{"id":899,"date":"2018-02-02T11:11:15","date_gmt":"2018-02-02T04:11:15","guid":{"rendered":"http:\/\/stat.fsm.undip.ac.id\/v1\/?page_id=899"},"modified":"2025-08-01T10:47:39","modified_gmt":"2025-08-01T03:47:39","slug":"dra-suparti-m-si","status":"publish","type":"page","link":"https:\/\/stat.fsm.undip.ac.id\/v1\/dra-suparti-m-si\/","title":{"rendered":"Dra. Suparti, M.Si"},"content":{"rendered":"

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Dra. Suparti, M.Si.<\/h1>\n

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NIP : 196509131990032001<\/strong><\/span><\/p>\n

NIDN : 0013096508<\/strong><\/span><\/p>\n

NUPTK : 9245743644230073<\/strong><\/span><\/p>\n

Jabatan : Lektor Kepala<\/strong><\/span><\/p>\n

Pangkat, Golongan : Pembina TK I, IV\/b<\/strong><\/span><\/p>\n

E-mail : suparti702 [at] gmail [dot] com<\/strong><\/span><\/p>\n

Kepakaran : Regresi Nonparametrik, Wavelet<\/strong><\/span><\/p>\n

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Dra. Suparti, M.Si. NIP : 196509131990032001NIDN : 0013096508NUPTK : 9245743644230073Jabatan : Lektor KepalaPangkat, Golongan : Pembina TK I, IV\/bE-mail : suparti702 [at] gmail [dot] comKepakaran : Regresi Nonparametrik, Wavelet<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"

\"532565_454416077927682_850083558_n\"<\/a><\/p>

DAFTAR RIWAYAT HIDUP<\/strong><\/p>

A. Identitas Diri<\/p>
Nama Lengkap<\/td>:<\/td>\u00a0Dra.Suparti, M.Si.<\/td><\/tr>
\u00a0Jabatan Fungsional<\/td>\u00a0:<\/td>\u00a0Lektor Kepala<\/td><\/tr>
\u00a0Jabatan Struktural<\/td>\u00a0:<\/td>\u00a0-<\/td><\/tr>
\u00a0NIP<\/td>\u00a0:<\/td>\u00a0196509131990032001<\/td><\/tr>
\u00a0NIDN \/ SERDOS<\/td>\u00a0:<\/td>\u00a00013096508<\/td><\/tr>
\u00a0Tempat Tanggal Lahir<\/td>\u00a0:<\/td>\u00a0Sragen, 13 September 1965<\/td><\/tr>
\u00a0Alamat Kantor<\/td>\u00a0:<\/td>Departemen Statistika
Gedung F Lantai 3
Fakultas Sains dan Matematika
Universitas Diponegoro
Jl. Prof. Sudarto, SH. Semarang 50275<\/td><\/tr>
\u00a0Alamat Email<\/td>\u00a0:<\/td>\u00a0supartisudargo@yahoo.co.id<\/a><\/td><\/tr>
\u00a0Lulusan yang Telah Dihasilkan<\/td>\u00a0:<\/td>\u00a0<\/td><\/tr>
\u00a0Mata Kuliah yang diampu<\/td>\u00a0:<\/td>1.Statistika Matematik
2.Analisis Regresi Nonparametrik
3.Metode Wavelet
4.Statistika Dasar<\/td><\/tr><\/tbody><\/table>

B. Riwayat Pendidikan<\/p>
Jenjang<\/strong><\/td>S1<\/strong><\/td>S2<\/strong><\/td>S3<\/strong><\/td><\/tr>
Nama Perguruan Tinggi<\/strong><\/td>\u00a0Undip<\/td>\u00a0UGM<\/td>\u00a0-<\/td><\/tr>
Bidang Ilmu<\/strong><\/td>\u00a0Matematika<\/td>Matematika<\/td>\u00a0-<\/td><\/tr>
Tahun Masuk - Lulus<\/strong><\/td>\u00a01984-1988<\/td>1996-1999<\/td>\u00a0<\/td><\/tr>
Judul Skripsi \/ Tesis \/ Disertasi<\/strong><\/td>\u00a0Regresi Isotonik<\/td>\u00a0Estimasi Fungsi Mulus dengan Metode Wavelet<\/td>\u00a0<\/td><\/tr>
Nama Pembimbing \/ Promotor<\/strong><\/td>\u00a0Drs. Ketut Sudana Tanaya<\/td>Prof. Drs. H. Subanar,Ph.D<\/td>\u00a0<\/td><\/tr><\/tbody><\/table>

