J-HEST Journal of Health Education Economics Science and Technology
https://j-hest.web.id/index.php/2
<table width="100%" bgcolor="#f0f0f0"> <tbody> <tr> <td width="20%">Journal title</td> <td width="50%"><strong>Journal of Health, Education, Economics, Science, and Tecnology</strong></td> <td rowspan="9" valign="top" width="20%"><img src="https://www.google.com/url?sa=i&url=http%3A%2F%2Fjournal2.uad.ac.id%2Findex.php%2Firip%2Fissue%2Farchive&psig=AOvVaw1HnWfrBMwUv1Q7dv5cn8OJ&ust=1652330185760000&source=images&cd=vfe&ved=2ahUKEwim-7rfz9b3AhW1XmwGHcfICIQQjRx6BAgAEAs" alt="" /><img 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" alt="" width="149" height="198" /><img style="background-color: #ffffff; font-size: 0.875rem;" src="blob:https://ejurnal.fmipa.uncen.ac.id/60972eb9-d224-404a-ba6f-9fc4b632d963" alt="" /><img style="background-color: #ffffff; font-size: 0.875rem;" src="blob:https://ejurnal.fmipa.uncen.ac.id/52042669-f8b6-418a-801d-1fcfc463df6a" alt="" /><img style="background-color: #ffffff; font-size: 0.875rem;" src="https://www.google.com/imgres?imgurl=http%3A%2F%2Fjournal2.uad.ac.id%2Fpublic%2Fjournals%2F21%2Fcover_issue_297_en_US.jpg&imgrefurl=http%3A%2F%2Fjournal2.uad.ac.id%2Findex.php%2Firip%2Fissue%2Farchive&tbnid=8TNYsQru8KlSxM&vet=12ahUKEwi60r2pz9b3AhV2IrcAHXohBSoQMygEegQIARAl..i&docid=P8L5tIuHYjQuxM&w=1241&h=1754&q=irip%20uad&ved=2ahUKEwi60r2pz9b3AhV2IrcAHXohBSoQMygEegQIARAl" alt="" /></td> </tr> <tr> <td width="20%">Initials</td> <td width="50%"><strong>J-HEST</strong></td> </tr> <tr> <td width="20%">Abbreviation</td> <td width="50%"><em><strong>J-HEST</strong></em></td> </tr> <tr> <td width="20%">Frequency</td> <td width="50%"><strong>2 issues per year | December and June</strong></td> </tr> <tr> <td width="20%">DOI</td> <td width="50%"><img src="http://journal2.uad.ac.id/index.php/eltej/management/settings/context/data:image/png;base64,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" alt="" /><strong>Prefix 10.36339 by</strong><img src="http://journal2.uad.ac.id/index.php/eltej/management/settings/context/" alt="" /><strong><img src="http://journal2.uad.ac.id/index.php/eltej/management/settings/context//public/site/images/dyoyo/CROSREFF_Kecil2.png" alt="" /></strong><strong><br /></strong></td> </tr> <tr> <td width="20%">ISSN</td> <td width="50%"><strong>E-ISSN: <a href="https://portal.issn.org/api/search?search[]=MUST=default=j-hest&search_id=23439082" target="_blank" rel="noopener">2685-1792</a></strong></td> </tr> <tr> <td width="20%">Editor-in-chief</td> <td width="50%"><a title="https://scholar.google.com/citations?user=fzT0e1gAAAAJ&hl=id&authuser=3" href="https://scholar.google.com/citations?user=fzT0e1gAAAAJ&hl=id&oi=ao" target="_blank" rel="noopener"><strong>Hardi Hamzah</strong></a></td> </tr> <tr> <td width="20%">Publisher</td> <td width="50%"><strong>Dewan Pengurus Daerah Sulawesi Barat Forum Dosen Indonesia</strong></td> </tr> <tr> <td width="20%">Citation Analysis</td> <td width="50%"><strong><a href="https://scholar.google.com/citations?user=yOP7xwMAAAAJ&hl=id">Google Scholar</a> </strong></td> </tr> </tbody> </table> <p><strong>J-HEST Journal of Health, Education, Economics, Science, and Technology</strong> diterbitkan oleh <strong>Forum Dosen Indonesia DPD Sulawesi Barat</strong> satu kali dalam enam bulan (Desember dan Juni). Jurnal ini sebagai media komunikasi ilmiah bidang kesehatan, pendidikan, ekonomi, sains, dan teknologi. </p>Polewali: Dewan Pengurus Daerah Sulawesi Barat Forum Dosen Indonesiaen-USJ-HEST Journal of Health Education Economics Science and Technology2685-1792<p><a href="http://creativecommons.org/licenses/by/4.0/" target="_blank" rel="noopener"><img src="http://ojs.umsida.ac.id/public/site/images/tanzilmultazam/88x311.png" alt="" /></a></p>Konsep Pidana Mati delam Prespektif Pancasila, Undang-Undang 1945, dan RUU KUHP di Indonesia
https://j-hest.web.id/index.php/2/article/view/76
