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Dwi Novia Prasetyanti
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Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering

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Implementasi Profile Matching Pada Seleksi Ketua dan Wakil Ketua OSIS Alif Iftitah; Linda Perdana Wanti; Dwi Novia Prasetyanti; Nur Wachid Adi Prasetya; Andriansyah Zakaria
Infotekmesin Vol 13 No 2 (2022): Infotekmesin: Juli, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i2.1536

Abstract

The OSIS chairman is the highest leader in the OSIS management structure and is accompanied by a vice-chairman. Therefore, a selection with several criteria is needed to determine the best candidate. Things that are considered in this selection are realism, maturity, organizational experience, public speaking, discipline, character, organizational activity, and responsibility. By utilizing a decision support system, the best candidates are obtained for the candidate for chairman and vice-chairman of the student council. This system is made with the method used to assist the selection process, namely, profile matching. Profile matching is used to find the profile of a job that is sought from a predetermined specification. This method provides a solution and has a clear objective in decision-making. On the other hand, the method used to develop a decision support system is the incremental method. The selection of the incremental method is based on the fact that this method has an iterative nature, which can adapt to the many repetitions that occur during the development process. The novelty of this research is the recommendations generated from the developed decision support system. There are notifications about the results of decisions to users, in this case, the candidates for the OSIS chairman and vice chairman who are alternatives in the election process. This study resulted in recommendations in the form of candidates for OSIS chairman and vice chairman by the candidate's profile.
Penerapan Location Based Service (LBS) dan QR Code Detection pada Aplikasi Pemetaan dan Penjemputan Retribusi Parkir Kendaraan Berbasis Android Dwi Novia Prasetyanti; Purwanto, Riyadi; Rostika Listyaningrum
Infotekmesin Vol 14 No 1 (2023): Infotekmesin: Januari, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i1.1662

Abstract

One source of regional income for Cilacap Regency is the management of vehicle parking lots. Currently, parking area management is carried out by recording the identity of the parking location based on the street name, while the withdrawal of parking fees is carried out by towing officers who come to the parking location and then record it in a book. The current management of parking lots is still inaccurate because there are several street names that have more than one parking area which results in data redundancy. The conventional parking fee collection system causes frequent discrepancies in reports due to the potential for misuse of parking fees. The absence of tools that can be used by related agencies to control reports is the cause of the problem. The research objective is to develop an information system by applying LBS technology which functions to detect parking points precisely and QR Code Detection which functions to detect the identity of parking attendants. System development uses the ADDIE model. The results of the research are an information system for mapping parking lots and picking up parking fees based on Andorid which can help manage vehicle parking lots which includes mapping the location of parking lots and picking up vehicle parking fees.
Optimalisasi Sistem Informasi Layanan Keuangan dengan Metode First Come First Served (FCFS) Purwanto, Riyadi; Dwi Novia Prasetyanti; Cahya Vikasari; Rostika Listyaningrum
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2562

Abstract

One of the important things in financial management is financial services. Cilacap State Polytechnic (PNC) is a PTN as a Work Unit. Financial management at PNC refers to applicable government regulations, but financial service policies are the authority of the leadership as a strategy to create fast, effective, and accountable financial services. The budget usage policy stipulates that work units must propose budget usage based on the Fund Withdrawal Plan through a down payment form approved by the Financial Management Officer. The current problem is that down payment forms are often scattered or lost, so the response time for payments from finance is slow, and payment queues are often not in sequence. This results in activities being hampered. This research aims to create a prototype or development design for the Financial Services Information System at PNC. The FCFS method is used as a service scheduling algorithm based on arrival time to optimize financial services. In this way, the financial service process will be more organized, the response time for financial services will be faster, and the queue for service requests will be in line.
Pemanfaatan Algoritma Random Forest Regression dalam Memprediksi Kepuasan Mahasiswa Terhadap Dosen Listyaningrum, Rostika; Purwanto, Riyadi; Dwi Novia Prasetyanti; Cahya Vikasari; Artdhita Fajar Pratiwi
Infotekmesin Vol 16 No 2 (2025): Infotekmesin: Juli 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i2.2808

Abstract

Student satisfaction with lecturers is a key indicator in assessing the quality of higher education. However, commonly used evaluation approaches remain largely descriptive and subjective, making them less effective in supporting sustainable quality improvement. Moreover, the comprehensive use of lecturer competency indicators in predictive models is still limited. This study addresses the gap by developing a student satisfaction prediction model using the Random Forest Regression algorithm, optimized through grid search and feature selection using the Recursive Feature Elimination (RFE) method combined with 5-fold cross-validation. Data were collected from the EDOM system of Politeknik Negeri Cilacap, involving 24 indicators based on national lecturer competency standards, and analyzed using R software. The best model was achieved with parameters mtry = 1 and ntree = 300, yielding RMSE = 0.0222, MAE = 0.0118, and R² = 0.9959. The three most influential indicators identified were structured assignments, diversity of teaching methods, and punctuality. These findings are expected to inform policies for improving the quality of higher education.
Co-Authors Alif Iftitah Andriansyah Zakaria Cahya Vikasari Linda Perdana Wanti Listyaningrum, Rostika Nur Wachid Adi Prasetya Riyadi Purwanto Rostika Listyaningrum