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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 JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) E-Link: Jurnal Teknik Elektro dan Informatika 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 Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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ECG-Based Heart Rate Variability and KNN Classification for Early Detection of Baby Blues Syndrome in Postpartum Mothers Megawati, Citra Dewi; Asriningtias, salnan Ratih; Bima Romadhon Parada Dian; Teo Pei Kian; Sutawijaya, Bayu; Fransiska, Ratna Diana
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 4 (2025): Articles Research October 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i4.14956

Abstract

Early detection of baby blues syndrome plays an important role in preventing postpartum emotional disturbances from developing into more serious mental health conditions. This study proposes a simple and non-invasive approach to identify early signs of baby blues in postpartum mothers by analyzing electrocardiogram (ECG) signals using the K-Nearest Neighbor (KNN) algorithm. The ECG data were gathered through wearable sensors and processed to extract heart rate variability (HRV) features such as RMSSD, SDNN, entropy, and energy. These features were then used to train and test a KNN classification model through a five-fold cross-validation process. KNN was chosen because it is easy to implement, does not assume any specific data pattern, and works well with small datasets like those commonly found in clinical settings. Its ability to group data based on similarity makes it suitable for recognizing subtle physiological changes linked to emotional stress. The model reached an accuracy of 87.5%, with strong precision and recall scores, showing its reliability in distinguishing mothers who show early symptoms of baby blues from those who do not. Among all features, RMSSD and SDNN had the highest impact, pointing to reduced parasympathetic activity in affected individuals. These findings suggest that combining HRV analysis with a straightforward machine learning approach like KNN offers a promising, low-cost solution for early emotional screening in maternal care, especially where resources are limited.
RANCANG BANGUN SISTEM INFORMASI DESTINASI DAN KALKULATOR PAKET WISATA DI KABUPATEN TRENGGALEK UNTUK SERATUS DESA WISATA BERBASIS WEB Asriningtias, Salnan Ratih; Rosalin, Sovia; Pawestri, Titi Ayu; Natalia, Deasy Chrisnia; Irmawati, Dini Kurnia
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
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. 
Integrating Agile Development and Content-Based Filtering for Personalized Digital Cultural Heritage Applications: A Case Study of Sri Ranggah Rajasa Sang Amurwabhumi Megawati, Citra Dewi; Asriningtias, salnan Ratih; Teo Pei Kian; Sutawijaya, Bayu
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15555

Abstract

The preservation of Indonesia’s cultural heritage increasingly requires digital innovation that not only archives historical material but also engages users through adaptive interaction. However, existing digital cultural platforms seldom provide personalized learning experiences and often lack iterative user-centered development, creating a clear gap in adaptive digital cultural heritage applications. This study aims to design and develop a cultural application titled Sri Ranggah Rajasa Sang Amurwabhumi using a hybrid framework that integrates the Agile Development Method with a Content-Based Filtering (CBF) approach. Agile was applied through iterative cycles of design, development, implementation, integration, and testing, enabling continuous enhancement based on user feedback. Meanwhile, the CBF algorithm was used to generate personalized cultural content recommendations by analyzing semantic similarities among historical items. The novelty of this research lies in the unified hybridization of Agile and CBF to support adaptive, personalized digital cultural learning centered on a specific Indonesian cultural figure. Data were gathered from 30 respondents, including students and cultural practitioners, through usability testing and structured questionnaires. Results indicate high performance across key aspects: functionality (91%), usability (90%), recommendation accuracy (88%), and user satisfaction (93%). These findings demonstrate that combining Agile and CBF strengthens technical reliability while improving engagement through adaptive content delivery. Agile supports iterative refinement of user interfaces and system responsiveness, whereas CBF enables intelligent personalization in cultural learning environments. Nevertheless, this study is limited by its modest sample size and its focus on a single cultural topic, which may reduce generalizability. Future work will expand the dataset, incorporate multimodal cultural content, and validate the hybrid framework across broader Indonesian cultural domains..
Rancang Bangun Rhodamine Detector menggunakan Metode Fuzzy Tsukamoto berbasis Internet of Things Andayani, Ulfa; Wulandari, Eka Ratri Noor; Asriningtias, Salnan Ratih; Sutawijaya, Bayu; Rahmah, Hafrida
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.16269