<p>Pelaksanaan hukuman mati di Indonesia didasarkan pada putusan pengadilan yang telah dijatuhkan kekuatan hukum tetap. Hanya melalui putusan pengadilan seorang dapat dieksekusi hukuman mati bagi yang bersalah yang dituduhkan kepadanya. Aplikasi hukuman mati di Indonesia diatur dalam hukum positif yang bersifat khusus atau umum. Sebagai sebuah negara memiliki vonis terbanyak dengan pidana mati, baik terhadap warganya maupun terhadapnya warga negara asing yang melakukan pelanggaran di wilayah hukum Republik Indonesia, memicu adanya sikap pro dan kontra terhadap hukuman mati eksekusi. Sikap menentang mendasarkan argumennya pada perspektif hak asasi manusia, menegaskan bahwa pidana mati dapat dikategorikan sebagai bentuk biadab dan hukuman yang tidak manusiawi dan bertentangan dengan konstitusi. Sedangkan sikap mendukung pelakasanaan pidana mati didasarkan pada argumentasi bahwa pelaku harus dibalas sesuai dengan perbuatannya, untuk memberikan efek jera bagi orang lain yang ini melakukan pelanggran yang serupa. Namun demikian ternyata masih banyak terjadi pelanggaran yang serupa.</p>Ansharullah Alimuddin
Copyright (c) 2022 Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
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2022-12-142022-12-145111110.36339/jhest.v5i1.76Pembentukan Peraturan Daerah yang Demokratis di Era Otonomi Daerah
https://j-hest.web.id/index.php/2/article/view/75
<p>Perda berisi aturan-aturan yang mengatur segala hal yang berkaitan dengan daerah dalam rangka mewujudkan kehidupan masyarakat yang adil dan makmur. Aspek hukum, politik, ekonomi, sosial, dan budaya menjadi faktor yang sangat mempengaruhi pembentukan Perda. Perda yang berkualitas berarti produk hukum yang penyusunan materi dan teknisnya sesuai dengan ketentuan peraturan perundang-undangan, dapat menyelesaikan masalah dan menjawab kebutuhan masyarakat. Perda yang baik harus mencerminkan aspek filosofis yang berkaitan dengan asas keadilan, sosiologis yang berkaitan dengan harapan bahwa perda yang dibentuk merupakan keinginan masyarakat setempat, dan aspek yuridis terkait dengan jaminan kepastian hukum.</p>Faradilah Faradilah
Copyright (c) 2022 Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
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2022-12-142022-12-1451121610.36339/jhest.v5i1.75Penerapan Model Pembelajaran Kooperatif Tipe Team Assisted Individualization Untuk Meningkatkan Hasil Belajar Matematika Siswa Kelas V UPTD SD Negeri 26 Parepare
https://j-hest.web.id/index.php/2/article/view/13
<p>Permasalahan dalam penelitian ini yaitu hasil belajar siswa kelas V UPTD SD Negeri 26 Parepare belum mencapai SKBM. Masalah dalam penelitian ini adalah bagaimana penerapan model pembelajaran kooperatif tipe <em>Team Assisted Individualization</em> dapat meningkatkan proses belajar matematika siswa kelas V UPTD SD Negeri 26 Parepare dan apakah penerapan model pembelajaran kooperatif tipe <em>Team Assisted Individualization </em>dapat meningkatkan hasil belajar matematika siswa kelas V UPTD SD Negeri 26 Parepare. Tujuan dalam penelitian ini adalah untuk mengetahui penerapan model pembelajaran kooperatif tipe <em>Team Assisted Individualization</em> dapat meningkatkan proses belajar matematika siswa kelas V UPTD SD Negeri 26 Parepare dan untuk mengetahui apakah penerapan model pembelajaran kooperatif tipe <em>Team Assisted Individualization </em>dapat meningkatkan hasil belajar matematika siswa kelas V UPTD SD Negeri 26 Parepare. Pendekatan yang digunakan adalah pendekatan kualitatif. Penelitian ini merupakan Penelitian Tindakan Kelas (PTK). Subjek Penelitian yaitu guru dan siswa yang berjumlah 20 siswa. Teknik pengumpulan data yang digunakan adalah observasi, tes, dan dokumentasi. Teknik analisis data yang digunakan adalah reduksi data, <em>display data </em>(penyajian data), dan penarikan kesimpulan. Pelaksanaan tindakan penelitian ini dilakukan dalam 2 siklus diawali dengan kegiatan pra tindakan, kemudian pada setiap siklus terdiri dari 4 tahapan yang meliputi perencanaan, pelaksanaan, observasi, dan refleksi. Hasil penelitian menujukkan bahwa pada siklus I hasil observasi aktivitas guru dengan kategori baik (B) dan observasi aktivitas siswa dengan kategori cukup (C) dengan hasil tes belajar dengan kategori cukup (C). Sedangkan pada siklus II mengalami peningkatan yang menunjukkan hasil observasi aktivitas guru dengan kategori baik (B) dan observasi aktivitas siswa meningkat dengan kategori baik (B) dengan hasil tes belajar mengalami peningkatan dengan kategori baik (B). Simpulan penelitian ini adalah penerapkan model pembelajaran kooperatif tipe <em>Team Assisted Individualization </em>dapat meningkatkan proses dan hasil belajar matematika siswa kelas V UPTD SD Negeri 26 Parepare</p>St. Maryam MZaid ZainalSari Bunga
