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Pemetaan Tingkat Kriminalitas di Indonesia: Analisis Spasial dengan Pendekatan SIG pada Tingkat Provinsi Ronal Watrianthos; Sudi Suryadi; Kusmanto; Samsir Samsir
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.861

Indonesia memiliki Indeks Pembangunan Manusia yang rendah, yang menunjukkan bahwa masih ada pekerjaan yang harus dilakukan untuk meningkatkan kualitas hidup dan kesehatan masyarakatnya. Selain itu, Indonesia menghadapi banyak masalah sosioekonomi, termasuk populasi yang berlebihan, kemiskinan, tingkat pengangguran yang tinggi, dan sistem pendidikan yang buruk. Masalah-masalah ini dapat memengaruhi masyarakat, termasuk meningkatkan kejahatan. Banyak indikator yang umum digunakan dalam bidang statistik kriminal untuk mengukur kejahatan dari perspektif yang luas dan untuk menilai tingkat keparahannya. Tujuan dari penelitian ini adalah untuk menggambarkan distribusi tingkat kejahatan secara keseluruhan di antara provinsi-provinsi Indonesia, dengan penekanan khusus pada Sumatra dan Jawa. Studi ini menggunakan data dari Badan Pusat Statistik dari tahun 2010 hingga 2020 tentang jumlah kejahatan yang dilaporkan oleh petugas polisi regional. Objek yang diamati di masing-masing provinsi dikelompokkan ke dalam kelompok yang saling terkait menggunakan teknik pembelajaran tidak terbimbing dengan algoritma klasifikasi K-Means. Hasil menunjukkan bahwa antara tahun 2010 dan 2020, provinsi Bengkulu, Kepulauan Bangka Belitung, dan Banten memiliki tingkat kejahatan terendah dibandingkan provinsi lain di Sumatra dan Jawa. Hasil ini menunjukkan bahwa ketiga provinsi ini mungkin memiliki kemampuan yang lebih baik untuk mengatasi masalah sosioekonomi yang diketahui berkontribusi pada kejahatan.

Distribusi Spasial Unmet Need Pelayanan Kesehatan dengan Algoritma K-Means untuk Pemetaan Provinsi di Indonesia Kusmanto; Samsir Samsir; Ronal Watrianthos; Sudi Suryadi
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.862

Pemetaan spasial terhadap kebutuhan pelayanan kesehatan yang belum terpenuhi (unmet need) penting dilakukan untuk mengenali wilayah yang memerlukan prioritas intervensi guna meningkatkan akses dan kualitas layanan kesehatan. Penelitian ini bertujuan memetakan tingkat unmet need pelayanan kesehatan di 34 provinsi Indonesia tahun 2015-2022 dengan algoritma klasterisasi K-Means. Data unmet need dianalisis dan dievaluasi menggunakan Indeks Davies-Bouldin untuk menentukan jumlah klaster optimal. Hasil analisis menunjukkan 3 klaster provinsi optimal berdasarkan tingkat unmet need. Klaster 1 (DKI Jakarta, Bali, Papua) memiliki rata-rata unmet need terendah 2,47%. Klaster 2 (sebagian provinsi di Jawa dan Kalimantan) memiliki rata-rata unmet need sedang 5,46%. Klaster 3 (sebagian besar provinsi di luar Jawa) merupakan kelompok dengan unmet need tertinggi rata-rata 7,35%. Secara spasial, provinsi di luar Jawa cenderung berada di klaster dengan unmet need tinggi, sejalan dengan tantangan aksesibilitas pelayanan kesehatan. Hasil pemetaan K-Means ini dapat menjadi acuan dalam merumuskan rekomendasi peningkatan akses dan kualitas layanan kesehatan di provinsi-provinsi prioritas berdasarkan tingkat unmet need.

A Comprehensive Bibliometric Analysis of Deep Learning Techniques for Breast Cancer Segmentation: Trends and Topic Exploration (2019-2023) Agus Perdana Windarto; Anjar Wanto; S Solikhun; Ronal Watrianthos
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5274

