Garuda - Garba Rujukan Digital

Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik pada PT. XYZ dengan Metode Profile Matching dan Interpolasi Nicolas, Prayogi Perdana; Soetanto, Hari; Wahyudi, Wahyudi; Rossi, Ardiane
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 9, No 2 (2021)
Publisher : Jurusan Informatika Universitas Tanjungpura

Karyawan terbaik adalah tenaga kerja perusahaan yang memiliki kinerja terbaik diantara karyawan-karyawan lainnya. Salah satu upaya untuk meningkatkan kinerja karyawan dalam bekerja adalah dengan mengadakan kegiatan pemilihan karyawan terbaik. Masalah yang dihadapi PT. XYZ pada saat sebelum diadakannya penelitian ini adalah penilaian karyawan dilakukan dengan cara manual, yang tentu saja setiap penilai memiliki cara penilaian tersendiri dalam memilih karyawan terbaik. Hal ini menyebabkan proses pengambilan keputusan membutuhkan waktu yang lama dan hasilnya pun cenderung subjektif. Untuk menghilangkan masalah tersebut, diperlukan suatu sistem terkomputerisasi yang membantu pengambil keputusan dalam memilih karyawan terbaik, yaitu sistem pendukung keputusan (SPK) pemilihan karyawan terbaik pada PT. XYZ yang dibuat dengan menggunakan metode Profile Matching dan Interpolasi. Metode Profile Matching digunakan untuk pengambilan keputusan penilai, sedangkan metode Interpolasi digunakan untuk proses pembobotan tiap nilai, sehingga hasilnya akan menjadi objektif. Kriteria yang digunakan adalah Kualitas Kerja, Kuantitas Kerja, Disiplin, Inisiatif, Motivasi, Tanggung Jawab, Kerjasama, Adaptasi, Pemahaman Tugas, Pemecahan Masalah, Kepemimpinan, dan Pengambilan Keputusan. Setelah perhitungan nilai dilakukan dengan metode Profile Matching dan pembobotan dilakukan dengan metode Interpolasi, maka karyawan kode A099 (Dadap Hardiansyah) berhak menerima penghargaan karyawan terbaik dengan nilai tertinggi 3.875. Dengan demikian, SPK dengan menggunakan metode Profile Matching dan Interpolasi mampu merekomendasikan pemilihan karyawan terbaik dengan hasil perhitungan yang lebih cepat dan objektif, sehingga dapat digunakan sebagai pendukung keputusan pada PT. XYZ.

Academic Dashboard For Monitoring KPI Based Using Data Feeder Dikti Andi Leo; Ardiane Rossi Kurniawan Maranto; Fernando Fanjaya; Jupiter Supriyadi
bit-Tech Vol. 4 No. 3 (2022): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v4i3.442

University management requires accurate and fast academic reports that make it easier to make strategic decisions and in order to improve the quality of education. Therefore we need a tool that can monitor, evaluate and measure the performance of universities. A common problem is that there is a lot of academic data stored but to present it in reports at the time of evaluating academic activities is difficult and takes a long time. Academic evaluation can be presented with a dashboard so that it becomes easy for decision making. Dashboard is a page that shows graphs as KPIs (Key Performance Indicators) of an organization and provides all the important measurements needed to make key executive decision making. Universities in Indonesia report data on students, lecturers and lecture activities to the PDDIKTI (Higher Education Database). The data contained in the PDDIKTI Feeder is made an academic Dashboard in the form of visualization to assist and support decision making at the academic level and also to monitor using KPI as an evaluation. With the existence of an academic dashboard based on KPI, the presentation of reports becomes faster and easier to understand because it is in the form of visuals and indicators to find out what things need to be improved and the extent to which the achievements of each academic component are used as benchmarks in submitting study program accreditation.

Decision Support System Scholarship Using Profile Matching Ardiane Rossi Kurniawan Maranto; Suwitno Suwitno; Andri Wijaya
Tech-E Vol. 6 No. 1 (2022): Tech-E
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v6i1.1468

Education is very necessary in social life. Education has a role that will improve the quality of resources to be able to have the competencies needed in an increasingly advanced and developing era. Giving this scholarship will also greatly help someone in pursuing and even getting an education. Scholarships must also be done objectively, not just subjectively. Because the problems that occur when objectively granting scholarships may not be in accordance with the target of the scholarship award. Scholarships must also be given according to the right criteria so that the scholarship grants get maximum results for the administrators and scholarship recipients. The research was conducted using the Profile Matching method with Interpolation at the Indonesian Christian Church Pos Cikoleang, it will require decision makers to determine the weight value for each criterion. The results issued by the system are the congregations that are accepted and rejected in the scholarship application. and the system can provide scholarships with an accuracy rate of 78%.

