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All Journal JURNAL EKONOMI DAN KEBIJAKAN PEMBANGUNAN Jurnal Manajemen dan Organisasi MANAJEMEN IKM: Jurnal Manajemen Pengembangan Industri Kecil Menengah FORUM STATISTIKA DAN KOMPUTASI Forum Pasca Sarjana Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Media Statistika Jurnal Agro Ekonomi Analisis Kebijakan Pertanian Indonesian Journal of Business and Entrepreneurship (IJBE) Jurnal Pembangunan dan Alam Lestari Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Jurnal Manajemen Teori dan Terapan Jurnal Ilmu Keluarga dan Konsumen Informatika Pertanian BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Zero : Jurnal Sains, Matematika, dan Terapan IJID (International Journal on Informatics for Development) Jambura Journal of Mathematics Jurnal Kesehatan Ibu dan Anak ComTech: Computer, Mathematics and Engineering Applications Jurnal Matematika UNAND Indonesian Journal of Electrical Engineering and Computer Science Jurnal Agro Ekonomi Analisis Kebijakan Pertanian International Journal of Advances in Data and Information Systems InPrime: Indonesian Journal Of Pure And Applied Mathematics ARRUS Journal of Mathematics and Applied Science Journal Of Sustainability Perspectives Makara Journal of Technology Prosiding Seminar Nasional Official Statistics Journal of Sustainability Perspectives Jurnal Ilmu Kehutanan Xplore: Journal of Statistics Scientific Journal of Informatics Indonesian Journal of Jamu Indonesian Journal of Statistics and Its Applications

Hari Wijayanto

Department Of Statistics And Data Science, School Of Data Science, Mathematics, And Informatics, IPB University, Indonesia

Author-ID : 275693

Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Pemilahan Volatilitas Harga Daging Sapi Menggunakan Metode Ensemble Empirical Mode Decomposition Fitria Hasanah; Hari Wijayanto; I Made Sumertajaya
Jurnal Agro Ekonomi Vol 38, No 1 (2020): Jurnal Agro Ekonomi
Publisher : Pusat Sosial Ekonomi dan Kebijakan Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21082/jae.v38n1.2020.41-54

EnglishStaple food prices include the major determinants of households food security and general inflation. Beef is a basic food which its price is controlled by the Government of Indonesia. This study aims to identify the determinants beef price volatility using the Ensemble Empirical Mode Decomposition (EEMD) method. The data was a weekly series of Januari 2006–Desember 2018 obtained from the Ministry of Trade. EEMD extracts data into a number of Intrinsic Mode Functions (IMFs) that are independent which are then used to forecast beef prices with the ARIMA model. EEMD produced 6 IMFs and one residual. The residual contributed 99.85% to beef price volatility. This means that the long-term trend of beef prices is determined by the residual trends. The EEMD results indicate that the high beef price volatility in certain periods is mainly due to high demand during the Ramadhan month and Idul Fitri, import quota policy, and changes in exchange rates and petroleum prices. The IMF and residual based ARIMA forecasting model obtained MAPE value of 0.42% but with contradicting directions. The Government may use the import quota as a policy instrument for stabilizing the beef price.IndonesianHarga pangan pokok termasuk faktor penentu utama ketahanan pangan rumah tangga dan inflasi umum. Daging sapi adalah salah satu bahan pangan pokok yang harganya dikendalikan Pemerintah Indonesia. Penelitian ini bertujuan mengidentifikasi faktor penentu volatilitas harga daging sapi dengan metode Ensemble Empirical Mode Decomposition (EEMD). EEMD menguraikan data menjadi sejumlah Intrinsic Mode Function (IMF) yang saling bebas yang selanjutnya digunakan untuk melakukan peramalan harga daging sapi dengan model ARIMA. Data yang digunakan adalah harga daging sapi mingguan Januari 2006–Desember 2018 yang diperoleh dari Kementerian Perdagangan. EEMD menghasilkan 6 IMF dan satu sisaan. Sisaan IMF memberikan kontribusi sebesar 99,85% terhadap pergerakan harga daging sapi. Artinya bahwa tren jangka panjang harga daging sapi ditentukan oleh tren sisaan. Berdasarkan hasil EEMD, volatilitas harga daging sapi yang tinggi pada periode-periode tertentu dipengaruhi oleh beberapa faktor terutama tingginya permintaan selama bulan Ramadhan dan Idul Fitri dan kebijakan kuota impor, serta perubahan nilai tukar rupiah dan harga BBM. Model peramalan ARIMA yang diduga berdasarkan IMF dan sisaan IMF menghasilkan nilai MAPE sebesar 0,42%, namun arah perubahannya tidak bersesuaian. Disarankan agar pemerintah menggunakan kuota impor sebagai salah satu instrumen kebijakan stabilisasi harga daging sapi.

