Article Per Year (5 Year)
p-Index From 2020 - 2025
1.99
P-Index
This Author published in this journals
All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Dinamisia: Jurnal Pengabdian Kepada Masyarakat Infotekmesin Journal of Innovation Information Technology and Application (JINITA) TIERS Information Technology Journal Jurnal Administrasi Bisnis Jurnal Abdimas: Pengabdian dan Pengembangan Masyarakat E-Amal: Jurnal Pengabdian Kepada Masyarakat
Laura Sari
Department Of Informatics, Politeknik Negeri Cilacap
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences Other

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 11 Documents
Search

 1   2 
Implementasi Metode Research and Development Pada Pengembangan Pembelajaran Matematika Berbasis Multimedia Linda Perdana Wanti; Laura Sari
Infotekmesin Vol 12 No 1 (2021): Infotekmesin: Januari 2021
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v12i1.279

Abstract

Mathematics is a lesson that is still a frightening specter for some students. There are several methods used to make mathematics fun to learn. One of them is to package material in mathematics to be more attractive and interesting, especially for children this can make them become interested in learning mathematics. The developed using research and development methods. This method begins by exploring the problem, collecting data needed, designing the product to be developed, validating the product design, testing the use of the system to be developed, revising the product, testing the product, revising the product and product design if there are errors or deficiencies and the last is mass production of product. This research aims to develop an interactive multimedia-based mathematics learning which can later be optimized to increase student interest in learning mathematics and be used to improve the quality of education.
Sistem Pakar Deteksi Dini Penyakit Preeklamsia pada Ibu Hamil Menggunakan Metode Certainty Factor Nur Wachid Adi Prasetya; Linda Perdana Wanti; Laura Sari; Lina Puspitasari
Infotekmesin Vol 13 No 1 (2022): Infotekmesin: Januari, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i1.1050

Abstract

Preeclampsia is a disease in pregnant women characterized by high blood pressure and positive urine protein. The disease has a high risk of maternal and fetal death, so there is a need for early detection of mothers at risk of preeclampsia. Early online detection of preeclampsia is the best solution during the Covid-19 pandemic by analyzing the influencing factors. The purpose of this study is to build an expert system for early detection of preeclampsia in pregnant women using the Certainty Factor method and the waterfall system development model in order to provide the possibility of pregnant women suffering from preeclampsia. Testing the accuracy of 30 medical record data for pregnant women resulted in a system accuracy level of 90%, while usability testing resulted in a user satisfaction level of 55 with the System Usability Testing (SUS) score criteria being "Poor", therefore improvements are needed on expert system in the future.
Comparison of Naive Bayes Method and Certainty Factor for Diagnosis of Preeclampsia Linda Perdana Wanti; Nur Wachid Adi Prasetya; Laura Sari; Lina Puspitasari; Annisa Romadloni
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 13 No 2 (2022): Vol. 13, No. 2 August 2022
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2022.v13.i02.p04

Abstract

Preeclampsia is a disease often suffered by pregnant women caused by several factors such as a history of heredity, blood pressure, urine protein, and diabetes. The data sample used in this study is data on pregnant women in the 2020 time period recorded at health services in the former Cilacap Regency. This study was conducted to compare the final results of the Naive Bayes method and the certainty factor method in providing the results of a diagnosis of preeclampsia seen from the symptoms experienced by these pregnant women. The naïve Bayes approach provides decisions by managing statistical data and probabilities taken from the prediction of the likelihood of a pregnant woman showing symptoms of preeclampsia. Symptoms of preeclampsia, while the certainty factor method determines the certainty value of the diagnosis of preeclampsia in pregnant women based on the calculation of the CF value. The research output compares the two methods, showing that the certainty factor method provides more accurate diagnostic results than the Naive Bayes method. It happens because the CF method requires a minimum value of 0.2 and a maximum of 1 for each rule on the factors/symptoms involved, while the Naive Bayes method only requires values of 0 and 1 for each factor causing preeclampsia in pregnant women.
Penerapan Data Mining dalam Analisis Prediksi Kanker Paru Menggunakan Algoritma Random Forest Laura Sari; Annisa Romadloni; 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.v14i1.1751

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.
Penerapan Analisis SWOT Terhadap Penentuan Strategi Peningkatan Daya Saing Saleh Pisang Nazen Rawalo Hety Dwi Hastuti; Laura Sari
xxxx-xxxx
Publisher : JADBISFISH: Jurnal Administrasi Bisnis Fakultas Ilmu Sosial dan Hukum

