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Ari Wibowo

UIN Raden Mas Said Surakarta

Author-ID : 7184965

Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Pengaruh Kecemasan Matematis Dan Disposisi Matematis Terhadap Kemampuan Pemecahan Masalah Matematis Siswa Ahmad Rafli Hidayat; Ari Wibowo; Heldy Ramadhan Putra Pembangunan; Wiwin Astuti
Science and Education Journal (SICEDU) Vol 5 No 2 (2026): Science and Education Journal 2026
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/sicedu.v5i2.281

Penelitian ini bertujuan untuk mengkaji pengaruh kecemasan matematis dan disposisi matematis terhadap kemampuan memecahkan masalah matematis siswa kelas VIII MTs N 3 Boyolali pada tahun ajaran 2025/2026. Penelitian ini menggunakan pendekatan kuantitatif dengan desain asosiatif-kausal yang melibatkan 120 siswa sebagai responden. Data dikumpulkan melalui kuesioner yang mengukur kecemasan matematis dan disposisi matematis, serta tes kemampuan memecahkan masalah. Analisis data dilakukan melalui regresi liniear berganda, yang didahului oleh uji prasyarat termasuk uji normalitas, linearitas, multikolinearitas, dan heteroskedastisitas. Temuan menunjukkan bahwa kecemasan matematis tidak memiliki pengaruh parsial yang signifikan terhadap kemampuan pemecahan masalah, sebagaimana ditunjukkan oleh nilai signifikansi 0,06 > 0,05. Sebaliknya, disposisi matematika memiliki pengaruh parsial yang signifikan dengan nilai signifikansi 0,000 < 0,05. Secara simultan, kedua variabel tersebut secara signifikan memengaruhi kemampuan pemecahan masalah matematika siswa, berkontribusi sebesar 35,8%, sedangkan 64,2% sisanya disebabkan disebabkan variabel lain yang tidak terdapat pada penelitian ini.

Metode Interpolasi Newton dengan Selisih Terbagi Menggunakan Python dan Excel: Studi Efisiensi dan Visualisasi Meita Rehania; Ratih Irmawanti; Ari Wibowo
Griya Journal of Mathematics Education and Application Vol. 6 No. 2 (2026): Juni 2026
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v6i2.678

Interpolation is one of the numerical methods used to estimate the value of a function between known data points. One commonly used technique is Newton's divided difference method. This study aims to explore the implementation of this method using two applications, namely Microsoft Excel and Python, and to compare their accuracy, efficiency, and ease of use. The method employed is a descriptive quantitative case study with data consisting of four points (x, f(x)), and it calculates the approximate function value at the point x=2.5. The calculations were performed manually in Excel and automatically through a Python script. The results show that both applications produced the same interpolation value, f(2.5) = 13.3125, with zero error. The graphical visualization in both applications also aids in understanding the function's approximation. Excel is rated superior in ease of use and initial visualization, while Python is more flexible for processing large-scale data and automation. This study recommends the complementary use of both learning and advanced numerical analysis.

Implementasi Metode Bisection dalam Menentukan Nilai Ambang Target Penurunan Tingkat Kemiskinan di Provinsi Jawa Tengah Tahun 2025 Istnaniah Hani Salami; Dimas Maulidani; Ari Wibowo
Mandalika Mathematics and Educations Journal Vol 8 No 2 (2026): Edisi Juni
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v8i2.11866

Poverty remains a central issue in Indonesia’s development planning, particularly in Central Java Province, where poverty rates consistently exceed the national average. The Human Development Index (HDI) serves as a composite indicator reflecting quality of life through education, health, and living standards. This study aims to determine the minimum HDI thresholds required for regencies/cities in Central Java to achieve targeted poverty rates (8%, 9%, 10%, and 11%) by integrating simple linear regression with the bisection method. The data consist of HDI values for 2024 and poverty rates for 2025 across 35 regencies/cities, obtained from the Central Statistics Agency (BPS). The regression model produced the equation K(x) = 47.6038 − 0.5170x with a coefficient of determination (R²) of 0.64, indicating that HDI explains 64% of poverty variation. The bisection method converged in 23 iterations with a final error of 0.000004. The resulting HDI thresholds range from 70.80 to 76.60 depending on the target. These findings provide a quantitative basis for policymakers to design more effective and evidence-based poverty reduction strategies.