Kinerja Penyuluh dari Perspektif Petani dan Eksistensi Penyuluh Swadaya Sebagai Pendamping Penyuluh Pertanian Kurnia Suci Indraningsih; Basita G. Sugihen; Prabowo Tjitrpranoto; Pang S. Asngari; Hari Wijayanto
Analisis Kebijakan Pertanian Vol 8, No 4 (2010): Analisis Kebijakan Pertanian
Publisher : Pusat Sosial Ekonomi dan Kebijakan Pertanian

Kinerja penyuluh pertanian PNS belum menunjukkan manfaat yang signifikan dalam peningkatan pendapatan dan kesejahteraan petani. Azas keseimbangan kegiatan penyuluhan, yang memperhatikan keseimbangan antara kebijakan, inovasi teknologi dengan kearifan masyarakat setempat, keseimbangan pemanfaatan sumberdaya dan kelestarian lingkungan, serta keseimbangan antar kawasan yang maju dengan kawasan yang relatif tertinggal, masih belum terlaksana dengan baik. Azas kerjasama dalam penyelenggaraan penyuluhan yang seharusnya dilaksanakan secara sinergis dalam kegiatan pembangunan pertanian, perikanan dan kehutanan serta sektor lain belum tercapai dengan baik. Azas berkeadilan, belum tercermin dalam penyelenggaraan penyuluhan yang memposisikan pelaku utama dan pelaku usaha berhak mendapatkan pelayanan secara proporsional sesuai dengan kemampuan, kondisi, serta kebutuhan pelaku utama dan pelaku usaha. Satu tenaga penyuluh pertanian PNS di Cianjur dan Garut membina 3-4 desa, ditambah tugas-tugas administratif. Kebijakan yang telah dicanangkan Kementerian Pertanian menetapkan satu desa satu penyuluh pertanian. Untuk pencapaian target tersebut, alternatif yang dipandang sejalan dengan UU RI Nomor 16 Tahun 2006 adalah merekrut ketua kelompok tani sebagai penyuluh swadaya yang bertugas mendampingi penyuluh pertanian PNS.

Prediction of Undergraduate Student’s Study Completion Status Using MissForest Imputation in Random Forest and XGBoost Models Intan Nirmala; Hari Wijayanto; Khairil Anwar Notodiputro
ComTech: Computer, Mathematics and Engineering Applications Vol. 13 No. 1 (2022): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v13i1.7388

The number of higher education graduates in Indonesia is calculated based on their completion status. However, many undergraduate students have reached the maximum length of study, but their completion status is unknown. This condition becomes a problem in calculating the actual number of graduates as it is used as an indicator of higher education evaluation and other policy references. Therefore, the unknown completion status of the students who have reached the maximum length of study must be predicted. The research compared the performance of Random Forest and Extreme Gradient Boosting (XGBoost) classification models in predicting the unknown completion status. The research used a dataset containing 13.377 undergraduate students’ profiles from the Higher Education Database (PDDikti), Ministry of Education, Culture, Research, and Technology. The dataset was incomplete, and the proportion of missing data was 20,9% of the total data. Because missing data might lead to prediction bias, the research also used MissForest imputation to overcome the missing data in the classification modelling and compared it to Mean/Mode and Median/Mode imputation. The results show that MissForest outperforms the other two imputations in both classifiers but requires the longest computation time. Furthermore, the XGBoost model with MissForest is significantly superior to the Random Forest model with MissForest. Hence, the best model chosen to predict the completion status is XGBoost with MissForest imputation.

