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All Journal SAINS DAN MATEMATIKA Indonesian Journal of Applied Statistics Jurnal Kesehatan Vokasional Insect (Informatics and Security) : Jurnal Teknik Informatika BAREKENG: Jurnal Ilmu Matematika dan Terapan Dialektika: Jurnal Ekonomi dan Ilmu Sosial JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer Networks, Architecture and High Performance Computing Idealis : Indonesia Journal Information System Parameter: Journal of Statistics Enthusiastic : International Journal of Applied Statistics and Data Science Brilliance: Research of Artificial Intelligence International Journal Software Engineering and Computer Science (IJSECS) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Bulletin of Data Science Khazanah: Jurnal Mahasiswa Community Services and Social Work Bulletin Jurnal Ilmiah Ilmu Terapan Universitas Jambi Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Jurnal Sintak Innovative: Journal Of Social Science Research Jurnal Pengabdian Nasional (JPN) Indonesia Dedikasi : Jurnal Pengabdian Lentera Muara: Jurnal Manajemen Pelayaran Nasional Emerging Statistics and Data Science Journal Joong-Ki
Edy Widodo
UNDIP
Religion Agriculture, Biological Sciences & Forestry Humanities 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 Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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ANALISIS PENGARUH INTENSITAS DAN TIPE PENGGUNAAN INSTAGRAM TERHADAP SELF-ESTEEM MAHASISWA FMIPA UII Putri, Wafiq Rahma Aulia; Haifa, Hanadia; Widodo, Edy
Khazanah: Jurnal Mahasiswa Vol. 17 No. 2 (2025): Khazanah: Jurnal Mahasiswa
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/khazanah.vol17.iss2.art6

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh intensitas dan tipe penggunaan instagram terhadap self-esteem mahasiswa dengan social comparison sebagai variabel mediator. Pesatnya penggunaan instagram di kalangan mahasiswa menimbulkan kekhawatiran terkait dampaknya terhadap kesejahteraan psikologis, khususnya selfesteem. Penelitian ini menggunakan pendekatan kuantitatif dengan desain crosssectional. Data dikumpulkan melalui kuesioner dari dari 119 mahasiswa aktif program sarjana Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Islam Indonesia yang memiliki akun instagram aktif. Analisis data dilakukan menggunakan (PLS-SEM) dengan bantuan perangkat lunak R. Hasil penelitian menunjukkan bahwa social comparison berperngaruh negatif dan signifikan terhadap self-esteem, sedangkan intensitas dan tipe penggunaan instagram tidak berpengaruh signifikan secara langsung terhadap self-esteem. Model sturuktural mampu menjelaskan 28.4 % variasi self-esteem. Temuan ini mengindikasikan bahwa dampak pengunaan isntagram terhadap self-esteem tidak sepenuh ditentukan oleh seberapa sering. Penelitian ini menegaskan pentingnya peran social comparison dalam menjelaskan pengaruh media sosial berbasis visual terhadap kondisi psikologis mahasiswa.
Analisis Faktor-Faktor Kemiskinan di Provinsi Sulawesi Tengah Tahun 2013-2023 Menggunakan Model Koyck: Analisis Faktor-Faktor Kemiskinan di Provinsi Sulawesi Tengah Tahun 2013-2023 Menggunakan Model Koyck Amna, Faiz Mustafid; Widodo, Edy; Shiddiq, Yazid Mumtaz; Qonita, Rosyada Laili; Safira, Aulia; Refgina, Refgina
Emerging Statistics and Data Science Journal Vol. 4 No. 1 (2026): Emerging Statistics and Data Science Journal
Publisher : Statistics Department, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/esds.vol4.iss.1.art03

