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<![CDATA[DAMPAK MEDIA SOSIAL (FACEBOOK) DAN GADGET TERHADAP MOTIVASI BELAJAR ]]>
<![CDATA[Mariskhana, Kartika]]>
<![CDATA[ Perspektif : Jurnal Ekonomi dan Manajemen Akademi Bina Sarana Informatika Vol 16, No 1 (2018): Maret 2018 ]]>
Publisher : <![CDATA[www.bsi.ac.id ]]>
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DOI: 10.31294/jp.v16i1.3120
<![CDATA[ABSTRACT Mts Al Makmur Parungpanjang is the first junior high school to promote Islamic religious education and general knowledge. In MTs Al Makmur parungpanjang there is a phenomenon that concerns educators in schools and also parents where in the daily life of the wider community is well known ie social media (facebook) and gadgets. This study aims to test and analyze how big the impact of social media (facebook) and gadgets on student motivation in MTs Al-Makmur Parungpanjang. The survey method used in this study is by random sampling and calculate the questionnaire results that have been filled by students by using slovin formula, where there are population for class VIII as many as 202 students and from that number obtained sample of 135 students. The results showed that social media (facebook) and gadgets impact simultaneously on students' motivation in MTs Al Makmur parungpanjang. The conclusion of this research is social media (facebook) and gadget is electronic media which become means in obtaining various information, both in the interest of education and also outside of education. Social media (facebook) and gadgets also contribute to the formation of the mindset and behavior of students in learning activities and activities outside the school, so it can be the attention of the school to its students to see the pattern of increased or decreased student learning motivation, therefore the required power better efforts of the school and parents as supervisors of student activities in order to create a good generation. Keywords: Social Media (facebook), Gadget and Student Motivation ]]>
<![CDATA[Perancangan dan Implementasi Modul Manufacture Odoo pada Bengkel Body Paint Premium ]]>
<![CDATA[Riva Abdilah Aziz]]>;
<![CDATA[Arfan Sansprayada]]>;
<![CDATA[Kartika Mariskhana]]>
<![CDATA[ Jurnal Teknologi Informatika dan Komputer Vol 9, No 2 (2023): Jurnal Teknologi Informatika dan Komputer ]]>
Publisher : <![CDATA[Universitas Mohammad Husni Thamrin ]]>
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DOI: 10.37012/jtik.v9i2.1646
<![CDATA[Odoo merupakan sistem ERP (Enteprise Resource Planning) yang menyediakan versi open source/community selain juga menyediakan versi berbayar/enterprise. Berbeda dengan sistem ERP yang berbayar dimana pada umumnya ketika akan mengimplementasikan ERP tersebut akan menggunakan jasa konsultan ERP, maka odoo versi open soource/community dapat diimplementasikan tanpa bantuan pihak konsultan. Namun kenyataannya tidaklah mudah mengimplementasikan Odoo pada sebuah perusahaan. Dibutuhkan skill/kemampuan khusus untuk mengimplementasikan Odoo. Sebelum mengimplementasikan Odoo dibutuhkan analisa bisnis proses yang cermat dan tepat sehingga menghasilkan keputusan yang tepat untuk menentukan modul mana yang akan digunakan. Kecermatan dan ketepatan hasil analisa menjadi salah satu faktor kunci keberhasilan implementasi Odoo. Oleh karena itu sebelum melakukan implementasikan Odoo harus melalui proses analisa ini, sehingga apa yang diharapkan dan ditargetkan akan dapat tercapai. Tujuan penelitian ini adalah untuk melakukan analisa dan menentukan modul-modul Odoo mana saja yang dapat digunakan oleh divisi body repair PT XYZ untuk mendukung proses bisnisnya. Dalam penelitian ini, penulis melakukan metode penelitian dengan menggunakan beberapa langkah yang dijadikan sebagai metodelogi penelitian. Adapun langkah-langkah tersebut adalah: identifikasi masalah, perancangan sistem, analisa kebutuhan modul Odoo, dan implementasi sistem. Hasil peneilitian ini menyimpulkan bahwa ada beberapa modul-modul Odoo yang cocok digunakan oleh divisi body repair PT XYZ. Adapaun modul-modul tersebut adalah: modul accounting, modul purchases, modul inventory, dan modul manufacturing.]]>
<![CDATA[Perancangan dan Implementasi Modul Manufacture Odoo pada Bengkel Body Paint Premium ]]>
<![CDATA[Riva Abdilah Aziz]]>;
<![CDATA[Arfan Sansprayada]]>;
<![CDATA[Kartika Mariskhana]]>
<![CDATA[ Jurnal Teknologi Informatika dan Komputer Vol. 9 No. 2 (2023): Jurnal Teknologi Informatika dan Komputer ]]>
Publisher : <![CDATA[Universitas Mohammad Husni Thamrin ]]>
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DOI: 10.37012/jtik.v9i2.1646