Penerapan Metode Interpolasi Polinomial Newton dengan Selisih Terbagi untuk Estimasi Pertumbuhan Jumlah Penduduk di Kota Surakarta Deshinta Yura Saraswati; Astutik Apriliana; Dhina Laras Ati; Ari Wibowo
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 8 No. 1 (2026): Juni 2026
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v8i1.17109

Population growth is a key indicator in regional development planning because it affects economic, social, and infrastructure aspects. The city of Surakarta has experienced steady population growth, necessitating the use of accurate estimation methods. This study aims to estimate population growth using the Newton polynomial interpolation method with divided differences and to compare it with linear regression. This study employs a quantitative approach using secondary data from 2021 to 2025 obtained from the Central Statistics Agency of Surakarta City. The analysis was conducted by compiling a split-difference table, forming a Newton polynomial, and creating a linear regression model using Python. The results show that the Newton interpolation method produced population estimates of 540,943 people for 2026 and 583,103 people for 2027, with a MAPE of 0% and an RMSE of 0. Meanwhile, linear regression produced population estimates of 531,259 for 2026 and 533,025 for 2027, with a MAPE of 0.116% and an RMSE of 694.5. Thus, the Newton interpolation method is more appropriate for representing historical data, while linear regression is more appropriate for long-term predictions.

Aproksimasi Integral Pada Data Inflasi Bulanan Menggunakan Metode Aturan Jumlah Kiri, Kanan, dan Tengah Berbantuan Microsoft Excel Rika Bekti Nur Wahyuni; Rulia Nurul Qomariah; Ari Wibowo
Jurnal Pendidikan Tambusai Vol. 10 No. 2 (2026): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v10i2.40660

Penelitian ini bertujuan mengaproksimasi integral pada data inflasi bulanan Indonesia tahun 2025 menggunakan metode aturan jumlah kiri, kanan, dan titik tengah berbantuan Microsoft Excel. Penelitian ini merupakan penelitian kuantitatif dengan pendekatan simulasi numerik terhadap data inflasi bulanan yang bersifat diskrit dari Badan Pusat Statistik. Data disusun dalam tabel, kemudian dihitung nilai aproksimasi integral pada tiap metode dengan partisi interval yang sama. Hasil perhitungan menunjukkan bahwa metode aturan jumlah kiri menghasilkan nilai 2,28, aturan jumlah kanan 3,68, dan aturan jumlah titik tengah 2,98. Nilai pembanding yang digunakan dalam penelitian ini adalah 2,98. Berdasarkan analisis galat, metode aturan titik tengah memiliki galat 0,00, sedangkan metode aturan kiri dan kanan masing-masing memiliki galat 0,70. Temuan ini menunjukkan bahwa metode titik tengah paling akurat dan paling representatif dalam mengaproksimasi integral pada data inflasi bulanan. Selain itu, Microsoft Excel terbukti efektif membantu proses perhitungan, pengolahan data, dan penyajian hasil dalam bentuk tabel dan grafik secara sistematis. Dengan demikian, pendekatan integral numerik dapat digunakan sebagai cara praktis untuk menganalisis data ekonomi diskrit, terutama ketika nilai eksak sulit diperoleh melalui metode analitik. Hasil ini juga menegaskan pentingnya pemilihan titik representatif dalam menentukan tingkat ketelitian aproksimasi dalam konteks analisis inflasi bulanan di Indonesia pada penelitian matematika terapan sederhana.

Perbedaan Keaktifan Belajar Matematika Siswa yang Menggunakan Model Pembelajaran Kooperatif Tipe TGT dan PBL Berbantuan LKPD Kontekstual Lathifah Aulia Dewi; Ari Wibowo; Moh. Bisri; Wiwin Astuti
Jurnal Cendekia : Jurnal Pendidikan Matematika Vol 10 No 2 (2026): Jurnal Cendekia: Jurnal Pendidikan Matematika Volume 10 Nomor 2 Tahun 2026
Publisher : Mathematics Education Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cendekia.v10i2.5014

