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All Journal AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Infotekmesin
Listyaningrum, Rostika
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Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering Social Sciences

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Penerapan Aplikasi Retribusi Tiket Masuk (ARTM) Obyek Wisata Pantai Widarapayung Kabupaten Cilacap Purwanto, Riyadi; Prasetyanti, Dwi Novia; Listyaningrum, Rostika; Supriyono, Abdul Rohman; Prabowo, Annas Setiawan; Bahroni, Isa; Syafirullah, Lutfi; Satriawan, Dodi
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 8 No 4 (2024): November
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v8i4.15164

Abstract

Salah satu obyek wisata di Kabupaten Cilacap yang dapat dikunjungi adalah Pantai Widarapayung. Pengelolaan obyek wisata tersebut merupakan tugas Dinas Pariwisata dan Kebudayaan Kabupaten Cilacap dan pelaksanaannya dikelola oleh Koperasi KODIM 0703 Cilacap. Retribusi tiket masuk pengunjung dilokasi obyek wisata Pantai Widarapayung merupakan salah satu sumber pendapatan Daerah. Sistem retribusi tiket masuk ke lokasi Pantai Widarapayung yang berjalan saat ini masih dilakukan secara konvensional dimana penjaga loket menghitung besaran biaya tiket masuk secara manual dan selanjutnya dicatat dalam buku laporan. Berdasarkan hasil observasi, hal ini mengakibatkan beberapa permasalahan antara lain, pengelolaan retribusi tiket masuk masih belum terorganisir dengan baik, sering terjadi kesalahan dalam perhitungan biaya tiket masuk yang disebabkan oleh human error, adanya ketidaksesuaian antara jumlah pengunjung dengan jumlah pendapatan yang diterima. Disamping itu, buku laporan mudah rusak dan hilang sehingga pengelola pantai sering mengalami kesulitan dalam mengontrolnya. Salah satu solusi permasalahan ini adalah perlu dikembangkan Aplikasi Retribusi Tiket Masuk (ARTM) yang berfungsi untuk mengelola retribusi tiket masuk obyek wisata Pantaiwidara Payung, sehingga pengelelolaan retribusi tiket masuk menjadi lebih terorganisir. Dengan demikian permasalahan-permasalah yang ada pada pengelolaan retribusi tiket masuk menuju obyek wisata Pantai Widarapayung saat ini dapat terselesaikan.
Penerapan Aplikasi Retribusi Tiket Masuk (ARTM) Obyek Wisata Pantai Widarapayung Kabupaten Cilacap Purwanto, Riyadi; Prasetyanti, Dwi Novia; Listyaningrum, Rostika; Supriyono, Abdul Rohman; Prabowo, Annas Setiawan; Bahroni, Isa; Syafirullah, Lutfi; Satriawan, Dodi
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 8 No 4 (2024): November
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v8i4.15164

Abstract

Salah satu obyek wisata di Kabupaten Cilacap yang dapat dikunjungi adalah Pantai Widarapayung. Pengelolaan obyek wisata tersebut merupakan tugas Dinas Pariwisata dan Kebudayaan Kabupaten Cilacap dan pelaksanaannya dikelola oleh Koperasi KODIM 0703 Cilacap. Retribusi tiket masuk pengunjung dilokasi obyek wisata Pantai Widarapayung merupakan salah satu sumber pendapatan Daerah. Sistem retribusi tiket masuk ke lokasi Pantai Widarapayung yang berjalan saat ini masih dilakukan secara konvensional dimana penjaga loket menghitung besaran biaya tiket masuk secara manual dan selanjutnya dicatat dalam buku laporan. Berdasarkan hasil observasi, hal ini mengakibatkan beberapa permasalahan antara lain, pengelolaan retribusi tiket masuk masih belum terorganisir dengan baik, sering terjadi kesalahan dalam perhitungan biaya tiket masuk yang disebabkan oleh human error, adanya ketidaksesuaian antara jumlah pengunjung dengan jumlah pendapatan yang diterima. Disamping itu, buku laporan mudah rusak dan hilang sehingga pengelola pantai sering mengalami kesulitan dalam mengontrolnya. Salah satu solusi permasalahan ini adalah perlu dikembangkan Aplikasi Retribusi Tiket Masuk (ARTM) yang berfungsi untuk mengelola retribusi tiket masuk obyek wisata Pantaiwidara Payung, sehingga pengelelolaan retribusi tiket masuk menjadi lebih terorganisir. Dengan demikian permasalahan-permasalah yang ada pada pengelolaan retribusi tiket masuk menuju obyek wisata Pantai Widarapayung saat ini dapat terselesaikan.
PENERAPAN METODE SIMPLEKS UNTUK OPTIMASI PRODUKSI IKAN AIR TAWAR DAN IKAN AIR PAYAU DI KABUPATEN CILACAP SERTA ANALISIS KELAYAKAN PRODUKSI SECARA SENSITIVITAS Listyaningrum, Rostika; Nur Afiati, Ika
Infotekmesin Vol 9 No 02 (2018): Infotekmesin, Juli 2018
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v9i02.16

