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All Journal Jurnal EECCIS Jurnal VOK@SINDO Jurnal Informatika dan Teknik Elektro Terapan Journal of Development Research Sinkron : Jurnal dan Penelitian Teknik Informatika J I M P - Jurnal Informatika Merdeka Pasuruan Jurnal Pengabdian Masyarakat Bestari (JPMB)
Salnan Ratih Asriningtias, Salnan Ratih
Program Studi Magister Teknik Elektro Fakultas Teknik, Universitas Brawijaya
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering Social Sciences Other

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Cluster Validity Index to Determine the Optimal Number Clusters of Fuzzy Clustering for Classify Customer Buying Behavior I Dewa Made Widia; Salnan Ratih Asriningtias; Sovia Rosalin
Journal of Development Research Vol. 5 No. 1 (2021): Volume 5, Number 1, May 2021
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/jdr.v5i1.134

Abstract

One of the strategies in order to compete in Batik MSMEs is to look at the characteristics of the customer. To make it easier to see the characteristics of customer buying behavior, it is necessary to classify customers based on similarity of characteristics using fuzzy clustering. One of the parameters that must be determined at the beginning of the fuzzy clustering method is the number of clusters. Increasing the number of clusters does not guarantee the best performance, but the right number of clusters greatly affects the performance of fuzzy clustering. So to get optimal number cluster, we can measured the result of clustering in each number cluster using the cluster validity index. From several types of cluster validity index, NPC give the best value. Optimal number cluster that obtained by the validity index is 2 and this number cluster give classify result with small variance value
Optimasi Training Neural Network Menggunakan Hybrid Adaptive Mutation PSO-BP Salnan Ratih Asriningtias; Harry Soekotjo Dachlan; Erni Yudaningtyas
Jurnal EECCIS Vol 9, No 1 (2015)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (264.293 KB)

Abstract

Optimization of training neural network using particle swarm optimization (PSO) and genetic algorithm (GA) is a solution backpropagation’s problem. PSO often trapped in premature convergent (convergent at local optimum) and GA takes a long time to achieve convergent and crossover makes worse the results. In this research adaptive mutation particle swarm optimization and backpropagation (AMPSO-BP) is used for training the neural network of the iris plant, breast cancer, wine, glass identification and pima indian diabetes. The addition of PSO with adaptive mutation to prevent premature convergent and BP to increase the efficiency of local searching. AMPSO-BP training results will be compared with the GA and BP. The test results showed AMPSO-BP is able to optimize the process of training the neural network. AMPSO-BP more rapidly achieve the minimum error (global minimum), fast convergent and have the ability memorization and generalization with more accurate results than the other methods.Index Terms—Adaptive Mutation, Backpropagation, Particle Swarm Optimization, Training Neural Network.
Black Box Testing Menggunakan Boundary Value Analysis dan Equivalence Partitioning pada Aplikasi Pengadaan Bahan Baku Batik dengan Pendekatan Use Case I Dewa Made Widia; Sovia Rosalin; Salnan Ratih Asriningtias; Elta Sonalitha
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 6, No 1 (2021): MARET
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v6i1.300

Abstract

The batik raw material purchase order application is a website application that will be used by Batik MSMEs to be able to help managers make decisions in determining the quantity of raw material orders. To ensure the application meets the expected functional requirements, testing is required. Testing is done using Black Box Testing, which is validating the output from the given data input. Test cases in black box testing can be designed using use cases, because the functional requirements of the application are described in the use case diagram. Test case design that can assist in finding application errors are an important consideration in application testing. There are several types of methods that can be used in determining test cases including Boundary Value Analysis and Equivalence Partitioning. Boundary value analysis can only be used to test data types with range values. Whereas the Equivalence partition is used to exploit all possible data based on defined criteria. So in this study the test was carried out by combining Boundary Value Analysis and Equivalence Partitioning. The test results show the method can find errors from effective applications, this is evidenced by the DRE value obtained of 0.45, which means that 45% of the test cases built did not pass the test.Keyword— Black Box Testing, Boundary Analysis Value, Equivalence Partitioning, MSMEs, Use Case
Training on Using Google Data Studio for Real-Time and Interactive Management of Beji Village Data and Information Rachmad Andri Atmoko; Salnan Ratih Asriningtias; Myro Boyke Persijn
Jurnal Pengabdian Masyarakat Bestari Vol. 1 No. 8 (2022): November 2022
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/jpmb.v1i8.1710

