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Peningkatan Visibilitas Produk pada Rekomendasi Long-Tail dengan Pendekatan Frequent Maximal Itemset Rosyid Muarif; Tubagus Mohammad Akhriza; Eni Farida
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Long-tail products are often overlooked in Collaborative Filtering recommendation systems due to their low purchase frequency and reliance on user interaction history. This study proposes the use of a Frequent Maximal Itemset (FMI) to improve the visibility of long-tail products in an online electronic cigarette (vape) store. Unlike Collaborative Filtering, FMI does not require user data and identifies historical transaction patterns to recommend relevant long-tail products alongside popular ones. Experimental results show that FMI is effective in identifying maximal itemsets that combine popular and long-tail products. Validation with 10 users revealed that 90% found the recommendations relevant to the main products they were searching for, and 90% indicated that they were likely to try the recommended long-tail products. The long-tail products included in the recommendations had logical associations with popular products, such as nicotine liquids with vaping devices. Thus, the FMI approach proves to be more flexible and effective in addressing popularity bias, while also providing long-tail products with greater visibility and increasing their potential for sales.
INDONESIAN CONSUMER PRICE INDEX (CPI) FORECASTING USING AN EXPONENNTIAL SMOOTHING-STATE SPACE MODEL Maknunah, Jauharul; As'ad, Mohamad; Setyowibowo, Sigit; Farida, Eni; Mumpuni, Indah Dwi
International Journal of Economics, Business and Accounting Research (IJEBAR) Vol 8, No 4 (2024): IJEBAR, VOL. 08 ISSUE 04, DECEMBER 2024
Publisher : LPPM ITB AAS INDONESIA (d.h STIE AAS Surakarta)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijebar.v8i4.15378

Abstract

Abstract: CPI (consumer price index) is one of the economic measurement tools that can explain or inform about the development of prices for services/goods consumed or used by consumers. The CPI is related to determining inflation, therefore the CPI and inflation are important variables in viewing the economic conditions of a particular country or city. Current month inflation depend on previous CPI and current CPI. The CPI and inflation are so important that many researchers are studying inflation and the CPI. The purpose of this research is to predict the value of Indonesia's monthly CPI with a simple, easy, and highly accurate forecasting model using open-source software. The data used are monthly CPI data from the Central Statistics Agency (BPS) for January 2014 to August 2024. The benchmark for the best ETS model is based on the minimum value of the Akaike information criteria (AIC) and Bayesian information criteria (BIC). The best model obtained is the ETS (M, N, N) model with a smoothing parameter (α) of 0.9933, has a root mean square error (RMSE) of 3.275868 and a mean absolute percentile error (MAPE) of 0.6595211%. Keywords: Price Consumer Index (PCI), Forecasting of Indonesia PCI, Exponential Smoothing-State Space, ETS (M,N,N).
INDONESIAN CONSUMER PRICE INDEX (CPI) FORECASTING USING AN EXPONENNTIAL SMOOTHING-STATE SPACE MODEL Maknunah, Jauharul; As'ad, Mohamad; Setyowibowo, Sigit; Farida, Eni; Mumpuni, Indah Dwi
International Journal of Economics, Business and Accounting Research (IJEBAR) Vol 8 No 4 (2024): IJEBAR, VOL. 08 ISSUE 04, DECEMBER 2024
Publisher : LPPM ITB AAS INDONESIA (d.h STIE AAS Surakarta)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijebar.v8i4.15378

Abstract

Abstract: CPI (consumer price index) is one of the economic measurement tools that can explain or inform about the development of prices for services/goods consumed or used by consumers. The CPI is related to determining inflation, therefore the CPI and inflation are important variables in viewing the economic conditions of a particular country or city. Current month inflation depend on previous CPI and current CPI. The CPI and inflation are so important that many researchers are studying inflation and the CPI. The purpose of this research is to predict the value of Indonesia's monthly CPI with a simple, easy, and highly accurate forecasting model using open-source software. The data used are monthly CPI data from the Central Statistics Agency (BPS) for January 2014 to August 2024. The benchmark for the best ETS model is based on the minimum value of the Akaike information criteria (AIC) and Bayesian information criteria (BIC). The best model obtained is the ETS (M, N, N) model with a smoothing parameter (α) of 0.9933, has a root mean square error (RMSE) of 3.275868 and a mean absolute percentile error (MAPE) of 0.6595211%. Keywords: Price Consumer Index (PCI), Forecasting of Indonesia PCI, Exponential Smoothing-State Space, ETS (M,N,N).
DESAIN WEB LOKAPASAR INTELIJEN DENGAN SISTEM REKOMENDASI UNTUK MENINGKATKAN VISIBILITAS PRODUK MBOISMART MALANG Akhriza, Tubagus Mohammad; Farida, Eni; Widodo, Anang Aris
JURNAL APLIKASI DAN INOVASI IPTEKS "SOLIDITAS" (J-SOLID) Vol. 7 No. 2 (2024): Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS
Publisher : Badan Penerbitan Universitas Widyagama Malang