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pertumbuhan ekonomi Indonesia turut dikembangkan oleh usaha kecil dan menengah (UKM). UKM sendiri terkadang dihadapkan kurangnya akses pasar dan berjuang untuk merumuskan strategi bisnis yang tepat untuk diaplikasikan. UKM Saleh Pisang Nazen merupakan usaha makanan ringan yang berada di desa Tambaknegara Kecamatan Rawalo. Usaha ini mulai berdiri sejak tahun 2020. Makanan ringan berbahan dasar pisang ini hadir dengan cita rasa manis yang khas karena terbuat dari pisang yang matang dan manis. Penelitian ini bertujuan untuk menerapkan analisis SWOT terhadap strategi peningkatan daya saing Saleh Pisang Nazen. Metode penelitian yang digunakan adalah metode deskriptif kualitatif. Berdasarkan hasil penelitian, dismpulkan bahwa UKM Saleh Pisang Nazen memiliki peluang yang bagus untuk dikembangkan dengan memaksimalkan branding Saleh Pisang Nazen, terus melakukan inovasi dan lebih kreatif dalam menciptakan varian rasa baru dan aneka olahan pisang, harus menjaga kualitas bahan baku yang digunakan untuk memastikan kualitas produk olahannya serta aktif melakukan promosi melalui media sosial.
Pelatihan SIPAKPRIH untuk Deteksi Dini Preeklamsia sebagai Dukungan Peningkatan Kinerja IBI Kabupaten Cilacap Linda Perdana Wanti; Nur Wachid Adi Prasetya; Lina Puspitasari; Laura Sari; Annisa Romadloni
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 3 (2023): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v7i3.11586

Abstract

IBI (Indonesian Midwives Association) Cilacap Regency is a forum for the association of midwife medical personnel in the Cilacap Regency. The performance of midwives can be continuously improved through training that supports all health service activities in the community. One of them is training in the use of information systems to detect the presence of preeclampsia in pregnant women (SIPAKPRIH) from the first to the third trimester by selecting the causative factors experienced by pregnant women. Midwives can take advantage of the expert system to support the performance of midwives in terms of health services for the community, especially pregnant women and the babies/fetus they contain. The solution proposed through this PkM activity is to improve the performance of midwives, especially midwives in Cilacap Regency in supporting health service activities to the community that are useful for monitoring the health of mothers and babies during pregnancy. The output target of this PkM activity is to increase the skills and knowledge of midwives for monitoring the health of pregnant women who are detected with preeclampsia through optimizing SIPAKPRIH.
Implementation of LightGBM and Random Forest in Potential Customer Classification Laura Sari; Annisa Romadloni; Rostika Lityaningrum; Hety Dwi Hastuti
TIERS Information Technology Journal Vol. 4 No. 1 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v4i1.4355

Abstract

Classification is one of the data mining techniques that can be used to determine potential custumers. Previous research show that the boosting method, especially LGBM, produces the highest accuracy value of all models, namely 100%. Meanwhile, for the two bagging methods, Random Forest produced the highest accuracy compared to Extra Trees, namely 99.03%. The research uses the LGBM and Random Forest methods to classify potential customers. The results of this study indicate that in imbalance data the LightGBM method has better accuracy than the Random Forest, which is 85.49%, when the Random Forest is unable to produce a model. The SMOTE method used in this study affects the accuracy of the random forest but does not affect the accuracy of LightGBM. Over all the Accuracy, Recall, Specificity, and Precision values, Random Forest produces a good value compared to LightGBM on balanced data. Meanwhile, LightGBM is able to handle unbalanced data.
Peningkatan Pemahaman Jiwa Leadership Mahasiswa Politeknik Negeri Cilacap Melalui Pelatihan Kepemimpinan Oman Somantri; Ratih Hafsarah Maharrani; Annisa Romadloni; Abdul Rohman Supriyono; Laura Sari
Jurnal Abdimas: Pengabdian dan Pengembangan Masyarakat Vol 5 No 1 (2023)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/jppm.v5i1.1107

