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All Journal Jurnal Agroindustri JAIS (Journal of Applied Intelligent System) JTT (Jurnal Teknologi Terapan) Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Infotekmesin Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Santi Purwaningrum
Politeknik Negeri Cilacap
Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Public Health

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Implementasi Sistem Informasi Arsip Desa Widarapayung Wetan Cilacap Untuk Peningkatan Pelayanan Pemerintah Ratih Hafsarah Maharrani; Prih Diantono Abda’u; Muhammad Nur Faiz; Agus Susanto; Hety Dwi Astuti; Oman Somantri; Santi Purwaningrum
Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Vol 5, No 1 (2022): Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstormin
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/japhb.v5i1.3099

Abstract

Kondisi pengelolaan arsip di Desa Widarapayung Wetan Cilacap saat ini masih dilakukan secara konvensional, sedangkan kecepatan dan ketepatan dalam pencarian data arsip surat sangat berpengaruh kepada kualitas layanan. Dokumentasi surat masuk dan surat keluar saat ini masih secara konvensional dan berbentuk catatan yang ditulis pada buku besar berakibat sering terjadinya kesalahan dalam peyimpanan data kearsipan dan pencarian surat. Berdasarkan kesepakatan, untuk mengatasi permasalahan maka diberikanlah solusi dengan membangun sebuah aplikasi sistem informasi arsip yang dimplementasikan di desa Widarapayung Wetan Cilacap dengan harapan masalah dapat teratasi dan adanya peningkatan pelayanan. Tahapan kegiatan yang dilakukan yakni dengan melakukan assessment permasalahan, perencanaan kegiatan, pembangunan sistem, ujicoba sistem, implementasi dan evaluasi sistem, serta tahapan akhir adalah pelatihan user dan pendampingan. Berdasarkan hasil pembangunan sistem yang telah dibuat Desa Widarapayung Wetan Cilacap saat ini sudah dapat berupaya untuk meningkatkan pelayanan khususnya dalam pengelolaan arsip yang sudah dapat diakukan secara digital.
Comparation of Dice Similarity and Jaccard Coefficience Against Winnowing Algorithm For Similarity Detection of Indonesian Text Documents Santi Purwaningrum; Agus Susanto; Nur Wachid Adi Prasetya
Journal of Applied Intelligent System Vol 6, No 1 (2021): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v6i1.4453

Abstract

Plagiarism is the act of imitating and quoting and even copying or acknowledging other people's work as one's own work. Plagiarism is currently growing rapidly, especially in the world of education. So that plagiarism detection is needed to prevent plagiarism from growing rapidly. In response to this, this paper intends to conduct research that compares the dice similarity and the jaccard coefficient to find the best document similarity value level against the Winnowing algorithm which functions to find the fingerprint value of each document. The test results show that the winnowing algorithm is quite good at using the dice similarity level with the results of an average similarity value of 71.17615%  than testing using jaccard coefficient with the resulting value 35,58837%.
MODEL SUPPORT VEKTOR MACHINE (SVM) BERDASARKAN PARAMETER WINDOWS UNTUK PREDIKSI KEKUATAN GEMPA BUMI Oman Somantri; Santi Purwaningrum; Riyanto Riyanto
Jurnal Teknologi Terapan Vol 8, No 1 (2022): Jurnal Teknologi Terapan
Publisher : P3M Politeknik Negeri Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31884/jtt.v8i1.352

Abstract

Earthquakes are a type of natural disaster that currently cannot be predicted. Predicting the value of earthquake magnitude for related parties such as government and National Disaster Management Authority is very important. Furthermore, the results of earthquake predictions by several parties are used as indicators in post-earthquake response in minimizing the risks that will occur. Several studies have applied machine learning methods to predict earthquakes such as deep neural networks and parallel Support Vector Regression. In this article, we propose a data mining method using the Support Vector Machine (SVM) algorithm accompanied by the optimization of the windowing parameter value in the model that is applied to predict the value of the earthquake magnitude. Based on its advantages, the SVM model was chosen because it has been applicable in time series data processing. In the experimental stage process, parameter settings are first carried out, namely setting the kernel type, sampling type, and number of windowing to optimize the level of accuracy of the resulting model. The results showed that the best model with the smallest Root Mean Square Error (RMSE) was 0.712.
EFFECT OF ADDITION OF CARRAGEENAN CONCENTRATION ON QUALITY OF BREADFRUIT (Artocarpus atili) AND CANNABIS (Canna edulis) WET NOODLES Ari Kristiningsih; Khoeruddin Wittriansyah; Sari Widya Utami; Santi Purwaningrum
Jurnal Agroindustri Vol 12, No 1 (2022)
Publisher : BPFP Faperta UNIB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31186/j.agroindustri.12.1.39-47

