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All Journal Nuansa Informatika Buffer Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Tekno Kompak Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal AbdiMas Nusa Mandiri International Journal Administration, Business & Organization Journal of Innovation and Sustainable Empowerment Journal of Elektronik Sistem InformasI
Nita Mirantika
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Physics Social Sciences Other

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PERBANDINGAN METODE K-NEAREST NEIGHBOR DAN NAIVE BAYES UNTUK REKOMENDASI PENENTUAN MAHASISWA PENERIMA BEASISWA PADA UNIVERSITAS KUNINGAN Sumiah, Aah; Mirantika, Nita
BUFFER INFORMATIKA Vol 6, No 1 (2020)
Publisher : TI S1 FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/buffer.v6i1.2907

Abstract

ABSTRAKBeberapa tahun terakhir,  data semakin heterogen dan kompleks dengan volume yang meningkat cepat hingga diperkirakan akan mencapai 44 zettabyte di tahun 2020 (turner 2014). Hal ini sering disebut dengan Big data. Era Big data menghasilkan data yang menumpuk sehingga perlu dilakukan pengolahan untuk mencari knowladge dari tumpukan data tersebut menggunakan data mining.  Penelitian ini merupakan penelitian lanjutan dari penelitian sebelumnya yang berjudul “ Implementasi data Mining untuk Rekomendasi Penentuan Mahasiswa Penerima Beasiswa menggunakan Metode Naive Bayes Studi Kasus Universitas Kuningan”.Pada penelitian ini mencoba membandingkan dua agoritma untuk mengetahui algortima mana yang paling cocok digunakan untuk rekomendasi penentuan mahasiswa penerima beasiswa pada universitas kuningan menggunakan algoritma K-Nearest Neighbor dan algoritma Naive Bayes. Metode ini di pilih karena kedua algoritma merupakan algoritma yang populer digunakan dalam proses pengklasifikasian data Hasil analisis data di implementasikan menjadi sebuah sistem informasi menggunakan visual basic.net dan sql server yang dapat digunakan oleh bagian akademik sebagai rekomendasi dalam proses seleksi penerimaan beasiswa.Keyword :  sistem informasi, data mining, beasiswa, naive bayes classifier, K-Nearest Neighbor, visual basic.net, sql server  ABSTRACTIn recent years, data has become increasingly heterogeneous and complex with volumes increasing rapidly until it is estimated to reach 44 zettabytes by 2020 (turner 2014). This is often referred to as Big Data. The era of Big Data generates data that is piling up, so it needs to be processed to find knowladge from the data stack using data mining. This research is a continuation of previous research entitled "Implementation of Mining Data for Recommendations for Determining Scholarship Recipients using the Naive Bayes Method of Case Study at Kuningan University". In this study, trying to compare two agorithms to find out which algorithm is the most suitable for the recommendation of determining scholarship recipients at a brass university using the K-Nearest Neighbor algorithm and the Naive Bayes algorithm. This method was chosen because both algorithms are popular algorithms used in the process of classifying data.The results of data analysis are implemented into an information system using visual basic.net and SQL Server that can be used by the academic department as a recommendation in the selection process for scholarship acceptance. Keywords: Information systems, data mining, scholarships, naive bayes classifier, K-Nearest Neighbor, visual basic.net, sql server
ANALISIS TINGKAT KESIAPAN PENGGUNA E-LEARNING UNIVERSITAS KUNINGAN DENGAN MENGGUNAKAN MODEL TECHONOLOGY READINESS INDEX (TRI) Yusuf, Fahmi; Syamfithriani, Tri Septiar; Mirantika, Nita
NUANSA INFORMATIKA Vol 14, No 2 (2020)
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (123.252 KB) | DOI: 10.25134/nuansa.v14i2.2991