Keaktifan belajar matematika siswa MAN 3 Boyolali terpantau rendah karena pembelajaran masih bergantung pada guru. Tujuan studi ini adalah menganalisis komparasi tingkat keaktifan belajar matematika antara siswa di kelas Teams Games Tournament (TGT) dengan kelas pembelajaran berbasis masalah (PBL) yang difasilitasi oleh LKPD kontekstual. Riset kuantitatif ini mengaplikasikan metode kuasi-eksperimen tanpa kelas kontrol, secara spesifik menggunakan posttest only nonequivalent group design. Populasi ditarik dari keseluruhan kelas X (157 siswa), di mana dua kelas ditetapkan sebagai sampel lewat penarikan acak berbasis area (cluster random sampling). Pengukuran tingkat keaktifan belajar siswa mengandalkan instrumen kuesioner yang kelayakan validitas serta reliabilitasnya telah teruji. Pengolahan data melalui statistik deskriptif, pengujian asumsi dasar, serta independent sample t-test. Temuan evaluasi mengindikasikan perbedaan keaktifan yang sangat besar antara kelompok TGT dan PBL, dibuktikan lewat angka signifikansi sebesar 0,0006 (p < 0,05). Kelompok yang menerima intervensi PBL terintegrasi LKPD kontekstual menunjukkan level keaktifan yang lebih tinggi daripada kelompok TGT. Tingginya skor tersebut didorong oleh peran instrumen berorientasi fenomena nyata yang bertindak sebagai scaffolding saat siswa berkolaborasi. Di sisi lain, suasana kompetitif pada kelas TGT justru memicu munculnya kecenderungan dominance effect serta social loafing. Riset ini menegaskan bahwa implementasi PBL dengan dukungan LKPD kontekstual terbukti lebih efektif untuk meningkatkan keaktifan belajar siswa selama pembelajaran matematika.

PERBEDAAN KEMAMPUAN MENYELESAIKAN SOAL TIPE HOTS MENGGUNAKAN MODEL PEMBELAJARAN PBL DENGAN PBL BERBASIS DEEP LEARNING Lailatul Maghfiroh Sya’baniyah; Ari Wibowo; Moh. Bisri; Lila Pangestu Hadiningrum
SCIENCE : Jurnal Inovasi Pendidikan Matematika dan IPA Vol. 6 No. 3 (2026)
Publisher : Pusat Pengembangan Pendidikan dan Penelitian Indonesia (P4I)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51878/science.v6i3.12352

The ability to solve Higher Order Thinking Skills (HOTS) problems is a critical competency that needs to be developed in 21st-century mathematics education. However, real-world evidence indicates that most students still struggle with solving HOTS problems, particularly in the areas of analysis (C4), evaluation (C5), and creation (C6). This study aims to determine the differences in HOTS problem-solving abilities between students using the Problem-Based Learning (PBL) model and those using the deep learning-based PBL model among 10th-grade students at Al-Islam 1 High School in Surakarta during the 2025/2026 academic year. This study employed a quantitative approach using a quasi-experimental method and a posttest-only nonequivalent groups design. The study population consisted of 267 students, with a sample of 42 students selected using cluster random sampling, comprising Class X.2 as Experimental Group 1 (PBL) and Class X.5 as Experimental Group 2 (deep learning-based PBL). The research instrument consisted of HOTS-type essay questions that had undergone validity and reliability tests with a Cronbach’s Alpha coefficient of 0.880. Data analysis utilized the Shapiro-Wilk normality test, Levene’s Test for homogeneity, and an independent samples t-test for hypothesis testing using IBM SPSS Statistics version 25. The results showed a significant difference in HOTS problem-solving ability between the two classes, with a significance level of 0.040 < α = 0.05. The average score for the deep learning-based PBL class (80.29) was higher than that of the standard PBL class (72.52), indicating that the deep learning-based PBL model is more effective in enhancing students’ ability to solve HOTS-type problems. ABSTRAK Kemampuan penyelesaian soal tipe Higher Order Thinking Skills (HOTS) merupakan kompetensi penting yang perlu dikembangkan dalam pembelajaran matematika abad ke-21. Namun kenyataan di lapangan menunjukkan bahwa sebagian besar siswa masih mengalami kesulitan dalam menyelesaikan soal HOTS, khususnya pada indikator menganalisis (C4), mengevaluasi (C5), dan mencipta (C6). Penelitian ini bertujuan untuk mengetahui perbedaan kemampuan penyelesaian soal tipe HOTS antara siswa yang menggunakan model pembelajaran Problem Based Learning (PBL) dengan siswa yang menggunakan model pembelajaran PBL berbasis deep learning pada siswa kelas X SMA Al-Islam 1 Surakarta tahun pelajaran 2025/2026. Penelitian ini menggunakan pendekatan kuantitatif dengan metode quasi eksperimen dan desain posttest-only nonequivalent groups design. Populasi penelitian berjumlah 267 siswa, dengan sampel sebanyak 42 siswa yang dipilih menggunakan teknik cluster random sampling, terdiri atas kelas X.2 sebagai kelas eksperimen 1 (PBL) dan kelas X.5 sebagai kelas eksperimen 2 (PBL berbasis deep learning). Instrumen penelitian berupa soal uraian bertipe HOTS yang telah melalui uji validitas dan uji reliabilitas dengan koefisien Cronbach's Alpha sebesar 0,880. Analisis data menggunakan uji normalitas Shapiro-Wilk, uji homogenitas Levene's Test, dan uji hipotesis independen sample t-test dengan bantuan IBM SPSS Statistics versi 25. Hasil penelitian menunjukkan bahwa terdapat perbedaan yang signifikan antara kemampuan penyelesaian soal HOTS kedua kelas dengan nilai signifikansi 0,040 < α = 0,05. Rata-rata nilai kelas PBL berbasis deep learning (80,29) lebih tinggi dibandingkan kelas PBL (72,52), sehingga model PBL berbasis deep learning terbukti lebih unggul dalam meningkatkan kemampuan penyelesaian soal tipe HOTS siswa.