Copyright (c) 2022 Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
https://creativecommons.org/licenses/by/4.0
2022-12-292022-12-2951172610.36339/jhest.v5i1.13Peranan Alat Peraga Terhadap Pemikiran Inkuiri Siswa
https://j-hest.web.id/index.php/2/article/view/85
<p>Tujuan penelitian ini adalah untuk mengetahui peranan alat peraga terhadap pemikiran inkuiri siswa. Metode dalam penelitian ini yaitu menggunakan metode kajian pustaka. Metode kajian pustaka adalah kumpulan teori-teori referensi yang menjadi dasar dalam sebuah penelitian serta menjawab secara teori tentang permasalahan dari sebuah ide pokok penelitian. Alat peraga merupakan salah satu media pembelajaran siswa dalam melakukan sebuah eksperimen yang didalamnya siswa berperan aktif serta menuntut siswa menghubungkan suatu percobaan dengan suatu teori yang ada. Dalam melakukan suatu eksperimen atau praktikum siswa dituntut untuk memiliki kemampuan yang baik dalam berkomunikasi maupun kemampuan kerja sama dalam kelompok, hal tersebut sesuai dengan model pembelajaran inkuiri.</p>Achmad Dzikri Fadholi RobbiLutfiah Hafifatul JannahNala FauziyahRina Dian NoviantiI Ketut MahardikaSinggih Bektiarso
Copyright (c) 2022 Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
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2022-12-292022-12-2951273110.36339/jhest.v5i1.85Efektivitas Elco dalam Penghematan Penggunaan Daya Listrik pada Lampu LED
https://j-hest.web.id/index.php/2/article/view/84
<p>Dalam kehidupan modern, listrik menjadi salah satu kebutuhan yang utama untuk menunjang aktivitas manusia setiap harinya. Namun dalam penggunaannya, sering kali terjadi pemborosan akibat pemasangan lampu yang memiliki daya listrik yang tinggi. Semakin besar daya yang dibutuhkan oleh lampu untuk menyala maka energi listrik yang dihasilkan juga semakin besar sehingga hal ini menyebabkan terjadinya lonjakan dalam tagihan listrik. Dalam penelitian ini, metode yang digunakan yaitu metode eksperimen secara kuantitatif yang datanya bersumber dari data primer atau data yang didapat dalam penelitian secara langsung. Hasil dari penelitian ini yaitu penggunaan Elco pada lampu led mampu menurunkan daya listrik pada sebuah lampu dengan tegangan yang sama. Ukuran kapasitor juga mempengaruhi presentase penurunan daya pada lampu led. Semakin besar kapasitornya maka daya yang dihasilkan semakin kecil. Kesimpulannya elco mampu mengurangi daya listrik pada sebuah lampu led pada tegangan 400 volt meskipun nyala lampu yang dihasilkan pada ketiga kapasitor berbeda.</p>I Ketut MahardikaSinggih BaktiarsoRoifatul MasrurohLinda AyuningtiyasSri Handayani
Copyright (c) 2022 Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
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2022-12-292022-12-2951323810.36339/jhest.v5i1.84Isolasi dan Penentuan Aktivitas Spesifik Enzim α-Glukosidase Dari Jagung Pulut (Zea Mays Ceratina L)
https://j-hest.web.id/index.php/2/article/view/82
<p><em>Enzim α-Glukosidase merupakan golongan enzim hidrolase yang berperan dalam hidrolisis ikatan 1,4 α-glikosida, Enzim α-Glukosidase terdapat di dalam epitel usus halus, berperan dalam pemecahan glukosa yang dapat menyebabkan tingginya kadar gula darah di dalam tubuh sebagai pemicu penyakit ganguan metaboliseme yakni diabetes militus tipe II. Enzim α-Glukosidase dibutuhkan dalam pengujian antidiabetes yang dapat diisolasi dari jagung pulut. Tujuan penelitian ini adalah untuk mengisolasi dan mengetahui aktivitas spesifik enzim α-Glukosidase dari jagung pulut </em>(<em>Zea mays ceratina L</em>.). <em>Tahapan penelitian yaitu pembuatan larutan buffer fosfat pH 7, produksi ekstrak kasar enzim α-Glukosidase, pemanenan enzim α-Glukosidase, uji aktivitas enzim α-Glukosidase dengan metode DNS dan penentuan kadar protein dengan metode Lowry. Hasil menunjukkan Unit aktivitas ekstrak kasar enzim α-Glukosidase sebesar 97 Um/mL, dengan kadar protein sebesar 19,2 mg/mL dan aktivitas spesifik enzim sebesar 5,05 mU/mg.</em></p>Nada Pertiwi PaprianiYusriadi YusriadiAisyah Rusdin
Copyright (c) 2022 Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