<![CDATA[Odoo merupakan sistem ERP (Enteprise Resource Planning) yang menyediakan versi open source/community selain juga menyediakan versi berbayar/enterprise. Berbeda dengan sistem ERP yang berbayar dimana pada umumnya ketika akan mengimplementasikan ERP tersebut akan menggunakan jasa konsultan ERP, maka odoo versi open soource/community dapat diimplementasikan tanpa bantuan pihak konsultan. Namun kenyataannya tidaklah mudah mengimplementasikan Odoo pada sebuah perusahaan. Dibutuhkan skill/kemampuan khusus untuk mengimplementasikan Odoo. Sebelum mengimplementasikan Odoo dibutuhkan analisa bisnis proses yang cermat dan tepat sehingga menghasilkan keputusan yang tepat untuk menentukan modul mana yang akan digunakan. Kecermatan dan ketepatan hasil analisa menjadi salah satu faktor kunci keberhasilan implementasi Odoo. Oleh karena itu sebelum melakukan implementasikan Odoo harus melalui proses analisa ini, sehingga apa yang diharapkan dan ditargetkan akan dapat tercapai. Tujuan penelitian ini adalah untuk melakukan analisa dan menentukan modul-modul Odoo mana saja yang dapat digunakan oleh divisi body & repair PT XYZ untuk mendukung proses bisnisnya. Dalam penelitian ini, penulis melakukan metode penelitian dengan menggunakan beberapa langkah yang dijadikan sebagai metodelogi penelitian. Adapun langkah-langkah tersebut adalah: identifikasi masalah, perancangan sistem, analisa kebutuhan modul Odoo, dan implementasi sistem. Hasil peneilitian ini menyimpulkan bahwa ada beberapa modul-modul Odoo yang cocok digunakan oleh divisi body & repair PT XYZ. Adapaun modul-modul tersebut adalah: modul accounting, modul purchases, modul inventory, dan modul manufacturing.]]>
<![CDATA[Assignment of Motor Mechanics at the Tire Palace Using the Hungarian Method and Testing Software Quality Management (QM) ]]>
<![CDATA[Widiarina, Widiarina]]>;
<![CDATA[Mariskhana, Kartika]]>;
<![CDATA[Sintawati, Ita Dewi]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v7i2.11336
<![CDATA[Measurement of working time (time study) is basically an attempt to determine the placement of mechanical work from the length of work time required by a mechanic to complete a job. This study aims to place the optimal mechanical work in the context of service operational time efficiency and obtain optimal time savings that can be achieved by mechanics in working on motorcycle servicing so as to maximize income using the Hungarian Method. The purpose of this research is to optimize employee assignments by looking at the mechanical working time. The problems that occur at ISTANA BAN are the ineffectiveness of the work process time and the swelling of operational costs, especially in the work of Matic Kaburator, Injection Matic, Injection Duck, Kaburator Duck and Sport with 5 workers. The results of the Assignment Application with the Hungarian Method and Software Quality Management (QM) Testing, Evan mechanics serviced the Duck Kaburator motorbike with a service time of 25 minutes, Minus mechanic serviced the Injection Duck motorbike with a service time of 24 minutes, Hermon mechanic serviced the Sport motorbike with a service time of 27 minutes, mechanic Anton servicing the Matic Injection motorbike with a service time of 25 minutes, mechanic Zola servicing the Matic Kaburator motorbike with a service time of 26 minutes. After analyzing the possibilities, it can be concluded that all mechanics can service each type of motor if the assigned mechanic has worked on the specified type of motor. By minimizing mechanical service time, it will have an impact on Tire Zone revenue because the number of motorbikes being serviced is increasing. Total Tire Zone revenue can be increased from pre-implementation revenue using the Hungarian Method.]]>
<![CDATA[Implementation of Data Mining to predict sales of Bogo helmets using the Naïve Bayes algorithm ]]>
<![CDATA[Mariskhana, Kartika]]>;
<![CDATA[Sintawati, Ita Dewi]]>;
<![CDATA[Widiarina, Widiarina]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 4 (2022): Article Research: Volume 6 Number 4, October 2022 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v7i4.11768
<![CDATA[Consumer needs for safety and comfort in driving are very important, especially for two-wheeled or motorcycle riders. A good helmet is a helmet that is safe and comfortable when worn. Helmet qualifications that meet SNI standards are open helmets and closed helmets. Transactions are carried out online, because it was still in a pandemic situation when it was established. By carrying the tag line "Ride Safety With Your Own Style", trying to educate the younger generation to keep paying attention to safety when driving but also not neglecting fashion. For the type of sale of bogo and retro helmet brands, with a variety of colors and affordable prices. A common problem faced is how to predict or forecast future helmet sales based on pre-recorded data. This prediction is very influential on the decision to determine the number of helmets that must be provided, if you order helmets in sufficient quantities and it turns out that only a few helmet sales are sold and this will cause the stock of helmets to accumulate. The results of predictions for the sale of bogo helmets in Baris True Instances amounted to 16 data, which means Valid with 53% data accuracy. Meanwhile, there are 10 data classified as Instancely Classified Instance which means Invalid, with data accuracy of 46.67%. The amount of accuracy in the Weka application is the same as the amount of accuracy in Excel calculations. From the explanation above, the Naïve Bayes algorithm method is the best solution for predicting important things in a business need and others.]]>
