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All Journal Jurnal Hortikultura Indonesia (JHI) Jurnal Ilmu dan Teknologi Kelautan Tropis Signifikan : Jurnal Ilmu Ekonomi E-Jurnal Ekonomi Sumberdaya dan Lingkungan Media Statistika Ekonomi Bisnis Jurnal Ekonomi : Journal of Economic Journal of Economics, Business, & Accountancy Ventura Equilibrium JURNAL EKONOMI DAN BISNIS AIRLANGGA Quantitative Economics Journal JIET (Jurnal Ilmu Ekonomi Terapan) JDE (Journal of Developing Economies) Agricore: Jurnal Agribisnis dan Sosial Ekonomi Pertanian Unpad Jurnal Ilmiah Ekonomi dan Bisnis Sistemasi: Jurnal Sistem Informasi JPPUMA: Jurnal Ilmu Pemerintahan dan Sosial Politik Universitas Medan Area Kinerja: Jurnal Ekonomi dan Manajemen Inovasi : Jurnal Ekonomi, Keuangan, dan Manajemen SRIWIJAYA INTERNATIONAL JOURNAL OF DYNAMIC ECONOMICS AND BUSINESS Jurnal Pertanian Agros Journal of Computer Science and Informatics Engineering (J-Cosine) EQIEN - JURNAL EKONOMI DAN BISNIS JURTEKSI Ekonomi dan Bisnis Jurnal Pendidikan Lingkungan dan Pembangunan Berkelanjutan Eksis: Jurnal Riset Ekonomi dan Bisnis EIGEN MATHEMATICS JOURNAL Jurnal Humaniora : Jurnal Ilmu Sosial, Ekonomi dan Hukum INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Perencanaan Pembangunan Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) TheJournalish: Social and Government Riset: Jurnal Aplikasi Ekonomi Akuntansi dan Bisnis Cendekia Niaga Jurnal Ekonomi Indonesia Jurnal Ekonomi Bisnis, Manajemen dan Akuntansi (JEBMA) Dynamic Management Journal Jurnal Ketenagakerjaan Jurnal Akuntansi, Manajemen, Bisnis dan Teknologi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Journal of Mathematics: Theory and Applications Margin Eco : Jurnal Ekonomi dan Perkembangan Bisnis Indonesian Journal of Economics and Management Journal of Economics Research and Policy Studies Prosiding Seminar Nasional Official Statistics Jurnal Ekonomi dan Pembangunan Indonesia Efficient: Indonesian Journal of Development Economics JIEP: Jurnal Ilmu Ekonomi dan Pembangunan Eko-Regional: Jurnal Pembangunan Ekonomi Wilayah Eko-Regional: Jurnal Pembangunan Ekonomi Wilayah
Fitri Kartiasih
Subdirektorat Statistik Pertambangan dan Energi, Badan Pusat Statistik
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Potensi Ekonomi Industri Pengolahan Indonesia: Analisis Input Output Hayuningtyas, Aulia; Lubis, Mahira Fachrunnisa; Anam, Mohammad; Kusumawardani, Sukma Ayu; Kartiasih, Fitri
MARGIN ECO Vol. 8 No. 2 (2024): Margin Eco: Jurnal Ekonomi dan Perkembangan Bisnis
Publisher : Fakultas Ekonomi Universitas KH. A. Wahab Hasbullah Tambakberas Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/margin.v8i2.5145

Abstract

Industri manufaktur merupakan sektor yang memiliki share terbesar terhadap PDB Indonesia di tahun 2023. Menteri Perindustrian menargetkan pertumbuhan kinerja industri manufaktur sebesar 5,80% pada tahun 2024. Dampak dari perubahan permintaan akhir terhadap sektor industri manufaktur akan mempengaruhi sektor-sektor perekonomian lainnya. Maka dari itu, penelitian ini bertujuan untuk mengidentifikasi angka pengganda output, tenaga kerja, dan pendapatan rumah tangga akibat kenaikan permintaan akhir. Penelitian ini juga memprediksi peningkatan output setiap sektor sebagai respons terhadap peningkatan permintaan akhir sektor industri pengolahan sesuai dengan target pertumbuhan tersebut. Tabel Input-Output hasil updating ke tahun 2023 digunakan sebagai alat analisis utama untuk mengidentifikasi interaksi sektor manufaktur dengan sektor perekonomian lainnya. Hasil penelitian menunjukkan bahwa sektor dengan angka pengganda output terbesar di tahun 2023 adalah Sektor Pengadaan Listrik dan Gas. Sektor dengan angka pengganda pendapatan terbesar adalah Sektor Jasa Pendidikan sedangkan Sektor Pengadaan Air, Pengelolaan Sampah, Limbah dan Daur Ulang menjadi sektor dengan pengganda tenaga kerja terbesar. Sektor lain yang paling terdampak oleh target pertumbuhan final demand 5,8% pada sektor industri pengolahan adalah sektor pertanian, kehutanan, dan perikanan.
Utilizing Google Trends Data to Examine the Impact of Unemployment Rates on Indonesia's Gross Domestic Product Jane, Giani Jovita; Hasabi, Rafif; Purnatadya, Sinatrya Dwi; Kartiasih, Fitri
Sistemasi: Jurnal Sistem Informasi Vol 13, No 6 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i6.3603