Abstract

Salah satu isu yang menjadi perhatian saat ini di negara berkembang, khususnya Indonesia, adalah kemiskinan. Pada tahun 2023, Indonesia menempati peringkat ke 70 dari 100 negara termiskin di dunia. Provinsi Sulawesi Tengah berada di peringkat kedua pada pulau Sulawesi dengan persentase penduduk miskin mencapai 12,41%. Beberapa variabel yang diduga mempengaruhi penentuan Persentase Penduduk Miskin (PPM) merupakan Rata-rata Lama Sekolah (RLS), Indeks Pembangunan Manusia (IPM), dan Tingkat Pengangguran Terbuka (TPT). Berdasarkan perihal diatas, jurnal ini ditulis untuk mengetahui faktor pada periode sebelumnya berpengaruh terhadap PPM pada periode yang ditentukan di Provinsi Sulawesi Tengah menggunakan Model Koyck. Penelitian menggunakan data sekunder yang diperoleh melalui website BPS Pusat RI. Diperoleh hasil analisis berupa Model Koyck dengan uji asumsi yang terpenuhi, model Koyck menunjukkan bahwa RLS, IPM, dan TPT mempengaruhi persentase penduduk miskin di Sulawesi Tengah pada tahun 2013-2023. Model Koyck dapat dikategorikan sangat baik untuk memprediksi nilai PPM berdasarkan variabel RLS, IPM, dan TPT dengan nilai MAPE sebesar 1,928%, 1,9935%, dan 3,155%. Dimana hasil MAPE tersebut menunjukkan nilai di bawah 10% yang berarti model yang digunakan memiliki Tingkat akurasi sampai dengan 98% pada RLS dan IPM, serta 97% TPT.
Penerapan Teknik Ensemble Dalam Analisis Sentimen Pelayanan Bea Cukai Pada Platform X Berbasis Soft Voting Widodo, Edy; Tantowi, Raihan
Jurnal Pelita Teknologi Vol 19 No 2 (2024): September 2024
Publisher : Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/pelitatekno.v19i2.7298

Abstract

Penelitian ini menganalisis sentimen publik terhadap pelayanan Bea Cukai di Indonesia yang menjadi sorotan di media sosial X. Metode Soft Voting digunakan dengan menggabungkan prediksi algoritma Naïve Bayes, K-Nearest Neighbor, dan Decision Tree pada data unggahan pengguna yang diproses melalui tahapan KDD, preprocessing, N-Gram 1–3, serta SMOTE, dan dievaluasi menggunakan Stratified K-Fold Cross Validation (5 fold). Hasil menunjukkan akurasi Naïve Bayes sebesar 93%, Decision Tree 85%, dan KNN 57%, sedangkan metode Soft Voting menghasilkan akurasi 99% pada data uji dan turun sekitar 4% pada data baru, menandakan kemampuan generalisasi yang baik serta pengurangan kesalahan klasifikasi, khususnya pada tweet negatif. Walaupun secara kuantitatif sentimen mayoritas tampak positif, analisis wordcloud menunjukkan dominasi isu negatif seperti penahanan barang, dugaan korupsi, dan permasalahan sistem yang menjadi perhatian utama publik. Oleh karena itu, Direktorat Jenderal Bea dan Cukai perlu memperkuat penerapan kode etik serta penegakan regulasi terkait guna meningkatkan transparansi dan kepercayaan masyarakat.
Identification of Indonesian Provinces Based on Socioeconomic Indicators in 2024 Using K-Means Permatasari, Erika Putri; Iriani, Lathifa Aurellia; Widodo, Edy
JURNAL SINTAK Vol. 4 No. 2 (2026): MARET 2026
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/jsintak.v4i2.789

Abstract

Poverty remains a persistent development challenge in Indonesia, characterized by substantial disparities across regions. Differences in social and economic conditions among provinces highlight the need for a comprehensive regional classification to support the formulation of targeted development policies. This study aims to classify Indonesian provinces based on their poverty and development characteristics. The data used are secondary data for the year 2024 obtained from Statistics Indonesia (Badan Pusat Statistik), with 38 provinces as the units of analysis. The variables include the poverty rate, Human Development Index (HDI), Open Unemployment Rate (OUR), and gross regional domestic product (GRDP) per capita. The analytical method employed is K-Means clustering, with variables standardized using Z-Scores. The optimal number of clusters was determined using the Elbow method and confirmed by the Silhouette Score. The results indicate that Indonesian provinces can be grouped into four clusters with distinct social and economic characteristics. Each cluster reflects different levels of poverty, human development quality, and labor market conditions. These findings emphasize that poverty in Indonesia is a multidimensional issue, underscoring the need for development and poverty alleviation policies that are tailored to the specific characteristics of each cluster.
Identification Of Disparities In Educational Facilities Among Indonesian Provinces Using K-Means Clustering Putri, Ananda Desilia; Dewi, Harni Selasih; Widodo, Edy
JURNAL SINTAK Vol. 4 No. 2 (2026): MARET 2026
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/jsintak.v4i2.790