<![CDATA[Application Of The C4.5 Algorithm to Determine Security Guard Work Schedules ]]>
<![CDATA[Sintawati, Ita Dewi]]>;
<![CDATA[Widiarina, Widiarina]]>;
<![CDATA[Mariskhana, Kartika]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i2.12247
<![CDATA[All agencies, companies, and public spaces must employ security guards to maintain security. The problem with the security guard's schedule is that there is an imbalance in disciplinary issues, poor performance because there is no seniority that is emulated so that the guard is not optimal which results in the problem of losing employee items, working time is not according to the rules and there is a vacancy in personnel due to personnel not coming to work, suing With the existence of a policy in the placement and distribution of the right employee work schedule, it is hoped that it can synergize all elements in the institution so that the quantity and quality of the security guard's work can increase and be completed on time. One of the techniques in data mining is classification. By applying classification techniques to security guard data and work schedules, the Decision Tree method and C4.5 algorithm are developed. The results of data processing form the root node of the gender tree as the root, that those who get schedule A are men while those who get schedule B with high school and junior level education are women, besides that they get schedule A. The accuracy of all classifications of the correct number is 61, 53%.]]>
<![CDATA[Application of Data Mining for Clustering Human Development Index Based on West Java Province 2017-2022 ]]>
<![CDATA[Widiarina, Widiarina]]>;
<![CDATA[Mariskhana, Kartika]]>;
<![CDATA[Sintawati , Ita Dewi]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v9i1.13148
<![CDATA[Human development is used as a parameter to see development from the human side. The Human Development Index (HDI) explains how people get sufficient income, adequate health and education. Geographically, Indonesia is an archipelagic country where each province is spread across various islands separated by sea. Making the disparity in human development between provinces relatively high. The gap that occurs is still a problem that must be resolved immediately, because the gap in the human development index can hamper the government's goal of equalizing human welfare in Indonesia. −One of the problems related to population that West Java Province still has to face is the problem of imbalance in population distribution. Incomplete population distribution causes problems with population density and population pressure in an area. This research uses data sources from the West Java Province Central Statistics Agency (BPS). The data used in this research is data from 2017-2022 which consists of 27 regencies and cities of West Java Province. Therefore, researchers utilized the K-Means algorithm in clustering 27 Regencies and Cities of West Java Province. The data will be processed by clustering into 3 clusters, namely the high population area level cluster, the medium population area level cluster and the low population area level cluster. This research classifies population density using Ms. software. Excel and RapidMiner. The iteration process took place 3 times so that the results obtained were 8 regencies and cities with high population area clusters (C0), 0 regencies and cities with medium population area clusters (C1) and 19 regencies and cities with low population area clusters (C1). C2).]]>
<![CDATA[Exploring Regional Development Patterns using Machine Learning: A Python-based Clustering Analysis of Human Development Index in West Java ]]>
<![CDATA[Mariskhana, Kartika]]>;
<![CDATA[Sintawati, Ita Dewi]]>;
<![CDATA[Widiarina, Widiarina]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 2 (2024): Article Research Volume 8 Issue 2, April 2024 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i2.13561
<![CDATA[Many local governments now prioritize human development when trying to raise the standard of living and welfare of their citizens. Developing effective development policies in West Java, one of Indonesia's most populous provinces, requires a thorough understanding of human development patterns in various districts and cities. Using the Human Development Index (HDI) as the primary indicator, we examine regional development patterns in this study using machine learning techniques, specifically clustering analysis. This study's scope includes an HDI analysis for each of West Java's 27 districts and cities from 2017 to 2022. Finding clusters of districts or cities with comparable human development traits and comparing and contrasting them are our primary goals. We provide a solution that allows for improved mapping and comprehension of human development patterns in West Java by utilizing the Python programming language as the primary tool and the K-Means clustering algorithm. The study's findings indicate that there are three major categories of districts and cities, each with a distinct human development pattern. By using clustering analysis, we can determine which districts or cities within each group have the highest and lowest levels of human development. This information helps policymakers plan more inclusive and sustainable development. In conclusion, a clustering analysis approach based on machine learning can be a helpful tool for understanding and creating more focused and efficient regional development policies in West Java and other areas.]]>