Abstract

Kesulitan dalam memahami kepemimpinan sekaligus memiliki jiwa pemimpin menjadi salah satu masalah penting diantara mahasiswa. Pemahaman atas jiwa leadership yang dimilii oleh dirinya akan membawa dampak yang signifikan terhadap kehidupannya terlebih dalam menjalankan sebuah organisasi kampus, sehingga diperlukan upaya memupuk jiwa kepemimpinan yang dapat diterapkan dan diimplementasikan untuk menjalankan roda organisasi di kampus. Metode pelaksanaan kegiatan dilakukan dengan beberapa proses yaitu tahapan perencanaan, tahapan assessment, tahapan pelaksanaan, dan tahapan evaluasi kegiatan. Hasil kegiatan pelatihan yang dilaksanakan cukup dapat memberikan pengaruh yang signifikan terhadap pemahaman para peserta pelatihan untuk memahami materi yang disampaikan. Hasil kepuasan peserta pelatihan memperlihatkan 80% peserta kegiatan tingkat pemahamannya terhadap materi yang disampaikan meningkat.
REKAYASA MESIN PEMBUAT PUPUK ORGANIK BERBENTUK PELET DARI CAMPURAN SAMPAH ORGANIK DAN KOTORAN SAPI DI KELURAHAN WIDARAPAYUNG WETAN Nurlinda Ayu Triwuri; Oto Prasadi; Ayu Pramita; Ilma Fadlilah; Fadhillah Hazrina; Laura Sari; Dwi Novia
E-Amal: Jurnal Pengabdian Kepada Masyarakat Vol 2 No 1: Januari 2022
Publisher : LP2M STP Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47492/eamal.v2i1.1221

Abstract

Permasalahan yang dialami oleh warga di Desa Widarapayung Wetan Kecamatan Binangun adakah minimnya pengetahuan warga tentang teknik pengolahan lombah kotoran ternak dan sampah organik menjadi produk yang bermanfaat. Melalui kegiatan pengabdian ini, dipandang perlunya ada pendampingan program produksi pupuk organik menggunakan mekanisasi pakan mandiri atau buatan sendiri. Memanfaatkan kotoran ternak dan sampah organik yang menumpuk di lingkungan Widarapayung menjadi pupuk organik dalam bentuk pelet dapat menjadi solusi alternatif bagi warga jika dihadapkan dalam kondisi sulitnya membeli pupuk NPK pabrik, jika harga satuan melonjak tinggi. Sampah organik yang berserakan akan diolah dengan baik sehingga dapat meningkatkan daya dukung lingkungan dan meningkatkan pendapatan peternak dan petani. Disamping itu, karena memanfaatkan bahan sisa peternakan dan pekerbunan warga, maka secara tidak langsung dapat meningkatkan produktifitas warga Widarapayung. Tujuan dari kegiatan ini adalah melakukan introduksi pemanfaatan teknologi kepada warga Widarapayung melalui pendampingan dan pelatihan untuk meningkatkan wawasan IPTEK bagi warga Widarapayung, selain itu untuk meminimalkan ketergantungan warga dengan produk pabrikan. Mesin pembuat pelet dibuat dengan kapasitas produksi 120 kg/jam. Mesin pelet yang dibuat digerakan oleh mesin diesel dengan kapasitas 6,5 HP, kapasitas maksimal 7 HP, dan kecepatan 2600 rpm. Secara keseluruhan mesin ini sangat efektif untuk menghasilkan pupuk organik dalam bentuk pelet. Strategi penyampaian materi dilakukan dengan memberikan pelatihan langsung kepada warga Widarapayung. Hasil dari pengabdian ini adalah bekal ilmu teknologi yang telah diwujudkan dalam bentuk mesin pelet, bahan baku, komposisi, dan proses produksi.
Metode Fuzzy Time Series Markov Chain Untuk Peramalan Curah Hujan Harian Laura Sari; Annisa Romadloni; Rostika Listyaningrum; Fadhilla Hazrina; Nur Wahyu Rahadi
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.
Co-Authors Abdul Fadlil Abdul Rohman Supriyono Annisa Romadloni Arif Wirawan Muhammad Ayu Pramita Davito Rasendriya Rizqullah Putra Dwi Novia Fadhilla Hazrina Fadhillah Hazrina Fadlilah, Ilma Hety Dwi Hastuti Imam Riadi Lina Puspitasari Linda Perdana Wanti Muhammad Nur Faiz Nur Wachid Adi Prasetya Nur Wahyu Rahadi Nurlinda Ayu Triwuri Oman Somantri Oto Prasadi Ratih Hafsarah Maharrani Rostika Listyaningrum Rostika Lityaningrum Santi Purwaningrum Sukma Aji