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2022-12-312022-12-3151394210.36339/jhest.v5i1.82Efektivitas Pelaksanaan Pembelajaran Daring Pada Mata Pelajaran Biologi Selama Masa Pandemi Covid-19
https://j-hest.web.id/index.php/2/article/view/79
<p><strong><em>ABSTRAK</em></strong></p> <p>Penelitian ini bertujuan untuk mengetahui: (1). Efektivitas pelaksanaan pembelajaran daring pada mata pelajaran biologi kelas XI MIA di SMA Negeri 1 Tinambung, (2). Kelebihan dan kekurangan pembelajaran daring, (3). Perbaikan yang diharapkan oleh siswa. Adapun pendekatan yang digunakan yaitu <em>mix methode</em>, desain <em>sequential exploratory</em>. Subjek penelitian yaitu siswa kelas XI MIA SMA Negeri 1 Tinambung. Data dikumpulkan melalui angket, wawancara dan dokumentasi, yang dianalisis menggunakan teknik analisis kualitatif model interaktif dari Miles dan Huberman, dan data kuantitatif dianalisis menggunakan rumus tuntas belajar.</p> <p>Temuan penelitian menunjukkan bahwa pelaksanaan pembelajaran daring pada mata pelajaran biologi kelas XI MIA di SMA Negeri 1 Tinambung selama masa pandemi Covid-19 sudah efektif. Adapun kelebihan pembelajaran daring: belajar dapat dilakukan dimana dan kapan saja, interaksi dengan guru lebih menyenangkan, materi dapat disimpan dan dipelajari kembali, sumber belajar lebih luas, dan menjadi mahir teknologi. Selanjutnya, kelemahan: bergantung pada ketersediaan jaringan internet, komunikasi dengan guru menjadi terbatas, keterbatasan hp atau laptop, menghabiskan banyak kuota internet serta kurangnya pemahaman terhadap materi. Saran untuk perbaikan proses pembelajaran kedepan nya yaitu guru seragam menggunakan satu aplikasi yang sama, menggunakan media daring yang dapat <em>live</em>, menjelaskan materi sebelum memberikan tugas, melakukan pembagian kuota secara merata, memulai pembelajaran sesuai dengan jadwal, selalu memberikan motivasi kepada siswa serta mencaritahu kendala siswa dalam pembelajaran daring.</p>Sainab SainabMirnawati MirnawatiM. IrfanSupardi Muh. Said
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2022-12-312022-12-3151435210.36339/jhest.v5i1.79Kendala dan Solusi Pembelajaran Daring Selama Masa Pandemi Covid-19 SMA Negeri 3 Polewali
https://j-hest.web.id/index.php/2/article/view/78
<p> </p> <p><em>Akibat penularan Covid-19 yang sangat cepat, pemerintah menerapkan pembatasan aktivitas sehingga proses pembelajaran dilaksanakan secara daring, berdasarkan hasil studi pendahuluan terdapat kendala yang dihadapi guru biologi serta siswa kelas XI MIPA 2 selama beradaptasi dalam pelaksanaan pembelajaran daring. Tujuan penelitian 1) Mengetahui kendala yang dihadapi guru biologi dalam persiapan, pelaksanaan serta evaluasi selama pembelajaran daring 2) Mengetahui kendala yang dihadapi siswa kelas XI MIPA 2 dalam persiapan, pelaksanaan serta evaluasi selama pembelajaran daring 3) Mengetahui solusi yang dilakukan pihak sekolah untuk mengatasi kendala-kendala yang dihadapi dalam pembelajaran daring. Hasil penelitian yaitu 1) Kendala yang dihadapi guru biologi yaitu kendala menyesuaikan pembuatan RPP dimasa sekarang, jaringan internet kurang stabil, kurangnya dukungan orang tua, belum menguasai penggunaan teknologi, kesehatan guru terganggu, kendala pada penggunaan aplikasi belajar, sulit mengawasi karakter siswa, mengukur keterampilan/sikap siswa menjadi terbatas dan beberapa kendala pada tugas. 2) Kendala yang dihadapi siswa kelas XI MIPA 2 yaitu jaringan internet kurang stabil, harga paket data yang mahal, kendala pada penggunaan aplikasi, konsentrasi belajar siswa kurang, siswa kurang interaktif, penyerapan materi pelajaran sedikit dan banyaknya tugas yang diberikan guru 3) Solusi untuk mengatasi kendala pembelajaran daring yaitu sekolah melaksanakan pelatihan penggunaan teknologi, menyediakan Wi-fi secara gratis, wali kelas bekerja sama dengan orang tua serta guru mata pelajaran yang lain mengenai perkembangan belajar siswa, mengurangi penggunaan smartphone, menggunakan aplikasi yang mudah digunakan, guru membuat materi pembelajaran semenarik mungkin, memberikan bantuan paket data serta memberikan kebijakan untuk mengerjakan tugas.</em></p> <p> </p> <p><strong><em>Kata kunci – </em></strong><em>Pembelajaran Daring, Kendala Covid-19. </em></p> <p><em> </em></p>Sainab SainabNur Iftita RHFirdaus Firdaus
