MODEL ADDITIVE VECTOR AUTOREGRESSIVE EXOGENOUS (VARX) UNTUK PERAMALAN CURAH HUJAN DI KABUPATEN INDRAMAYU

Suatu permasalahan yang sering dihadapi dalam pemodelan untuk meramalkan curah hujan seperti di Indramayu yakni adanya data hilang, data pencilan, dan keragaman curah hujan yang tinggi. Adanya keragaman curah hujan yang tinggi dapat diatasi dengan melakukan pewilayahan curah hujan. Pewilayahan curah hujan menghasilkan 3 wilayah, wilayah 1 terdiri atas stasiun Anjatan, Bugel, Tulung Kacang, Karang Asem, Lawang Semut, Wanguk, Gabus Wetan, Cikedung, Kroya, Sukadana, Sumur Watu, Tugu, Bondan; wilayah 2 terdiri atas stasiun Salamdarma dan Gantar ; wilayah 3 terdiri atas stasiun Cidempet, Losarang, Bangkir, Indramayu, Jatibarang, Juntinyuat, Kedokan Bunder, Lohbener, Sudi Mampir, Krangkeng, dan SudiKampiran. Berdasarkan pewilayahan tersebut dapat ditentukan model aditif Vector Autoregressive Exogenous (VARX) ordo 1 atau VARX (1) yang pemodelannya difokuskan pada Wilayah 2 dan dapat meramalkan curah hujan 1 bulan ke depan. Model aditif VARX (1) dikembangkan dari model VARX (1), fungsi smoothing spline dan peubah indikator curah hujan. Model VARX (1) dikembangkan dari model Vector Autoregressive (VAR (1)) dengan menambahkan faktor-faktor (eksogen) yang diduga mempengaruhi curah hujan yakni Sea Surface Temperature (SST) Nino 3.4, Indeks Osilasi Selatan (SOI), dan indeks Dipole Mode (DMI). Keandalan model aditif VARX di stasiun Salam Darma dan Gantar dievaluasi dengan kurva Relative Operating Characteristics (ROC). Hasil ROC menunjukkan bahwa model handal pada bulan Januari hingga April, November, Desember. Model akan optimal jika senantiasa dilakukan penambahan data baru. Kata kunci : smoothing spline, peubah indikator, VAR, VARX, aditif VARX, ROC

MEMPREDIKSI CURAH HUJAN (DATA SPATIO-TEMPORAL) DENGAN METODE BAYESIAN NETWORKS

Curah hujan merupakan salah satu parameter yang berkaitan dengan dampak perubahan iklim. Oleh karena itu, dalam penelitian klimatologi dan metereologi, parameter tersebut sering dilibatkan. Di Indonesia yang berada di kawasan tropis, simulasi curah hujan merupakan proses yang sukar untuk disimulasikan. Bahkan hingga saat ini, belum ada suatu model iklim yang mampu mensimulasikan curah hujan di Indonesia dengan baik. Beberapa penelitian yang telah dilakukan belum mampu memberikan hasil yang cukup memadai. Namun begitu, beberapa metode telah dikembangkan untuk menduga curah hujan. Salah satu metode yang sering digunakan adalah ARIMA (Auto Regressive Integrated Moving Average) untuk data musiman. Kelemahannya, metode tersebut hanya dapat dipergunakan pada pendugaan curah hujan berdasarkan data curah hujan yang ada di stasiun penakar hujan (temporal) tanpa mempertimbangkan lokasi stasiunnya (spatial). Dengan demikian, diperlukan suatu metode yang mempertimbangkan keduanya, salah satu metode yang dimaksudkan adalah Bayesian Networks (BNs). Struktur BNs dibangun berdasarkan model peluang ketergantungan antar stasiun yang dinyatakan dalam directed acyclic graph (DAC) dan untuk mengoptimalkan peluangnya dipergunakan algoritma K2. Dalam paper ini, disampaikan tentang BNs dalam pendugaan curah hujan, kelemahan dan kelebihannya. Metode yang dipakai dalam penelitian ini yakni deduksi dan induksi, dengan melakukan penelusuran terhadap materi tentang iklim dan metode prediksi curah hujan, utamanya tentang BNs. Penelusuran dilakukan terhadap penelitian-penelitian terdahulu serta pada beberapa textbook dan jurnal ilmiah serta beberapa diskusi ilmiah. Selanjutnya, mengkaji dan me-review beberapa teoritisnya yang dikaitkan dengan pemodelan curah hujan. Berdasarkan kajian ini, dapat dinyatakan bahwa BNs merupakan salah satu metode yang dapat dipertimbangkan untuk memprediksi data curah hujan karena dalam metode ini, BNs memperhitungkan nilai peluang untuk setiap stasiun penakar hujan. Namun, BNs lemah, saat menentukan urutan stasiun dalam membentuk suatu jaringan Bayes