Abstract

The use of information technology is very important to support speed and ease in serving the community. However, at the village level there is still a shortage of specialized staff in the field of providing information technology-based applications. So, it is necessary to do community service in the form of technical guidance to take advantage of the use of applications such as Google workspace. Google workspace makes it very easy to manage data and information management. The data collection process is carried out using the Google form, data processing uses Google sheets, and administrative work can use the collaboration feature on Google Docs. This community service program is intended to explore Google workspace facilities, in creating data visualization dashboards using Google Data Studio. Villagers can monitor the movement of data in real-time against input from the Google form in the form of interactive graphics so that it can be used as a basis for making decisions more quickly.
APLIKASI PENGADAAN BAHAN BAKU BATIK MENGGUNAKAN METODE FUZZY TSUKAMOTO DAN FUZZY ANALYTICAL HIERARCHY PROCESS Salnan Ratih Asriningtias; Novita Rosyida; I Dewa Made Widia; Eka Ratri Wulandari
VOK@SINDO : Jurnal Ilmu-Ilmu Terapan dan Hasil Karya Nyata Vol 10, No 1 (2023)
Publisher : Fakultas Vokasi Universitas Brawijaya

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

Abstract

UMKM menjadi perhatian untuk dioptimasi mengingat UMKM adalah usaha kecil menengah dengan modal yang tidak terlalu besar. Segala upaya efisiensi harus terus diupayakan untuk membantu kinerja dan penekanan biaya produksi. Pentingnya efisiensi dalam proses order mempengaruhi penghematan biaya yang harus dikeluarkan untuk persediaan. Faktor utama yang mempengaruhi efisiensi dalam proses order diantaranya adalah pemilihan pemasok yang tepat dan penentuan jumlah order yang tepat. Pada penelitian ini digunakan pengembangan aplikasi  pengadaan bahan baku batik yang menerapkan metode Fuzzy Tsukamoto dan Fuzzy AHP guna memperoleh efisiensi dan efektifitas proses order. Fuzzy Tsukamoto untuk menentukan jumlah order dan Fuzzy AHP untuk pemilihan pemasok. Aplikasi pengadaan bahan baku batik dapat merekomendasikan pemasok untuk beli bahan baku, jumlah pemesanan bahan yang harus dipesan oleh manager beserta total biaya yang dikeluarkan dengan nilai MAPE 8.85% yang menujukkan bahwa tingkat akurasinya tinggi.Kata Kunci: Fuzzy AHP, Fuzzy Tsukamoto, Pemasok, UMKM
RANCANG BANGUN SISTEM INFORMASI DESTINASI DAN KALKULATOR PAKET WISATA DI KABUPATEN TRENGGALEK UNTUK SERATUS DESA WISATA BERBASIS WEB Salnan Ratih Asriningtias; Sovia Rosalin; Titi Ayu Pawestri; Deasy Chrisnia Natalia; Dini Kurnia Irmawati
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i1.3931