Abstract

Excessive consumption of gluten can cause disturbances in the digestive system and can increase intestinal permeability. Breadfruit flour is an alternative in making wet noodles other than wheat flour which is low in gluten. Breadfruit flour which is processed into wet noodles has low adhesion and protein content.Canna flour and carrageenan were used to improve adhesion and squid ink and eggs were used to increase the protein content of breadfruit noodles. This  study aimed to  determine the effect of adding carrageenan with different concentrations on breadfruit noodles. The ratio of addition of carrageenan in this research was 0%,1%, 3%, 4%, and 5%. Carrageenan in breadfruit noodles causes the noodles break more easily than noodles without the addition of carrageenan. The use of eggs and squid ink on breadfruit noodles increased the protein content of noodles by ± 1.1%.The results of the proximate analysis of breadfruit noodles as a whole still do not reach the SNI standard for wet noodles.
SIPAMBULAN: Sistem Informasi Pelayanan Ambulan menggunakan Algoritma Djikstra Agus Susanto; Santi Purwaningrum
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.v14i1.1674

Abstract

The rapid development of information technology encourages innovation in various fields, including the field of disaster geographic information services. Lack of information on ambulance service providers is often the cause of delays in handling victims of natural disasters. Besides, the absence of information regarding the nearest route for ambulances to emergency service providers such as health centers and hospitals adds to the length of time for handling victims of natural disasters, resulting in increasingly severe victim losses, including life. This study aims to create a geographic information system that can be used to provide information on the location of the nearest ambulance service provider and emergency unit service. The system development research method uses the extreme programming method by implementing the Djikstra algorithm to determine the shortest route. This system testing process consists of testing the Djikstra algorithm and testing functionality using a usability scale. Djikstra's algorithm testing is done by comparing the results of calculating the shortest route for two location points with the results obtained when using the Google Maps application. The results of this test indicate that the system can display shorter routes than the routes generated by the Google Maps application. On the other hand, testing system functionality using the usability scale method to see system acceptance by users shows that the application can be used properly with a score obtained that is 77.
Model Library Support Vector Machine (LibSVM) untuk Sentiment Review Penilaian Pesisir Pantai Oman Somantri; Ratih Hafsarah Maharrani; Santi Purwaningrum
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.6367

Abstract

Improving services as an effort to provide the convenience of tourist destinations, especially on the south coast of Java, is a demand placed on tourism managers, which in the long run will yield positive impacts. The assessment is conducted to determine whether the tourism destination give positive impressions to the tourists. The application of machine learning-based text mining technology, especially a sentiment review, is one of the solutions proposed to overcome this problem, therefore predictions of coastal tourism potential can be known beforehand. This research proposed a coastal sentiment review model using the library support vector machine (LibSVM) method. The process proposed a model optimization based on feature weights using the particle swarm optimization (PSO) algorithm as a model optimization to increase the accuracy level. Efforts to improve the accuracy of the proposed model are the main contribution of this research. The results of research and experiments on the proposed model produced the best model named LibSVM_IG+PSO using the information gain (IG). On the other hand, PSO-based LibSVM method generated an accuracy level of 88.97%. The model proposed in this research is expected to serve as a decision support for tourists, government, and tourism managers in assessing sentiment towards the coastal maritime tourism.
Pengaruh Synonym Recognition dalam Deteksi Kemiripan Teks Menggunakan Winnowing dan Cosine Similarity Santi Purwaningrum; Agus Susanto; Ari Kristiningsih
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 3: Agustus 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i3.6375

Abstract

Plagiarism is an act of imitating, quoting and even copying or acknowledging the work of others as one’s own work. A final project is one of the mandatory requirements for students to complete learning at college. It must be written by the students based on their own ideas. However, there is much plagiarism because it is easy to carry out just by simply copying the text of other people’s ideas and then pasting it into a worksheet and admitting that the ideas are theirs. In addition, replacing some words in other people’s sentences with their own language style without properly acknowledging the original source of the quotation is also an act of plagiarism. A manual check for the final project also becomes an issue for the final project coordinator, i.e., it needs high accuracy and a relatively long time to check the plagiarism in the final project document. Therefore, implementing plagiarism detection mechanisms is necessary to mitigate the escalation of plagiarism occurrences. In response to those matters, this study aims to design a system capable of identifying textual similarities by focusing on sentences containing synonymous words. One of the used algorithms is synonym recognition, which detects words that possess synonymous meanings by comparing each term with the entries in a dictionary. The synonym recognition is combined with the winnowing method, functioning as a fingerprint-based text weighting. After the weight of each document is obtained, the similarity level between documents is calculated with the cosine similarity algorithm. The inclusion of synonym recognition in conjunction with the winnowing weighting method resulted in a notable gain of 3.11% in the average similarity scores for title and abstract detection, compared to the absence of synonym recognition. The results show that the used algorithms are accurate with accuracy testing and root mean squared error (RMSE).
Co-Authors Agus Susanto Ari Kristiningsih Hety Dwi Astuti Muhammad Nur Faiz Nur Wachid Adi Prasetya Oman Somantri Prih Diantono Abda`u Ratih Hafsarah Maharrani Riyanto Riyanto Sari Widya Utami Wittriansyah, Khoeruddin