Jurnal Pilar Nusa Mandiri
Jurnal Pilar merupakan jurnal ilmiah yang diterbitkan oleh program studi sistem informasi STMIK Nusa Mandiri. Jurnal ini berisi tentang karya ilmiah yang bertemakan: Rekayasa Perangkat Lunak, Sistem Pakar, Sistem Penunjang, Keputusan, Perancangan Sistem Informasi, Data Mining, Pengolahan Citra.
Articles
322 Documents
<![CDATA[PENYELEKSIAN JURUSAN TERFAVORIT PADA SMK SIRAJUL FALAH DENGAN METODE SAW ]]>
<![CDATA[Siti Nurlela]]>;
<![CDATA[Akmaludin Akmaludin]]>;
<![CDATA[Sri Hadianti]]>;
<![CDATA[Lestari Yusuf]]>
<![CDATA[ Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): PILAR Periode Maret 2019 ]]>
Publisher : <![CDATA[LPPM Universitas Nusa Mandiri ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (1096.159 KB)
|
DOI: 10.33480/pilar.v15i1.1
<![CDATA[SMK Sirajul Falah is a Vocational High School located in the Bogor area. However, the selection of the favorite majors in SMK Sirajul Falah is still qualitative so that the process of choosing the favorite majors become not accurate. This is what makes the need for a method that is able to manage the data of the selection of the favorite majors and generate a ranking of the calculation of the weight of the selection of the favorite majors. In the selection of these favorite majors, there is a method of Simple Additive Weighting (SAW) which can be used in quantitative problem-solving. The SAW method is used to compare each criterion with one another, so as to give the results of the favorite majors and provide an assessment of each department at the Sirajul Falah Vocational School.]]>
<![CDATA[PENERAPAN METODE TOPSIS DALAM PENILAIAN KINERJA GURU TETAP SD NEGERI KEBALEN 07 ]]>
<![CDATA[Susliansyah Susliansyah]]>;
<![CDATA[Indra Riyana Rahadjeng]]>;
<![CDATA[Heny Sumarno]]>;
<![CDATA[Chyntia Marianna Deleaniara. M]]>
<![CDATA[ Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): PILAR Periode Maret 2019 ]]>
Publisher : <![CDATA[LPPM Universitas Nusa Mandiri ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (979.127 KB)
|
DOI: 10.33480/pilar.v15i1.2
<![CDATA[To find out the problems faced in the teaching performance assessment process by utilizing the Technique For Order Preference method by Similiarity to Ideal Solution (TOPSIS), to manage the processing of Teacher data is a more optimal consideration. By using the (TOPSIS) method as a basis for processing teacher performance assessment data. This can allow the system to provide an assessment in accordance with the quality of each teacher and is expected to facilitate decision making in the assessment of Teacher's performance. The Technique For Order Preference by similiarity to Ideal Solution has been running well and can result in a weighting of assessment criteria and clear and fast information compared to manual calculations so SD Negeri Kebalen 07 can use it as a tool for making appropriate decisions.]]>
<![CDATA[PENERAPAN FEATURE WEIGHTING OPTIMIZED PADA NAÏVE BAYES UNTUK PREDIKSI PROSES PERSALINAN ]]>
<![CDATA[Hilda Amalia]]>;
<![CDATA[Achmad Baroqah Pohan]]>;
<![CDATA[Siti Masripah]]>
<![CDATA[ Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): PILAR Periode Maret 2019 ]]>
Publisher : <![CDATA[LPPM Universitas Nusa Mandiri ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (918.778 KB)
|
DOI: 10.33480/pilar.v15i1.3
<![CDATA[Birth of a baby is something that is very desirable for every married couple. All parties expect safety for mothers and babies who have just been born. Medical personnel make various efforts to help the delivery process run smoothly and the mother and baby survive. But in the labor process not all the baby's birth process runs smoothly. Problems often occur during labor. There are several obstacles so that there is a risk of labor, namely maternal and infant mortality. Every mother wants to be able to give birth to a baby normally, but due to medical reasons the delivery process is done by cesarean. The act of choosing a type of delivery faster can affect the safety of the mother and baby. The selection of the cesarean method is carried out late so it will increase the risk of maternal and infant mortality. For this reason, it is necessary to conduct research by using labor delivery data so that they can choose the right type of labor. In this study the classification of maternity labor will be carried out with data mining methods, namely Naive Bayes, which are improved by using the Optimize Weight (PSO) method. Naive Bayes was able to produce a high accuracy value for processing labor data for mothers, namely 94%. The final results of this study obtained the value of naïve bayes performance that can be improved by the Optimize Weights (PSO) method to be better at 98%]]>
<![CDATA[OPTIMASI ALGORITMA NEURAL NETWORK DENGAN ALGORITMA GENETIKA DAN PARTICLE SWARM OPTIMIZATION UNTUK MEMPREDIKSI HASIL PEMILUKADA ]]>