Abstract

Cilacap Regency is one of region whose good potential in process of waterpark cultivation. The resource potential of fresh water cultivation and brackish water and is distribution is almost in CilacapRegency, and it still has potential to develop. This research discussed the application of simplex method on the productivity of fresh water cultivation and brackish water in Cilacap Regency. The optimal solution from simplex method was tested its change of reliability with sensitivity analysis. The maximum productivity of fresh water and brackish water in 2014 till 2016 was 28.784,4494 tons.
Penerapan Data Mining dalam Analisis Prediksi Kanker Paru Menggunakan Algoritma Random Forest Sari, Laura; Romadloni, Annisa; Listyaningrum, Rostika
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.v14i1.1751

Abstract

Cancer is the second highest cause of death in the world. In Indonesia, it is a disease with a high mortality rate. Most patients do not realize that they have lung cancer thus the treatment is sometimes too late. A prediction method with a high degree of accuracy is needed to detect lung cancer earlier. Previous research used data mining calcification methods with the Naïve Bayes algorithm to predict lung cancer. This research resulted in high recall values for the positive class (Yes class) but low for the negative class (No class). This research was made using the Random Forest algorithm which is known to have good performance. The modeling is optimized by applying the K-fold Cross Validation technique. The Random Forest algorithm produces a higher Accuracy value than the Naïve Bayes algorithm, which is 98.4%. This algorithm produces 100% Recall for the positive class, 80% for the negative class and provides a 100% correct prediction as can be seen from the AUC value of 1. Although a statistical test with a significance level of 5% shows the results of the two algorithms are not significantly different.
Metode Fuzzy Time Series Markov Chain Untuk Peramalan Curah Hujan Harian Sari, Laura; Romadloni, Annisa; Listyaningrum, Rostika; Hazrina, Fadhilla; Rahadi, Nur Wahyu
Infotekmesin Vol 15 No 1 (2024): Infotekmesin: Januari, 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i1.2182

Abstract

Cilacap Regency has diverse topography and geographical conditions which cause this region to have rainfall that varies spatially and temporally; therefore, a forecasting method to overcome these uncertainties and fluctuations is needed. Fuzzy Time Series Markov Chain utilizes Fuzzy logic which provides flexibility in handling uncertain and unstructured data. Moreover, the addition of Markov chain elements that utilize Fuzzy logic concepts provides flexibility in handling data allowing the model to capture inter-time relationships and changes in system state that depend on previous states. Therefore, the research aims to see the suitability of the Fuzzy Time Series Markov Chain for predicting daily rainfall in Cilacap Regency. The method is suitable for predicting rainfall data for Cilacap Regency. The accuracy value in this study can be seen from the RMSE and SMAPE values ​​on the training data (in-sample), respectively, which are 58.76469 and 0.7227493. Meanwhile, the testing data (out sample) was 56.01818 and 0.7055117.
Evaluasi Kinerja Model Machine Learning dalam Klasifikasi Penyakit THT: Studi Komparatif Naïve Bayes, SVM, dan Random Forest Prasetya, Nur Wachid Adi; Wanti, Linda Perdana; Purwanto, Riyadi; Bahroni, Isa; Listyaningrum, Rostika
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.v16i2.2798

Abstract

Classification of Ear, Nose, and Throat (ENT) diseases is essential to support faster and more accurate diagnosis. However, no prior studies have specifically compared the performance of Naïve Bayes, Support Vector Machine (SVM), and Random Forest algorithms in ENT cases. This study aims to evaluate and compare the three classification models in identifying ENT diseases with or without comorbidities. Medical record data were processed through preprocessing, feature selection using ANOVA, and class balancing with SMOTE. The results showed that SVM outperformed the other models with the highest accuracy (59%), followed by Random Forest (57%), and Naïve Bayes (48%). SVM demonstrated superior performance due to its consistent scores across all evaluation metrics. The study concludes that the choice of classification model significantly impacts the accuracy of ENT disease diagnosis.
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 Annas Setiawan Prabowo Annisa Romadloni Cahya Vikasari Dodi Satriawan, Dodi Dwi Novia Prasetyanti Dwi Novia Prasetyanti Hazrina, Fadhilla Isa Bahroni, Isa Lutfi Syafirullah Nur Afiati, Ika Nur Wachid Adi Prasetya Prasetyanti, Dwi Novia Rahadi, Nur Wahyu Riyadi Purwanto Sari, Laura Supriyono, Abdul Rohman Wanti, Linda Perdana