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All Journal International Journal of Electrical and Computer Engineering Jurnal Mahasiswa Matematika Vidya Karya Jurnal Penelitian Pendidikan IPA (JPPIPA) Journal of Mathematics and Mathematics Education (JMME) EduLine: Journal of Education and Learning Innovation
Tesdiq Prigel Kaloka
Politeknik Hasnur
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Physics Other

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ANALISA MODEL ANTRIAN PELAYANAN PEMBUATAN SURAT IZIN MENGEMUDI (SIM) (Studi Kasus di Polres Tabalong Kalimantan Selatan) Kaloka, Tesdiq Prigel
Jurnal Mahasiswa Matematika Vol 4, No 2 (2016)
Publisher : Jurnal Mahasiswa Matematika

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Robusta coffee leaf diseases detection based on MobileNetV2 model Yazid Aufar; Tesdiq Prigel Kaloka
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp6675-6683

Abstract

Indonesia is a major exporter and producer of coffee, and coffee cultivation adds to the nation's economy. Despite this, coffee remains vulnerable to several plant diseases that may result in significant financial losses for the agricultural industry. Traditionally, plant diseases are detected by expert observation with the naked eye. Traditional methods for managing such diseases are arduous, time-consuming, and costly, especially when dealing with expansive territories. Using a model based on transfer learning and deep learning model, we present in this study a technique for classifying Robusta coffee leaf disease photos into healthy and unhealthy classes. The MobileNetV2 network serves as the model since its network design is simple. Therefore, it is likely that the suggested approach will be deployed further on mobile devices. In addition, the transfer learning and experimental learning paradigms. Because it is such a lightweight net, the MobileNetV2 system serves as the foundational model. Results on Robusta coffee leaf disease datasets indicate that the suggested technique can achieve a high level of accuracy, up to 99.93%. The accuracy of other architectures besides MobileNetV2 such as DenseNet169 is 99.74%, ResNet50 architecture is 99.41%, and InceptionResNetV2 architecture is 99.09%.
MODEL KLASTERING SKM3 (SUBCONTROLLED K-MEANS MAX-MIN) DAN APLIKASINYA DALAM MENGHITUNG ELEKTABILITAS PASANGAN CALON KEPALA DAERAH Patuan P Tampubolon; Tesdiq Prigel Kaloka; Olivia Swasti; Widya Fajar Mustika; Alhadi Bustamam
Journal of Mathematics and Mathematics Education Vol 8, No 2 (2018): Journal of Mathematics and Mathematics Education (JMME)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jmme.v8i2.25838

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Abstract: Indonesia is a legal state that chooses a leader based on the results of general elections, such as the election of presidents and regional leaders. Electability is statistical data for each pair of candidates who show public interest to choose the candidate. Electability data is usually obtained from the results of questionnaires or interviews with constituents. The data search process is carried out by a survey institution. Most people discuss voluntarily in social media related to the candidate that they will choose. This study uses discussion data from social media to calculate the electability of each pair of candidates by using cluster method. The cluster method is K-Means. K-Means employs euclidean distance to determine the cluster of each data, while the number of cluster can be determined by the user. This study proposes SKM3 model (Subcontrolled K-Means Max-Min), which applies the minimum and maximum average values to decide the cluster of each data. SKM3 cluster is controlled by K-Means method that uses Euclidian distance. SKM3 model is processed using news data from detik.com site for the election of regional leader of West Java, Central Java, and East Java. The error value of SKM3 model is calculated through RMSE (Root Mean Square Error). The error value of West Java is 0.0452, the error value of Central Java up to 0.0343, and the error value of East Java is 0.2382. Based on the error values of each electoral region, it shows that SKM3 model has a small error value, so it can be concluded that SKM3 model is good for calculating the electability of the leader by using clustering method.Keywords:Electability, Clustering, K-Means, SKM3.
Pemetaan Prediksi Wilayah Rawan Bencana Hidrometeorologi di Provinsi Kalimantan Tengah Indah Gumilang Dwinanda; Kadek Ayu Cintya Adelia; Robiatul Witari Wilda; Febrianto Afli; Tesdiq Prigel Kaloka; Desy Lutfiani Pratiwie
Jurnal Penelitian Pendidikan IPA Vol 10 No 2 (2024): February
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i2.6238