Abstract

Abstract Data related to the economy have varying frequencies and have delays in publication time. Such as data on the Open Unemployment Rate (OUR) with a semi-annual frequency and Gross Domestic Product at Constant Prices (riil GDP) according to expenditure with a quarterly frequency. So, frequency conversion is required to conduct simple regression modelling using these data. On the other hand, big data such as Google Trends is an additional predictor to estimate OUR and GDP data to overcome delays in publication time. Then the estimated data is modelled to investigate the effect of OUR on GDP. Data conversion uses the Chow-Lin method, while estimation with Google Trends data uses robust regression. The study shows that the estimation results using Google Trends as an additional predictor provide more accurate results than without Google Trends data for OUR and GDP data. Based on the robust regression results, it can be concluded that the OUR has a negative and significant effect on GDP. The findings provide valuable insights for supporting sustainable economic policy and further research on economic analysis.
Comparison Methods of Machine Learning and Deep Learning to Forecast The GDP of Indonesia Subian, Alwan Rahmana; Mulkan, Drajat Ali; Ahmady, Haidar Hilmy; Kartiasih, Fitri
Sistemasi: Jurnal Sistem Informasi Vol 13, No 1 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i1.3445

Abstract

The success of an economy can bring significant benefits to a country and its society. One way to measure economic growth is by looking at the value of gross domestic product (GDP). The value of a country's GDP is influenced by many factors, including inflation, exports, and imports. Therefore, predicting future economic growth requires forecasting the value of GDP. GDP forecasts are crucial as they provide information about the economic development of a country over a specific period of time. By forecasting GDP, governments and investors can make informed decisions to optimize profits or minimize risks when investing or doing business in a country. This research aims to forecast Indonesia's GDP for the second, third, and fourth quarters of 2023 using the best models from machine learning or deep learning methods. Forecasts are made for each method with and without additional variables. The results indicate that the SimpleRNN algorithm from deep learning without additional variables is the method with the smallest RMSE and MAPE for GDP forecasting. Therefore, the best method used to forecast GDP is the SimpleRNN algorithm, and the forecasted GDP values for Indonesia's second, third, and fourth quarters are 5.350.840,00, 5.483.895,00, and 5.610.077,50 billion rupiah.
ESTIMATION OF JAVA GRDP IN REGENCY/CITY LEVEL: SATELLITE IMAGERY AND MACHINE LEARNING APPROACHES Pemayun, Anak Agung Gede Rai Bhaskara Darmawan; Azizi, M Ziko; Daulay, Nur Ainun; Apriliani, Nur Hidayah; Kartiasih, Fitri
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 2 (2024): Maret 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i2.2993