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Abstract

Koperasi Pemasaran "Malang Kreatif Mbois" (MKKM) mengelola Mboismart sebagai toko fisik di gedung Malang Creative Center (MCC) Kota Malang, yang menghadapi tantangan dalam hal visibilitas produk yang terbatas pada pengunjung MCC. Untuk mengatasi keterbatasan ini, Tim Pengabdian kepada Masyarakat (PkM) dari STIMATA Malang dan Universitas Merdeka Pasuruan berkolaborasi mengembangkan lokapasar digital Mboismart.com. Artikel ini membahas kegiatan pengembangan prototipe web lokapasar ini sebagai solusi untuk memperluas jangkauan pasar dan meningkatkan eksposur produk UMKM yang menjadi mitra supplier Mboismart. Pengembangan lokapasar mencakup pembentukan dataset master produk dan supplier untuk kategori fashion, kriya, dan kuliner, yang sebelumnya belum terstruktur, serta pengintegrasian sistem rekomendasi berbasis association rule learning. Sistem rekomendasi ini menyarankan kombinasi produk populer dan non- populer untuk meningkatkan visibilitas produk yang kurang diminati. Selain itu, Focus Group Discussion (FGD) yang dilakukan mengidentifikasi persiapan penting terkait operasional lokapasar, seperti penanganan lonjakan order dan strategi promosi digital. Hasil awal menunjukkan potensi lokapasar ini dalam memperkuat pemasaran digital Mboismart, dengan dukungan administrasi konten yang efektif dan strategi promosi berkelanjutan. Artikel ini juga membahas tantangan yang dihadapi dan rencana keberlanjutan untuk mendukung peningkatan visibilitas produk UMKM di bawah naungan MKKM.
Peramalan Produk Domestik Regional Bruto Provinsi Jawa Timur Untuk Triwulan ke depan Dengan Model ETS Mohamad, As'ad; Setyowibowo, Sigit; Dwi Mumpuni, Indah; Farida, Eni; Maknunah, Jauharul
KONSTELASI: Konvergensi Teknologi dan Sistem Informasi Vol. 5 No. 1 (2025): Juni 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/konstelasi.v5i1.11656

Abstract

Abstrak. Penelitian ini bertujuan untuk meramalkn PDRB dengan model peramalan yang mudah,sederhana dan mempunyai akurasi tinggi. Peramalan PDRB di Jawa Timur ini dilatar belakangi olehbesarnya jumlah penduduk ke dua se Indonesia di provinsi ini setelah Jawa barat, sehingga besarnyanilai PDRB bisa dipakai sebagai indikator untuk melihat pertumbuhan ekonomi di Jawa Timur. Datayang digunakan adalah data sekunder berupa data triwulan PDRB Jawa Timur yang di peroleh daribadan pusat statistik (BPS) Jawa Timur. Model peramalan yang digunakan yaitu ETS, dimana modelini bisa digunakan secara simultan untuk meramalkan data yang berpola stasioner, trend danmusiman. Hasil dari penelitian ini dipilih model ETS(M,A,A) yang mempunyai error yang bersifatmultiplikatif, trend bersifat additive, musiman bersifat additive. Model ETS(M,A,A) mempunyaikreteria model terkecil AIC sebesar 1291.601 dan BIC sebesar 1310.598. Akurasi peramalan diukurdengan RMSE sebesar 4950.843 dan MAPE sebesar 0.7287398 %. Nilai MAPE lebih kecil dari 10% berarti hasil peramalan PDRB di Jawa Timur ini sangat baik. Hasil ramalan tiga triwulan kedepannaik pada triwulan ke dua dan ketiga serta turun sedikit pada triwulan ke empat, tetapi kesemuaramalan masih diatas nilai riil tertinggi tahun yang lalu (2024). Kata kunci: PDRB; BPS Jawa Timur; Model ETS(M,A,A); Pertumbuhan Ekonomi
Pengaruh Kepuasan Kerja dan Komitmen Organisasi terhadap Organizational Citizenship Behavior (Study pada Karyawan Pemerintah Kabupaten Malang) Widayanti, Rahayu; Farida, Eni
Jurnal Aplikasi Manajemen Vol. 14 No. 4 (2016)
Publisher : Universitas Brawijaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (91.706 KB) | DOI: 10.18202/jam23026332.14.4.10

