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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Transformatika JURNAL ILMIAH INFORMATIKA SINTECH (Science and Information Technology) Journal JUTEKIN (Jurnal Manajemen Informatika) Jurnal Manajemen Informatika Jurnal Teknologi dan Informasi Antivirus : Jurnal Ilmiah Teknik Informatika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Ilmiah Sains dan Teknologi (SAINTEK) JATI (Jurnal Mahasiswa Teknik Informatika) Competitive Dharma Raflesia : Jurnal Ilmiah Pengembangan dan Penerapan IPTEKS Jurnal Teknik Informatika (JUTIF) Jurnal Sains Teknologi dan Sistem Informasi Merpati Jurnal Informatika Teknologi dan Sains (Jinteks) Data Sciences Indonesia (DSI) JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Competitive Jurnal Pengabdian Masyarakat Indonesia (JPMI)
Rahayu, Woro Isti
Universitas Logistik Dan Bisnis Internasional
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Library & Information Science Physics Social Sciences Transportation Other

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Analisis Penjualan Kopi Dengan Prediksi Sarima Dan Rekomendasi Berbasis Algoritma Apriori Maresti, Fata Amalia; Aristawidya, Muhammad Vito; Syahfajar, Laode Muhammad Aznur; Rahayu, Woro Isti
Data Sciences Indonesia (DSI) Vol. 5 No. 2 (2025): Article Research Volume 5 Issue 2, Desember 2025
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/dsi.v5i2.7176

Abstract

Penelitian ini menganalisis penjualan produk kopi menggunakan model Seasonal Autoregressive Integrated Moving Average (SARIMA) untuk prediksi penjualan dan algoritma Apriori untuk sistem rekomendasi di tiga cabang: Hell's Kitchen, Lower Manhattan, dan Astoria. Hasil prediksi SARIMA menunjukkan bahwa Lower Manhattan memiliki akurasi tertinggi dengan nilai RMSE 12.90 dan MAPE 5.47%, sedangkan Hell's Kitchen dan Astoria menunjukkan tingkat kesalahan prediksi lebih tinggi. Prediksi penjualan tertinggi terjadi di Astoria (300 produk), dan terendah di Hell's Kitchen (201 produk). Rekomendasi optimasi manajemen stok mencakup gangguan stok di Hell's Kitchen, pengelolaan stok presisi di Lower Manhattan, serta analisis pola penjualan lebih mendalam di Astoria. Algoritma Apriori berhasil mengidentifikasi pola pembelian, dengan Hell's Kitchen menunjukkan asosiasi produk terkuat (lift 2.372), Lower Manhattan memiliki aturan asosiasi terbanyak (430 aturan), dan Astoria menunjukkan hubungan asosiasi yang lebih lemah. Strategi yang direkomendasikan meliputi bundling produk di Hell's Kitchen, promosi di Lower Manhattan, serta peningkatan support dan lift di Astoria. Hasil ini diharapkan dapat meningkatkan efisiensi manajemen stok dan strategi penjualan di cabang ketiga.
Implementasi K-Means untuk Melakukan Segmnetasi Produk Berdasarkan Data Transaksi Retail Fatia Amalia Maresti; Woro Isti Rahayu; Maria Bernadina Cintany Lustin; Thiodas Heni Pakpahan
Jurnal Ilmiah Sains dan Teknologi Vol. 9 No. 1 (2025): Jurnal Ilmiah Sains dan Teknologi
Publisher : Teknik Informatika Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/saintek.v9i1.3856

Abstract

Retail companies are one form of business that has experienced significant development. Significant development can lead to many business competitors in the same field. Therefore, every company must be able to find strategies to get the attention of the target market. Fast service and good prices are included in the factors that influence customer interest in making transactions in the retail business. This research aims to classify products into several categories. The method used to perform segmentation is the data mining method with the K-Means algorithm and the elbow method to find the optimal number of clusters. The obtained results of many optimal clusters are 3, namely cluster 0, cluster 1, and cluster 2. The variable that has the most influence on cluster characteristics is the price variable, while the variable that has little influence on cluster characteristics is the quantity variable.
Penerapan Algoritma Apriori untuk Rekomendasi Produk dalam Rangka Peningkatan Hasil Penjualan KUD Sarwa Mukti Cisarua Fatia Amalia Maresti; Woro Isti Rahayu; Kiki Mustaqim; Muhammad Vito Aristawidya; Laode Muhammad Aznur Syahfajar
Jurnal Pengabdian Masyarakat Indonesia (JPMI) Vol. 2 No. 3 (2025): Februari
Publisher : Publikasi Inspirasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62017/jpmi.v2i3.4031

