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All Journal Kreano, Jurnal Matematika Kreatif-Inovatif Jurnal S2 Pendidikan Matematika Journal on Mathematics Education (JME) Jurnal Riset Pendidikan Matematika Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Mathematics and Mathematics Education Al-Jabar : Jurnal Pendidikan Matematika Al Ishlah Jurnal Pendidikan Union: Jurnal Ilmiah Pendidikan Matematika Jurnal Pembelajaran Matematika Indonesian Journal of Science and Mathematics Education BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika (JRPIPM) Jurnal Bumigora Information Technology (BITe) Nusantara Science and Technology Proceedings Journal of Applied Data Sciences Mosharafa: Jurnal Pendidikan Matematika Jurnal Pengabdian kepada Masyarakat Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Prosiding SNPBS (Seminar Nasional Pendidikan Biologi dan Saintek) Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Muslim Education Review Proceeding of International Conference on Humanity Education and Society Jurnal SUTASOMA Proceeding International Conference on Mathematics and Learning Research
Isnandar Slamet, Isnandar
Universitas Sebelas Maret Surakarta
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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The Factors Affecting Soybean Production in Indonesia Using Robust Regression with Least Median of Squares (LMS) Estimation Ratri, Aninda Puspa; Susanti, Yuliana; Slamet, Isnandar
Nusantara Science and Technology Proceedings Join Proceeding "Basic and Applied Science Conference (BASC) 2021 & 1st Education Research and Appli
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2021.1110

Abstract

Soybean is a product with a source of protein that improves the nutrition of Indonesians. The demand for soybeans is increasing, but the domestic production is not sufficient, so that the soybean production in Indonesia must be increased. This study aims to determine the influential factors on soybean production in Indonesia. The data of soybean production in Indonesia had outliers. Outliers cause the residual is not normally distributed so that the assumption of normality is violated. This problem was solved using robust regression. The estimation used was the Least Median of Squares because this estimation has a quite large breakdown point value. The results of the study show that the soybean production in Indonesia was influenced by the field area, the number of soybean seeds, and rainfall. The most influential factor on soybean production is the number of soybean seeds, field area, and rainfall. The attempts that must be conducted by the government to increase soybean production are by having socialization about soybean cultivation and ensuring the availability of soybean seeds in Indonesia.
Retinopathy Classification using Convolutional Neural Network Method with Adaptive Momentum Optimization and Applied Batch Normalization Slamet, Isnandar; Susilotomoa, Dhestahendra Citra; Zukhronah, Etik; Subanti, Sri; Susanto, Irwan; Sulandari, Winita; Sugiyanto, Sugiyanto; Susanti, Yuliana
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.309

Abstract

Retinopathy is a common eye disease in Indonesia, ranking fourth after cataracts, glaucoma, and refractive errors. It can be overcome by early diagnosis with optical coherence tomography (OCT), but this imaging technique takes much time. In this research, retinal imaging was carried out using an expert system. The expert system in this study was formed using the convolutional neural network (CNN or ConvNet) method. CNN is an algorithm of deep learning that uses convolution operations to process two-dimensional data, such as images and sounds. This research consisted of 4 stages: data collection, preprocessing, model design, and model testing. A CNN model was formed with three arrangements, consisting of two convolutional layers and one pooling layer. The ReLU activation function, zero padding, and batch normalization were used in all three formats. Then, the flattening process was carried out, and the Softmax activation function was used at the end of the architecture. The model was built using eight epochs, and optimization of Adaptive Momentum resulted in a 98.96% test data accuracy value. The result was considered good so that CNN could be used as an alternative in retinopathy diagnosis. Further research is suggested to use other optimizations or other model architectures.
Implementation of Scale-Invariant Feature Transform Convolutional Neural Network for Detecting Distracted Driver Fhadilla, Nahdatul; Sulandari, Winita; Susanto, Irwan; Slamet, Isnandar; Sugiyanto, Sugiyanto; Subanti, Sri; Zukhronah, Etik; Pardede, Hilman Ferdinandus; Kadar, Jimmy Abdel
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.222