Simulation on the Use of LOSAT Data for Rice Field Mapping Trisasongko, Bambang H.; Panuju, Dyah R; Tjahjono, Boedi; Barus, Baba; Wijayanto, Hari; Raimadoya, Mahmud A.; Irzaman, Irzaman
Makara Journal of Technology Vol. 14, No. 2
Publisher : UI Scholars Hub

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

Simulation on the Use of LOSAT Data for Rice Field Mapping. Since the launch of LAPAN-TUBSAT satellite in 2007, Indonesia has been developing mission on earth observation missions for various applications. The next generation mission, called LAPAN-ORARI Satellite (LOSAT), is currently under development and expected to be launched in 2011. In order to facilitate the applications, a thorough assessment of the sensor should be made. This paper presents an examination of simulated LOSAT data for rice monitoring and mapping purposes coupled with QUEST statistical tree. We found that three-band simulated LOSAT data were suitable for the task with reasonably high accuracy.

PEMANFAATAN ENSEMBLE LEARNING DAN PENGINDERAAN JAUH UNTUK PENGKLASIFIKASIAN JENIS LAHAN PADI Arif Handoyo Marsuhandi; Agus Mohamad Soleh; Hari Wijayanto; Dede Dirgahayu Domiri
Seminar Nasional Official Statistics Vol 2019 No 1 (2019): Seminar Nasional Official Statistics 2019
Publisher : Politeknik Statistika STIS

Pertanian adalah bidang yang sangat penting di Indonesia, sektor ini di tahun 2017 mencatat penyerapan tenaga kerja sebanyak 29.68% dari total seluruh pekerja (BPS, 2018), namun pentingnya sektor pertanian ini berbanding terbalik dengan data pertanian yang tersedia. Tahun 1998 Badan Pusat Statistik (BPS) bersama Japan International Cooperation Agency (JICA) telah mengisyaratkan overestimasi luas panen sekitar 17,07 persen. Ketidakuratan data pertanian ini kemudian diperbaiki pada tahun 2018 melalui kerjasama para stakeholder dengan menyusun suatu metodologi baru dalam menghitung luas lahan yang diberi nama kerangka sampel area. Selain metodologi yang sudah diperbarui, kemajuan teknologi dan teknik analisis di bidang ilmu pengetahuan juga mendukung perbaikan data pertanian. Citra satelit dan teknik klasifikasi menggunakan ensemble learning dapat dimanfaatkan dalam mengklasifikasikan jenis lahan padi. Pada penelitian ini digunakan citra satelit yang berasal dari United States Geological Survey (USGS) yaitu Landsat 8 dan teknik klasifikasi ensemble learning. Citra satelit dimanfaatkan untuk mengekstrak indeks vegetatif dari koordinat koordinat yang diteliti, sedangkan ensemble learning yang digunakan dalam penelitian ini yaitu Random Forest dan Boosting. Hasil pengolahan data menunjukkan Random Forest memiliki akurasi yang lebih tinggi daripada Boosting yaitu dengan nilai 76,52 untuk Random Forest dan 75,60 untuk Boosting. Keunggulan Random Forest terhadap Boosting tidak hanya dari sisi tingkat akurasi saja namun juga dari kestabilan model yang dibentuk.