C. Pengalaman Penelitian dalam 5 tahun Terakhir<\/p>
\u00a0No.<\/strong><\/td>Tahun<\/strong><\/td>Judul Penelitian<\/strong><\/td>\u00a0Sumber Pendanaan<\/strong><\/td>Jumlah Dana (Juta Rp)<\/strong><\/td><\/tr>
1.<\/td>\u00a02012<\/td>\u00a0Analisis Data Inflasi Indonesian\u00a0Menggunakan Model Regresi Kernel<\/td>\u00a0PNBP MIPA Undip<\/td>\u00a07,5<\/td><\/tr>
2.<\/td>\u00a02013<\/td>\u00a0Karakteristik Kabupaten\/Kota di Jawa Tengah Berdasarkan Produksi Bawang Putih, Bawang Merah,Cabe Besar dan Cabe Rawit Menggunakan Analisis Biplot<\/td>\u00a0PNBP MIPA Undip<\/td>\u00a07,5<\/td><\/tr>
3.<\/td>\u00a02014<\/td>\u00a0Pemilihan Model Terbaik untuk Analisis Data Inflasi di Indonesia<\/td>\u00a0Hibah Bersaing Dikti<\/td>\u00a050,225<\/td><\/tr>
4.<\/td>\u00a02014<\/td>\u00a0Pemodelan Volatilitas untuk Penghitungan VaR Menggunajan JST\u00a0 dan Algoritma \u00a0Genetika<\/td>\u00a0PNBP MIPA Undip<\/td>\u00a07,5<\/td><\/tr>
5.<\/td>\u00a02015<\/td>\u00a0Pemilihan Model Terbaik untuk Analisis Data Inlasi di Indonesia (Lanjutan)<\/td>\u00a0Hibah Bersaing Dikti<\/td>\u00a050,50<\/td><\/tr>
6.<\/td>\u00a02015<\/td>\u00a0Eksplorasi dan Pengembangan Terapan Wavelet pada Bidang Statistika<\/td>\u00a0Fundamental Dikti<\/td>\u00a052,50<\/td><\/tr>
7.<\/td>\u00a02015<\/td>\u00a0Analisis\u00a0 Data Inflasi Indonesia Sektor Transportasi, Komunikasi dan Jasa Keuangan Menggunakan Model ARIMA Box-Jenkins dan Regresi Polinomial Lokal<\/td>\u00a0PNBP MIPA Undip<\/td>\u00a07,5<\/td><\/tr>
8.<\/td>\u00a02016<\/td>\u00a0Pemodelan \u00a0Regresi Nonparametrik Untuk Data Longitudinal dengan Metode Polinomial Lokal-Spline Truncated<\/em>\u00a0 pada\u00a0 Kelompok Pengeluaran Inflasi<\/td>\u00a0Fundamental Dikti<\/td>\u00a050,00<\/td><\/tr>
9.<\/td>\u00a02016<\/td>\u00a0Pengembangan Model Inflasi Indonesia Pada Sektor Transportasi, Komunikasi Dan Jasa Keuangan Berdasarkan Perubahan Harga Bbm Menggunakan Model Hybrid\u00a0 Intervensi \u2013 B Spline<\/td>\u00a0PNBP MIPA Undip<\/td>\u00a050,00<\/td><\/tr>
10.<\/td>\u00a02016<\/td>\u00a0Pengembangan Model Hybrid Berbasis Arima-Anfis Untuk Prediksi Produksi Tanaman Hortikultura Di Jawa Tengah<\/td>\u00a0PNBP MIPA Undip<\/td>\u00a050,00<\/td><\/tr>
11.<\/td>\u00a02016<\/td>\u00a0Pemodelan Beban Listrik \u00a0di Kota Semarang Menggunakan Polinomial Lokal dan B - Spline<\/td>\u00a0PNBP MIPA Undip<\/td>\u00a08,50<\/td><\/tr>
12.<\/td>\u00a02017<\/td>\u00a0Pemodelan Regresi Nonparametrik untuk Data Longitudinal dengan metode Hybrid Polinomial Local-Spline Truncated dan Hybrid Fourier wavelet pada kelompok pengeluaran inflasi<\/td>\u00a0DRPM DIKTI PTUPT<\/td>\u00a0100<\/td><\/tr>
13.<\/td>\u00a02017<\/td>\u00a0Optimasi Heuristic pada Model Wavelet Neural Network untuk Prediksi Time Series<\/td>\u00a0PNBP MIPA Undip<\/td>\u00a040<\/td><\/tr><\/tbody><\/table>