Abstract

A distraction while driving a vehicle may result in fatal consequences, namely accidents that may leave road users seriously injured or even dead. In order to mitigate this risk, it is imperative to establish a distracted driver detection system that is both precise and real-time. This research focuses on the application of artificial intelligence, with a particular emphasis on deep learning, which is achieved through the utilization of the Convolutional Neural Network (CNN) model. In order to enhance the detection of inattentive drivers and produce a more precise model, a scaleinvariant feature transform (SIFT)-CNN combination is proposed. The activities of the driver while operating a vehicle are categorized into ten categories in this study. One of these categories is considered a normal condition, while the remaining nine are classified as inattentive behaviors. This study implemented Adam optimization with 64 batches, a learning rate of 0.001, and epochs of 20, 25, 50, and 100. The proposed CNNSIFT model is capable of achieving superior performance in comparison to the solitary CNN model, as evidenced by the experimental results. The CNN-SIFT model has achieved 99% accuracy and a 0.05 loss when the hyperparameter configuration is optimized for 50 epochs. The analysis indicates that the accuracy of the features obtained from CNN-SIFT can be improved by approximately 1% compared with CNN to classify the type of driver distraction behavior. The model's reliability was further enhanced by its evaluation on test data, which resulted in high accuracy, precision, recall, and F1-score values. The model's ability to accurately identify driver behavior with a high degree of reliability is demonstrated by these results, which are a positive contribution to the improvement of road safety.
Effectiveness of Mathematics Modules Based on Problem-Based Learning to Improve Students Reasoning Ability in Junior High School Lestari, Puji; Mardiyana, Mardiyana; Slamet, Isnandar
Muslim Education Review Vol. 1 No. 2 (2022)
Publisher : UIII Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56529/mer.v1i2.77

Abstract

This study aims to determine the effectiveness of mathematics modules based on problem-based learning to improve the reasoning ability of eighth grade students at Junior High School (SMPN) 2 Jumapolo. Reasoning ability is one of the goals of mathematics education, the problem is that the reasoning ability of eighth grade students in Indonesia, including at SMPN 2 Jumapolo, is still relatively low. The development of mathematics modules based on problem-based learning is expected to be a solution to overcome these problems. In this study, the mathematics module based on problem-based learning was tested on thirty eighth grade students at SMPN 2 Jumapolo. This research is quasi-experimental research with One Group Pretest Posttest Design. Samples were taken by cluster random sampling. Students are given a pretest to determine the students’ initial reasoning ability. The students were given treatment in the form of learning by using a mathematics module based on problem-based learning. After that, students were given a post-test to measure the students’ final reasoning ability. The data collection technique used in this study was a test of reasoning ability. The data analysis technique used was the paired t-test. Based on the results of the paired t-test, it was found that the students’ final reasoning ability was better than students’ initial reasoning ability. The students’ reasoning ability increased by 52.80 percent. This shows that the mathematics module based on problem-based learning was effective in improving the reasoning ability of grade eight students.
Implementasi High Order Intuitionistic Fuzzy Time Series Pada Peramalan Indeks Harga Saham Gabungan Nugraha, Titis Jati; Sulandari, Winita; Slamet, Isnandar; Subanti, Sri; Zukhronah, Etik; Sugianto, Sugianto; Susanto, Irwan
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 2: April 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20241127363