The objective of this study is to perform a comprehensive bibliometric analysis of the existing literature on breast cancer segmentation using deep learning techniques. Data for this analysis were obtained from the Web of Science Core Collection (WOS-CC) that spans from 2019 to 2023. The study is based on a comprehensive collection of 985 documents that cover a substantial body of research findings related to the application of deep learning techniques in segmenting breast cancer images. The analysis reveals an annual increase in the number of published works at a rate of 16.69%, indicating a consistent and robust increase in research efforts during the specified time frame. Examining the occurrence of keywords from 2019 to 2023, it is evident that the term "convolutional neural network" exhibited a notable frequency, reaching its peak in 2021. However, the term "machine learning" demonstrated the highest overall frequency, peaking around 2021 as well. This emphasizes the importance of machine learning in the advancement of image segmentation algorithms and convolutional neural networks, which have shown exceptional effectiveness in image analysis tasks. Furthermore, the utilization of latent Dirichlet Allocation (LDA) to identify topics resulted in a relatively uniform distribution, with each topic having an equivalent number of abstracts. This indicates that the data set encompasses a diverse range of topics within the field of deep learning as it relates to breast cancer image segmentation. However, it should be noted that topic 4 has the highest level of significance, suggesting that the application of deep learning for diagnosis was extensively explored in this study.

BERTopic Modeling of Natural Language Processing Abstracts: Thematic Structure and Trajectory Samsir Samsir; Reagan Surbakti Saragih; Selamat Subagio; Rahmad Aditiya; Ronal Watrianthos
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6426

The rapid growth in the academic literature presents challenges in identifying relevant studies. This research aimed to apply unsupervised clustering techniques to 13,027 Scopus abstracts to uncover structure and themes in natural language processing (NLP) publications. Abstracts were pre-processed with tokenization, lemmatization, and vectorization. The BERTopic algorithm was used for clustering, using the MiniLM-L6-v2 embedding model and a minimum topic size of 50. Quantitative analysis revealed eight main topics, with sizes ranging from 205 to 4089 abstracts per topic. The language models topic was most prominent with 4089 abstracts. The topics were evaluated using coherence scores between 0.42 and 0.58, indicating meaningful themes. Keywords and sample documents provided interpretable topic representations. The results showcase the ability to produce coherent topics and capture connections between NLP studies. Clustering supports focused browsing and identification of relevant literature. Unlike human-curated classifications, the unsupervised data-driven approach prevents bias. Given the need to understand research trends, clustering abstracts enables efficient knowledge discovery from scientific corpora. This methodology can be applied to various datasets and fields to uncover overlooked patterns. The ability to adjust parameters allows for customized analysis. In general, unsupervised clustering provides a versatile framework for navigating, summarizing, and analyzing academic literature as volumes expand exponentially.

Metaverse: Tantangan dan Peluang dalam Pendidikan Indarta, Yose; Ambiyar, Ambiyar; Samala, Agariadne Dwinggo; Watrianthos, Ronal
Jurnal Basicedu Vol. 6 No. 3 (2022)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/basicedu.v6i3.2615

Metaverse merupakan inovasi teknologi ruang virtual tiga dimensi yang saat ini sedang membuat penasaran banyak orang baik dari perkembangannya yang sangat pesat serta implementasinya yang mulai banyak digunakan dalam berbagai sektor kehidupan. Studi penelitian ini membahas tentang tantangan dan peluang metaverse dalam dunia pendidikan, serta bagaimana aplikasinya dalam dunia pendidikan. Metode penelitian yang digunakan adalah studi literatur dengan mengumpulkan data pustaka dari berbagai sumber jurnal ilmiah yang relevan dengan topik yang dibahas. Desain penelitian yang digunakan adalah narrative review. Pengumpulan data dirangkum dari artikel jurnal internasional, jurnal nasional terakreditasi dan non akreditasi, prosiding, tesis maupun skripsi dari tahun 2017-2022. Hasil penelitian menunjukkan bahwa popularitas Metaverse telah mencapai puncaknya dalam beberapa bulan terakhir dan akselerasi teknologi metaverse di dunia pendidikan sudah terlihat dengan adanya aplikasi media pembelajaran digital berbasis augmented reality maupun virtual reality. Metaverse diyakini dapat mengatasi batasan-batasan yang ada di dalam dunia pendidikan, seperti keterbatasan kapasitas kelas karena pandemi, keterbatasan jarak dan waktu untuk masuk ke kelas, dan lain-lain. Dengan konsep dunia virtual, pembelajaran secara online dapat dilakukan dengan lebih interaktif tanpa menghilangkan pengalaman belajar siswa. Metode belajar di mana saja dan kapan saja menjadi konsep menarik yang disenangi banyak generasi Z saat ini. Metaverse diprediksi akan memasuki banyak bidang kehidupan manusia dalam 10-15 tahun mendatang.Metaverse is a three-dimensional virtual space technology innovation that is currently making many people curious, both from its very rapid development and implementation, which is starting to be widely used in various sectors of life. This research study discusses the challenges and opportunities of the metaverse in the world of education, and how it is applied in the world of education. The research method used is literature study by collecting library data from various sources of scientific journals that are relevant to the topics discussed. The research design used is a narrative review. Data collection is summarized from international journal articles, accredited and non-accredited national journals, proceedings, theses and theses from 2017-2022. The results show that the popularity of Metaverse has reached its peak in recent months and the acceleration of metaverse technology in the world of education has been seen with the application of digital learning media based on augmented reality and virtual reality. Metaverse is believed to be able to overcome the limitations that exist in the world of education, such as limited class capacity due to the pandemic, limited distance and time to enter class, and others. With the concept of a virtual world, online learning can be done more interactively without losing the student learning experience. The method of learning anywhere and anytime is an interesting concept that is favored by many generation Z today. Metaverse is predicted to enter many areas of human life in the next 10-15 years.