Karakteristik Spektra Absorbansi NIR (Near Infra Red) Spektroskopi Kayu Acacia mangium WILLD pada 3 Umur Berbeda Lina Karlinasari; Merry Sabed; Nyoman J. Wistara; Aris Purwanto; Hari Wijayanto
Jurnal Ilmu Kehutanan Vol 6, No 1 (2012)
Publisher : Fakultas Kehutanan Universitas Gadjah Mada

Penelitian mengenai pengujian nondestruktif metode near infrared (NIR) spektroskopi di Indonesia masih sangat terbatas. Penelitian ini bertujuan untuk menentukan karakteristik spektra NIR spektroskopi (panjang gelombang 700 nm – 2500 nm) kayu Acacia mangium dari 3 umur yaitu 5, 6, dan, 7 tahun. Kayu mangium diperoleh dari daerah Maribaya, Parung Panjang, Bogor. Sampel contoh uji spektra terdiri dari bentuk solid atau padatan dan bentuk serbuk kayu. Hasil penelitian menunjukkan spektra absorban NIR sampel padatan kayu lebih tinggi dibandingkan bentuk sampel serbuk. Umur pohon untuk jenis kayu yang sama tidak memberikan informasi perbedaan pola spektra absorbansi NIR yang nyata untuk setiap lokasi panjang gelombangnya. Penelitian lebih lanjut dapat dilakukan untuk menentukan model pendugaan sifat kimia, fisis dan mekanis kayu menggunakan analisis statistik metode analisis multivariasi.Kata kunci: NIR spektroskopi, Acacia mangium, kayu solid, serbuk kayu Characteristics of Absorbency Spectra of NIR (Near Infra Red) Spectroscopy of Acacia mangium Willd Wood from Three Different AgeAbstractResearch on non-destructive test of near infrared (NIR) spectroscopy method was still limited in Indonesia. The aim of this study was to determine near infrared (NIR) spectroscopy (wavelength range within 780 nm -2500 nm) characteristic of wood species of Acacia mangium. The samples were selected from three different ages e.g. 5 year, 6 years, and 7 years grown in Maribaya area of Parung Panjang Distric. The NIR testing samples used were solid wood and ground wood. This study resulted that there was visually no significant difference of absorbance spectra NIR patterns based on wood ages. NIR absorbance spectra had same trend for both solid and ground wood samples in a range of wavelength, although those were in different values. The NIR absorbance spectra values of solid wood samples seemed higher than ground wood samples. Further research is needed to develop predicting model of NIR spectroscopy to determine wood properties of chemical, physical and mechanical properties using multivariate analysis method.

Penerapan Metode Resampling dan K-Nearest Neighbor dalam Memprediksi Keberhasilan Studi Mahasiswa Program Magister IPB Devi Andrian; Agus Mohamad Soleh; Hari Wijayanto
Xplore: Journal of Statistics Vol. 2 No. 1 (2018): 30 Juni 2018
Publisher : Department of Statistics, IPB

Graduate School IPB (SPs - IPB) has been established for a long time and is believed to produce high quality graduates and highly competitive. However, based on existing data recaps, there are a small number of students who did not graduate, either resigned or Drop Out (DO). It needs to be handled by conducting a selection process for prospective students based on the profile and educational background S1. One of them by applying the method of classification K - Nearest Neighbor (KNN). The response variable used is the success status of the study of prospective students, ie graduated and not graduated. While the explanatory variables used are the profiles and educational background of prospective students. There is an imbalance of data in the data obtained, where the class does not pass much less than the passing class. This can reduce the value of classification accuracy in minority class (sensitivity). So that the handling of data imbalance by using resampling method, either in the form of Random Over Sampling (ROS), Random Under Sampling (RUS), and Random Over-Under Sampling (ROUS). The result of comparison of evaluation result of KNN classification by using k = 1 to 6, resulted in greater sensitivity value when accompanied by the process of handling the data imbalance than without the process of handling the data imbalance, although the accuracy and specificity value becomes smaller. The greatest sensitivity value was obtained when applying the KNN classification method with k = 1, accompanied by the handling of data imbalance by the RUS method, with the mean and median sensitivity values of 0.89 and 0.90, respectively.