Abstract

Readiness in adopting new technology, especially in Online Learning in a certain University, is determined by user’s readiness i.e. the User in Online Learning.  In Kuningan University, we have concern in e-class: Online learning System, which is categorized as a new technology. The research is to analyze the user’s readiness and to measure the success of the e learning applied in our University. The method that we use in this research to measure user’s readiness level is the Technology Readiness Index (TRI). TRI is an index to measure the User’s readiness in using new technology to achieve the daily learning. The measurement is done by using four variables ; optimism, innovativeness, discomfort and insecurity. We use SPSS 21 application to analyze our data. The Research data is collected by giving Questioners to 371 respondents in Kuningan University (UNIKU). After we had calculated the data, we got the result that the TRI total value was 2.81 (categorized as Low Technology Readiness Index) and the user group was categorized as Skeptics Group (the optimism, innovativeness, discomfort and insecurity were low. These made the students of Kuningan University had uncertain feeling towards the e-class.Key words: Technology readiness index, e-learning, LMS
PENGARUH PENGGUNAAN MEDIA PEMBELAJARAN E-LEARNING TERHADAP MOTIVASI DAN PRESTASI BELAJAR MAHASISWA ( Studi Eksperimen pada Mata Kuliah Komputasi Paralel Mahasiswa Angkatan III Program Studi Teknik Informatika di FKOM UNIKU ) Nita Mirantika
NUANSA INFORMATIKA Vol 8, No 1 (2013)
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/nuansa.v8i1.15

Abstract

The presence of parallel computing courses in Informatics Engineering program is very relevant, applicable and can provide great inspiration for learners. But in reality, this parallel computing courses many students complain because the perceived difficult to learn. Course materials are always on the up grade in accordance with the technological developments that are in. Conventional teaching methods are still the favorite method is given, can not be a good solution to the above problems. because conventional study focused only on the educators in this faculty, so that students are passive, not pushing for creative thinking. Therefore we need another method, which can provide insight and inspiration to the students so that learning can take place effectively and in accordance with technological developments. One of these alternatives is the use of e-learning media.To assess the use of e-learning media are expected to be an alternative solution to the above problems, the authors conducted a study on Information Technology Student III level UNIKU who took a course parallel computing using three classes. The method used is the experimental method. With a variety of considerations, which became the experimental class is TI A class and TI C while the control class is TI B class. Data research conducted through written tests and questionnaires. Data were analyzed using a computerized program SPSS version 16 at the level of 95%. The results showed that the use of e-learning media can increase student motivation and achievement compared to conventional learning.  Keywords: E-learning, Learning Media, Experimental Study, learning motivation, learning achievement.   
Implementasi Metode Clustering Partisi dalam Menentukan Segmentasi Pelanggan Mirantika, Nita; Rijanto, Estiko
Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi Vol. 10 No. 1 (2024): Mei 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jtk3ti.v10i1.11320

Abstract

Segmentasi pelanggan termasuk bagian dari strategi pemasaran yang diperlukan perusahaan melalui pengelompokkan pelanggan yang memiliki kesamaan karakteristik. PT XYZ yang bergerak di bidang peternakan memiliki pelanggan yang tersebar di berbagai wilayah dengan karakteristik yang beragam sehingga membutuhkan segmentasi pelanggan dalam membuat strategi pemasarannya. Penelitian ini bertujuan untuk melakukan segmentasi pelanggan dengan menggunakan metode clustering partisi yaitu algoritma K-Means dan algoritma K-Medoids serta membandingkan kinerja kedua algoritma tersebut. Model RFM (Recency-Frequency-Monetary) digunakan dalam pemilihan atribut penelitian. Metode Elbow digunakan dalam penentuan jumlah cluster optimum dan metode Davies-Bouldin Index (DBI) digunakan dalam evaluasi hasil clustering. Segmentasi pelanggan menggunakan algoritma K-Means menghasilkan tiga jenis pelanggan yaitu superstar, typical customer dan dormant customer. Sedangkan segmentasi pelanggan menggunakan algoritma K-Medoids menghasilkan empat jenis pelanggan yaitu superstar, typical customer, customer needing attention dan dormant customer. Hasil evaluasi clustering diperoleh nilai DBI K-Means jauh lebih kecil dari nilai DBI K-Medoids. Hasil ini menunjukkan bahwa pada metode clustering partisi, algoritma K-Means lebih baik daripada algoritma K-Medoids dalam menentukan segmentasi pelanggan.
Penerapan Model UTAUT 2 Untuk Menganalisis Penerimaan Dan Penggunaan Aplikasi E-Wallet Di Kabupaten Kuningan Syamfithriani, Tri Septiar; Trisudarmo, Ragel; Mirantika, Nita
Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi Vol. 10 No. 1 (2024): Mei 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jtk3ti.v10i1.12754