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2022-12-312022-12-3151536310.36339/jhest.v5i1.78Penerapan Media Pembelajaran Visual Untuk Meningkatkan Hasil Belajar Matematika Siswa Kelas V UPTD SD Negeri 58 Parepare
https://j-hest.web.id/index.php/2/article/view/73
<p><em>Tujuan dalam penelitian ini yaitu Untuk mengetahui bagaimana penerapan media pembelajaran visual yang dapat meningkatkan proses belajar pada mata pelajaran matematika tentang sifat-sifat bangun ruang di kelas V UPTD SD Negeri 58 Parepare. dan untuk mengetahui penerapan model pembelajaran visual dalam meningkatkan hasil belajar matematika di kelas V UPTD SD Negeri 58 Parepare. Subjek penelitian ini yakni guru dan siswa kelas V berjumlah 12 siswa terdiri dari 7 siswa perempuan dan 5 siswa laki-laki. Teknik pengumpulan data yang digunakan yakni observasi, tes, dan dokumentasi. Teknik analisis data yang digunakan yakni deskriptif kualitatif. Pada siklus I hasil observasi guru berada pada kategori C, untuk hasil observasi siswa berada pada kategori B dan hasil tes belajar matematika siswa menunjukkan ketuntasan dikategori K. Pada siklus II hasil observasi guru berada pada kategori B, untuk hasil observasi siswa berada pada kategori B dan hasil tes belajar matematika siswa menunjukkan ketuntasan dikategori B. Kesimpulannya yaitu penelitian ini menunjukkan bahwa dengan penerapan media pembelajaran visual dapat meningkatkan proses dan hasil belajar belajar matematika siswa kelas V UPTD SD Negeri 58 Parepare.</em></p>Siti Maryam MuhammadYonathan Saba’ PasinggiShinta Prameswari
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2022-12-292022-12-2951647010.36339/jhest.v5i1.73Pajjappi dalam Pengobatan Tradisional Bugis di Desa Mattaropurae Kabupaten Bone
https://j-hest.web.id/index.php/2/article/view/87
<p>This study aims to examine the meaning of <em>Pajjappi</em> which is used in Bugis traditional medicine in Mattaropurae Village, Bone Regency by using heuristic and hermeneutic theories. The type and design of the research is descriptive qualitative research. The data in this study is <em>Pajjappi</em> which is used in Bugis traditional medicine in Mattaropurae Village. Riffaterre's Semiotic Theory is used to dissect the <em>Pajjappi</em> text to describe the meaning contained in <em>Pajjappi</em>. The results of this study found eight <em>Pajjappi</em> or healing mantras, namely, <em>pajjappi peddi eppong, pajjappi olong, pajjappi polo, pajjappi nanre api, pajjappi bitong, pajjappi semmeng, pajjappi kasuwiang </em>and <em>pajjappi peddi eppong</em> based on heuristic reading, there are several different meanings of <em>Pajjappi</em> texts if they have different meanings. interpreted word and if interpreted sentence. The process of reading the first level is done with sentence refinement to find out the heuristic meaning of the <em>Pajjappi</em> text. Hermeneutic reading on <em>Pajjappi</em> helps to find meaning in the text. <em>Sanro</em> made a communication or request to Allah SWT. via pajjappi. The results of data analysis showed that eight <em>pajjappi</em> or healing mantras were found to describe a request for healing and protection to Allah SWT.</p> <p> </p>Zainal ZainalAsia MAndi Agussalim Aj
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2022-12-312022-12-3151717610.36339/jhest.v5i1.87Hubungan Pemberian MP-ASI Dengan Kejadian Stunting Pada Anak Usia 6-24 Bulan Di Desa Bonde Utara Wilayah Kerja Puskesmas Pamboang Kabupaten Majene
https://j-hest.web.id/index.php/2/article/view/83
<p><em>Stunting malnutrisi merupakan masalah yang sangat serius karena dikaitkan dengan peningkatan risiko morbilitas dan mortalitas di masa depan<strong>. </strong>Tujuan dari penelitian ini untuk mengetahui Hubungan pemberian MP-ASI Dengan Kejadian stunting pada anak usia 6-24 bulan di desa bonde utara wilayah kerja puskesmas pamboang kabupaten majene. Desain yang digunakan adalah cross sectional salah satu desa bonde utara wilayah kerja puskesmas pamboang kabupaten majene Sampel dalam penelitian ini sebanyak 56. Terdapat hubungan yang signifikan antara waktu pemberian MP-ASI, jenis pemberian MP-ASI, frekuensi pemberian MP-ASI, porsi pemberian MP-ASI dengan kejadian stunting pada baduta usia 6-24 bulan di desa bonde utara Wilayah Kerja Puskesmas pamboang Kabupaten Majene. Sedangkan untuk variabel tekstur pemberian MP-ASI didapatkan hasil, tidak ada hubungan yang signifikan antara tekstur MP-ASI dengan kejadian stunting pada balita usia 6-24 bulan di desa bonde utara Wilayah Kerja Puskesmas pamboang kabupaten majene</em></p>Erliwati ErliwatiEvawaty EvawatyMasniati MasniatiMuhammad Taufik PageRahmaniah Rahmaniah