Analisis Tingkat Kesenjangan Pendapatan antar Provinsi di Indonesia Menggunakan Regresi Data Panel Model Pengaruh Tetap Thooriq Ghaith; Hari Wijayanto; Anang Kurnia
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.125

THOORIQ GHAITH. Analysis of Income Disparity Rates among Provinces in Indonesia Using Panel Data Regression. Supervised by HARI WIJAYANTO and ANANG KURNIA. Income disparities in Indonesia generally and in each province particularly is a serious problem from year to year. It is necessary to find out the factors that affect the income disparity rates (Gini ratio) to be taken into consideration in determining the economic policy. By using data of 33 provinces from 2007 until 2016, panel data regression with provincial fixed effect model approach was used to determine factors that affect Gini ratios in Indonesia and to capture the differences of Gini ratio characteristics of each province in form of intercept. Modeling was done for whole Indonesia and for five regions as well to find out what factors that affect the Gini ratio of provinces in Indonesia generally and what factors affect Gini ratios of provinces in each region particularly. The percentage of poor people is a significant factor to Gini ratio in the model throughout Indonesia and in the model of each region, except in Sumatera. Beside the percentage of the poor people, other explanatory variables affecting Gini ratios are GDP growth rates in Kalimantan, open unemployment rates in Sulawesi, and provincial minimum wage in Nusa Tenggara, Maluku and Papua. All of the predicted models are good enough because they produce MAPE values below 10%.

Identifikasi Faktor-Faktor yang Memengaruhi Prestasi Mahasiswa Menggunakan Regresi Logistik Ordinal dan Random Forest Ordinal: Studi Kasus Mahasiswa FMIPA IPB Angkatan 2015-2017 Zuhdiyah Izzatun Nisa'; Agus M Soleh; Hari Wijayanto
Xplore: Journal of Statistics Vol. 10 No. 1 (2021)
Publisher : Department of Statistics, IPB

Student achievement is the result of student learning processes and efforts. This research was conducted through a survey of students of the 2015-2017 FMIPA IPB with the selection of respondents using stratified random sampling. The purpose of this study is to identify the factors that influence the achievements of the 2015-2017 FMIPA IPB students using ordinal logistic regression and ordinal random forest. The response variable used is the PPKU GPA category and the last even semester GPA which is categorized based on the predicate of IPB graduation. The results of ordinal logistic regression get 7 explanatory variables that influence the PPKU GPA and 7 explanatory variables that influence the last even semester GPA. Explanatory variables that have a significant effect on ordinal logistic regression and become 10 variables with the highest level of importance in the ordinal random forest for both response variables are department, motherâ€™s education, internet access in a day for games, activity in the class, and active work on a group assignment.

Penerapan Support Vector Machine dengan SMOTE Untuk Klasifikasi Sentimen Pemberitaan Omnibus Law Pada Situs CNNIndonesia.com Widiananda Putri Hutami; Hari Wijayanto; Itasia Dina Sulvianti
Xplore: Journal of Statistics Vol. 11 No. 1 (2022)
Publisher : Department of Statistics, IPB

The declaration of the omnibus law reaped the pros and cons in the community. In a situation like this, the media should be neutral. One of the media that still maintains neutrality is Detik (Rumata 2017). Detik owns several channels such as detikNews, detikFinance, and CNN Indonesia. In this study, the neutrality of the CNN Indonesia media as part of Detik will be studied based on the tendency of sentiment on the omnibus law-related news. Sentiment analysis is used to examine the trend of opinion on news headlines. In conducting sentiment analysis, a method that supports classification is needed. The classification method that will be used in this research is the Support Vector Machine (SVM). There is an imbalance of data in the three categories of sentiment so that the Synthetic Minority Oversampling Technique (SMOTE) method is used to overcome this imbalance. The omnibus law tends to be reported neutrally by CNNIndonesia.com site. The one vs all method has a better classification result than the one vs one method. The application of SMOTE only gives slightly better results than data classification without the application of SMOTE because the imbalance in the data is not too extreme. Modeling using the one vs all method with SMOTE and distribution of data 90% train data 10% test data gives the best classification results with a macro average f1-score of 60,33%.