<![CDATA[Mohammad Badrul]]>
<![CDATA[ Jurnal Pilar Nusa Mandiri Vol 13 No 1 (2017): PILAR Periode Maret 2017 ]]>
Publisher : <![CDATA[LPPM Universitas Nusa Mandiri ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (744.59 KB)
|
DOI: 10.33480/pilar.v13i1.7
<![CDATA[Indonesia has one of the islands spread from Sabang to Merauke. State of Indonesia which consists of several islands gave birth to awide variety of ethnic and cultural diversity. State of Indonesia which consists of several islands divided into 34 provinces. Indonesia is one countrythat adheres to the democratic system in the world. to achieve this goal, one of which is seen at the democratic party to choose the future leaderswho will represent the people in parliament. Elections were held in Indonesia is to choose the heads of both the president and vice president,members of Parliament, Parliament and Council. Research relating to the election had been conducted by researchers is using decision treemethod or by using a neural network. The method used was limited without doing optimization method for the algorithm. In this study, researchers will conduct research focusing on the optimization using genetic algorithm optimization and particle swarm optimization with the aid of neural network algorithms. After testing the two models of neural network algorithms and genetic algorithms are the results obtained by the neural network algorithm ptimization particle swarm optimization algoritmasi accuracy value amounted to 98.85% and the AUC value of 0.996. While the neural network algorithm with genetic algorithm optimization accuracy values of 93.03% and AUC value of 0.971]]>
<![CDATA[ANALISIS PERANCANGAN MEDIA PEMBELAJARAN ANIMASI INTERAKTIF MENGENAL BAHASA JEPANG ]]>
<![CDATA[Rachman Komarudin]]>;
<![CDATA[Ridha Rifiana Noor]]>
<![CDATA[ Jurnal Pilar Nusa Mandiri Vol 13 No 1 (2017): PILAR Periode Maret 2017 ]]>
Publisher : <![CDATA[LPPM Universitas Nusa Mandiri ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (999.479 KB)
|
DOI: 10.33480/pilar.v13i1.9
<![CDATA[Analysis of animation instructional media interkatif know Japanese language aims to obtain a feasibility study media based on test validity and reliability and also to study the response of the user (user) regarding this interactive learning media. whereas in the design of interactive media is using the meotde development of multimedia applications, the steps being taken is the concept, design, material collecting, assembly, testing, and distribution (implementation). The results of calculations with the validity and reliability is obtained that the significance level (α) = 5% = 0.05. by using statistical test r-Spearman (Spearman rho) obtained critical value = value table (n-28) rtabel = rα; (N-2) = r 0:05; (28) = 0.3610. If tested the validity of each variable can be considered valid indicator entirely because r count larger than r table, and to test the reliability value of Cronbach's Alpha 0734 is greater than rtabel 0.3610. so its value is valid. It can be concluded that the media interactive animated learning Japanese language decent used to know.]]>
<![CDATA[PERANCANGAN PERANGKAT LUNAK SISTEM INFORMASI PENDATAAN GURU DAN SEKOLAH (SINDARU) PADA DINAS PENDIDIKAN KOTA TANGERANG SELATAN ]]>
<![CDATA[Yana Iqbal Maulana]]>
<![CDATA[ Jurnal Pilar Nusa Mandiri Vol 13 No 1 (2017): PILAR Periode Maret 2017 ]]>
Publisher : <![CDATA[LPPM Universitas Nusa Mandiri ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (1280.968 KB)
|
DOI: 10.33480/pilar.v13i1.10
<![CDATA[The development of technology in today's world influence and a great impact on the development of education information system. In the world of information systems there are many models of information systems aimed at providing various kinds of information, and with the progress of technology has developed very fast, it was marked by the increasing number of computer based information system, so that people can quickly to obtain the desired information, as well as a system of data collection on teacher and school information. One proposed solution to optimize data management and school teachers are implementing the Application System Data Collection Teacher And School (SINDARU). SINDARU is a computer-based information systems used to support teachers and school data collection system with the government agency South Tangerang City Department of Education.]]>
<![CDATA[SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KARYAWAN BERPRESTASI DENGAN METODE PROFILE MATCHING PADA PT. SARANA INTI PERSADA (SIP) ]]>
<![CDATA[Rani Irma Handayani]]>
<![CDATA[ Jurnal Pilar Nusa Mandiri Vol 13 No 1 (2017): PILAR Periode Maret 2017 ]]>
Publisher : <![CDATA[LPPM Universitas Nusa Mandiri ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (1089.153 KB)