Abstract

One of the keys to success in the organization's growth is the ability of organizations in recruiting, developing, and maintain the human resources wh ch the development of employee behavior are taken into account to improve the quality of service provided by the organization. One of the concepts of behavior is the organizational citizenship behavior (OCB), which is defined as a behavior beyond the standards defined by the organization. Some variables which affect the OCB development in the organization are the job satisfaction and organization commitment.On the other side, Malang Regency Government is currently trying to improve the OCB in SOEs (State Owned Enterprises), such as the State Electricity Company (PLN), in order to improve the quality of service to the public.65 employees of Malang regency government has been taken as an object in this study, multiple linear regression approach is used as an analysis method with job satisfaction and organizational commitment are treated as two independent variables, while the OCB itself is treated as the dependent variable. The results showed that both variables have an influence, but job satisfaction is the most dominant variable on OCB.
Peramalan Produk Domestik Regional Bruto Provinsi Jawa Timur Untuk Triwulan ke depan Dengan Model ETS Mohamad, As'ad; Setyowibowo, Sigit; Dwi Mumpuni, Indah; Farida, Eni; Maknunah, Jauharul
KONSTELASI: Konvergensi Teknologi dan Sistem Informasi Vol. 5 No. 1 (2025): Juni 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/konstelasi.v5i1.11656

Abstract

Abstrak. Penelitian ini bertujuan untuk meramalkn PDRB dengan model peramalan yang mudah,sederhana dan mempunyai akurasi tinggi. Peramalan PDRB di Jawa Timur ini dilatar belakangi olehbesarnya jumlah penduduk ke dua se Indonesia di provinsi ini setelah Jawa barat, sehingga besarnyanilai PDRB bisa dipakai sebagai indikator untuk melihat pertumbuhan ekonomi di Jawa Timur. Datayang digunakan adalah data sekunder berupa data triwulan PDRB Jawa Timur yang di peroleh daribadan pusat statistik (BPS) Jawa Timur. Model peramalan yang digunakan yaitu ETS, dimana modelini bisa digunakan secara simultan untuk meramalkan data yang berpola stasioner, trend danmusiman. Hasil dari penelitian ini dipilih model ETS(M,A,A) yang mempunyai error yang bersifatmultiplikatif, trend bersifat additive, musiman bersifat additive. Model ETS(M,A,A) mempunyaikreteria model terkecil AIC sebesar 1291.601 dan BIC sebesar 1310.598. Akurasi peramalan diukurdengan RMSE sebesar 4950.843 dan MAPE sebesar 0.7287398 %. Nilai MAPE lebih kecil dari 10% berarti hasil peramalan PDRB di Jawa Timur ini sangat baik. Hasil ramalan tiga triwulan kedepannaik pada triwulan ke dua dan ketiga serta turun sedikit pada triwulan ke empat, tetapi kesemuaramalan masih diatas nilai riil tertinggi tahun yang lalu (2024). Kata kunci: PDRB; BPS Jawa Timur; Model ETS(M,A,A); Pertumbuhan Ekonomi
Forecasting Performance of Double Exponential Smoothing Model and ETS Model for Predicting Crude Oil Prices Prapcoyo, Hari; As'ad, Mohamad; Sujito, Sujito; Setyowibowo, Sigit; Farida, Eni
Telematika Vol 20 No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.8104

Abstract

Purpose: This study aims to predict the price of monthly crude oil quickly and accurately by using an easy model and with easily available software.Design/methodology/approach: This study compares the DES-Holts and ETS models to predict price of monthly crude oil.Findings/result: The results of this study recommend the ETS(M,N,N) model to predict the price of monthly crude oil which produces an accuracy value of RMSE and MAPE of 4.385812 and 6.499007 %, respectively.Originality/value/state of the art: This study implements the DES_Holt's and ETS models to predict price of monthly crude oil with an RMSE and MAPE forecasting accuracy that has never been done in previous studies. 
Co-Authors Abd. Rasyid Syamsuri Ahmad Afifuddin Ahmad Wahid Efendi Anang Aris Widodo Anwar K, Anwar As'ad, Mohamad Eka Yuniar Hari Prapcoyo Indah Dwi Mumpuni Jauharul Maknunah Khoerul Anwar Mohamad As'ad Mohamad, As'ad Prapcoyo, Hari Rahayu Widayanti Risti Istira Rosyid Muarif Sigit Setyowibowo Sri Esti Trisno Sami Sujito Sujito Sujito Sujito Tubagus Mohammad Akhriza