Abstract

This study developed a detection device capable of identifying the presence of Rhodamine B in food using an Internet of Things (IoT)-based Fuzzy Tsukamoto method. Rhodamine B is a coloring agent commonly used in the food industry, but its presence poses health risks. The Fuzzy Tsukamoto method was applied for its ability to manage uncertain information, while IoT technology enabled real-time monitoring. The research resulted in a detection tool with high accuracy and fast response time. Based on validation using 28 field samples, the fuzzy Tsukamoto-based detection system achieved a classification accuracy of 96.5%. The integration of these technologies enhanced analytical precision and allowed direct monitoring across various food types. The findings demonstrate that the developed detection device is efficient, reliable, and compliant with food safety standards, making it suitable for use in food monitoring and quality control processes
PEMODELAN PREDIKSI KELULUSAN TEPAT WAKTU MAHASISWA D3 TEKNOLOGI INFORMASI MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS (KNN) Salnan Ratih Asriningtias; Dwi Utari Surya; Eka Ratri Noor Wulandari; Mochamad Dimas Putra Hermawan; Rifqi Alfiansyah Kamil; David Kurniawan
E-Link: Jurnal Teknik Elektro dan Informatika Vol. 20 No. 2: Oktober 2025
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/e-link.v20i2.10963

Abstract

Peningkatan jumlah mahasiswa pada Program Studi D3 Teknologi Informasi menyebabkan pengelolaan kelulusan tepat waktu menjadi semakin menantang. Dalam konteks ini, metode machine learning digunakan untuk menganalisis pola secara komprehensif dan memprediksi tingkat kelulusan tepat waktu. Dataset yang digunakan berjumlah 608 mahasiswa yang terdiri dari angkatan 2018 hingga 2020, dengan atribut seperti IPK Semester 1–6, jenis kelamin, serta jalur masuk, yang keseluruhannya berkontribusi pada pemahaman faktor-faktor yang memengaruhi kelulusan tepat waktu. Penelitian ini menerapkan dan mengevaluasi algoritma machine learning, khususnya K-Nearest Neighbors (KNN). Proses pemodelan dilakukan melalui pembagian data menggunakan metode train-test split dengan rasio 70:30 dan divalidasi lebih lanjut menggunakan 10-fold cross-validation untuk memastikan kemampuan generalisasi model. Evaluasi kinerja model dilakukan menggunakan metrik accuracy, precision, recall, dan F1-score. Hasil pengujian menunjukkan bahwa model KNN menghasilkan performa terbaik dengan nilai accuracy sebesar 84%, precision 79%, recall 98%, dan F1-score 87%, melampaui performa Decision Tree dan Random Forest. Tingginya nilai recall menunjukkan kemampuan KNN yang sangat baik dalam mendeteksi mahasiswa yang berpotensi lulus tepat waktu. Kebaruan penelitian ini terletak pada penerapan dan evaluasi komprehensif model KNN dengan validasi berlapis (train-test split dan cross-validation) pada konteks Program Studi D3 Teknologi Informasi di Indonesia, yang masih jarang dikaji dalam penelitian sebelumnya. Temuan ini diharapkan dapat menjadi dasar pengambilan keputusan akademik dalam perencanaan intervensi dini guna meningkatkan capaian kelulusan tepat waktu mahasiswa.
Co-Authors Abdullah, Harnan Malik Bima Romadhon Parada Dian David Kurniawan Dian Kusumaningtyas, Dian Dwi Utari Surya Dwi Utari Surya Eka Ratri Noor Wulandari 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 Irmawati, Dini Kurnia Megawati, Citra Dewi Mochamad Dimas Putra Hermawan Myro Boyke Persijn Natalia, Deasy Chrisnia Natalia, Deasy Chrisnia Novita Rosyida Pawestri, Titi Ayu Pawestri, Titi Ayu Persijn, Myro Boyke Rachmad Andri Atmoko Rahmah, Hafrida Ratna Diana Fransiska Rifqi Alfiansyah Kamil Rosalin, Sovia Rosyida, Novita Sovia Rosalin Sutawijaya, Bayu Teo Pei Kian Ulfa Andayani, Ulfa Widia, I Dewa Made Wulandari, Eka Ratri