D. Pengalaman Pengabdian Kepada Masyarakat 5 Tahun Terakhir<\/p>
\u00a0No.<\/strong><\/td>Tahun<\/strong><\/td>Judul Pengabdian Kepada Masyarakat<\/strong><\/td>\u00a0Sumber Pendanaan<\/strong><\/td>Jumlah Dana (Juta Rp)<\/strong><\/td><\/tr>
1.<\/td>\u00a02013<\/td>\u00a0Pelatihan Analisis Butir Soal Ujian Manggunakan Program SPSS Bagi Guru SMA Futuhiyyah Kec. Mranggen<\/td>\u00a0DIPA MIPA<\/td>\u00a07,50<\/td><\/tr>
2.<\/td>\u00a02014<\/td>\u00a0Pelatihan Statistika Kependudukan Menggunakan Program SPSS bagi Perangkat Desa di Kecamatan Kedungwuni<\/td>\u00a0DIPA MIPA<\/td>\u00a07,50<\/td><\/tr>
3.<\/td>\u00a02014<\/td>\u00a0Pelatihan Data Mining untuk Statistika<\/td>\u00a0DIPA MIPA<\/td>\u00a07,50<\/td><\/tr>
4.<\/td>\u00a02015<\/td>\u00a0Pelatihan Eviews untuk Pemodelan GSTAR.<\/td>\u00a0DIPA MIPA<\/td>\u00a07,50<\/td><\/tr>
5.<\/td>\u00a02015<\/td>\u00a0Pelatihan Pemodelan VAR Menggunakan Eviews.<\/td>\u00a0DIPA MIPA<\/td>\u00a07,50<\/td><\/tr>
6.<\/td>\u00a02015<\/td>\u00a0Pelatihan GUI Matlab untuk Pemodelan VAR.<\/td>\u00a0DIPA MIPA<\/td>\u00a07,50<\/td><\/tr>
7.<\/td>\u00a02015<\/td>\u00a0Pelatihan Jarimatika untuk Guru-Guru RA se-kecamatan Banyumanik Semarang<\/td>\u00a0DIPA MIPA<\/td>\u00a07,50<\/td><\/tr>
8.<\/td>\u00a02015<\/td>\u00a0Pelatihan Metode Klasifikasi Menggunakan SVM dengan Matlab<\/td>\u00a0DIPA FSM<\/td>\u00a010<\/td><\/tr>
9.<\/td>\u00a02016<\/td>\u00a0Analisa Teknikal dan Fundamental Pergerakan Harga Saham dengan Simulasi Yahoo! Finance<\/td>\u00a0DIPA FSM<\/td>\u00a010<\/td><\/tr>
10.<\/td>\u00a02016<\/td>\u00a0Algoritma Genetika pada Pemodelan Statistika dengan Program Matlab<\/td>\u00a0DIPA FSM<\/td>\u00a010<\/td><\/tr>
11.<\/td>\u00a02016<\/td>\u00a0Pelatihan Optimalisasi Fitur MS Word untuk Penulisan Karya Ilmiah<\/td>\u00a0DIPA FSM<\/td>\u00a010<\/td><\/tr>
12.<\/td>\u00a02016<\/td>\u00a0Pelatihan Spasial Data Panel dengan GUI \u00a0Matlab<\/td>\u00a0DIPA FSM<\/td>\u00a010<\/td><\/tr>
13.<\/td>\u00a02017<\/td>\u00a0Pengelolaan data persampahan pada bank sampah sempulur ASRI Gedawang<\/td>\u00a0DIPA PNBP FSM<\/td>\u00a08<\/td><\/tr><\/tbody><\/table>