Abstract

Education is one of the indicators used to measure a country's progress, due to its important role in producing quality human resources. Good education is certainly supported by the availability of adequate educational facilities. However, Indonesia's diverse geography poses a challenge in terms of equal access to education. Provinces classified as 3T regions face a shortage of educational facilities and teaching staff. This study aims to group provinces in Indonesia based on educational facility indicators for the 2023/2024 academic year using K-Means Clustering Analysis. The data used covers 38 provinces with 18 educational facility indicators, which were analyzed after data pre-processing. The results of this study obtained 3 clusters, where the first cluster consisted of 1 province with poor access and infrastructure conditions, the second cluster consisted of 17 provinces with fairly good access and infrastructure conditions, and the third cluster consisted of 20 provinces with very good access and infrastructure conditions. The clustering results from this study are expected to serve as a reference for the formulation of policies on the equitable distribution of educational facilities and the determination of development priorities in the education sector in Indonesia.
Segmentation Of Educational Quality In Indonesian Provinces Based On K-Means Clustering V.R, Baiq Jasmin Sabhira Safwa; Tectona, Zakiy Suryahadi; Widodo, Edy
JURNAL SINTAK Vol. 4 No. 2 (2026): MARET 2026
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/jsintak.v4i2.794

Abstract

The quality of education in Indonesia still exhibits disparities among provinces, reflecting differences in educational attainment and access. This study aims to segment the quality of education across Indonesian provinces based on the similarity of educational characteristics using the K-Means Clustering method. The data used consist of provincial-level education data that have undergone outlier detection and standardization to ensure comparability across variables. K-Means Clustering analysis was performed by forming three clusters representing provinces with low, medium, and high levels of educational quality. The clustering results indicate that most provinces fall into the medium education quality cluster, while a smaller number of provinces remain in the low education quality cluster. These findings demonstrate that the K-Means Clustering method is able to provide a clear representation of segmentation patterns and disparities in educational quality across Indonesian provinces and can serve as a basis for supporting more targeted and equity-oriented education policy formulation. Keywords: education; quality; K-Means; clustering; provinces
Optimalisasi Strategi Penjualan Sparepart Menggunakan Association Rule Berbasis Algoritma Apriori Amali, Amali; Widodo, Edy
Bulletin of Data Science Vol 5 No 2 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletinds.v5i2.9903

Abstract

The development of information technology encourages companies to utilize sales transaction data as a strategic source of information in business decision-making. However, the increasing amount of transaction data is often not optimally utilized to identify consumer purchasing patterns. This study aims to analyze consumer purchasing patterns in spare parts sales transactions using association rules based on the Apriori algorithm to support the optimization of sales strategies and inventory management. The research method used is a quantitative approach consisting of data collection, data preprocessing, transaction data transformation, frequent itemset generation, and association rule formation. The data used in this study consisted of 350 spare parts sales transactions processed using the Apriori algorithm with a minimum support value of 20% and a minimum confidence value of 70%. The results showed that the products Front Bumper and Brake Pads had the strongest association relationship with a confidence value of 76% and support value of 23%. In addition, the relationship between Radiator and Side Mirror products showed a confidence value of 71%. The study proves that the Apriori algorithm is effective in identifying relationships between products and can assist companies in determining promotional strategies, inventory management, and data-driven business decision-making to improve spare parts sales
Implementasi Clustering K-Medoids dalam Pengelompokan Kabupaten di Provinsi Aceh Berdasarkan Faktor yang Mempengaruhi Kemiskinan Hidayat, Freditasari Purwa; Putra, Royhan Pina; Alfitrah, M Dendi; Widodo, Edy
Indonesian Journal of Applied Statistics Vol 5, No 2 (2022)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v5i2.55080

Abstract

The economy is one of the parameters to see how the development of a country. Ending poverty anywhere and in any form is goal 01 of the Sustainable Development Goals (SDGs) program. Until now, poverty has become one of the main problems in Indonesia, so poverty must be a concern of the government. Based on data from the Central Statistics Agency (BPS) shows that as of September 2020 the percentage of poor people in Aceh Province is still the highest on the island of Sumatra, which is 15.43%. The purpose of this study is to classify districts based on factors that affect poverty in Aceh Province. The method used in this study is the K-Medoids Cluster Analysis algorithm. The optimal number of clusters is 2 clusters with cluster 1 consisting of 11 districts and cluster 2 consisting of 12 districts. Cluster 1 has a higher percentage of poor population and poverty depth index than cluster 2, while cluster 2 has higher Gini Ratio, AHH, and RLS values than cluster 1.Keywords : Clusters, Economy, Poverty, SDGs
Upaya Penegakan Emansipasi Wanita melalui Optimalisasi Pembangunan Gender dengan Metode Regresi Panel Phalufi, Inu Alifiyah; Alya Hartarie, Raden Nabila; Novitriani, Ellena; Widodo, Edy
Indonesian Journal of Applied Statistics Vol 5, No 2 (2022)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v5i2.58034