Abstract

Abstract: Gross Regional Domestic Product (GRDP) is one of the most important socio-economic indicators. In order to gain a more comprehensive understanding of the current economic situation and regional differences, estimating GRDP using integration of satellite imagery and official statistics data can provide valuable information. This research estimates the GRDP value in 2022 by using data in 2019 to 2021 related to two aspects, agriculture and non-agriculture. Soil adjusted vegetation index (SAVI), enhanced vegetation index (EVI), and land cover (LC) used as agriculture aspect, while nighttime light (NTL), human settlement index (HSI), land area, and population per regency/city used as non-agriculture aspect. GRDP estimation are produced with machine learning approach using support vector machine (SVM) and random forest (RF) method. Correlation test on each variable shows only land area that does not have a significant correlation with GRDP. RF model then chosen as the best model with RMSE, MSE, MAE, and R2 value of 0.2549; 0.5049; 0.7727; and 0.2543, respectively. The estimated values acquired in several regencies/cities have rather near, some even very close to the official statistics values. Keywords: GRDP; satellite imagery; machine learning; random forest; support vector machine   Abstrak: Produk Domestik Regional Bruto (PDRB) merupakan salah satu indikator sosio-ekonomi yang penting. Penghitungan nilai PDRB dengan pendekatan yang melibatkan kombinasi data citra satelit dan statistik resmi dapat memberikan informasi serta pemahaman yang lebih komprehensif. Penelitian ini melakukan estimasi nilai PDRB pada tahun 2022 menggunakan data tahun 2019 hingga 2021 dengan melibatkan dua aspek, agrikultur dan non-agrikultur. Data soil adjusted vegetation index (SAVI), enhanced vegetation index (EVI), dan tutupan lahan (land cover/LC) digunakan sebagai aspek agrikultur, sementara data citra cahaya malam (NTL), human settlement indeks (HSI), luas wilayah kabupaten/kota, dan jumlah populasi per kabupaten/kota digunakan sebagai aspek non-agrikultur. Estimasi PDRB dihasilkan dengan menggunakan pendekatan machine learning berupa support vector machine (SVM) dan random forest (RF). Pengecekan korelasi antarvariabel menunjukkan bahwa hanya variabel luas wilayah tidak berpengaruh signifikan terhadap nilai PDRB. Model random forest kemudian dipilih sebagai model terbaik dengan nilai evaluasi RMSE, MSE, MAE, dan  berturut-turut sebesar 0.2549, 0.5049, 0.7727, dan 0.2543. Nilai estimasi yang diperoleh di beberapa kabupaten/kota cukup mendekati, bahkan ada yang sangat dekat dengan nilai statistik resmi. Kata kunci: PDRB; citra satelit; machine learning; random forest; support vector machine
Analisis Pengaruh Harga Minyak Mentah dan Nilai Tukar terhadap Indeks Harga Saham Gabungan (IHSG) di Indonesia Pramesthi, Adinda Ayu; Hutajulu , Dhevri Leonardo; Putri , Nasya Zahira; Kartiasih, Fitri
Jurnal Ekonomi Bisnis, Manajemen dan Akuntansi (Jebma) Vol. 4 No. 1 (2024): Artikel Riset Maret 2024
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jebma.v4i1.3451

Abstract

Penelitian ini dilakukan untuk menganalisis pengaruh harga minyak mentah dan nilai tukar terhadap indeks harga saham gabungan (IHSG) di Indonesia menggunakan Error Correction Model (ECM). Indonesia sebagai negara berkembang memerlukan penelitian terkait hal ini untuk mengkaji pengaruh simultan antara harga minyak dan nilai tukar terhadap kondisi pasar saham yang direpresentasikan oleh indeks harga saham gabungan. Studi ini menggunakan data bulanan harga minyak mentah, kurs nominal rupiah terhadap dolar AS, dan IHSG dari Januari 2018 sampai Oktober 2023. Hasil penelitian menunjukkan bahwa harga minyak mentah, IHSG, dan nilai tukar terbukti memiliki hubungan jangka panjang ditandai dengan adanya kointegrasi yang signifikan. Harga minyak mentah dan nilai tukar terbukti signifikan mempengaruhi indeks harga saham gabungan secara simultan, baik dalam jangka panjang maupun jangka pendek. Estimasi model jangka panjang dan jangka pendek menunjukkan bahwa IHSG secara signifikan negatif dipengaruhi oleh nilai tukar. Dibutuhkan waktu 1 bulan untuk pertumbuhan IHSG mencapai keseimbangan jangka panjang. Hasil penelitian diharapkan dapat memberikan referensi bagi investor dalam pengambilan keputusan investasi yang dilakukan. Hasil penelitian ini diharapkan memberikan gambaran kepada pemerintah tentang pentingnya variabel makroekonomi, sehingga pemerintah tidak hanya mempertimbangkan pengaruh satu variabel saja dalam membuat keputusan terkait perekonomian Indonesia. Bagi Bank Indonesia hendaknya menetapkan kebijakan moneter yang efektif dengan meminimalkan dampak buruk harga minyak dan nilai tukar terhadap indeks harga saham gabungan.
Identifying LPG Usage Inequality and Its Determinants in Eastern Indonesia Fajritia, Rahajeng; Kartiasih, Fitri; A’mal , Ikhlasul
Jurnal Ilmu Ekonomi Terapan Vol. 10 No. 2 (2025)
Publisher : Department of Economics, Faculty of Economics and Business, Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jiet.v10i2.79636