E. Pengalaman Penulisan Artikel Ilmiah dalam Jurnal dalam 5 Tahun Terakhir<\/p>
\u00a0No.<\/strong><\/td>\u00a0Judul Artikel<\/strong><\/td>Volume \/ Nomor \/ Tahun<\/strong><\/td>Nama Jurnal<\/strong><\/td><\/tr>
\u00a01.<\/td>\u00a0Analisis Faktor-Faktor yang Mempengaruhi Banyaknya Klaim Asuransi Kendaraan Bermotor Menggunakan Model Regresi ZIP (Studi Kasus di\u00a0 PT Asuransi Sinar Mas\u00a0 Cabang Semarang Tahun 2010)<\/td>\u00a0Vol. 5\/ No. 1\/Th 2012, hal 49-61<\/td>
\u00a0Jurnal\u00a0 Media Statistika ISSN\u00a0 1979-3693<\/td><\/tr><\/tbody><\/table><\/td><\/tr>
\u00a02.<\/td>\u00a0Analisis Data Inflasi di Indonesia Menggunakan Model Regresi Spline<\/td>\u00a0Vol. 6\/ No. 1\/Th 2013, hal 1-9<\/td>\u00a0Jurnal\u00a0 Media Statistika ISSN\u00a0 1979-3693<\/td><\/tr>
\u00a03.<\/td>\u00a0Analisis Data Inflasi di Indonesia Pasca Kenaikan TDL dan BBM Tahun 2013 Menggunakan Model Regresi Kernel<\/td>\u00a0Vol. 6\/ No. 2\/Th 2013, hal 103-112<\/td>Jurnal\u00a0 Media Statistika ISSN\u00a0 1979-3693<\/td><\/tr>
\u00a04.<\/td>\u00a0Analisis Biplot Untuk Mengetahui Karakteristik Kabupaten\/Kota di Jawa Tengah Berdasarkan Produksi Bawang Putih, Bawang Merah<\/td>\u00a0Vol. 7\/ No. 1\/Th 2014, hal 47-52<\/td>\u00a0\u00a0Jurnal\u00a0 Media Statistika ISSN\u00a0 1979-3693<\/td><\/tr>
\u00a05.<\/td>\u00a0Pemodelan Volatilitas Untuk Penghitungan Value At Risk <\/em>(Var) Menggunakan Feed Forward Neural Network<\/em> \u00a0dan Algoritma Genetika<\/td>\u00a0Vol. 7\/ No. 2\/Th 2014, hal 53-61<\/td>\u00a0Jurnal\u00a0 Media Statistika ISSN\u00a0 1979-3693<\/td><\/tr>
\u00a06.<\/td>\u00a0Analisis Data Inflasi di Indonesia Menggunakan Model Regresi Polinomial Lokal<\/td>\u00a0Vol 2 no 1, 2014, hal 65-78<\/td>\u00a0\u00a0IndoMS Journal on Statistics ISSN 2301-8410<\/td><\/tr>
\u00a07.<\/td>\u00a0Analisis Data Inflasi Indonesia Menggunakan Model Autoregressive Integrated Moving Average<\/em> (Arima)\u00a0Dengan Penambahan Outlier<\/td>\u00a0Vol. 8\/ No. 1\/Th 2015, hal 1-11<\/td>\u00a0\u00a0Jurnal\u00a0 Media Statistika ISSN\u00a0 1979-3693<\/td><\/tr>
\u00a08.<\/td>\u00a0Pemodelan Data Inflasi Indonesia Pada Sektor Transportasi, Komunikasi \u00a0dan Jasa Keuangan Menggunakan Metode Kernel dan Spline<\/td>\u00a0Vol. 8\/ No. 2\/Th 2015, hal 103-110<\/td>Jurnal\u00a0 Media Statistika ISSN\u00a0 1979-3693<\/td><\/tr>
\u00a09.<\/td>\u00a0Modeling of Indonesian Inflation Data in The Transportation, Communication and Financial Services Sector Using Local Polynomial Regression<\/td>\u00a0Jurnal Internasional Terindeks<\/td>

Jurnal Internasional Applied Mathematical Sciences (accepted Oktober 2015)<\/p>

ISSN: 1312-885X(Print)
ISSN: 1314-7552(Online)<\/p><\/td><\/tr><\/tbody><\/table><\/td><\/tr>