MENGOPTIMALKAN KORELASI PADA MODEL PERGERAKAN NILAI TUKAR DOLLAR DENGAN ALGORITMA ACE (ALTERNATING CONDITIONAL EXPECTATIONS)

Terdapat beberapa faktor fundamental dan sentimen yang mempengaruhi nilai tukar rupiah terhadap dollar. Pada suatu penelitian sebelumnya, model pergerakan nilai tukar rupiah tersebut menggunakan 11 faktor (peubah): GDP riil Indonesia, perbedaan tingkat suku bunga antara Indonesia dan Amerika, tingkat inflasi Indonesia, investasi asing, pembayaran utang luar negeri, cadangan devisa, jumlah uang beredar, capital inflow domestik, trade balance, harga minyak dunia, dan indeks keyakinan konsumen. Adapun model yang digunakan, regresi linear dengan korelasinya () sebesar 0,781. Sementara itu, di sisi lainnya, terdapat metode yang berbasis algoritma ACE (Alternating conditional expectations). yang dapat digunakan untuk mengoptimalkan korelasi. Oleh karena itu, dalam paper ini, dilakukan pengoptimalan korelasi pada model nilai tukar rupiah yang telah diformulasikan oleh peneliti sebelumnya. Metode yang dipakai dalam penelitian ini yakni deduksi dan induksi, dengan melakukan penelusuran terhadap algoritma ACE. Penelusuran dilakukan terhadap penelitian terdahulu serta pada beberapa textbook dan jurnal ilmiah. Selanjutnya, dilakukan implementasi pada nilai tukar dolar dan faktor-faktor yang mempengaruhinya, melakukan reduksi terhadap faktor yang berpengaruh serta memperoleh nilai korelasinya. Berdasarkan penelitian ini, faktor-faktor yang mempengaruhi pergerakan nilai tukar rupiah terhadap dollar dapat dikoreksi dengan 9 faktor : GDP riil Indonesia, perbedaan tingkat suku bunga antara Indonesia dan Amerika, tingkat inflasi Indonesia, investasi asing, pembayaran utang luar negeri, cadangan devisa, jumlah uang beredar, capital inflow domestik, trade balance. Selain itu, diperoleh juga peningkatan korelasi sebesar 0,94 dan dapat diidentifikasi bentuk fungsional antara peubah respon (nilai tukar dollar) dan peubah penjelas (9 faktor) secara akurat

CABLE NEWS NETWORK (CNN) ARTICLES CLASSIFICATION USING RANDOM FOREST ALGORITHM WITH HYPERPARAMETER OPTIMIZATION

The growth of news articles on the internet occurs in a short period with large amounts so necessary to be grouped into several categories for easy access. There is a method for grouping news articles, namely classification. One of the classification methods is random forest which is built on decision tree. This research discusses the application of random forest as a method of classifying news articles into six categories, these are business, entertainment, health, politics, sport, and news. The data used is Cable News Network (CNN) articles from 2011 to 2022. The data is in form of text and has large amounts so good handling is needed to avoid overfitting and underfitting. Random forest is proper to apply to the data because the algorithm works very well on large amounts of data. However, random forest has a difficult interpretation if the combination of parameters is not appropriate in the data processing. Therefore, hyperparameter optimization is needed to discover the best combination of parameters in the random forest. This research uses search cross-validation (SearchCV) method to optimize hyperparameters in the random forest by testing the combinations one by one and validating those. Then we obtain the classification of news articles into six categories with an accuracy value of 0.81 on training and 0.76 on testing

THE COMPARISON OF GROUP INVESTIGATION AND THINK PAIR SHARE WITH ASSESSMENT FOR LEARNING VIEWED FROM STUDENTS’ SELF CONFIDENCE OF EIGHTH GRADE STUDENTS OF JUNIOR HIGH SCHOOL