Abstract

Indeks Harga Saham Gabungan (IHSG) adalah indeks yang mengukur kinerja harga semua saham yang terdaftar di Bursa Efek Indonesia (BEI) Peramalan IHSG menjadi referensi bagi investor untuk memperoleh keuntungan di pasar modal. Penelitian ini membahas penerapan metode High Order Intuitionistic Fuzzy Time Series (HOIFTS) dalam peramalan IHSG di BEI. Metode HOIFTS melibatkan tiga indikator, yaitu derajat keanggotaan, derajat non- keanggotaan, dan fungsi skor (indeks intutionistic) sehingga model yang dihasilkan mampu menangani ketidakpastian dalam data. Tahapan penting dalam pemodelan HOIFTS adalah pada fuzzifikasi intuitionistic, penentuan relasi logika fuzzy intutionistic, dan proses defuzifikasi order tinggi intuitionistic. Penelitian ini menetapkan metode Chen, baik order satu maupun order tinggi sebagai metode pembanding untuk melihat seberapa jauh keberhasilan metode HOIFTS dalam meramalkan data bulanan IHSG. Hasil perbandingan nilai RMSE (root mean square error) dan MAPE (mean absolute percentage error) yang dihasilkan oleh ketiga model menunjukkan bahwa metode HOIFTS memiliki nilai kesalahan yang paling kecil. Dengan demikian, metode HOIFTS lebih direkomendasikan dalam peramalan IHSG dibandingkan dua metode lain yang dibahas dalam penelitian ini. 
SIMULATION OF THE DISCRETE TIME MARKOV CHAIN SUSCEPTIBLE INFECTED RECOVERED (DTMC SIR) EPIDEMIC MODEL FOR COVID-19 TRANSMISSION IN CENTRAL JAVA Valentino, Yohanes Felix; Respatiwulan, Respatiwulan; Slamet, Isnandar
International Conference on Humanity Education and Society (ICHES) Vol. 3 No. 1 (2024): Third International Conference on Humanity Education and Society (ICHES)
Publisher : FORPIM PTKIS ZONA TAPAL KUDA

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

Abstract

An epidemic is a situation when an area has a very high number of cases of individuals infected with an infectious disease in a short time frame. Susceptible Infected Recovered (SIR) epidemic models that explain changes in the number of infected individuals in discrete time intervals are called Discrete Time Markov Chain SIR (DTMC SIR) epidemic models. This research aims to discuss the DTMC SIR epidemic model and its simulation of the COVID-19 outbreak. The research methods used are literature reviews and simulation of the dynamics of COVID-19 transmission in Central Java. Central Java's COVID-19 dynamics are analyzed using the obtained DTMC SIR model with a contact rate and cure rate . This research has yielded a DTMC SIR epidemic model that uses transition probabilities to study the dynamics of COVID-19 transmission. The model applied with an initial value of and , and shows that COVID-19 stops when and occurs at . The model was also applied when the contact rate was reduced and increased. The conclusion is that the smaller the contact rate, the longer the epidemic ends and the fewer individuals are infected at the time the epidemic ends.
Pemodelan Faktor-Faktor Yang Mempengaruhi Tingkat Pengangguran Terbuka (Tpt) Di Provinsi Jawa Tengah Menggunakan Regresi Spline Truncated Multivariabel Azhar, Zenitha Amalia; Handajani, Sri Sulistijowati; Slamet, Isnandar
Jurnal SUTASOMA (Science Teknologi Sosial Humaniora) Vol 2 No 2 (2024): Juni 2024
Publisher : Universitas Tabanan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58878/sutasoma.v2i2.264

Abstract

Human life depends on work as it brings self-actualization to families, societies, and nations. Increasing the Open Unemployment Rate (OPR) is an employment problem. Statistically speaking, regression analysis is a tool for discovering how one or more variables (the predictors) affect another (the response variables). For this TPT case study in Central Java, researchers looked into the nonpatometric regression model of spline reduced using the UBR and GCV approaches for knot selection. The results demonstrated that the GCV model produced MSE values of 1.381e-01 and R2 of 95.69%, while the UBR model generated MSE value of 1.380e-01, and R2.
In-depth Analysis of Students' Mathematical Problem-Solving Skills: Influence Factors Motivation and Effective Teaching Strategies Tririnika, Yuliana; Suryadi, Imam; Slamet, Isnandar
AL-ISHLAH: Jurnal Pendidikan Vol 16, No 3 (2024): AL-ISHLAH: JURNAL PENDIDIKAN
Publisher : STAI Hubbulwathan Duri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35445/alishlah.v16i3.5474