Penerapan Metode Dijkstra Pada Jalur Distribusi LPG Untuk Penentuan Jarak Terpendek Adi, Novi Hendri; Giatman, Muhammad; Simatupang, Wakhinuddin; Afrina, Afrina; Watrianthos, Ronal
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Determining a shortest path is a crucial and necessary thing in connection with optimizing the time used and some savings in other fields. This research aims to design a software for determining the shortest distance on a web-based LPG gas distribution line by applying the Dijkstra solving procedure at PT. Amartha Anugrah Mandiri. This study uses the SDLC (software development life cycle) development method using waterfall modeling, to determine the closest route during the distribution of LPG gas using the Dijkstra solution procedure, namely by determining which location is used as the initial node, then set the distance value at the initial node to neighboring nodes. the closest one by one. The results of this study make it easier for drivers to find the closest route that can be passed to the base location. Dijkstra's solving procedure in the software for determining the shortest distance in the PT. Amartha Anugrah Mandiri can form the shortest distance traveled to get to the base

Implementation Naïve Bayes Classification for Sentiment Analysis on Internet Movie Database Samsir, Samsir; Kusmanto, Kusmanto; Dalimunthe, Abdul Hakim; Aditiya, Rahmad; Watrianthos, Ronal
Building of Informatics, Technology and Science (BITS) Vol 4 No 1 (2022): June 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

A film review is a subjective opinion of someone who has different feelings about each film. As a result, film enthusiasts will struggle to assess whether the film meets their requirements. Based on these issues, sentiment analysis is the best way to fix them. Sentiment analysis, also known as opinion mining, is the study of assigning views or emotional labels to texts in order to determine if the text contains positive or negative thoughts. The Nave Bayes method was chosen because it can classify data based on the computation of each class's probability against objects in a given data sample. The best model was created utilizing data without lemmatization, 500 vector sizes, and Nave Bayes classification, with an accuracy of 78.96 percent and a f1-score of 78.81 percent. Changes in vector size affect the system's capacity to foresee positive and negative sentiments. The difference in accuracy and recall values shows that when vector size 300 is utilized, the precision and recall outcomes are lower than when vector size 500 is used.

Applying Data Mining Techniques to Investigate the Impact of Smoking Prevalence on Life Expectancy in Indonesia: Insights from Random Forest Models Dalimunthe, Abdul Hakim; Samsir, Samsir; Subagio, Selamat; Siagian, Taufiqqurrahman Nur; Watrianthos, Ronal
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5201

This study investigates the relationship between smoking prevalence and life expectancy in Indonesian provinces using data mining techniques, specifically focusing on the application of random forests. The primary objective is to quantify the potential impact of reducing smoking prevalence on population health outcomes. Data were sourced from the Indonesian Central Bureau of Statistics, which included life expectancy and smoking prevalence data from 2021 to 2023. The methodology involved aggregating life expectancy data from the district to the province level, followed by the application of a random forest model to predict life expectancy based on smoking prevalence and other socioeconomic indicators. Key findings indicate a weak to moderate negative correlation between smoking prevalence and life expectancy, with higher smoking rates associated with lower life expectancies. Predictive modeling suggests that a reduction in smoking prevalence could lead to significant improvements in life expectancy. For example, a 5% reduction in smoking rates could increase the average life expectancy by approximately 0.3 years, while a 15% reduction could result in an increase of about 0.9 years by 2025. These results underscore the detrimental impact of smoking on population health and highlight the importance of effective tobacco control measures. The predictive models developed in this study provide valuable information for policymakers, enabling targeted public health strategies and resource allocation. This research contributes to the field by demonstrating the utility of data mining techniques in public health and offering a comprehensive analysis of the relationship between smoking and life expectancy in Indonesia. The findings advocate for the urgent implementation of smoking cessation programs to enhance life expectancy and improve public health outcomes