Abstract

The role of women nowadays is no different from the men, only to a reasonable extent. The role of women's emancipation itself has been upheld in Indonesia, as those who will be the spearheads in family education for their children that must have broad skills and insights. The Human Development Index (HDI) is mostly becoming an important index as a measurement of the success level in quality of human life (community) building efforts. By conducting an analysis using the panel regression method in the Regency / City of West Sulawesi (as a province in Indonesia that has the 4th lowest HDI score) to find out how much women's participation can affect the level of quality of life in Indonesia and as an evaluation of which components must be improved by government for the next period in the welfare of its people. This analysis concludes that the Mamuju regency is known as the region that contributes the largest weight to the increase in GDI while the Pasangkayu regency contributes the lowest weight to the increase in GDI so that the government should make the development of supporting facilities for community welfare more equitable.Keywords : GDI, Woman Emancipation, Panel Regression
Pengelompokan Kabupaten/Kota di Provinsi Jawa Barat Berdasarkan Dampak Kerusakan Bencana Banjir Menggunakan K-Medoids Gustiara, Dela; Mulyaningsih, Anisa Dwi; Anadra, Rahmi; Widodo, Edy
Indonesian Journal of Applied Statistics Vol 5, No 2 (2022)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v5i2.65668

Abstract

The territory of Indonesia is located in geographical, geological, hydrological, and demographic conditions that allow Indonesia to be prone to disasters. The most common natural disaster in Indonesia is flooding. If accumulated, there have been 682 flood events in the country since the beginning of 2022. In Indonesia, especially West Java Province, flooding is the most common disaster, especially during the rainy season. So a study will be conducted that aims to determine the grouping of districts / cities in West Java Province based on the occurrence of flood disasters. The data used in this study were obtained from the publication of the National Disaster Management Agency. In this study, there are 4 variables of the impact of flood disasters, namely total deaths, total submerged houses, total damaged houses and total injured. The clustering method used in this research is K-Medoids. K-Medoids is one of the clustering methods that uses the partition clustering method in grouping a set of n objects into a number of k clusters. From the results of the K-Medoids analysis, three clusters were obtained. The first cluster consists of 3 districts/cities with high impact of flood disasters, the second cluster consists of 23 districts/cities with moderate impact of flood disasters, and the third cluster consists of 1 district/city with low impact of flood disasters. Based on the results of the analysis, efforts can be made by the government to focus more on designing steps that must be taken in preventing or overcoming the impact of flood disasters.Keywords: Cluster; K-Medoids; Floods West Java