Co-Authors . Aunuddin . Barizi . Gunawan Aan Kardiana Afnan, Irsyifa Mayzela Agus Heru Darjono Agus M Soleh Agus M. Sholeh Agus Mohamad Soleh Ahmad Syauqi Aji Hamim Wigena Akhmad Fauzi Aldi Cahyanugroho Alim Setiawan Slamet Amin Leksono Anadra, Rahmi Anang Kurnia Anas Miftah Fauzi Andres Purmalino Anggraini Sukmawati Anindia Nufitasari Arief Hendarto Arif Handoyo Marsuhandi Aris Purwanto Aruddy Aruddy ASEP SAEFUDDIN Astridina, Astridina Aunuddin Aunuddin Ayunda Pratiwi Baba Barus Bagus Sartono Bambang Hendro Trisasongko Barizi . Basita G. Sugihen Bertho Tantular Boedi Tjahjono Budi Susetyo Cici Suhaeni Cici Suhaeni Cut Zaraswati DAHRUL SYAH Dede Dirgahayu Domiri Dedi Budiman Hakim Denanda Aufadlan Tsaqif Devi Andrian Dyah R Panuju Dyah R. Panuju Dyah R. Panuju Edi Abdurrachman Eko S. Pribadi Erfiani Erfiani Erliza Noor Fachry Abda El Rahman Fani Fahira Farit M Afendi Farit Mochamad Afendi Farly Shabahul Khairi fatimah Fatimah Femmy Diwidian Fitria Hasanah Fitrianto, Anwar Ghada Abd Elsattar Mohammed, Oraby H S, Rahmat Hefni Effendi Heny K Daryanto Heriansyah Putra Hikmah, Zetil Hwan-Seung Yong I K Marla Lusda I Made Sumertajaya I Nyoman Jaya Wistara IBNUL QAYIM Ilma, Meisyatul Ina Widayanty Indah Dwi Pratama Indahwati Indahwati Inna Firindra Fatati Intan Nirmala Irzaman, Irzaman Istiqlaliyah Muflikhati Itasia Dina Sulvianti Jajah K. Wagiono Jayawarsa, A.A. Ketut Khairil Anwar Notodiputro Kristuisno Martsuyanto Kapiluka Kurnia Suci Indraningsih Kusman Sadik La Ode Abdul Rahman La Ode Abdul Rahman Laily Nissa Atul Mualifah Leny Maryesa Lilik Noor Yuliati Lina Karlinasari Luvy Mayanda M. Syamsul Maarif Mahmud A. Raimadoya Mahmud A. Raimadoya Masrukin Masrukin Maulina Lamuse Merry Sabed Mohamad Solehudin Zaenal Muhammad Nur Aidi Mulianto Raharjo Musa Hubeis Nunung Nurjanah Nurrahman, Fathu Oktaviyani Daswati Panca Wiputra Pang S. Asngari Pannu, Abdullah Prabowo Tjitrpranoto Rachma Venita Rahmania, Farhani Nurshafa Ramadhanis, Zainab Riana Riskinandini Rizal Bakri Rizky Nurkhaerani Rysda Rysda Sachnaz Desta Oktarina Sri Kustiara Sutoro Sutoro Thooriq Ghaith Ujang Sumarwan Utami Dyah Syafitri Utami, Anisa Dwi Widiananda Putri Hutami Yandhika Hary Wibowo Yarah, Helena Ramadhini Yenni Angraini Yonny Koesmaryono Yuli Sukmawati Yuni Suci Kurniawati Zilrahmi, Zilrahmi Zuhdiyah Izzatun Nisa'

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