Abstract

Problem-solving (PS) skills are efforts to find solutions when faced with challenges. This study aims to examine students' mathematical PS skills by focusing on the influence of learning motivation and identifying factors that were previously overlooked. A qualitative approach with a case study design was used, where the researcher acted as the primary instrument. The research also utilized PISA-type test instruments, observation sheets, and interviews. PISA-type questions were designed around content, context, and process components, adhering to the PISA framework. The study was conducted in a school in Surakarta, chosen for its alignment with the minimum competency assessment system similar to PISA. Using snowball sampling, nine students were selected for response analysis. These students were categorized based on their motivation levels: high, moderate, and low. The results show that students with high motivation are proactive in problem-solving, directly addressing the problem, reviewing each step as they proceed, and ensuring accuracy. Moderately motivated students take more time, often using scratch paper, and review their work only at the end. Low-motivation students face greater difficulties, frequently making mistakes, relying heavily on scratch paper, and often skipping the review process due to time pressure. To improve PS skills, future research could explore the integration of interactive digital tools with instant feedback, adaptive learning platforms tailored to student motivation, and collaborative learning exercises. Additionally, incorporating real-world scenarios into problem-based learning could enhance engagement and develop deeper problem-solving abilities across different motivation levels.
Eksperimentasi Model Pembelajaran Make A Match (MAM) Ditinjau dari Kecerdasan Emosional pada Pokok Bahasan Lingkaran Kelas XI SMA Negeri Se-Kabupaten Sukoharjo Tahun Ajaran 2016/2017 Sari, Putri Permata; Budiyono, B; Slamet, Isnandar
Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya 2017: Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (642.324 KB)

Abstract

Penelitian ini adalah penelitian eksperimental semu untuk mengetahui perbedaan pengaruh model pembelajaran, kecerdasan emosional, dan interaksinya terhadap prestasi belajar pada materi lingkaran. Populasi meliputi seluruh siswa kelas XI Tahun Ajaran 2016/2017 SMAN Kabupaten Sukoharjo. Pengambilan sampel dilakukan dengan teknik stratified cluster random sampling. Data sampel dikumpulkan dengan dokumentasi, tes, dan angket, kemudian dianalisis menggunakan Lilliefors, Bartlett, ANAVA(uji kesetimbangan dan uji hipotesis), dan Scheffe. Kesimpulan hasil penelitian ini: (1) TAPPS prestasinya lebih baik daripada langsung. (2) Siswa dengan kecerdasan emosional tinggi prestasinya lebih baik daripada siswa dengan kecerdasan emosional rendah, siswa dengan kecerdasan emosional sedang prestasinya lebih baik daripada siswa dengan kecerdasan emosional rendah, dan siswa dengan kecerdasan emosional tinggi maupun sedang prestasinya sama. (3a) pada TAPPS, siswa dengan kecerdasan emosional tinggi, sedang maupun rendah prestasinya sama. (3b) pada langsung, siswa dengan kecerdasan emosional tinggi maupun sedang prestasinya sama dan siswa dengan kecerdasan emosional sedang maupun rendah prestasinya sama. (4a) pada kecerdasan emosional tinggi dengan TAPPS maupun langsung prestasinya sama. (4b) pada kecerdasan emosional sedang dengan TAPPS maupun langsung prestasinya sama. (4c) pada kecerdasan emosional rendah dengan TAPPS prestasinya lebih baik daripada langsung.
Eksperimentasi Model Pembelajaran Kooperatif Missouri Mathematics Project (MMP) dan Teams Games Tournament (TGT) pada Pokok Bahasan Persamaan Garis Lurus Ditinjau dari Emotional Quotient (EQ) pada Peserta Didik Kelas VIII SMP Negeri Se-Kodya Surakarta Tah Setyawan, Indra; Budiyono, B; Slamet, Isnandar
Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya 2017: Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (411.348 KB)