Abstract

Menurunnya jumlah wisatawan yang berkunjung ke Kabupaten Trenggalek di tahun 2020 pasca pandemi covid 19, menuntut pemerintah kabupaten Trenggalek untuk menyusun strategi dalam meningkatkan perekonimian. Dalam strateginya, Bupati Trenggalek menggagas program pengembangan Trenggalek Seratus Desa Wisata (SADEWA) dengan jargon MEROKET (Maju ekonomi rakyatnya, SDM yang kreatif dan Ekosistem yang terjaga). Dalam mewujudkan misi tersebut, Dinas Pariwisata Kabupaten Trenggalek meluncurkan program Peningkatan Daya Tarik Destinasi Pariwisata melalui Pemasaran Pariwisata. Pemasaran pariwisata dilakukan melalui media digital berupa website, karena memiliki tampilan yang lebih menarik, interaktif, informatif serta memiliki jangkauan pasar yang lebih luas. Namun, informasi tentang tempat wisata saja tidak cukup. Perlu adanya informasi pariwisata yang lebih lengkap terkait dengan fasilitas-fasilitas pendukung seperti penginapan, rumah makan, dan tranportasi yang terintegrasi. Oleh sebab itu perlu dikembangkanan Tourism Centre System dengan nama Sistem Informasi Destinasi dan Kalkulator Paket Wisata Di Kabupaten Trenggalek. Melalui sistem ini, selain mendapatkan informasi-informasi detail tentang destinasi wisata, para calon wisatawan dapat mengetahui kisaran biaya yang dibutuhkan ketika akan mengunjungi destinasi wisata serta produk-produk wisata di Kabupaten Trenggalek
Identification of Public Library Visitor Profiles using K-means Algorithm based on The Cluster Validity Index Asriningtias, Salnan Ratih; Wulandari, Eka Ratri Noor; Persijn, Myro Boyke; Rosyida, Novita; Sutawijaya, Bayu
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12901

Abstract

The existence of a public library in the Gampingan village has a positive impact, such as increasing the literacy culture of the village community. However, the library collection is not sufficient for the needs of visitors. Therefore, it is necessary to add library collections to fulfill the requirement. One of the solutions is mapping the library needs of visitors. The mapping can be done by identifying visitor profiles by grouping visitors based on the criteria of age, gender, type of visitor, and category of book library. One of the methods that can be used in the process of grouping visitors based on criteria is to use the K-Means Clustering method. Determining the number of K cluster centers at K-Means Clustering method that are not appropriate will give bad results, it is necessary to test the number of K cluster centers using the Cluster Validity index by measuring the clusters with cluster variance, within-cluster variance, and between-cluster variance. From the grouping process using K-Means Clustering with Cluster Validity index, we get 3 clusters of visitor profiles with a cluster variance value of less than 0.1. This shows that this method was able to identify the visitor profiles with high grouping accuracy values.
APLIKASI PENGADAAN BAHAN BAKU BATIK MENGGUNAKAN METODE FUZZY TSUKAMOTO DAN FUZZY ANALYTICAL HIERARCHY PROCESS Asriningtias, Salnan Ratih; Rosyida, Novita; Widia, I Dewa Made; Wulandari, Eka Ratri
VOK@SINDO : Jurnal Ilmu-Ilmu Terapan dan Hasil Karya Nyata Vol. 10 No. 1 (2023)
Publisher : Fakultas Vokasi Universitas Brawijaya

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

Abstract

UMKM menjadi perhatian untuk dioptimasi mengingat UMKM adalah usaha kecil menengah dengan modal yang tidak terlalu besar. Segala upaya efisiensi harus terus diupayakan untuk membantu kinerja dan penekanan biaya produksi. Pentingnya efisiensi dalam proses order mempengaruhi penghematan biaya yang harus dikeluarkan untuk persediaan. Faktor utama yang mempengaruhi efisiensi dalam proses order diantaranya adalah pemilihan pemasok yang tepat dan penentuan jumlah order yang tepat. Pada penelitian ini digunakan pengembangan aplikasi  pengadaan bahan baku batik yang menerapkan metode Fuzzy Tsukamoto dan Fuzzy AHP guna memperoleh efisiensi dan efektifitas proses order. Fuzzy Tsukamoto untuk menentukan jumlah order dan Fuzzy AHP untuk pemilihan pemasok. Aplikasi pengadaan bahan baku batik dapat merekomendasikan pemasok untuk beli bahan baku, jumlah pemesanan bahan yang harus dipesan oleh manager beserta total biaya yang dikeluarkan dengan nilai MAPE 8.85% yang menujukkan bahwa tingkat akurasinya tinggi.Kata Kunci: Fuzzy AHP, Fuzzy Tsukamoto, Pemasok, UMKM
PERANCANGAN SENSOR GAS BERBASIS IoT UNTUK PEMANTAUAN KUALITAS UDARA Wulandari, Eka Ratri Noor; Rosyida, Novita; Sutawijaya, Bayu; Abdullah, Harnan Malik; Asriningtias, Salnan Ratih
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.4977

