) criteria, namely managerial ability, knowledge and skills, collaborative communication responsibilities and discipline. With the application of the ELECTRE method, it is expected to be able to achieve these objectives. With the implementation of the ELECTRE method in the process of electing the student council president at SMK PGRI 35 Jakarta, it can determine the student council chair with accurate results in accordance with the criteria given by the school. The results of calculations with the Electre method will obtain the highest rating, namely: A3 (Miranti Sofia) because if it indicates that the alternative is the chosen alternative.

COMPARISON OF DATA MINING CLASSIFICATION ALGORITHM FOR PREDICTING THE PERFORMANCE OF HIGH SCHOOL STUDENTS Tiska Pattiasina; Didi Rosiyadi
Jurnal Techno Nusa Mandiri Vol 17 No 1 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Data Mining is a series of processes to explore added value in the form of unknown information manually from the database. In the world of data mining education can be used to obtain information about student performance. In this study the researchers took research samples from class XI (eleven) students at SMAN 3 Ambon by classifying student performance based on thirteen attributes, namely: age, sex, school organization, extracurricular activities, pocket money, duration of study at home, duration of social media, online game duration, attendance, illness, permits, semester 1 and semester 2 grades. Using the KDD (Knowledge Discovery Database) method and classification algorithm that will be used, namely, decision tree, Naïve Bayes and K-Nearest Neighbor. And then do the test using k-fold cross validation.

MOBILE-BASED ONLINE EXAM APPLICATIONS USING PROBLEM WEIGHT CLASSIFICATION TECHNIQUES, GROUPING AND RANDOMIZING Muhammad Iqbal; Abdul Hamid; Nuraeni Herlinawati; Mochammad Abdul Azis; Muhammad Rezki; Ali Mustopa
Jurnal Techno Nusa Mandiri Vol 17 No 1 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Education is an agenda for designing the country's development. Implementation in the field of education is a joint responsibility of both the government and the community, educational institutions are one that plays an important role in the ongoing learning process activities one of which is the examination activities. The test is an evaluation of the learning process to obtain learning outcomes as a form of achievement recognition or completion in an educational unit. The test is still cheating, it is triggered by the lack of confidence in working on the exam questions and the same type of exam questions will provide an opportunity to chat and work together. The author aims to provide a solution in the form of the application of online-based online test applications using question weight classification techniques, grouping and randomization. This mobile-based online exam application was developed using the waterfall model. The results obtained from research on this mobile-based exam application has features to prevent screen capture or screenshots, prevent video recording or video recorder and prevent switching applications that can run multiplatform on Android and iOS. This application has been through the process of testing the user and distributing questionnaires to determine the feasibility of using the weight classification technique with a percentage of 80% so it is suitable for use in examination activities.

NAIVE BAYES ALGORITHM IMPLEMENTATION TO DETECT HUMAN PERSONALITY DISORDERS Yoga Aditama Ika Nanda; Bety Wulan Sari
Jurnal Techno Nusa Mandiri Vol 17 No 1 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

We live in a society that still sees problems regarding one's soul and personality as taboo, even though mental health is as important as physical health. A personality disorder itself is a disorder that can be seen from behavior, mindset, and attitude, which brings difficulties to life. Based on this problem, this study applies the method of Naive Bayes classifier as early detection of human personality disorders. Using a data set of 130 correspondences from the AMIKOM university scope with the age limit of 18-25 years and identified personality disorders is a borderline type disorder. The data obtained was 94 with undiagnosed classes and 36 with undiagnosed classes, with the research variables in the form of questionnaire questions as many as 13 questions. The testing process is done with 10 fold and 5 fold cross-validation, and confusion matrix with the results in the form of accurate 10 folds superior with a value of 88.8% compared to 5 folds that is 88.2%, for precision 10 folds superior with 88.7%, but for 5 fold recall superior with 88.3%, while the final results of these two performances in F1-Score, produce the same value, which is 86.1%.

DATA MINING FOR PREDICTING THE AMOUNT OF COFFEE PRODUCTION USING CRISP-DM METHOD Ali Khumaidi
Jurnal Techno Nusa Mandiri Vol 17 No 1 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

The production of coffee plantations has become the leading plantation commodity with the export value of the fourth rank after oil palm, rubber and coconut. The number of coffee needs for export every year always increases, therefore it is necessary to predict the yield of coffee plants to estimate planting and anticipation that will be done so as to achieve the target. Coffee plant productivity is influenced by internal and external factors, namely the quality of the plant itself, soil, altitude and climate. The method used in this study is the CRISP-DM method and multiple linear regression algorithm to predict the amount of coffee production and determine the relationship between the variables. The steps taken are business understanding, data understanding, data preparation, modeling and evaluation. The data set that is used as many as 170 data after going through the data preparation stage produced 150 data with 5 attributes in the table. With calculations using tools, the coefficient of determination is 91.96%. That the variation in the value of the production of coffee plants is influenced by independent variables, namely the area of plantations, rainfall, air pressure and solar radiation by 91.96% and 8.04% influenced by other variables not measured in this study. The results of the evaluation and validation of predictions produce good accuracy with an RMSE value of 0.3477.

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Journal Mail Official
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Kota adm. jakarta pusat,

Dki jakarta

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