Abstract

Penelitian ini merupakan penelitian eksperimental semu dengan desain faktorial 3 x 3. Populasi dalam penelitian ini adalah seluruh peserta didik kelas VIII SMP Negeri se-Kodya Surakarta semester ganjil tahun pelajaran 2016/2017. Pengambilan sampel dilakukan secara stratified cluster random sampling. Sekolah yang menjadi sampel adalah SMPN 6, SMPN 14, dan SMPN 27 Surakarta. Uji instrumen dengan uji validitas, reliabilitas, daya beda dan tingkat kesukaran. Uji normalitas dengan rumus Lilliefors, uji homogenitas variansi dengan uji Bartlett, dan uji keseimbangan dengan anava satu jalan dengan sel tak sama. Uji hipotesis dengan anava dua jalan dengan sel tak sama. Hasil penelitian menunjukkan: (1) Prestasi belajar matematika model pembelajaran MMP sama baiknya dengan model pembelajaran TGT, model pembelajaran MMP lebih baik daripada model pembelajaran Langsung. (2) Prestasi belajar matematika pada emotional quotient tinggi lebih baik daripada emotional quotient sedang dan rendah, prestasi belajar matematika pada emotional quotient sedang lebih baik daripada emotional quotient rendah. (3) Pada emotional quotient tinggi, model pembelajaran MMP dan TGT memberikan prestasi yang sama, model pembelajaran MMP dan TGT memberikan prestasi lebih baik daripada model pembelajaran Langsung. Pada emotional quotient sedang, model pembelajaran MMP dan TGT memberikan prestasi lebih baik dari model pembelajaran Langsung. Pada emotional quotient rendah, model pembelajaran MMP, TGT, dan Langsung memberikan prestasi yang sama. (4) Pada model pembelajaran MMP, emotional quotient tinggi memberikan prestasi yang lebih baik daripada emotional quotient sedang, emotional quotient sedang memberikan prestasi yang lebih baik daripada emotional quotient rendah. Pada model pembelajaran TGT, emotional quotient tinggi dan sedang memberikan prestasi belajar yang sama, emotional quotient tinggi memberikan prestasi yang lebih baik daripada emotional quotient rendah. Pada model pembelajaran Langsung, emotional quotient tinggi, sedang, dan rendah memberikan prestasi yang sama.
Co-Authors Abda Abda Adi Wicaksono, Nanda Anggraini, Putri Nurika Aprilia, Nabila Churin Aulia Ar Rakhman Awaludin Ayuningrum, Retna Azhar, Zenitha Amalia B Budiyono Budiyono Budiyono Budiyono, Budiyono Ek Ajeng Rahmi Pinahayu Fachry Abda El Rahman Fhadilla, Nahdatul Fitriana, Laila Fitriana, Laila Nur Getut Pramesti Hadi Prayitno, Hadi Handajani, Sri Sulistijowati Heldy Ramadhan Putra P Hendriyanto, Agus Heritin, Anisak Hermawati, Evi Hodiyanto, Hodiyanto Husna Afanyn Khoirunissa Ikrar Pramudya, Ikrar Imam Sujadi Imam Suryadi, Imam Indra Raditya , Dionisius Indra Setyawan Irwan Susanto Isnaini, Bayutama Janah, Rahmawati Fatkhul Kadar, Jimmy Abdel Kayyisa, Alfien Diva Lintang Fitra Utami Mardiyana Mardiyana Meilasari, Venty Muhammad Riza Naufalia Nuraya, Naufalia Neyun, Ignasia N.G. Ningrum, Sri Adiningsih Utami Nugraha, Titis Jati Nugroho, Muhamad Asif Cahya Aji Nur Hasanah Nurfauziyyah, Nuha Pardede, Hilman Ferdinandus Permatasari, Nisa Permatasari, Nisa Pitra Dwiningsih, Pitra Pratama, Yulian Surya PUJI LESTARI Raditya, Dionisius Indra Ratri, Aninda Puspa Respatiwulan, Respatiwulan Sari, Putri Permata Shanti Indah Lestari, Shanti Indah Sri Subanti Suci Irawati Sugianto Sugianto Sugiyanto - Sugiyanto, Sugiyanto Sulandari, Winita Susanti, Sarah Wahyu Susilotomoa, Dhestahendra Citra Tajuddin, Annas Tasyah Tririnika, Yuliana Valentino, Yohanes Felix Vera Rosalina Bulu Wahyu Kurniawan Winita Sulandari Wulandari, Setyati Puji Yudi Pramono Pawiro, Yudi Pramono Yuliana Susanti, Yuliana Zukhronah, Etik