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Disaster is an event or a series of events that threatens and disrupts people's lives and livelihoods, caused by natural and/or non-natural factors and human factors, resulting in human casualties, environmental damage, property losses, and psychological impacts. Hydrometeorological disasters are events related to water, atmosphere, and oceans. It is recorded that hydrometeorological disasters occurring in Indonesia reach 86%, including floods, tornadoes, landslides, forest and land fires, and droughts. Specifically, in Central Kalimantan Province, forest and land fires and floods are frequent disasters. Both fall into the category of hydrometeorological disasters, closely related to the climate in Central Kalimantan. In this study, the prediction of rainfall, temperature, and humidity values in Central Kalimantan Province was calculated using the Auto-Regressive Integrated Moving Average method at 5 stations in the province. Subsequently, the prediction analysis of flood events was carried out using the machine learning random forest method based on the rainfall data, temperature, humidity, and event data. According to the calculation results, flood disasters are not predicted to affect almost all areas of Central Kalimantan Province. However, by the end of 2023, it is anticipated that most areas in the province will still be categorized as experiencing a normal level of drought. Notably, there are two areas that must increase awareness of this drought disaster, namely Pulang Pisau and Sampit, especially in October 2023.
Vokametri: Mobile Application for Observation of Attitude Aspects Based on KKNI in Vocational Students Ridhoni, Wahyu; Kaloka, Tesdiq Prigel; Pratomo, Danang Yugo
Vidya Karya Vol 38, No 2 (2023)
Publisher : FKIP ULM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jvk.v38i2.17186

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Findings at Hasnur Polytechnic show that some aspects of attitude assessment still do not produce diverse scores. In one class, all students obtained the same grade. This problem arises because there are no guidelines for making observations. This research focuses on building a mobile app so that lecturers can more easily assess each learning session. The research method used as a framework in the development process is ADDIE (Analysis, Design, Development, Implementation and Evaluation).  The result of this research is the Vokametri application, built with the Ionic framework for the Android platform. All functions of the application have worked well. Therefore, it can be used by lecturers to conduct KKNI-based attitude observations. This application works offline so that the assessment can be done without being connected to the internet. Lecturers can view student attitude score records and download Excel files that list the attitude scores of all students in a course.
Insights of Using Mobile Application to Assess Creative and Creative Thinking of Indonesian Students Ridhoni, Wahyu; Prigel Kaloka, Tesdiq; Setyosari, Punaji; Kuswandi, Dedi; Ulfa, Saida
EduLine: Journal of Education and Learning Innovation Vol. 5 No. 1 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.eduline3561

Abstract

World education organizations such as UNESCO and OECD have determined that creative and critical thinking are core 21st-century skills essential for students to master. Indonesia also views these two skills as very important, thus formulating creative and critical thinking into two of the six dimensions of the Pancasila Learner Profile. This study analyzes the data we collected during a creative and critical thinking assessment experiment with university students using the CC Thinker android application. The investigation was conducted on 46 participants with three assessment sessions. The research results showed that Creative Thinking in men showed a higher value than women. The Critical Thinking of men is more consistent than women. Creative Thinking of undergraduate students is more consistent than D3 students. However, the Critical Thinking of undergraduate students has increased. Creative Thinking of exact students is higher than non-exact students. In Critical Thinking, exact students develop as continuous exams are carried out. Creative thinking of students outside Java or Java is equal but in critical thinking Javanese students are better than students outside Java.
Co-Authors Bustamam, Alhadi Danang Yugo Pratomo Dedi Kuswandi Desy Lutfiani Pratiwie Febrianto Afli Indah Gumilang Dwinanda Kadek Ayu Cintya Adelia Olivia Swasti Patuan P Tampubolon Punaji Setyosari Ridhoni, Wahyu Saida Ulfa Titin Siswantining Widya Fajar Mustika Wilda, Robiatul Witari Yazid Aufar