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2022-12-312022-12-3151778210.36339/jhest.v5i1.83Analisis Ragam Bahasa di Masa Pandemi Covid-19
https://j-hest.web.id/index.php/2/article/view/77
<p>Analisis Ragam Bahasa di Masa Pandemi Covid-19 (Corona Virus Disease 2019)”. Penelitian ini bertujuan untuk: (1) mendeskripsikan bentuk ragam bahasa di masa pandemi Covid-19; (2) mendeskripsikan fungsi ragam bahasa di masa pandemi Covid-19. Jenis penelitian ini adalah penelitian kualitatif. Desain penelitian yang digunakan ialah deskriptif kualitatif. Penelitian ini dilakukan dengan menyimak dan mencatat ragam bahasa yang terdapat dalam imbauan mengenai pandemi Covid-19<em>.</em> Sumber data dalam penelitian ini yaitu imbauan terkait pandemi Covid-19 di media sosial <em>youtube.com. </em>Teknik yang digunakan dalam pengumpulan data adalah pengamatan, simak, dan catat. Hasil penelitian ditemukan bentuk dan fungsi ragam bahasa di masa pandemi Covid-19. Bentuk ragam bahasa di masa pandemi Covid-19, yaitu ragam resmi, ragam usaha, ragam santai, dan ragam akrab. Fungsi ragam bahasa di masa pandemi Covid-19, yaitu fungsi mengelola perbuatan pendengar (<em>direktif</em>), fungsi menunjukan rasa kebersamaan dalam hubungan kemasyarakatan (<em>fatik</em>), fungsi untuk mendiskusikan kejadian di sekitar (<em>referensial</em>), dan fungsi untuk memberikan informasi (<em>informatif</em>)</p>Isra DeviyantiUsman UsmanSakaria Sakaria
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2022-12-312022-12-3151839410.36339/jhest.v5i1.77Penggunaan Bahasa Persuasif Dalam Sosialisasi Protokol Kesehatan Covid-19 di Televisi
https://j-hest.web.id/index.php/2/article/view/72
<p>Penelitian ini bertujuan untuk mendeskripsikan bentuk bahasa persuasif yang digunakan dalam sosialisasi protokol kesehatan Covid-19 di televisi dan mendeskripsikan fungsi penggunaan bahasa persuasif dalam sosialisasi protokol kesehatan Covid-19 di televisi. Jenis penelitian ini adalah penelitian kualitatif yang bersifat deskriptif. Penelitian ini dilakukan dengan menyimak dan mencatat penggunaan bahasa persuasiff yang terdapat dalam sosialisasi protokol kesehatan Covid-19 yang tayang di televisi melalui situs youtube. Sumber data dalam penelitian ini diperoleh dari program berita di televisi berupa bentuk dan fungsi bahasa persuasif. Teknik yang digunakan dalam pengumpulan data adalah teknik pengamatan, teknik simak, dan teknik catat. Instrumen penelitian ini terdiri atas instrumen pokok yaitu peneliti sendiri. Hasil penelitian ditemukan bentuk bahasa persuasif dalam sosialisasi protokol kesehatan Covid-19 di televisi dan fungsi penggunaan bahasa persuasif dalam sosialisasi protokol kesehatan Covid-19 di televisi. Bentuk (1) Kalimat Imperatif mengandung maksud memerintah, (2) Kalimat Introgatif mengandung maksud menanyakan, dan (3) Kalimat Deklaratif mengandung maksud memberitakan. Fungsi persuasif adalah penggunaan bahasa yang bersifat mempengaruhi atau mengajak orang lain untuk melakukan atau tidak melakukan suatu hal secara baik-baik</p>Muslika SariUsman PaharHasriani Hasriani
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2022-12-312022-12-31519510410.36339/jhest.v5i1.72Penerapan Model Pembelajaran Kooperatif Tipe Talking Stick Untuk Meningkatkan Hasil Belajar Siswa Tentang Indah Kebersamaan Siswa Kelas IV UPTD SDN 24 Parepare
https://j-hest.web.id/index.php/2/article/view/74