Abstract

The rapid advancement of technology has significantly impacted various aspects of life, including payments and financial transactions using e-wallet applications. Kuningan Regency possesses a considerable economic potential and numerous opportunities to enhance the business and technology sectors through the use of e-wallet applications. In adopting e-wallet application technology, understanding the factors influencing its acceptance and usage is crucial. One model employed for comprehending these factors is the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2), which focuses on seven key elements influencing the acceptance and use of technology: performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit. This research aims to identify the factors influencing the acceptance and use of e-wallet applications using the UTAUT 2 model, with the addition of the security factor in e-wallet applications. The study involves a quantitative method with 397 respondents, and data analysis using the Structural Equation Modeling-Partial Least Squares (SEM-PLS) approach with the assistance of SmartPLS version 3.0. The results indicate that performance expectancy, facilitating conditions, hedonic motivation, and habit play crucial roles in shaping the intention to use e-wallet applications in Kuningan Regency. These factors are able to explain 68.5% of the research model, the remaining 31.5% is explained by other variables. Understanding these factors allows for efforts to enhance the acceptance and use of e-wallet applications in Kuningan Regency, so that it can help improve the economy.
Predictive Analysis of the Amount of Batik Production Using the Fuzzy Sugeno Algorithm Darmawan, Erlan; Mirantika, Nita; Yusuf, Fahmi; Nita, Gita Sri
International Journal Administration, Business & Organization Vol 5 No 2 (2024): IJABO
Publisher : Asosiasi Ahli Administrasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61242/ijabo.24.410

Abstract

To meet market demand, a company must be able to plan and determine the amount of appropriate and timely production to compete with other companies. To support this, we need a system that can determine the product's production amount so that the product can be sold according to expectations and the desired target. This study aims to determine the amount of production through a decision support system using the Fuzzy Sugeno algorithm in the form of logic used to produce a single decision or crisp. This research was conducted on batik production in a company. The problem in the batik production process is the amount of production that differs from the market demand. The factors that influence the process of determining the amount of production are the number of inventories and the number of requests used as variables in this study. The results of this study are in the form of a decision support system that can determine the amount of batik production based on the analysis of the number of requests and the amount of supply used to assist companies in making decisions with a truth value of 80%. Thus, the company can be assisted in determining the amount of production to meet market demand and increase profits and achievement targets by minimizing stockpiling.
Web-Based Raw Material Inventory Forecasting System : Using Double Exponential Smoothing Method In Selera Baru Bakery Malika, Melda; Endra Suseno; Nita Mirantika
JESII: Journal of Elektronik Sistem InformasI Vol. 2 No. 1 (2024): JournaI of Elektronik Sistem InformasI - JESII (JUNE)
Publisher : Departement Information Systems Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/jesii.v2i1.3412

Abstract

Controlling raw material inventory is important in every production process, but Selera Baru Bakery has not received control over the raw material inventory procurement process, so business owner does not know when the right time to procure raw materials is. This causes bread production to be carried out in accordance with the availability of existing raw materials when the production process is carried out not based on sales needs. The production process that is not in accordance with these needs results in a shortage or excess stock so that the bread is moldy and not suitable for sale. Based on this condition, research is conducted using the Double Exponential Smoothing method with PHP programming language and MySQL uses database. System design uses UML and system development uses Waterfall, based on the categories of wheat raw materials, flour, yeast, sugar, eggs and margarine with alpha parameter testing of 0.2 showing effectiveness in using the Double Exponential Smoothing method with a MAPE value of less than 10%, this proves that the forecasting results are effective and accurate in controlling the raw material inventory procurement process in Selera Baru Bakery.
Pelatihan Penggunaan Microsoft Office Sebagai Penunjang Keberhasilan Bisnis UMKM di Desa Nangka Kecamatan Kadugede Syamfithriani, Tri Septiar; Mirantika, Nita; Herlina, Elin
Journal of Innovation and Sustainable Empowerment Vol. 1 No. 2 (2022)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) Universitas Kuningan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (247.85 KB) | DOI: 10.25134/jise.v1i2.21