\u00a010.<\/td>Pemodelan Tinggi Pasang Air Laut di Kota Semarang dengan Menggunakan Maximal Overlap Discrete Wavelet Transform (MODWT)<\/td>\u00a0Vol. 2, No. 2, Juni 2015<\/td>\u00a0Jurnal Meteorologi, Klimatologi dan Geofisika, ISSN: 2355-7206<\/td><\/tr>
\u00a011.<\/td>\u00a0The Shift Invariant Discrete Wavelet Transform (SIDWT) with Inflation Time Series Application<\/td>\u00a0Vol 48, No. 4, Agustus 2016<\/td>\u00a0Journal of Mathematics Research, \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 ISSN 1916-9795 (Print)\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 ISSN 1916-9809 (on line)<\/td><\/tr>
\u00a012.<\/td>\u00a0Modelling Local Polynomial for Longitudinal Data a case study: inflation sectors in Indonesia<\/td>\u00a0Vol. 11 No. 23 Desember 2016<\/td>\u00a0ARPN Journal of Engineering and Applied Sciences; ISSN 1819-6608<\/td><\/tr>
\u00a013.<\/td>Volatility Modeling of Financial Time Series Data Using ANFIS<\/td>\u00a0Vol. 23, No. 4, April 2017, pp.6562-6566<\/td>\u00a0Advanced Science Letter (ASL), p-ISSN:1936-6612; e-ISSN:1936-7317<\/td><\/tr><\/tbody><\/table>

F. Pengalaman Penyampaian Makalah Secara Oral pada Pertemuan \/ Seminar Ilmiah dalam 5 Tahun Terakhir<\/p>
\u00a0No.<\/strong><\/td>Nama Pertemuan \/ Seminar Ilmiah<\/strong><\/td>\u00a0Judul Artikel Ilmiah<\/strong><\/td>\u00a0Waktu dan Tempat<\/strong><\/td><\/tr>
\u00a01<\/td>\u00a0Seminar Nasional Ilmu Komputer<\/td>\u00a0Pemakalah dengan judul \u201dAnalisis Antrean Bus Kota di Terminal Induk Purabaya Surabaya\u201d<\/td>

12 Mei 2012<\/p>

PS\u00a0 Ilmu Komputer Undip<\/p><\/td><\/tr>

\u00a02<\/td>\u00a0Seminar Nasional Statistika<\/td>\u00a0Pemakalah dengan judul \u201d Analisis Data Inflasi di Indonesia Menggunakan Model Regresi Kernel\u201d<\/td>

14 September 2013<\/p>

Jurusan Statistika Undip<\/p><\/td><\/tr>

\u00a03<\/td>\u00a0Prosiding Seminar Internasional 4th<\/sup> ISNPINSA<\/td>\u00a0The Analysis Of Indonesia Inflation \u00a0Data\u00a0\u00a0 Using Box-Jenkins Models<\/td>

28 Oktober 2014<\/p>

Hotel Patra Jasa Semarang<\/p><\/td><\/tr>

\u00a04<\/td>\u00a0Prosiding Seminar Matematika Saintekinfo MIPA UNS,<\/td>\u00a0Analisis Data Inflasi Di Indonesia Menggunakan Model Arima Box-Jenkins, Kernel dan Spline<\/td>

25 April 2015<\/p>

UNS Surakarta<\/p><\/td><\/tr>

\u00a05<\/td>\u00a0Prosiding Seminar Internasional IconSSE UKSW Salatiga,<\/td>\u00a0Performance of Neural Network Model in Forecasting Indonesian Inflation<\/td>

1 Agustus 2015<\/p>

UKSW Salatiga<\/p><\/td><\/tr>

\u00a06<\/td>Seminar Nasional SENDMATSA Unissula 2016<\/td>\u00a0Analisis Data Inflasi Indonesia pada Sektor Transportasi, Komunikasi dan Jasa Keuangan Menggunakan ARIMA dengan Outlier<\/td>

19 Maret 2016<\/p>

UNISSULA Semarang<\/p><\/td><\/tr>

\u00a07<\/td>Seminar Nasional SENDMATSA Unissula 2016<\/td>\u00a0Adaptive Spline Threshold Autoregresive (ASTAR) pada Pemodelan Tinggi Permukaan Air Laut di Kota Semarang<\/td>

19 Maret 2016<\/p>

UNISSULA Semarang<\/p><\/td><\/tr>

\u00a08<\/td>\u00a0Seminar Internasional ISNPINSA 2016 , Undip<\/td>\u00a0Volatility Modeling of Financial Time Series Data Using ANFIS<\/td>