<p><em>Masalah penelitian ini adalah rendahnya hasil belajar siswa pada mata pelajaran Bahasa Indonesia. Rumusan masalah dalam penelitian ini yaitu bagaimana hasil belajar siswa tentang indahnya kebersamaan di kelas IV UPTD SDN 24 Model Parepare sebelum penerapan model pembelajaran kooperatif tipe talking stick ? Bagaimana penerapan model kooperatif tipe talking stick </em><em>siswa kelas IV UPTD SDN 24 Model Parepare dan bagaimana hasil belajar siswa tentang </em><em>indahnya kebersamaan di kelas IV UPTD SDN 24 Model Parepare setelah penerapan model pembelajaran tipe talking stick. Tujuan penelitian ini adalah untu mengetahui hasil belajar siswa, penerapan model kooperatif tipe talking stick </em><em>siswa kelas IV UPTD SDN 24 Model Parepare serta hasil belajar siswa tentang </em><em>indahnya kebersamaan di kelas IV UPTD SDN 24 Model Parepare setelah penerapan model pembelajaran tipe talking stick. Pendekatan dalam penelitian ini adalah pendekatan kualitatif bersifat deskriptif. Jenis penelitian ini adalah PTK berdaur ulang. Fokus dalam penelitian ini adalah 1) Penerapan pembelajaran kooperatif tipe talking stick, 2) Hasil belajar siswa. Subjek dalam penelitian adalah siswa kelas IV UPTD SDN 24 Parapare. Subjek dalam penelitian ini adalah siswa dengan jumlah 30 orang yang terdiri dari 12 laki-laki dan 18 perempuan. Teknik pengumpulan data yang digunakan adalah observasi, tes dan dokumentasi. Teknik analisis data dalam penelitian ini adalah reduksi data, penyajian data dan menarik kesimpulan. Hasil penelitian menujukkan adanya peningkatan. Siklus I mencapai kualifikasi Baik (B) dan pada siklus II mencapai kualifikasi Sangat Baik (A). Kesimpulan penelitian ini adalah dengan menerapkan model pembelajaran kooperatif tipe talking stickdapat meningkatkan hasil belajar siswa pada mata pelajaran Bahasa Indonesia di Kelas IV UPTD SDN 24 Parepare.</em></p>Musfirah MusfirahNurjannah NurjannahSt Salwa Dinita
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2022-12-312022-12-315110510910.36339/jhest.v5i1.74Penerapan Model Pembelajaran Numbered Head Together (NHT) Dapat Meningkatkan Hasil Belajar Siswa Pada Mata Pelajaran Matematika Di Kelas IV UPTD SD Negeri 145 BARRU
https://j-hest.web.id/index.php/2/article/view/58
<p>Jenis penelitian yang digunakan adalah penelitian tindakan kelas (PTK) dengan pendekatan kualitatif. Teknik pengumpulan data yang digunakan yaitu observasi, tes dan dokumentasi. Teknik analisis data yang digunakan dalam penelitian ini adalah teknik analisis data kualitatif yaitu reduksi data, penyajian data, dan menarik kesimpulan. Subjek penelitian yaitu guru kelas IV dan siswa yang berjumlah 10 siswa. Hasil penelitian pada siklus I untuk proses pembelajaran berada pada kualifikasi cukup (C) dan untuk tes hasil belajar berada pada kualifikasi kurang (K). Hasil penelitian siklus II untuk proses pembelajaran berada pada kualifikasi baik (B) dan untuk tes hasil belajar pada kualifikasi baik (B). Kesimpulan pada penelitian ini adalah dengan penerapan model pembelajaran <em>Numbered Head Together</em> pada materi Statistika dapat meningkatkan proses dan hasil belajar siswa kelas IV UPTD SDN 145 Barru</p>St. Maryam MHasnah HasnahElian Yurika Mengkanna
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2022-12-312022-12-315111012010.36339/jhest.v5i1.58Penerapan Model Pembelajaran Kooperatif Tipe Student Team Achievement Division (STAD) Untuk Meningkatkan Hasil Belajar Matematika Siswa Kelas V UPTD SD Negeri 31 Parepare
https://j-hest.web.id/index.php/2/article/view/71
<p>Studi ini menelaah penerapan model pembelajaran kooperatif tipe <em>student team achievement division </em>untuk meningkatkan hasil belajar siswa pada materi volume bangun ruang di kelas V UPTD SD Negeri 31 Parepare. Tujuan dilakukannya penelitian ini adalah untuk mengetahui proses penerapan model pembelajaran kooperatif tipe <em>student team achievement division</em> dalam meningkatkan proses dan hasil belajar matematika pada materi volume bangun ruang. Pendekatan yang digunakan adalah pendekatan kualitatif dan jenis penelitian adalah penelitian tindakan kelas (PTK). Subjek dalam penelitian ini adalah guru dan siswa kelas V UPTD SD Negeri 31 Parepare pada tahun ajaran 2022/2023 yang berjumlah 8 orang siswa terdiri dari 3 orang laki-laki dan 5 orang perempuan. Data diperoleh melalui teknik observasi, tes dan dokumentasi. Teknik analisis data yang digunakan adalah teknik analisis data kualitatif. Hasil penelitian menunjukkan bahwa pada siklus I hasil observasi aktivitas guru yaitu 66,7% dengan kategori cukup, dan observasi aktivitas siswa 72,2% dengan kategori cukup. Pada siklus II menunjukkan peningkatan hasil observasi aktivitas guru menjadi 90,4% dengan kategori baik dan observasi aktivitas siswa 94,64% dengan kategori baik. Hasil penelitian terkait dengan hasil belajar, pada siklus I hanya 37,5% siswa yang tuntas dengan rata-rata 67,25. Pada siklus II mengalami peningkatan menjadi 87,5% siswa yang tuntas dengan rata-rata 86,25. Simpulan penelitian ini adalah dengan menerapkan model pembelajaran kooperatif tipe <em>student team achievement division </em>dapat meningkatkan proses dan hasil belajar siswa pada materi volume bangun ruang di kelas V UPTD SD Negeri 31 Parepare</p>Nurjannah NurjannahZaid ZainalAsriana Asriana