Abstract

Di era Society 5.0 para pelaku usaha dituntut untuk adaptif, bergerak cepat menghadapi segala perubahan yang tidak dapat terprediksi, para pelaku usaha dituntut untuk dapat menyelesaikan segala tantangan dan permasalahan social dengan memanfaatkan segela jenis bentuk inovasi teknologi informasi. Untuk mempersiapkan hal demikian maka dibutuhkan literasi teknologi kepada pengguna dan pelaku usaha agar mampu menggunakan aplikasi teknologi, mampu mengakses dan mampu mengevaluasi informasi dengan baik. Desa Nangka merupakan bagian dari Kecamatan Kadugede Kabupaten Kuningan dikepalai oleh Kepala Desa Bapak Sukmana, S.T., terdiri dari 2 Dusun, dimana di Desa Nangka sebagian besar mata pencaharian masyarakatnya adalah bercocok tanam, 90% warganya menanam sayuran di pekarangan, adapun jenis sayur yang ditanam adalah, cabai, bawang, bayam, kangkung, sawi, untuk nantinya ditampung di bank sayur desa yang akan dijual ke konsumen. Pengelolaan administrasi di Bank Sayur tersebut dilakukan oleh ibu-ibu UMKM dimana pengelolaan manajemen perkantoran ini dibutuhkan sebagai kegiatan administrasi yang dilakukan sehari-hari seperti mencatat, mengawasi dan mengontrol. PkM ini mempunyai tujuan untuk memberikan pelatihan, meningkatkan keterampilan mitra dalam memanfaatakan perangkat teknologi informasi sehingga penyelenggaraan administrasi penunjang bisnis berjalan dengan tertib. PkM ini dilaksanakan selama 3 hari, dengan cara memberikan pelatihan administrasi perkantoran menggunakan Microsoft Word, Excel dan powerpoint. Pelatihan ini mendapat antusiasme dari mitra dan respon sangat baik, sehingga hasil dari pelatihan ini adalah meningkatnya keterampilan mitra untuk memanfaatkan teknologi informasi.
Membangun Kesadaran dan Keamanan Penggunaan Fintech di Masyarakat Desa Timbang Kecamatan Cigandamekar Kabupaten Kuningan Syamfithriani, Tri Septiar; Herlina, Elin; Mirantika, Nita
Journal of Innovation and Sustainable Empowerment Vol. 3 No. 2 (2024)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) Universitas Kuningan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/jise.v3i2.77

Abstract

Pengabdian masyarakat ini dilaksanaka di Desa Timbang Kabupaten Kuningan, dengan tujuan meningkatkan kesadaran masyarakat Desa Timbang tentang penggunaan fintech yang aman dan terpercaya, serta meningkatkan literasi keuangan masyarakat dalam penggunaan fintech agar terhindar dari berbagai ancaman keamanan seperti kebocoran data dan penipuan. Kegiatan ini dilakukan secara luring bertemu dengan masyarkat pelaku UMKM Desa Timbang, dengan pendekatan sosialiasi dan pelatihan. Sesi sosialiasasi di paparkan pengetahuan mengenai fintech (pengertian, peran dan jenis fintech, manfaat dan resiko), dilanjut dengan memberikan pengetahuan mengenai kesadaran dan literasi keuangan, terakhir di lanjut dengan pelatihan praktik penggunaan fintceh (demonstrasi transaksi dan panduan keamanan) diakhiri dengan tanya jawab. Hasil menunjukan 80% dari mereka mengalami peningkatan tingkat pemahaman dari rendah menjadi tingkat sedang atau tinggi.
Implementation of Naive Bayes Algorithm for Early Detection of Stunting Risk Mirantika, Nita; Trisudarmo, Ragel; Syamfithriani, Tri Septiar
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9144

Abstract

This study aimed to develop an early detection model for stunting risk in children in Kuningan Regency using the Naïve Bayes algorithm. The model used 3,155 data with a division of 50% training data and 50% testing data, utilizing five predictor variables: gender, age, weight, height, and nutritional intake. The results demonstrated an accuracy of 66.8%, precision of 62.4%, and recall of 69.5%, indicating that the model performs adequately but requires further refinement to enhance predictive quality. Improvements can be achieved by incorporating additional variables, such as environmental factors, sanitation, and maternal nutritional status, as well as optimizing data preprocessing techniques. The findings provide a scientific basis for the Kuningan Regency Health Office to design targeted intervention strategies, including regular screening programs, specific nutritional interventions, and community health education. Effective implementation of these strategies requires collaborative efforts among local government, community health centers (puskesmas), integrated health posts (posyandu), and other stakeholders to ensure a holistic and sustainable approach to stunting prevention. This study highlights the potential of data-driven models in supporting evidence-based public health policies and interventions.
Co-Authors Aah Sumiah Amalia Asikin, Nida Ariani, Fitrah Ramadanti Dadan Nugraha Elin Herlina, Elin Erlan Darmawan Estiko Rijanto Fahmi Yusuf Malika, Melda Nita, Gita Sri Renaldi, Aldi Riddwan, Iwan Mohammad Suseno, Endra Syamfithriani, Tri Septiar Trisudarmo, Ragel