This research was a quasi-experimental research with a factorial design 2×3 aims to determine the comparison of Group Investigation (GI) with Assessment for Learning (AfL) through peer-assessment (GI-AfL-Peer) and TPS with AfL through peer-assessment (TPS-AfL-Peer) viewed from self confidence for student’s achievement in mathematics. The population of this research were all of Junior High School students 8th grade in Karanganyar Regency schools in academic year 2016/2017. Research samples obtained by stratified cluster random sampling. The data was collected by using methods of documentation, students’ self confidence questionnaires, and mathematics achievement test. Data analysis technique used two way analysis of variance (ANOVA) with unequal cell. According to research result, it could be concluded that: (1) students’ mathematics achievement which applied GI-AfL-Peer better than TPS-AfL-Peer, (2) mathematics achievement of students with high self confidence better than students’ with medium and low self confidence, and mathematics achievement of students’ with medium self confidence as good as students with low self confidence, (3) in each category of self confidence, students’ mathematics achievement which applied GI-AfL-Peer better than TPS-AfL-Peer, (4) in each learning model, mathematics achievement of students with high self confidence better than students’ with medium and low self confidence, and mathematics achievement of students’ with medium self confidence as good as students with low self confidence.Keywords: AfL, GI, peer-assessment, self confidence, students’ mathematics achievement, TP

THE COMPARISON OF THINK TALK WRITE AND THINK PAIR SHARE WITH TALKING STICK VIEWED FROM STUDENTS' INDEPENDENT LEARNING EIGHTH GRADE STUDENTS OF JUNIOR HIGH SCHOOL

This research was a quasi-experimental research with 2×3 factorial design. It aimed to determine the learning model between Think Talk Write with Talking Stick (TTW-TS) and Think Pair Share with Talking Stick (TPS-TS) that gave the best achievement on mathematics subject viewed from students' independent learning. The population of this research were all of Junior High School students at the 8th grade in Ngawi Regency, East Java, Indonesia in academic year 2016/2017 which applied KTSP curriculum. The sample was taken by using stratified cluster random sampling. The data were collected by using methods of documentation, students' independent learning questionnaires, and mathematics achievement test. Data analysis technique used two ways analysis of variance (ANOVA) with unequal cell. According to the research findings, it could be concluded that: (1) students' mathematics achievement which were taught by using TTW-TS is as good as students' mathematics achievement which were taught by using TPS-TS in relation and function material, (2) mathematics achievement of students with high independent learning is better than students with medium and low independent learning, and mathematics achievement of students with medium independent learning is as good as students with low independent learning in relation and function material, (3) in each learning model, mathematics achievement of students with high independent learning is better than students with medium and low independent learning, and mathematics achievement of students with medium independent learning is as good as students with low independent learning in relation and function material (4) in each category of high and medium independent learning, student’s mathematics achievement which were taught by using TTW-TS is better than student’s mathematics achievement which were taught by using TPS-TS and in low independent learning student’s mathematics achievement which were taught by using TTW-TS is as good as student’s mathematics achievement which were taught by using TPS-TS in relation and function material. Keywords: Think talk write, think pair share, talking stick, independent learning, relation and functio

Teaching Materials based on Reciprocal Teaching to Improve Mathematical Communication Skills

The most significant concern in teaching mathematical concepts is developing and improving mathematical communication skills. However, the reality reveals that communication skills possessed by students are still relatively low. This causes students’ difficulty in understanding the material, solving problems, and conveying mathematical ideas both in oral or written form. Furthermore, students’ teaching material is not adequate to support the expected learning goals. It creates students’ difficulty in understanding the materials and it doesn’t integrate mathematical communication skills. This study aims to develop teaching materials in the form of mathematics module based on reciprocal teaching to improve students' mathematical communication skills. This is a research development that employs Four-D model. Subjects of the study are the teachers and the seventh grade Junior High School. In collecting the data, the researchers employ observation, interviews, questionnaires, and mathematical communication skills test. The results show that teaching material in the form of module that is assessed by experts has reached excellent criteria in terms of material and media. The module is also practically used by students and teachers in the learning process. It means, module based on reciprocal teaching can improve students' mathematical communication skill

MASALAH NILAI AWAL ITERASI NEWTON RAPHSON UNTUK ESTIMASI PARAMETER MODEL REGRESI LOGISTIK ORDINAL TERBOBOTI GEOGRAFIS (RLOTG)

