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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

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.

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

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.

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

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.

Analisis Kinerja Algoritme TCP Congestion Control Berdasarkan Single dan Multiple Flow pada Multi-Path Routing Sutawijaya, Bayu; Basuki, Achmad; Bachtiar, Fitra Abdurrachman
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 5: Oktober 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020752402

Teknik multi-path routing merupakan solusi efektif untuk menambah kapasitas bandwidth jaringan. Namun, TCP menggunakan multiple paths sama dengan di single path. Penelitian ini melakukan analisis kinerja algoritme TCP congestion control Reno, BIC, CUBIC, dan BBR pada multi-path routing dengan setiap multiple paths menggunakan cost yang sama. Analisis yang dilakukan meliputi perbandingan antara single path routing dengan multi-path routing, single flow, dan multiple flow. Analisis single flow meliputi link delay dan loss rate. Sedangkan analisis multiple flow meliputi inter TCP protocol fairness dan fairness antara TCP dengan UDP. Semua evaluasi dilakukan berdasarkan emulasi pada VirtualBox. Berdasarkan hasil emulasi, multi-path routing dapat berdampak pada packet reordering, tetapi tidak mengakibatkan penurunan rata-rata throughput yang signifikan. Pada single flow, BBR merupakan algoritme TCP congestion control terbaik pada multi-path routing. Namun, pada multiple flow, CUBIC merupakan algoritme TCP congestion control terbaik pada multi-path routing. Pada evaluasi link delay, rata-rata RTT BBR lebih rendah hingga 58 ms dibandingkan dengan Reno, BIC, dan CUBIC. Sedangkan pada evaluasi loss rate, rata-rata throughput BBR lebih tinggi hingga 12 Mbps dibandingkan dengan Reno, BIC, dan CUBIC. Pada evaluasi inter TCP protocol fairness dan fairness antara TCP dengan UDP, fairness CUBIC paling mendekati 1 dibandingkan dengan Reno, BIC, dan BBR. AbstractThe multi-path routing technique is an effective solution to increase network bandwidth capacity. However, TCP uses multiple paths similar to a single path. This study analyzes the performance of TCP congestion control algorithms Reno, BIC, CUBIC, and BBR on multi-path routing with each multiple paths using the same cost. The analysis includes a comparison between single path routing and multi-path routing, single flow, and multiple flows. In a single flow, the analysis includes link delay and loss rate. Whereas in multiple flows, the analysis includes inter TCP protocol fairness and fairness between TCP and UDP. All evaluations are based on emulation in VirtualBox. Based on the results from emulation, multi-path routing can have an impact on packet reordering but does not result in a significant degrade in average throughput. In a single flow, BBR is the best TCP congestion control algorithm on multi-path routing. However, in multiple flows, CUBIC is the best TCP congestion control algorithm on multi-path routing. In the link delay evaluations, the average RTT on BBR up to 58 ms lower than Reno, BIC, and CUBIC. Whereas in the loss rate evaluations, the average throughput on BBR up to 12 Mbps higher than Reno, BIC, and CUBIC. In the evaluation of inter TCP protocol fairness and fairness between TCP and UDP, fairness on CUBIC is closest to 1 than Reno, BIC, and BBR.

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

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

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..

DIGI-TREE: Manajemen Digital Pohon untuk Edukasi, Rekreasi, dan Konservasi Berbasis Komunikasi Visual Susenohaji, Susenohaji; Dhanias, Fitriana Rakhma; Sutawijaya, Bayu; Muhammad, Rifki; Nabila, Nabila
ABDI MOESTOPO: Jurnal Pengabdian Pada Masyarakat Vol 9, No 1 (2026): Januari 2026
Publisher : Universitas Prof. Dr. Moestopo (Beragama)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32509/abdimoestopo.v9i1.6278

Tree management and conservation in urban and rural areas is still dominated by conventional methods that limit access to information and community participation. This community service activity aims to implement DIGI-TREE, a QR code-based digital tree management system as a medium for environmental education and conservation. The implementation method was descriptive-applicative through system design, installation of QR codes on trees, provision of visual content in the form of infographics and educational videos, and assistance in the use of the system to the community. The results of the community service showed that DIGI-TREE made it easier for the community to access real-time tree information, increased understanding of the ecological functions of trees, and encouraged community involvement in environmental monitoring. Information presented visually has proven to be easier to understand than conventional media. Therefore, DIGI-TREE has the potential to become a technology-based community service model that supports participatory and sustainable tree management and environmental conservation.

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

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

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