Sentiment analysis of face-to-face learning based on social media Batubara, Hendra Saputra; Ambiyar, Ambiyar; Syahril, Syahril; Fadhilah, Fadhilah; Watrianthos, Ronal
Jurnal Pendidikan Teknologi Kejuruan Vol 4 No 3 (2021): Regular Issue
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jptk.v4i3.22623

The use of restricted face-to-face learning during the epidemic in Indonesia was discussed not just by education and health professionals, but also on social media. The study used the Twitter dataset with the keywords 'school' and 'face-to-face' to examine public opinion about face-to-face learning. The research data was obtained from Twitter utilizing Drone Emprit Academic, and it was then processed using the Naive Bayes method to create sentiment analysis. During that time, research revealed that 32% of people were positive, 54% were negative, and 14% were indifferent. Because of worries about the dangers associated with the use of face-to-face learning, negative attitudes predominate.

Metaverse: Tantangan dan Peluang dalam Pendidikan Indarta, Yose; Ambiyar, Ambiyar; Samala, Agariadne Dwinggo; Watrianthos, Ronal
Jurnal Basicedu Vol. 6 No. 3 (2022)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/basicedu.v6i3.2615

Metaverse merupakan inovasi teknologi ruang virtual tiga dimensi yang saat ini sedang membuat penasaran banyak orang baik dari perkembangannya yang sangat pesat serta implementasinya yang mulai banyak digunakan dalam berbagai sektor kehidupan. Studi penelitian ini membahas tentang tantangan dan peluang metaverse dalam dunia pendidikan, serta bagaimana aplikasinya dalam dunia pendidikan. Metode penelitian yang digunakan adalah studi literatur dengan mengumpulkan data pustaka dari berbagai sumber jurnal ilmiah yang relevan dengan topik yang dibahas. Desain penelitian yang digunakan adalah narrative review. Pengumpulan data dirangkum dari artikel jurnal internasional, jurnal nasional terakreditasi dan non akreditasi, prosiding, tesis maupun skripsi dari tahun 2017-2022. Hasil penelitian menunjukkan bahwa popularitas Metaverse telah mencapai puncaknya dalam beberapa bulan terakhir dan akselerasi teknologi metaverse di dunia pendidikan sudah terlihat dengan adanya aplikasi media pembelajaran digital berbasis augmented reality maupun virtual reality. Metaverse diyakini dapat mengatasi batasan-batasan yang ada di dalam dunia pendidikan, seperti keterbatasan kapasitas kelas karena pandemi, keterbatasan jarak dan waktu untuk masuk ke kelas, dan lain-lain. Dengan konsep dunia virtual, pembelajaran secara online dapat dilakukan dengan lebih interaktif tanpa menghilangkan pengalaman belajar siswa. Metode belajar di mana saja dan kapan saja menjadi konsep menarik yang disenangi banyak generasi Z saat ini. Metaverse diprediksi akan memasuki banyak bidang kehidupan manusia dalam 10-15 tahun mendatang.Metaverse is a three-dimensional virtual space technology innovation that is currently making many people curious, both from its very rapid development and implementation, which is starting to be widely used in various sectors of life. This research study discusses the challenges and opportunities of the metaverse in the world of education, and how it is applied in the world of education. The research method used is literature study by collecting library data from various sources of scientific journals that are relevant to the topics discussed. The research design used is a narrative review. Data collection is summarized from international journal articles, accredited and non-accredited national journals, proceedings, theses and theses from 2017-2022. The results show that the popularity of Metaverse has reached its peak in recent months and the acceleration of metaverse technology in the world of education has been seen with the application of digital learning media based on augmented reality and virtual reality. Metaverse is believed to be able to overcome the limitations that exist in the world of education, such as limited class capacity due to the pandemic, limited distance and time to enter class, and others. With the concept of a virtual world, online learning can be done more interactively without losing the student learning experience. The method of learning anywhere and anytime is an interesting concept that is favored by many generation Z today. Metaverse is predicted to enter many areas of human life in the next 10-15 years.

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