Abstract

Semakin bertambahnya jumlah penduduk maka semakin banyak pula sampah yang dihasilkan. Sampah yang membusuk atau terbakar menghasilkan beberapa komponen gas antara lain metana (CH4), amonia (NH3), karbon monoksida (CO), dan lain-lain. Dampak yang ditimbulkan dari gas-gas tersebut adalah menurunnya kualitas udara terutama di sekitar lokasi pembuangan sampah. Penurunan kualitas udara ini dapat membahayakan kondisi kesehatan. Dengan adanya persyaratan kualitas udara, maka perlu dilakukan analisa dan pemantauan kualitas gas secara berkala. Oleh karena itu, dengan pesatnya perkembangan teknologi, maka dikembangkan perangkat portabel untuk pemantauan kualitas udara berbasis Internet of Things (IoT). Sensor gas yang digunakan terdiri atas sensor metana TGS2911 dan sensor gas amonia MQ137. ESP32 digunakan sebagai unit pemrosesan yang memungkinkan transmisi dan analisis data secara real-time. Data yang dihasilkan dari pembacaan sensor akan ditampilkan pada sebuah website sehingga pengguna yang dapat digunakan untuk memantau kualitas udara secara real. 
Hyperparameter-Tuned Artificial Neural Networks for Early Stunting Prediction in Toddlers Asriningtias, Salnan Ratih; Megawati, Citra Dewi; Kusumaningtyas, Dian; Surya, Dwi Utari
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14695

Abstract

The growing accessibility of varied health data requires the creation of efficient and practical techniques for deriving actionable insights, particularly for the early identification of severe health issues. This study tackles the issue of recognizing stunting—a disorder with enduring health consequences—among children under five by employing Artificial Neural Networks (ANN) with hyperparameter optimization by GridSearchCV. The dataset, sourced from Kaggle, comprises 121,000 records detailing age, gender, height, and nutritional status according to WHO standards. Critical hyperparameters, including dropout rate, batch size, and epochs, were optimized using a five-fold cross-validation approach within GridSearchCV, ensuring a robust model that reduces overfitting and generalizes well to new data. The findings demonstrate a notable performance improvement, as the optimized ANN model attained an accuracy of 99%, exceeding the baseline model's 98%. Enhancements in accuracy, recall, and F1-score across the four stunting classifications—normal, stunted, severely stunted, and tall—underscore the improved specificity and sensitivity of the optimized model. This research demonstrates the efficacy of hyperparameter tuning in ANN for stunting prediction, offering a reliable tool for early intervention in malnutrition management.
Co-Authors Abdullah, Harnan Malik Bima Romadhon Parada Dian Dian Kusumaningtyas, Dian Dwi Utari Surya Eka Ratri Noor Wulandari Eka Ratri Wulandari Elta Sonalitha Erni Yudaningtyas Harry Soekotjo Dachlan I Dewa Made Widia I Dewa Made Widia Irmawati, Dini Kurnia Megawati, Citra Dewi Myro Boyke Persijn Natalia, Deasy Chrisnia Novita Rosyida Pawestri, Titi Ayu Persijn, Myro Boyke Rachmad Andri Atmoko Ratna Diana Fransiska Rosyida, Novita Sovia Rosalin Sutawijaya, Bayu Teo Pei Kian Widia, I Dewa Made Wulandari, Eka Ratri