|
DOI: 10.33480/pilar.v13i1.11
<![CDATA[Having a Human Resources (HR) quality is required by the company to improve the productivity performance of a company. PT. Sarana Inti Persada (SIP) is a company engaged in telecommunications. In the employee performance evaluation is still subjective, because the limited time and the limited ability to accurately view all aspects often led to errors in decision making. Therefore, in assessing the performance of employees needed some aspects in order to obtain accurate results. Necessary Decision Support System (DSS) for the selection of the performance appraisal performing employees. In a profile matching, identification of the employee groups for better or worse. The employees in the group are measured using several assessment criteria. If pelakasana good obtaining different scores from implementing bad or a characteristic, then the variable is beneficial to choose a good executor.]]>
<![CDATA[ANALISA EFEKTIFITAS METODE FORWARD CHAINING DAN BACKWARD CHAINING PADA SISTEM PAKAR ]]>
<![CDATA[Ibnu Akil]]>
<![CDATA[ Jurnal Pilar Nusa Mandiri Vol 13 No 1 (2017): PILAR Periode Maret 2017 ]]>
Publisher : <![CDATA[LPPM Universitas Nusa Mandiri ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (923.614 KB)
|
DOI: 10.33480/pilar.v13i1.12
<![CDATA[The use of forward-chaining and backward-chaining in an expert system is something usual. Where forward-chaining is a data-driven algorithm, while backward-chaining is goal-driven. Both methods are usually used for reasoning. Here, the writer will analyze effectively both method in their using for an expert system.]]>
<![CDATA[OPTIMASI ALGORITMA VECTOR SPACE MODEL DENGAN ALGORITMA K-NEAREST NEIGHBOUR PADA PENCARIAN JUDUL ARTIKEL JURNAL ]]>
<![CDATA[Siti Fauziah]]>;
<![CDATA[Siti Fauziah]]>;
<![CDATA[Daning Nur Sulistyowati]]>;
<![CDATA[Taufik Asra]]>
<![CDATA[ Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): PILAR Periode Maret 2019 ]]>
Publisher : <![CDATA[LPPM Universitas Nusa Mandiri ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (895.206 KB)
|
DOI: 10.33480/pilar.v15i1.27
<![CDATA[Articles is one part of the scientific work which was manifested in the form of writing and containing a lot of information that are requisite and suited therein to the exclusion of .Many small article day with allah is as a variety of sorts of the title and the methodology that was used , but does not make up for the possibility of a resemblance of the title of the article that is there is .This study aims to for determining the rate of a resemblance between an article of the american journal of public from the point of view of the title of the articles the american journal of public by the use of an algorithm of vector space the model and compare it with an algorithm k-nearest neghbour .The data used pt pgn promised to supply 10 the title of an article of the american journal of public keyword on information retrieval .Testing the data with of these keywords documents produced by the only by the magnitude of the resemblance of its on the highest a method of vsm it will be on a doc 5 , doc 7 , doc 8 and doc 4 .While for the program knn generate a level of the resemblance of its on range doc7 , doc10| doc8 , doc10| doc4 , d10| doc5 , doc10| doc3 , doc10. So that came to the conclusion that the occurrence of the addition of the criteria used to they obtain documents they do similaritas keyword after]]>
<![CDATA[KOMPARASI ALGORITMA DENGAN PENDEKATAN RANDOM UNDERSAMPLING UNTUK MENANGANI KETIDAKSEIMBANGAN KELAS PADA PREDIKSI CACAT SOFTWARE ]]>
<![CDATA[Ginabila Ginabila]]>;
<![CDATA[Ahamd Fauzi]]>
<![CDATA[ Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): PILAR Periode Maret 2019 ]]>
Publisher : <![CDATA[LPPM Universitas Nusa Mandiri ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (1063.258 KB)
|
DOI: 10.33480/pilar.v15i1.28
<![CDATA[Testing is a process that becomes a standard in producing quality software. In predictions of software defects, prediction errors are very bad. Incorrect and inappropriate data sets result in inaccurate prediction results will be affect the software itself. This study aims to overcome the problem of class imbalance with the software defect prediction data set, through the Random Undersampling (RUS) data level approach by taking several algorithms namely Naive Bayes (NB), J48 and Random Forest (RF) which aims to compare the accuracy level highest so that maximum results are obtained in the process of predicting software defects. From the results of this study it can be found that to overcome class imbalances using the Random Undersampling level data approach to predict software defects, the highest level of accuracy is obtained by the Random Forest algorithm with an accuracy rate of 71.932%.]]>