Co-Authors Abdul Aziz, Hilmy Abdul Halim Anshor Abidah Nur Anisah, Hergina Achmad Isya Alfassa Afnan, Irsyifa Mayzela Agustin, Widya Saputri Akbar, Purnama Akhsan, Salafudin Al Al Farizi, Danial AL-Azkia, Muhammad Wildan Alfiah, Febiyanti Alfitrah, M Dendi Aliamsyah, Moh. Almadayani, Almadayani Alya Hartarie, Raden Nabila Amali, Amali Amna, Faiz Mustafid Anadra, Rahmi Andani, Febria Pradita Prima Andini, Wiranti Nugrah Andri Firmansyah Anekawati, Fitri Anggreany, Anggun Nur ARDIANSYAH, FAISAL Arfian, A Ariani, Putri Meliana Arief Hadi Prasetyo, Arief Hadi Ariyani, Dwi Faridha Asyiah, Noor Asyiah, Rizkiana Avitariella, A Ayu Wardani, Dheandra Ayuningtyas, Rachel Aziza, Himelda Bahtiar, Reza Yusuf Bariklana, Muhammad Budiarto, Eko Choerunnisa, Riza Amelia Cusanti, Cusanti Desmitasari, Rosi Dewati, Nabila Ratna Dewayanti, Arlinda Amalia Dewi Trisnawati Dewi, Diana Kusuma Dewi, Harni Selasih Dewi, Rosiana Rahma Diba, Sheila Farah Dodit Ardiatma Dzakiroh, Alliyah Fadlurrohman, Muhammad Shiddiq Febriana, Ella Tasia Febriyanti, Syintya Ferdiansyah, Febby Fikri, Bana Ali Fikry, Muhammad Dirga Ghaisani, Salwa Yudanti Gustiara, Dela Haifa, Hanadia Hamid, Yudhistira Hasanah, Insani Hendri, Martius Hermawan, Rachmat Hidayat, Freditasari Purwa Hidayati, Irina Hijriyany, Meyla Hikmawan, Dimas Wahyu Hitayuwana, Nurul Huda, Tri Atmaja Ilma, Hafizah Iriani, Lathifa Aurellia Ismayani, Indrianti Jati, Wahyu Pratama Jennifer, Dwirany Puspitasari Junita, Tarisya Permata Kashi, Rahma Yuliati Khaeriyah, Rakhil Khaerunnisa, Muthia Khusna, Zulfa Aulia Kurnia Ramadhani, Kurnia Kusuma, Tihat Jaya Laksono, Arif Anjang Lathifah, Lailla Nur Latifah, Evi Fitria Umi Latupono, Boki Lestari, Indri Fauzi Lestari, Ninik Kardinah Lutfi, Ahmad Zainul Majid, Annisa Maulana Manthovani, Andi Nurhanna Mardiyah, Meiga Isyatan Mardiyyah, Safwah Ayu Masthura, M Maulana, Donny Maulidaniar, Aulia Nurul Maulidya, Rizka Putri Maulina, Gina Meimunah, M Mu'minin, Aisyah Ummi Muhammad, Juliana Saputra Muhammad, Shodiq Muhtajuddin Danny Muinah, Ummi Maftuhatul Muktiwijaya, Aldi Wilaga Mulyaningsih, Anisa Dwi Mutia, Sani Nalurita, Wening Nawangsih, Ismasari Nilam Novita Sari Ningrum, Noorzahrah Cintya Nisa, Annida Jahratun Novianti, Afdelia Novitriani, Ellena Novyantika, Rizky Dwi Nowi, Nurul Aulia Nur Edma, Syifa’ul Mufidati Nur Hidayah Nur Hikmah Nurfalah, Meylinda Dwi Nurhikmat, Triano Nurinayah, N Panggol, Sri Arista Papua, Oceano Alpheratza Permatasari, Erika Putri Permatasari, Retno Pertiwi, Riezki Phalufi, Inu Alifiyah Pinasty, Salsabila Pradana, Sendhyka Cakra Pradana, Wahyu Aji Prasetyo, Adwi Guntur Prasetyo, Bagas Dwi Prawesti, Inna Prayoga, Dimas Prianda, Bayu Galih Pupung Purnamasari Purwanto Purwanto Putra, Royhan Pina Putri, Ananda Desilia Putri, Naomighina Putri, Rahayu Kia Sandi Cahaya Putri, Selvina Sela Annisa Putri, Wafiq Rahma Aulia Putri, Zarmeila Qonita, Rosyada Laili Rachmania Mulkiyah, Ananda Raharjo, Alifian Wahyu Rahmawan, Afandi Ahmad Rakhmalia, Riza Indriani Ramdhanti, Tiara Ratri Astuti, Morti Refgina, Refgina Rini, Halimah Setio Safira, Aulia Safitrah, Ilham Saputra, Johan Saputri, Bening Saraswasti, Lidya Palupi Sari, Cindy Fatika Sari, Rima Juridar Usfita Sartika, Indang Satria Permana, Muhammad Safri Septian, Yayan Dwi Serdawati, Septi Shiddiq, Yazid Mumtaz Simanjuntak, Antonius Soesmono, Salma Sri Utami Sriwiji, Rina Subangkit, Andreas Sulhaerati, S Suriyani, Ade Irma Suwandi Suwandi Tantowi, Raihan Tanza, Alifia Tectona, Zakiy Suryahadi Tria Anggraini, Devita Tusyakdiah, Halima Ulinnuha, Muhammad Utama, Rafi Ilmi Badri Utami, Pertiwi Bekti V.R, Baiq Jasmin Sabhira Safwa Wahyu Hadikristanto Wicaksono, Bima Yudha Widi, Tegar Anugrah Widiawati, Ika Fitia Wijayanto, Feri Wirdaniyati, Sri Siska Wiyanto - Yadin, Muhammad Atma Yahya, Adiba Yuan Badrianto Yubinas, Febritista Yumna, Pradipa Arka Yuniarti, Mazna Yusnandar, Y Zahra , Qolbiyatus Syifa Az