Perbandingan Penyelesaian SPL dengan Metode Eliminasi Gauss Menggunakan Aplikasi Berbasis Windows dan Android Novia Rista Ramadhani; Anysa Puspitasari; Nazwa Afrilia Soliha; Ari Wibowo
Griya Journal of Mathematics Education and Application Vol. 6 No. 2 (2026): Juni 2026
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v6i2.1142

This study aims to compare the solution of systems of linear equations (SLE) using the Gaussian elimination method through Windows and Android-based applications. This study is a comparative study with a quantitative descriptive approach focusing on the analysis of calculation results and the efficiency of software usage in the context of numerical analysis. Data were obtained from two SLE problem scenarios involving fractional and decimal coefficients, which were then solved using several applications, namely Maple, Microsoft Excel, and the Gauss-Elim calculator. The analysis was conducted based on aspects of accuracy, efficiency, possibility of errors, and ease of use. The results show that Windows and Android-based applications produce the same solutions despite following different solution procedures. Maple demonstrates a high level of accuracy with a systematic and structured solution process. Microsoft Excel requires greater precision because most procedures are carried out manually through elementary row operations. Meanwhile, the Gauss-Elim calculator is the most practical and efficient application because it can display solutions automatically in a short time. Therefore, each application has its own advantages and limitations in supporting SLE solutions using the Gaussian elimination method.

Penerapan Metode Kuadratur Gauss-Legendre dalam Estimasi Akumulasi Curah Hujan Harian DAS Bengawan Solo Linda Agustin WWidyawati Lestari; Mukaromah Mafaza; Ari Wibowo
Griya Journal of Mathematics Education and Application Vol. 6 No. 2 (2026): Juni 2026
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v6i2.1190

This study applies the Gauss-Legendre Quadrature method with order variations n = 2 to n = 6 to calculate discrete daily rainfall accumulation at the Jurug 2 Station of BBWS Bengawan Solo during the period of March 17 - April 15, 2026, which is directly relevant to the major flooding event in Solo Raya on April 14 - 15, 2026. The method adaptation was carried out through interval transformation using the formula xᵢ = 15tᵢ + 16 and linear interpolation to obtain function values at non-integer evaluation points, with all computations implemented using Microsoft Excel. The actual rainfall accumulation value of 353.5 mm was used as the error reference. The calculation results show that the estimates for each order are 293.222 mm (n = 2; error 17.05%), 78.114 mm (n = 3; error 77.90%), 289.299 mm (n = 4; error 18.16%), 252.338 mm (n = 5; error 28.62%), and 414.449 mm (n = 6; error 17.24%). The error convergence pattern is non-monotonic and deviates from theoretical expectations due to the non-smooth characteristics of daily rainfall data with 13 zero-value days. Order n = 2 produces the smallest error, although this advantage is situational. The study concludes that simultaneous cross-order validation is more reliable than applying a single order to support flood early warning systems.