Abstrak: Model RLOTG merupakan pengembangan dari model regresi logistik dengan variabel respon memiliki lebih dari dua kategori dan memiliki tingkatan. Model tersebut merepresentasikan hubungan antara variabel bebas dengan variabel respon dan peluang kejadian yang diakibatkan oleh variabel bebas yang memperhatikan pengaruh lokasi pengamatan. Parameter untuk model RLOTG menunjukkan karakteristik populasi pengamatan, umumnya estimasi parameter menggunakaan metode maximum likelihood. Metode tersebut menghasilkan suatu sistem persamaan nonlinier yang sulit ditentukan penyelesaian eksaknya maka digunakan pendekatan numerik. Pendekatan numerik yang digunakan adalah iterasi Newton Raphson. Iterasi tersebut dimulai dengan menentukan nilai awal (initial value). Perhitungan dengan Newton Raphson dapat konvergen atau divergen sesuai pada nilai awal yang diberikan. Tujuan penelitian ini adalah melakukan estimasi parameter pada model RLOTG dengan iterasi Newton Raphson menggunakan dua nilai awal yaitu 0 dan nilai awal dari estimator parameter model regresi logistik ordinal (RLO). Penerapan dilakukan pada pemodelan tingkat banyak penderita demam berdarah dengue (DBD) di Kota Semarang dengan model RLO untuk mendapatkan estimator parameter sebagai nilai awal, selanjutnya ditentukan nilai estimasi parameter model RLOTG. Hasil penelitian menunjukkan bahwa dengan nilai awal 0 dicapai konvergen pada seluruh lokasi, namun iterasi yang diperlukan lebih banyak daripada nilai awal dari estimasi parameter model RLO. Pada penerapan, ditunjukkan bahwa estimasi parameter dengan nilai awal dari estimator parameter model RLO membutuhkan iterasi yang lebih sedikit daripada nilai awal 0, namun untuk beberapa lokasi, estimasi parameter modelnya tidak mencapai konvergen.Kata kunci: Estimasi Parameter, Newton Raphson, Nilai Awal, Model RLOT

HILL CLIMBING ALGORITHM ON BAYESIAN NETWORK TO DETERMINE PROBABILITY VALUE OF SYMPTOMS AND EYE DISEASE

One of the five human senses referred to as photoreceptors is the eye because the eye is very sensitive to light stimuli. Refractive abnormalities in the eyes are often experienced, which are abnormalities that occur when the eyes cannot see clearly in the open or blurred vision. An unhealthy lifestyle is a trigger for an increase in individuals who experience complaints of eye diseases. In diagnosing a disease, doctors need patient information in the form of symptoms experienced so that patients can be treated immediately. Information in the form of symptoms and types of eye diseases can be used to make conjectures about eye diseases through the structure of BN. The symptom information and type of the disease are represented through nodes, while the relationships are represented through the edge. BN is one of the Probabilistic Graphical Models (PGM) consisting of nodes and edges. BN is also known as a direct acyclic graph (DAG), which is a directed graph that does not have a cycle. The approach method used is scored based on the evaluation process with the bic scoring function. The algorithm used in this study is the HC algorithm. The research data used consisted of 52 symptoms and 15 eye diseases. The results of the study were obtained by the final structure of BN formed by the HC algorithm produced 93 edges and 65 connected nodes, and the probability value of the disease and the symptoms of the disease in the eye

Eksperimentasi Model Pembelajaran Kooperatif Tipe Think Talk Write Dan Think Pair Share Pada Materi Operasi Aljabar Ditinjau Dari Keterampilan Sosial Siswa Kelas VIII SMP Negeri Se-kabupaten Semarang Tahun Pelajaran 2014/2015

The purposes of this study was to determine the effect of the learning models on the learning achievement in Mathematics viewed from the sosial skill of the students. The learning models compared were the cooperative learning model of the Think Talk Write (TTW) type with scientific approach, Think Pair Share (TPS) type with scientific approach, and classical model with scientific approach.The type of this study was a quasi-experimental study with a 3x3 factorial design. The study population were all of grade VII students of Junior High School in Kabupaten Semarang. Instruments used for data collection were mathematics achievement test and sosial skill questionnaire. The proposed hypotheses of the research were analyzed by using the two way analysis of variance with unbalanced cells. Based on the hypothesis testing it can be concluded as follows. (1) Students\u27 learning achievement treated by TTW learning model with scientific approach are better than students treated by TPS model with scientific approach and classical learning model with scientific approach. In addition to, students\u27 learning achievement treated by TPS model with scientific approach are better than students treated by classical learning model with scientific approach. (2) Students\u27 learning achievement who have high social skill are better than students who have moderate and low social skill. Furthermore, students who have moderate social skill are better than students who have low social skill. (3) In high, moderate, and low social skill category, students learning achievement treated by TTW model with scientific approach are better than student who treated by TPS learning model with scientific approach and classical learning model with scientific approaching. Asides from that, students learning achievement are treated by TPS learning model with scientific approach are better than students who treated by classical learning model with scientific approach. (4) In TTW learning model with scientific approaching, TPS with scientific approach and classical learning with scientific approach, students learning achievement who have high social skill are better than students who have moderate and low social skill. Moreover, students who have moderate social skill are better than students who have low social skill