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2022-12-312022-12-315112112810.36339/jhest.v5i1.71Penerapan Model Pembelaran Kooperatif Tipe Team Assisted Individualization dalam Meningkatkan Hasil Belajar Matematika Siswa Kelas V SDN 001 Ranteliang Kab. Mamasa
https://j-hest.web.id/index.php/2/article/view/70
<p>Permasalahan dalam penelitian ini yaitu hasil belajar siswa kelas V SDN 001 Ranteliang Kabupaten Mamasabelum mencapai SKBM. Masalah dalam penelitian ini adalah bagaimana penerapan model pembelajaran koopereatif tipe <em>Team Assisted Individualization </em>dapat meningkatkan proses matematika siswa kelas V SDN 001 Ranteliang Kabupaten Mamasa dan apakah penerapan model pembelajaran pembelajaran koopereatif tipe <em>Team Assisted Individualization </em>dapat meningkatkan hasil belajar matematika siswa kelas V SDN 001 Ranteliang Kabupaten Mamasa. Tujuan dalam penelitian ini adalah untuk mengetahui penerapan model pembelajaran koopereatif tipe <em>Team Assisted Individualization </em>dapat meningkatkan proses matematika siswa kelas V SDN 001 Ranteliang Kabupaten Mamasa dan untuk mengetahui penerapan model pembelajaran koopereatif tipe <em>Team Assisted Individualization </em>dapat meningkatkan hasil belajar matematika siswa kelas V SDN 001 Ranteliang Kabupaten Mamasa. Pendekatan yang digunakan adalah pendekatan kualtitatif. Penelitian ini merupakan Penelitian Tindakan Kelas (PTK). Subjek Penelitian yaitu guru dan siswa yang berjumlah 12 siswa. Teknik pengumpulan data yang digunakan adalah observasi, tes, dan dokumentasi. Teknik analisis data yang digunakan reduksi data, <em>display </em>data (penyajian data), dan penarikan kesimpulan. Pelaksanaan tindakan penelitian ini dilakukan 2 siklus diawali dengan kegiatan pra tindakan, kemudian pada setiap siklus terdiri dari 4 tahapan yang meliputi perencanaan, pelaksanaan, observasi, dan refleksi. Hasil penelitian menunjukkan bahwa pada siklus 1 hasil observasi aktivitas guru dengan kategori cukup ( C) dan observasi aktivitas siswa dengan kategori ( C) dengan hasil tes belajar dengan kategori ( C). Sedangkan pada siklus mengalami peningkatan yang menunjukkan hasil observasi aktivitas guru dengan kategori(B) dan observasi aktivitas siswa dengan kategori ( B) dengan hasil tes belajar dengan kategori ( B). Simpilan peneltian ini adalah penerapan model pembelajaran koopereatif tipe <em>Team Assisted Individualization </em>dapat meningkatkan proses dan hasil belajar matematika siswa kelas V SDN 001 Ranteliang Kabupaten Mamasa.</p>Zaid ZainalAbdul HakimPutri Milaniagara
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2022-12-312022-12-315112913810.36339/jhest.v5i1.70Penerapan Media Kancing Untuk Meningkatkan Pemahaman Konsep Bilangan pada Anak di TPA Fathina
https://j-hest.web.id/index.php/2/article/view/88
<p><em>Penelitian tindakan Kelas yang dilaksanakan di TPA Fathina kabupaten Majene. Secara khusus penelitian ini bertujuan untuk meningkatkan pemahaman konsep bilangan melalui media kancing pada anak TPA Fathina kabupaten Majene yang berjumlah 15 anak. Penelitian dilaksanakan pada tahun pelajaran 2021/2022 dalam dua siklus, dimana masing-masing-masing siklus terdiri dari tahap perencanaan, pelaksanaan, pengamatan, dan refleksi. Siklus I terdiri dari lima pertemuan , demikian pula halnya dengan Siklus II. Hasil penelitian di TPA Fathina mengalami peningkatan pemahaman konsep bilangan melalui media kancing dengan melihat rata-rata hasil belajar pada siklus I berada pada kategori kurang mengalami peningkatan pada siklus II dengan berada pada kategori baik</em></p>St. Maria Ulfah
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2022-12-312022-12-315113914210.36339/jhest.v5i1.88