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All Journal Jurnal Agroindustri Jurnal Teknologi & Industri Hasil Pertanian
Rahmany, Mahathir
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Agriculture, Biological Sciences & Forestry Computer Science & IT Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering

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Quality and consumer preferences on Gayo Arabica coffee brew based on the blending formulation and brewing method [Mutu dan konsumen terhadap seduhan kopi Arabika Gayo berdasarkan formulasi pencampuran bubuk kopi dan metode penyeduhan] Hasni, Dian; Hidayanti, Nori Asri; Rahmany, Mahathir; Widayat, Heru Prono; Muzaifa, Murna; Rahmad, Dedy
Jurnal Teknologi & Industri Hasil Pertanian Vol 30, No 1 (2025): Jurnal Teknologi & Industri Hasil Pertanian
Publisher : Teknologi Hasil Pertanian Fakultas Pertanian Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtihp.v30i1.1-11

Abstract

Gayo Arabica coffee has three cultivars that farmers in the Gayo Highlands commercially manage: Timtim, Borbor, and Ateng Super. Coffee blending is necessary to optimize the quality of Gayo Arabica coffee brews. In addition to the blend formulation, the brewing method also affects the quality of the brew. This study aims to understand the quality of coffee brews and consumer acceptance of two blending formulations optimized from previous research, brewed using four different brewing methods. The research used a factorial randomized block design with two factors. The first factors were the Gayo coffee blend formulation, 25% Timtim + 50% Borbor + 25% Ateng Super and 50% Borbor + 50% Ateng Super. The second factor was the coffee brewing method consisting of 4 levels: manual brew, French press, V60, and espresso. Brew quality parameters included pH, total dissolved solids, antioxidant activity, and sensory attributes such as aroma, flavor, body, aftertaste, and overall. The results showed that the interaction between the coffee blend formulation and the brewing method did not significantly affect the flavor in the sensory test. The coffee blend formulation significantly affected aroma, aftertaste, body, and overall but did not significantly affect antioxidant activity (65.87-65.42%), total dissolved solids (1.35°Brix), and pH. The Simple Additive Weighing method ranking test indicated that the best treatment combination was found in the formulation of 25% Timtim + 50% Borbor + 25% Ateng Super brewed using the French press method.
Quality and consumer preferences on Gayo Arabica coffee brew based on the blending formulation and brewing method [Mutu dan konsumen terhadap seduhan kopi Arabika Gayo berdasarkan formulasi pencampuran bubuk kopi dan metode penyeduhan] Hasni, Dian; Hidayanti, Nori Asri; Rahmany, Mahathir; Widayat, Heru Prono; Muzaifa, Murna; Rahmad, Dedy
Jurnal Teknologi & Industri Hasil Pertanian Vol. 30 No. 1 (2025): Jurnal Teknologi & Industri Hasil Pertanian
Publisher : Teknologi Hasil Pertanian Fakultas Pertanian Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtihp.v30i1.1-11

Abstract

Gayo Arabica coffee has three cultivars that farmers in the Gayo Highlands commercially manage: Timtim, Borbor, and Ateng Super. Coffee blending is necessary to optimize the quality of Gayo Arabica coffee brews. In addition to the blend formulation, the brewing method also affects the quality of the brew. This study aims to understand the quality of coffee brews and consumer acceptance of two blending formulations optimized from previous research, brewed using four different brewing methods. The research used a factorial randomized block design with two factors. The first factors were the Gayo coffee blend formulation, 25% Timtim + 50% Borbor + 25% Ateng Super and 50% Borbor + 50% Ateng Super. The second factor was the coffee brewing method consisting of 4 levels: manual brew, French press, V60, and espresso. Brew quality parameters included pH, total dissolved solids, antioxidant activity, and sensory attributes such as aroma, flavor, body, aftertaste, and overall. The results showed that the interaction between the coffee blend formulation and the brewing method did not significantly affect the flavor in the sensory test. The coffee blend formulation significantly affected aroma, aftertaste, body, and overall but did not significantly affect antioxidant activity (65.87-65.42%), total dissolved solids (1.35°Brix), and pH. The Simple Additive Weighing method ranking test indicated that the best treatment combination was found in the formulation of 25% Timtim + 50% Borbor + 25% Ateng Super brewed using the French press method.
RANCANG BANGUN ALAT DETEKSI KEMATANGAN BUAH KOPI ARABIKA MENGGUNAKAN SENSOR TCS3200 BERBASIS ARDUINO Rahma, Alti; Muzaifa, Murna; Rahmi, Faidha; Rahmany, Mahathir
Jurnal Agroindustri Vol. 16 No. 1 (2026): May 2026
Publisher : BPFP Faperta UNIB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31186/jagroindustri.16.1.112-124

Abstract

Ketepatan pemanenan buah kopi sangat menentukan kualitas biji kopi yang dihasilkan. Namun, metode manual yang masih banyak digunakan petani sering menghasilkan ketidakkonsistenan dan memerlukan waktu yang relatif lama. Penelitian ini bertujuan untuk merancang dan mengembangkan alat deteksi kematangan buah kopi Arabika berbasis Arduino menggunakan sensor warna TCS3200 dan algoritma k-Nearest Neighbor (k-NN). Sensor TCS3200 digunakan untuk membaca nilai RGB buah kopi, yang kemudian diklasifikasikan menjadi tiga tingkat kematangan, yaitu mentah, setengah matang, dan matang. Penelitian ini menggunakan 300 sampel sebagai data latih dan 150 sampel sebagai data uji, dengan evaluasi kinerja menggunakan confusion matrix. Hasil penelitian menunjukkan bahwa nilai k optimal adalah k = 20, yang memberikan keseimbangan antara bias dan varians serta menghasilkan tingkat kesalahan yang lebih rendah dibandingkan nilai k lainnya. Model yang dihasilkan mencapai akurasi 81,33%, presisi rata-rata 81,42%, recall 81,33%, dan F1-score 81,36%. Penelitian berpotensi memberikan kontribusi terhadap pengembangan teknologi pertanian presisi melalui integrasi sensor warna dan pengolahan data berbasis Python untuk mendeteksi kematangan buah kopi secara akurat dan efisien.
Co-Authors Dian Hasni, Dian Faidha Rahmi, Faidha Heru Prono Widayat, Heru Prono Hidayanti, Nori Asri Murna Muzaifa Rahma, Alti Rahmad, Dedy