5- 6 Oktober 2016<\/p>

Hotel Grand Candi Semarang<\/p><\/td><\/tr>

\u00a09<\/td>International of Conference on Theoretical and Applied Statistics (ICTAS ) ITS 2016<\/td>\u00a0Modelling of Intervention Multi Input : A Case Study Inflation in Central Java Based on Price Changing Fuel Oil in Indonesia<\/td>

19-20 Oktober 2016<\/p>

Hotel Majapahit Surabaya<\/p><\/td><\/tr>

\u00a010<\/td>\u00a0International of Conference on Theoretical and Applied Statistics (ICTAS ) ITS 2016<\/td>\u00a0Modelling Inflation of Transportation, Comunication, and Service Sectors in Indonesia Using Intervention Model<\/td>

19-20 Oktober 2016<\/p>

Hotel Majapahit Surabaya<\/p><\/td><\/tr>

\u00a011<\/td>\u00a0Seminar Nasional Pendidikan Sains dan Teknologi 2017<\/td>\u00a0Kajian Pemodelan Spline untuk Data Longitudinal Sebagai Perkembangan dari Regresi Nonparametrik<\/td>

7 Oktober 2017<\/p>

Universitas Muhammadiyah Semarang<\/p><\/td><\/tr><\/tbody><\/table>

G. Pengalaman Penulisan Buku dalam 5 Tahun Terakhir<\/p>
\u00a0No.<\/strong><\/td>Judul Buku\u00a0<\/strong><\/td>Tahun<\/strong><\/td>Jumlah Halaman\u00a0<\/strong><\/td>Penerbit<\/strong><\/td><\/tr>
\u00a01.<\/td>\u00a0<\/td>\u00a0<\/td>\u00a0<\/td>\u00a0<\/td><\/tr><\/tbody><\/table>

H. Pengalaman Perolehan HKI dalam 5-10 Tahun Terakhir<\/p>
\u00a0No.<\/strong><\/td>\u00a0Judul \/ Tema HKI<\/strong><\/td>Tahun<\/strong><\/td>Jenis\u00a0<\/strong><\/td>Nomor P\/ID\u00a0<\/strong><\/td><\/tr>
1.<\/td>\u00a0<\/td>\u00a0<\/td>\u00a0<\/td>\u00a0<\/td><\/tr><\/tbody><\/table>

I. Pengalaman Merumuskan Kebijakan Publik \/ Rekayasa Sosial Lainnya dalam 5 Tahun Terakhir<\/p>
\u00a0No.<\/strong><\/td>Judul \/ Tema \/ Jenis Rekayasa Sosial lainnya yang telah diterapkan<\/strong><\/td>Tahun<\/strong><\/td>Tempat Penerapan<\/strong><\/td>Respons Masyarakat<\/strong><\/td><\/tr>
1.<\/td>\u00a0<\/td>\u00a0<\/td>\u00a0<\/td>\u00a0<\/td><\/tr><\/tbody><\/table>

J. Penghargaan yang Pernah diraih dalam 10 Tahun Terakhir (Dari Pemerintah, Asosiasi atau Institusi Lainnya)<\/p>
\u00a0No.<\/td>\u00a0Jenis Penghargaan<\/strong><\/td>Institusi Pemberi Penghargaan\u00a0<\/strong><\/td>Tahun<\/strong><\/td><\/tr>
\u00a01.<\/td>\u00a0<\/td>\u00a0<\/td>\u00a0<\/td><\/tr><\/tbody><\/table>","_et_gb_content_width":"","footnotes":""},"class_list":["post-899","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/stat.fsm.undip.ac.id\/v1\/wp-json\/wp\/v2\/pages\/899","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/stat.fsm.undip.ac.id\/v1\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/stat.fsm.undip.ac.id\/v1\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/stat.fsm.undip.ac.id\/v1\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/stat.fsm.undip.ac.id\/v1\/wp-json\/wp\/v2\/comments?post=899"}],"version-history":[{"count":24,"href":"https:\/\/stat.fsm.undip.ac.id\/v1\/wp-json\/wp\/v2\/pages\/899\/revisions"}],"predecessor-version":[{"id":6250,"href":"https:\/\/stat.fsm.undip.ac.id\/v1\/wp-json\/wp\/v2\/pages\/899\/revisions\/6250"}],"wp:attachment":[{"href":"https:\/\/stat.fsm.undip.ac.id\/v1\/wp-json\/wp\/v2\/media?parent=899"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}