Abstract

Objective: This study aims to measure the extent of LPG usage inequality and to examine the factors influencing it across 13 provinces in Eastern Indonesia (KTI) over the period 2015–2023. Specifically, this study seeks to address two research questions: (1) To what extent does LPG usage inequality vary across provinces in Eastern Indonesia? and (2) What factors contribute to the occurrence of this inequality?Methods: This study uses panel data sourced from the National Socioeconomic Survey (Susenas) and official publications of BPS-Statistics Indonesia. LPG usage inequality is measured using the Gini Coefficient and the Lorenz Curve. The empirical model is analyzed using the Fixed Effect Model (FEM), which is then corrected with Feasible Generalized Least Squares–Seemingly Unrelated Regression (FGLS-SUR) to address heteroskedasticity and cross-sectional unit correlation issues.Findings: The research findings reveal that five provinces (East Nusa Tenggara, Maluku, North Maluku, Papua, and West Papua) experience very high disparities in LPG usage, primarily influenced by limited access and high LPG prices. Empirically, it was found that per capita income and education significantly reduce inequality, while an increase in LPG prices significantly increases inequality.Originality/Value: This research makes a novel contribution by focusing on LPG usage inequality across the provinces of Eastern Indonesia. The use of panel data analyzed through the FGLS-SUR method enables a more robust and precise identification of the determinants of inequality.Practical/Policy implication: The government should enhance the equity of energy distribution infrastructure, ensure price stability, and promote energy literacy as part of a just clean energy transition. Furthermore, improving educational attainment and strengthening micro, small, and medium enterprises (MSMEs) are essential to increasing public awareness, raising income levels, and stimulating regional economic development.
Co-Authors A'mal, Ikhlasul Abioga, Naufal Raffie Achmad Noerkhaerin Putra Addaruqutni, Adnan Dahiya Aditya, Randy Daffa Afifah, Aisyah Nur Agustina, Serly Ahmady, Haidar Hilmy Aini, Mifrotun Akhmad, Afied Albab, Muhammad Hafiz Amalia Isti Widiyasari Amalia, Mutiara Friska Anam, Mohammad Aprianto, Stenislaus Angga Apriliani, Nur Hidayah Arif Maulana, Arif Arif Rahman Hakim Arindah, Yuli Arini, Rechtiana Putri Arisanti, Rohimma Arnanda, Feza Raffa Asri, Yualita Surya Atmaja, Anugerah Surya Audina, Resda Aninditya Aulia, Miranda Aurellia, Nur Aisya Aysyah, Putri Azhari Azhari Azizi, M Ziko Azmi, Annisa Nurul A’mal , Ikhlasul Belantika, Bernica Tiyas Budiman, Muhammad Amirul Cahyarani, Arista Ika Camalia, Nur Dina Daulay, Nur Ainun Dini, Putri Muthi’ah Dyah Widyastuti Dzunnurain, Zena Azzahra Elvaretta , Katrina Lavenia Erviana, Rissa Esharja, Zul Ahmad Fajritia, Rahajeng Fauzan, Fardhi Dzakwan Fitriyyah, Nur Retno Gayatri, Tayasi Ditoresmi Habibi, Hasan Bahtiar Hafiz, Muhammad Sultan Hamdani Hamdani Hardinata, Rizki Harum, Nisrina Sekar Hasabi, Rafif Hasanah, Lailatul Hasibuan, Sri Rahayu Hasna, Nisa Fatharani Hayuningtyas, Aulia