Abstract

Koperasi Unit Desa (KUD) Sarwa Mukti merupakan salah satu koperasi produksi susu sapi perah yang masih aktif beroperasi di Cisarua, Kabupaten Bandung Barat, Jawa Barat.  Secara umum, program bertujuan untuk menerapkan strategi peningkatan penjualan produk KUD Sarwa Mukti, dengan menampilkan dashboard visualisasi hasil penjualan produk dan menerapkan rekomendasi sistem pemesanan produk menggunakan Algoritma Apriori. Algoritma Apriori adalah teknik dalam data mining untuk menemukan aturan asosiasi dalam dataset besar, dengan fokus pada item-item yang sering muncul bersama dalam transaksi. Hasil analisis menunjukkan bahwa produk berbasis susu, seperti Susu Murni dan Milk Shake Ice Cream, memiliki tingkat pembelian tinggi dan sering dibeli bersamaan dengan produk lain seperti Pisang Keju dan Roti Kukus. Dengan nilai lift rata-rata sebesar 1.53, ditemukan keterkaitan kuat antara beberapa produk, yang dapat dimanfaatkan untuk strategi bundling dan promosi. Penerapan association rules menghasilkan 180 aturan asosiasi yang menunjukkan hubungan positif antara produk antecedents dan consequents. Aturan dengan nilai lift tertinggi menunjukkan kecenderungan kuat bagi pelanggan untuk membeli produk secara bersamaan, seperti pada kombinasi Puding Sumur dan Pisang Kipas.
Analisis Faktor-Faktor Penyebab Depresi Mahasiswa di Indonesia Menggunakan Metode Regresi Logistik Kiki Mustaqim; Woro Isti Rahayu; Muhammad William Farma; Muhammad Rizky El Sulthani Lintang
SATESI: Jurnal Sains Teknologi dan Sistem Informasi Vol. 6 No. 1 (2026): April 2026
Publisher : Yayasan Pendidikan Penelitian Pengabdian ALGERO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/satesi.v6i1.7071

Abstract

Depression is one of the most common mental health disorders experienced by university students and can have a serious impact on their psychological state, academic performance and social interactions. Academic pressure, financial demands, and changes in living environment are often factors that trigger an increased risk of depression in this age group. Therefore, a comprehensive analysis is needed to identify factors that contribute to the emergence of depression so that prevention efforts can be targeted. This study aims to analyze the factors associated with depression among university students in Indonesia using logistic regression method as a classification approach. The research data was obtained from the Kaggle platform and included several independent variables, namely age, gender, academic pressure, sleep duration, diet, financial stress, study satisfaction, and suicidal thoughts. The results of the analysis showed that the suicidal thoughts variable was the most significant factor affecting the likelihood of students experiencing depression, with a coefficient value of 15.0964. In addition, the logistic regression model built is able to provide good prediction performance with an accuracy rate of 95%. The findings are expected to serve as a basis for educational institutions and policy makers in designing early detection strategies, interventions, and depression prevention programs to create a healthier and more supportive campus environment.
Co-Authors Annisa Cahyani ARISTAWIDYA, MUHAMMAD VITO Ariwati Hanek, Melvin Aulyardha Anindita Awalina, Eriskiannisa Febrianty Luchia Aznur Syahfajar, Laode Muhammad Damayanti, Fanny Shafira Dwi Prasetyo Nugroho, Ilham ema ainun novia Eni Lestari Farhan Maulana Febrisa Sidabutar, Audry Firwanda, Arjun Yuda Gideon Manik, Teddy Habibi, Roni Haekal Hilmi Zain* Hanum, Nisa Harani, Nisa Hanum Helmi Setywan, Muhammad Yusril Hidayatullah, Muhammad Reefy Hilmi Zain*, Haekal Ichsan Hizman Hardy Kaka Kamaludin Kiki Mustaqim Kishendrian, Hanan Laode Muhammad Aznur Syahfajar M. Yusril Helmi Setyawan Maresti, Fata Amalia Maresti, Fatia Amalia Maria Bernadina Cintany Lustin Maulana Awannga, Rolly Mohamad Nurkamal Fauzan Muhammad Rizky El Sulthani Lintang Muhammad Vito Aristawidya Muhammad William Farma Mustaqim, Kiki Mustaqimr, Kiki Ningrumsari Mulyanan, Ikrima Nisa Hanum Harani Nisa Hanum Harani Nur Raisa Nurul Izza Hamka Prianto, Cahyo Rakasona Rifqi Fathurrohman Riza, Noviana Rolly Maulana Awannga Santoso Seta Permana Siti Fathonah, Rd Nuraini Siti Fathonah, Rd. Nuraini Situmorang, Ryan Sujana, Ahmad Mugiar Sujana Syafrial Fachri Pane Syahfajar, Laode Muhammad Aznur Thiodas Heni Pakpahan Ulfiani Ramadhani, Firna Wardana, Aulia Yusril Helmi Setyawan, Muhammad Yusuf