Penyelesaian Persamaan Diferensial Biasa dengan Metode Euler dan Heun Menggunakan Microsoft Excel Della Kusumawati; Karismatun Nisak; Ari Wibowo
GAUSS: Jurnal Pendidikan Matematika Vol. 8 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/gauss.v8i1.10556

Abstrak Tujuan dari penelitian ini adalah untuk mengkaji Microsoft excel dalam menyelesaikan persamaan diferensial biasa (PDB) secara numerik menggunakan metode Euler dan metode Heun, baik kelebihan maupun kekurangnnya. Penelitian ini merupakan penelitian kualitatif dengan pendekatan studi kasus. Data diperoleh dari berbagai sumber seperti buku, artikel ilmiah dan berbagai sumber digital lainnya yang relevan dengan topik penelitian. Analisis data meliputi penentuan soal persamaan diferensial biasa kemudian diimplementasikan secara sistematis dalam Microsoft excel. Hasil penelitian menunjukkan bahwa Microsoft excel terbukti dapat digunakan sebagai alat bantu yang efektif dalam menyelesaikan Persamaan Diferensial Biasa (PDB) secara numerik. Namun, pada implementasinya memiliki kelebihan dan kekurangan. Kata kunci: Metode euler, metode heun, persamaan diferensial biasa, Microsoft excel Abstract The purpose of this research is to examine Microsoft Excel in solving ordinary differential equations (ODEs) numerically using the Euler method and the Heun method, both its advantages and disadvantages. This research is conducted as a qualitative study with a causal approach. Data were obtained from various sources such as books, scientific articles, and other relevant digital sources related to the research topic. Data analysis includes the determination of ordinary differential equation problems, which are then systematically implemented in Microsoft Excel. The research results show that Microsoft Excel has proven to be an effective tool in numerically solving Ordinary Differential Equations (ODEs). However, in its implementation, it has advantages and disadvantages.. Keywords: Euler Method, Heun Method, Ordinary Differential Equations, Microsoft Excel

Co-Authors Ahmad Rafli Hidayat Anysa Puspitasari Arifin, Ahmad Jayadi Aristika, Bella Astuti , Wiwin Astutik Apriliana Aulia Az Zahra Baedowi, Hilmina Rofa' Bisri , Moh. Cynthiagustin Cahya Kartika Della Kusumawati Deshinta Yura Saraswati Dewi, Lathifah Aulia Dhina Laras Ati Dimas Maulidani Erlinda Rahma Dewi Hardi Hardi Heldy Ramadhan Putra P Hidayah, Tsalatsatun Nur Hidayat, Ahmad Rafli INAYAH, ISTIQOMAH SARAH NUR Isnaini Qoiriyah Istnaniah Hani Salami Karismatun Nisak Kiki Insani Sholihah Lailatul Maghfiroh Sya’baniyah Lathifah Aulia Dewi Lesmana, Anung Candra Lila Pangestu Hadiningrum Linda Agustin WWidyawati Lestari Meita Rehania Moh. Bisri Moh. Bisri Mukaromah Mafaza Nabila Istiana Natarina, Lilia Mey Nazwa Afrilia Soliha Nisa’, Adillah Khairun Novia Rista Ramadhani Nur Hidayati Nur Hidayati Nurul Rohmawati, Nurul Ratih Irmawanti Rejeki, Trimo Bagiono Rika Bekti Nur Wahyuni Rosidah, Anisa Rulia Nurul Qomariah Salsabilla Ahadiyyah Shabiya Hasna Prastyla Suyatman Suyatman Syafiqa Lindu Permata SYAHID, IBNU AMIRUS Utami Fitriani Vera Kumala Sari Wiwin Astuti Wiwin Astuti Zahra Nabila Bilqis, Zahra Nabila Bilqis

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