Herindra, Tsabit Bintang Hermawan, Kadek Dody Kusuma Hidayat, Anang Kurnia Hilal, Yanuar Nurul Holyness Nurdin Singadimedja Husain, Farah Fadhilah Hutabarat, Josephin Pirdinansius Hutajulu , Dhevri Leonardo Ishak, Rani Mardiyah Ismail, Ghaffar Jamaluddin, Halim Nur Jane, Giani Jovita Jannah, Nazwa Thoriqul Junianto, Raihan Rahmanda Kamal, Firhand Yusuf Khasanah, Alif Fitriatul Khotibul Umam Kurniawati, Reny Dyah Kusumawardani, Sukma Ayu Kuswardani, Rakaninda Indah Laksmana Putri, Calivi Kezia Latifa, Afina Lesmana, Faqih Indra Lubis, Adrian Kesar Pratama Lubis, Mahira Fachrunnisa Lukman, Raif Maulana Lukytawati Anggraeni Luthfia, Nisrina Maharani, Rafaela Suryadiva Indira Mahardika, Mayza Hanif Abbad Maruli, Surya Mauboy, Lourna Mariska Maulana, Arswenda Putra Miswa, Sabrina Do Mulkan, Drajat Ali Mumtazah, Soraya Afkarina Muzakki, Naufal Fadli Nainggolan, Gibson Daniel Andrianto Nasir, Andi Ardiansyah Nurfayza, Fairuz Azizah Nurhayati, Saniyyah Sri Oktaviana, Lisda Oktaviana, Siska Wahyu Oktaviani, Anisa Nur Pamungkas, Khrisna Aji Pemayun, Anak Agung Gede Rai Bhaskara Darmawan Perangin-Angin, Elgresia Egita Br Pertiwi, Intan Puspaning Prakoso, Nurihisha Nadya Putri Pramesthi, Adinda Ayu Pramesthy, Widhelia Echa Prasetyo, Rokhmirati Prasojo, Naufal Anhar Pratama, Bagus Putra Pratiwi Pratiwi Prayoga, Suhendra Widi Primadani, Avelia Deavy Purnatadya, Sinatrya Dwi Putri , Nasya Zahira Putri Yunardi, Nabila Fatma Putri, Ananda Rania Putri, Azmi Zulfani Putri, Hala Mutiara Putri, Khuzaimah Putri, Natasya Yunita Putri, Nimas Ayu Eka Putri, Syofmarlianisyah Rachma Safitri, Viola Rahma, Hanny Nur Rahma, Suci Fadhila Rahmadani, Alif Hidayah Nur Rahmanto, Karina Cindy Rahmawati, Iftina Ika Rajagukguk, Marlon Brando Ramadanty, Shashella Zelicha Ramadhan, Arfian Kurniawan Ramadhani, Anindita Ayu Ramadian.M, Vivi Adelia Randa, Abigail Brenda Pasorong Rayhan, Dhymas Adhyza Rega, Raina Revanadillaa, Daradinanti Aulia Rinangku, Rahadian Eka Bagus Indra Risxi, Muhammad Alfa Rita Yuliana Rizky Rahmadani, Rizky Rohmah, Nur Amaliyatur Rohmat, Erwin Agung Nur Rosanti, Hanifah Putri Ryan Hawari, Ryan Sabillah, Hanif Sabrina, Rizka Sagita, Fauzan Faris Samosir, Cecilia Putri Dianti Samosir, Immanuel Nicholas Fransepta Sandi, Imella Mendita Sandy, Nicholas Rahardian Kurnia Sari, Fahra Permata Sari, Linda Monica Sari, Mutiara Indryan Sepbrina Br Lumban Gaol, Ruth Natasya Setiawan, Kevin Rizkika Setyaningtyas, Ashita Shabrina, Amara Putri Siahaan, Rio Manuppak Sibagariang, Fahri Azis Simamora, Kevin Simamora, Patrick Noel Siregar, Arsyka Laila Oktalia Siregar, Tiara Khorijah Hamid Sofa, Wahyuni Andriana Subian, Alwan Rahmana Suhaib, Aida Muthia Suhendi, Brigitta Aurelia Putri Swardanasuta, I Bagus Putu Syahputri, Sabilla Hamda Syifa, Umu Arifatul Taridipa, Fitrisia Umami, Bafinatul Utami, Maulidya Fan Ghul Udzan Vianey, Arsdhewani Maria Wahyuni, Ribut Nurul Tri Wardana, Ardian Putra Wardani , Marshela Alya Kusuma Wibowo, Afina Zahrah Ananda Widiyasari, Amalia Isti Widyarta, I Kadek Purna Wijayanti, Sukma Kurnia Wilda, Marchadha Santi Yuliana, Niken Yusman Syaukat Zajidah, Annisa Muthi Zega, Alvandi Syukur Rahmat Zhafarina, Nadaa