Implementasi Machine Learning Sebagai Pengenal Nominal Uang Rupiah dengan Metode YOLOv3 Aditiya Hermawan; Leonardo Lianata; Junaedi; Ardiane Rossi Kurniawan Maranto
SATIN - Sains dan Teknologi Informasi Vol 8 No 1 (2022): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Jumlah disabilitas kesulitan melihat (Tunanetra) di atas 10 tahun sebanyak 6,36% dari total penduduk yang mengalami disabilitas yaitu 8,56% pada tahun 2015. Permasalahan yang dihadapi penyandang tunanetra dalam kehidupan sehari-hari salah satunya mengenali nominal uang rupiah. Walaupun pemerintah sudah membuat uang dengan emboss pada emisi 2016, tetapi masih kurang efektif karena uang yang beredar kadang dalam kondisi tidak rapih. Untuk mengatasi hal tersebut dapat dibantu dengan menggunakan teknologi Machine learning berbasis Yolov3 dalam mengenali nominal uang Rupiah. Metode YOLOv3 mempunyai keunggulan dalam kecepatan pelatihan model dan nilai akurasinya yang tinggi, dan memang dirancang untuk mengolah gambar. Dataset yang digunakan untuk membuat model machine learning dikumpulkan dari berbagai gambar uang rupiah nominal 1000, 2000, 5000, 10000, 20000, 50000, 10000 sebanyak 4200 gambar. Model yang sudah dibuat selanjutnya diimplementasikan kedalam bentuk aplikasi android. Aplikasi dijalankan seperti melakukan scan uang dan memberikan hasil berupa suara yang menyebutkan nominal uang tersebut secara otomatis. Model ini dievaluasi dengan Confusion Matrix menghasilkan nilai accuracy, precision dan recall sebesar 0.98. Berdasarkan Nilai akurasi tersebut, model yang dibuat dapat membantu penyandang tunanetra dalam mengenali nominal uang rupiah.

Clustering Mental Health pada Pengguna Instagram Menggunakan Algoritma K-Means Yuliastati Putri Sugiarta Karlim; Aditiya Hermawan; Ardiane Rossi Kurniawan Maranto
bit-Tech Vol. 6 No. 1 (2023): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v6i1.880

The use of Instagram too often can have an impact on the mental health of its users. Mental health that is not good requires early treatment so that it does not have a widespread impact on other health. Mental illness requires a professional to treat it as an effort to prevent a disease from getting worse. However, the stigma attached to sufferers is one of the significant causes behind the reluctance to seek treatment. Therefore we need a way so that Instagram users can find out for themselves the condition of their mental health. One way is to do Clustering the use of Instagram so that it can provide an early indication of a person's mental health. From the proposed model we can find out the categories of 600 respondents who were collected using a questionnaire with 10 main attributes. The proposed model is k-means with 3 clusters determined using the elbow method. In this study, the last centroid obtained through calculations was used to evaluate the k-means by comparing the results of the k-means calculations with the results of psychologists. The results of the K-means evaluation have an accuracy of 73.83% so that the last centroid can be applied to web-based applications that have been created. This mental health clustering model is expected to be able to help the community to get mental health conditions early and reduce the negative stigma that exists and can be used as evaluation material in using social media more wisely.