<![CDATA[Analysis of Malnutrition Status in Toddlers Using the K-MEANS Algorithm Case Study in DKI Jakarta Province ]]>
<![CDATA[Sintawati, Ita Dewi]]>;
<![CDATA[Widiarina, Widiarina]]>;
<![CDATA[Mariskhana, Kartika]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i4.14087
<![CDATA[Malnutrition in children is a serious health issue in various regions, including DKI Jakarta Province, which affects the physical and cognitive development of children. This research aims to classify malnutrition status in children using the K-Means algorithm, focusing on cases in DKI Jakarta. The objective is to identify patterns of malnutrition prevalence across different regions, serving as a basis for more effective interventions. The data used in this study includes the percentage of children with severely stunted, stunted, and normal nutritional status across six districts/cities in DKI Jakarta. The results of K-Means clustering show that Central Jakarta has the highest prevalence of severely stunted (10.50%) and stunted (13.01%) status, while West Jakarta has the lowest prevalence of severely stunted (4.62%) and stunted (10.22%) status. The solution offered by this research is the grouping of regions based on malnutrition prevalence, allowing for the identification of areas requiring priority intervention. The analysis results indicate that DKI Jakarta can be classified into several clusters based on malnutrition prevalence. The cluster with the highest malnutrition prevalence includes Central Jakarta, while the cluster with the lowest malnutrition prevalence includes West Jakarta and the Thousand Islands. The implementation of K-Means in this research provides an efficient approach to identifying groups of regions that need more attention in combating malnutrition in children. In conclusion, this research can serve as an important reference for policymakers in formulating more effective and efficient intervention strategies in DKI Jakarta, as well as inspire similar studies in other regions with different population characteristics]]>
<![CDATA[Penerapan Algoritma Naïve Bayes Untuk Prediksi Penjualan Motor Terlaris Pada PT. Ramayana Mitra Sejahtera ]]>
<![CDATA[Ainayah, Nazla]]>;
<![CDATA[Laoly, Pera Anjela]]>;
<![CDATA[Putri, Fadhiya Cintana Soleka]]>;
<![CDATA[Mulyadi, Mulyadi]]>;
<![CDATA[Mariskhana, Kartika]]>
<![CDATA[ IJCIT (Indonesian Journal on Computer and Information Technology) Vol 9, No 2 (2024): November 2024 ]]>
Publisher : <![CDATA[LPPM Universitas Bina Sarana Informatika ]]>
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DOI: 10.31294/ijcit.v9i2.23145
<![CDATA[Penjualan adalah aktivitas penting yang dapat meningkatkan pendapatan perusahaan. Namun, PT. Ramayana Mitra Sejahtera masih mengandalkan sistem manual dan belum memiliki metode yang efektif untuk mengidentifikasi produk terlaris. Hal ini menjadi kendala dalam menghadapi ketidakstabilan penjualan yang dipengaruhi oleh permintaan konsumen yang beragam. Penelitian ini bertujuan untuk membantu perusahaan dalam menentukan produk motor yang paling diminati menggunakan Algoritma Naïve Bayes. Berdasarkan hasil evaluasi, pada model yang menggunakan 60% data training (805 data) dan 40% data testing (537 data) menunjukkan kinerja yang sangat baik dengan akurasi mencapai 94,97%. Hasil ini menunjukkan bahwa model dengan perbandingan 60% data training dan 40% data testing merupakan paling optimal dalam mengukur akurasi pada data penjualan sepeda motor di PT. Ramayana Mitra Sejahtera. Sales is an important activity that can increase company revenue. However, PT. Ramayana Mitra Sejahtera still relies on a manual system and does not have an effective method for identifying best-selling products. This becomes an obstacle in dealing with sales instability which is influenced by varying consumer demand. This research aims to help companies determine the most popular motorbike products using the Naïve Bayes algorithm. Based on the evaluation results, the model that uses 60% training data (805 data) and 40% testing data (537 data) shows very good performance with an accuracy of 94.97%. These results show that a model with a ratio of 60% training data and 40% testing data is the most optimal in measuring accuracy in motorbike sales data at PT. Ramayana Mitra Sejahtera.]]>