User Interface Experience Analysis of PMB Online Buddhi Dharma Using System Usability Scale Junaedi; Ardiane Rossi Kurniawan Maranto; Maysha Permata Putri; Suwitno
bit-Tech Vol. 6 No. 2 (2023): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v6i2.1051

In the era of advanced digital technologies, the admission process for new students (PMBs) has become a critical aspect of education. To streamline and expedite this process, educational institutions are increasingly utilizing online enrollment applications. One such application, PMB Online Buddhi Dharma, plays a crucial role in this context. However, the success of these applications is not solely determined by technical ease; user experience, particularly the User Interface (UI), plays a pivotal role in influencing user satisfaction and efficiency. This study employs the System Usability Scale (SUS) method to comprehensively analyze the UI of the PMB Online Buddhi Dharma application, providing insights into usability and user satisfaction. Drawing from previous studies utilizing SUS in similar contexts, the research aims to contribute to the development and enhancement of the application's UI. This research evaluates too the effectiveness of Buddhi Dharma University's PMB Online in meeting the digital registration needs of prospective students, emphasizing ease of use and user acceptance. Through the SUS method, the study assesses user satisfaction and ease of use, obtaining an average SUS score of 78 from 30 respondents. This score categorizes Buddhi Dharma University Online PMB as "good," indicating a commendable level of acceptance from users, predominantly prospective students. The research concludes with implications for the application's further improvement and development, emphasizing the importance of user-friendly interfaces in digital admission processes.

Pengaruh Entrepreneurial Marketing dan Program Loyalty terhadap Loyalitas Pelanggan di E-Commerce dengan Customer Relationship Management sebagai Pemoderasi Ardiane Rossi Kurniawan Maranto; Alvin Rahayu; Aditiya Hermawan
eCo-Fin Vol. 6 No. 2 (2024): eCo-Fin
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/ef.v6i2.1183

Penelitian ini bertujuan untuk menyelidiki dampak faktor-faktor pemasaran inovatif, seperti Entrepreneurial Marketing dan Program Loyalty, terhadap loyalitas pelanggan di sektor E-Commerce. Selain itu, penelitian ini juga akan mengevaluasi peran moderasi yang dimainkan oleh Customer Relationship Management (CRM) dalam mengatur hubungan antara faktor-faktor pemasaran tersebut dengan loyalitas pelanggan.Metode pengumpulan data dilakukan melalui survei daring menggunakan Google Form, dengan partisipasi sebanyak 150 responden yang merupakan pelanggan aktif dari berbagai platform E-Commerce terkemuka. Data yang terkumpul akan dianalisis menggunakan model struktural Partial Least Square (PLS) untuk menguji hubungan antara variabel yang diteliti. Penelitian ini juga menemukan bahwa Customer Relationship Management (CRM) memiliki peran penting sebagai pemoderasi dalam memperkuat hubungan antara Entrepreneurial Marketing, Program Loyalty, dan loyalitas pelanggan. Manfaat dari penelitian ini sangatlah penting. Menentukan strategi pemasaran yang inovatif dan program loyalitas yang efektif menjadi lebih memungkinkan dengan pemahaman yang mendalam tentang pengaruh faktor-faktor tersebut terhadap perilaku pelanggan. Selain itu, keberhasilan bisnis E-Commerce juga ditentukan oleh efektivitas Customer Relationship Management (CRM) dalam memperkuat interaksi dengan pelanggan, meningkatkan pengalaman pelanggan, dan membangun hubungan jangka panjang yang berkelanjutan. Dengan demikian, penelitian ini diharapkan dapat memberikan wawasan yang berharga bagi praktisi pemasaran dan manajemen dalam industri E-Commerce untuk mencapai kesuksesan bisnis yang berkelanjutan.

Implementasi Sistem Verifikasi Ijazah dan Transkrip pada Jaringan Ethereum Blockchain Intan Anjali Putri; Aditiya Hermawan; Ardiane Rossi Kurniawan Maranto
bit-Tech Vol. 6 No. 3 (2024): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v6i3.1288

Blockchain, a decentralized database safeguarded by cryptographic security, has gained prominence for its resistance to manipulation. Its application extends notably to ensuring the security of financial transactions, including the acquisition of digital currencies. This study endeavors to develop a system aimed at validating diplomas and academic transcripts, enhancing their authenticity and bolstering the security of document storage. Leveraging the Ethereum Blockchain and Smart Contracts, the methodology focuses on the utilization of specialized codes executed within the Ethereum network. The outcome of this research manifests as a system blueprint designed for the verification of diplomas and transcripts, integrated within a web-based Ethereum Network platform. By harnessing the Ethereum Blockchain's inherent security features and employing Smart Contracts, the proposed system endeavors to streamline the verification process, ensuring the integrity and reliability of academic credentials while fortifying document storage against potential breaches. Through this innovative approach, the study contributes to advancing the authentication and security standards within the realm of academic documentation management.

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